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**Report of 1^st^ International GPM GV Requirements Workshop**

**\[4--7 November 2003; Abingdon, U.K.\]**

***Nations/Regions Represented***

**Australia, Austria, Brazil, Canada, China, European Union, Finland,**

**France, Germany, Greece, India, Israel, Italy, Japan, Korea,
Netherlands,**

**South Africa, Spain, Taiwan, United Kingdom, United States,**

**West Africa AMMA (Benin, Niger, Senegal)**

**Final: Version 1.1 (March 2005)**

***Editorial Committee***

1\. Chandra V. Chandrasekar \<chandra@engr.colostate.edu\>

2\. Elizabeth Ebert \<e.ebert@bom.gov.au\>

3\. John Goddard \<j.w.f.goddard@rl.ac.uk\>

4\. Martin Hagen \<martin.hagen@dlr.de\>

5\. Paul Hwang \<paul.h.hwang@nasa.gov\>

6\. Alberto Mugnai \<a.mugnai@isac.cnr.it\>

7\. Kenji Nakamura \<nakamura@ihas.nagoya-u.ac.jp\>

8\. Jae-Cheol Nam \<jcnam@metri.re.kr\>

9\. Eric A. Smith \<eric.a.smith@nasa.gov\>

10\. Chung-Hsiung Sui \<sui@c.c.ncu.edu.tw\>

11\. Carron Wilson \<c.l.wilson@rl.ac.uk\>

12\. Sandra E. Yuter \<yuter@atmos.washington.edu\>

**Table of Contents**

***[Page]{.underline}***

**Executive Summary *(E.A. Smith)* v**

**1.0 Overview of GPM Mission *(E.A. Smith)* 1**

**2.0 Description of GPM's Ground Validation Programme 3**

2.1 Introduction *(E.A. Smith)* 3

2.2 Principal Scientific Objectives of International GPM GV Research
Programme 6

*(E.A. Smith, A. Mugnia, & K. Nakamura)*

2.2.1 Standard GPM Precipitation Retrieval Algorithms *(A. Mugnai & K.*
7

*Nakamura)*

2.2.2 NWP as GV Evaluation Tool *(P. Bauer)* 9

2.2.3 Hydrometeorological Modeling as GV Evaluation Tool *(C.-H. Sui)*
10

2.3 Organizational Structure *(V. Levizzani)* 10

2.4 GV Measurement Requirements *(S. Yuter, E. Ebert, & J. Goddard)* 11

2.5 GV Data Policy *(J. Goddard, P. Hwang, & K. Nakamura)* 13

2.6 Multi-National, Multi-Regional, & Multi-Agency Sites 14

2.6.1 Concept of Virtual GV Site *(C.V. Chandrasekar, J. Goddard, & M.
Hagen)* 14

2.6.2 European Virtual GV Supersite *(M. Hagen)* 14

2.6.3 NOAA Hydrometeorological Testbed Program *(M. Ralph)* 15

2.6.4 DOE-ARM Southern Great Plains Site *(T. Ackerman & M. Miller)* 15

2.7 GV System Design 16

2.7.1 Copyleft and GNU General Public License *(S. Yuter)* 16

2.7.2 Validation System Design and Integration: International GV
Perspective 17

*(C.V. Chandrasekar)*

2.8 Web Site for International GV Coordination *(E. Ebert)* 20

**3.0 Working and Summary Group Reports 23**

3.1 Working Group Reports *(Working Group Chairs and Raporteurs)* 23

3.1.1 WG#1a: Retrieval Error Characterization ***(E. Ebert & T.
L'Ecuyer)*** 23

3.1.2 WG#2a: Regional Mapping of GV Error using Supersite Network 24

*(M. Hagen & R. Cifelli)*

3.1.3 WG#3a: New Challenges and Ideas for GV Research *(C.V.
Chandrasekar* 25

*& E. Gorgucci)*

3.1.4 WG#4a: GV Opportunities for Operational Raingauge/Radar Networks
25

*(R. Ferraro & C. Kidd)*

3.1.5 WG#1b: International GPM GV Organizational Requirements 27

*(V. Levizzani & R. Lawrence)*

3.1.6 WG#2b: Scientific Goals of GPM GV Research Program *(K. Okamoto*
28

*& P. Hwang)*

3.1.7 WG#3b: Accuracy Requirements *(P. Bauer & J. Schulz)* 29

3.1.8 WG#4b: Basic Radar Products & Implications for Observation
Strategy 31

*(S. Yuter & J. Koistinen)*

3.2 Summary Group Reports *(Summary Group Leads)* 38

3.2.1 Potential GV Site Concept *(V. Levizzani & J. Goddard)* 38

3.2.2 Country, Region, and Agency Site Readiness *(D. Everett & J-C.
Nam)* 40

**4.0 GV Site Status and Future Plans 41**

4.1 Nation by Nation Infrastructure Summaries 41

4.1.1 Australia *(Elizabeth Ebert)* 41

4.1.2 Austria *(Michael Schoenhuber)* 42

4.1.3 Brazil *(Roberto Calheiros & Humberto Ribeiro da Rocha)* 43

4.1.4 Canada *(Paul Joe)* 45

4.1.5 China *(Lu Naimeng & Zhang Wen-Jian)* 46

4.1.6 Finland *(Jarmo Koistinen)* 47

4.1.7 France *(Guy Delrieu)* 49

4.1.8 Germany *(Martin Hagen)* 51

4.1.9 Greece 52

4.1.10 India *(Gemsrinivasa Viswanathan)* 53

4.1.11 Israel *(Daniel Rosenfeld)* 54

4.1.12 Italy *(Eugenio Gorgucci & Giorgio Roth)* 55

4.1.13 Japan 62

4.1.14 Korea *(Jae-Cheol Nam and Byung-Ju Sohn)* 63

4.1.15 Netherlands *(Remko Uijlenhoet, Herman Russchenberg,*

*& Iwan Holleman)* 65

4.1.16 South Africa *(Deon Terblanche)* 67

4.1.17 Spain *(Daniel Sempere-Torres & Sergi Paricio-Ferrero)* 68

4.1.18 Taiwan *(Chung-Hsiung Sui)* 69

4.1.19 United Kingdom *(John Goddard & Carron Wilson)* 71

4.1.20 United States *(Steven Rutledge, Rober Cifelli, Sandra Yuter*

*& Robert Wood)* 74

4.1.21 West Africa *(Everett Joseph, Greg Jenkins Jose Fuentes)* 80

4.2 Nation-by-Nation GV Site Readiness Summary *(D. Everet, P. Hwang, &
J.-C. Nam)* 82

**5.0 High-level Recommendations for Successful International GPM GV
Programme 95**

***(E.A. Smith, A. Mugnai, & K. Nakamura)***

**6.0 GPM GV Point of Contact for Nation/Region 98**

**7.0 References 99**

**8.0 Appendices 101**

8.1 Attendees of Abingdon Meeting 101

8.2 Agenda of Abingdon Meeting 103

8.3 Web Access to Abingdon Meeting Presentation Materials 105

**Executive Summary**

The 1st International Global Precipitation Measurement (GPM) Ground
Validation (GV) Requirements Workshop, held in Abingdon, England in
November 2003 and hosted by the Rutherford-Appleton Laboratory, began
the process of developing an internationally organized GPM GV research
program \-- backed up by a globally-distributed network of GV sites with
concomitant support organizations and participating scientists. The
objectives of the 1st workshop were to define a set of broad science
requirements under which the GPM GV site network can be developed. As a
result, participants completed the definition plan of broad set of
scientific objectives and requirements which motivates the international
GPM GV research program and helps define the basic operation of the GV
site network.

The fundamental scientific objectives driving the international GPM GV
Research Program are: (1) to establish quantitative uncertainties in GPM
satellite precipitation retrievals, (2) to develop improved satellite
precipitation retrieval algorithms, and (3) to seek better understanding
of the underlying macro- and micro-physics of precipitation life cycles.

To help achieve these objectives, three types of GV sites are
envisioned: (1) Standard GV Sites, (2) GV Supersites, and (3) Virtual GV
Sites. A Standard GV Site would be expected to conduct its operations
autonomously, without any commitments for conducting operational,
near-realtime data acquisition, processing, or reporting \-- but to
contribute to the GV research program through scientific engagement and
making selective GV products available to GPM research and applications
participants, preferably via internet access.

GV Supersites, along with bearing the same scientific and GV product
dissemination responsibilities as the Standard GV Sites, will require
routine and near-realtime GV data acquisition, data processing, and low
bandwidth data communications (reporting and receiving) with GPM's
central Precipitation Processing System (PPS) at the NASA/Goddard Space
Flight Center under a standard protocol (yet to be defined). The
underlying GV data of consequence involved in Supersite activity will
enable: (a) the generation of independent error characterization
information concerning GPM's standard rainrate products, primarily for
use by data assimilation specialists at operational and experimental
weather and hydrometeorological prediction centers, and (2) the
identification of flaws and weaknesses in the standard algorithms in a
manner which stimulates continuous algorithm improvement.

Virtual GV Sites, such as being envisioned by a consortium of some nine
national groups within the European Union, will consist of a coordinated
array of Standard GV Sites and GV Supersites \-- with the main intent of
providing a much greater cross-cut of GV measurements. products, and
assimilated information than is allowable or affordable by any single
independent site.

Resulting from the Abingdon workshop, the following report was
generated. It is electronically available at GPM GV web site:
<http://gpm.gsfc.nasa.gov/workshops.html>, ***Report of 1st
International GPM GV Requirements Workshop.***

A GPM GV Point of Contact for Nations/Regions was established:

1\. Australia Elizabeth Ebert \<e.ebert@bom.gov.au\>

2\. Austria Michael Schoenhuber \<michael.schoenhuber@joanneum.at\>

3\. Brazil (2) Roberto Calheiros \<calheiros@www.radar.ipmet.unesp.br\>

Carlos Morales \<morales@model.iag.usp.br\>

4\. Canada (2) Paul Joe \[Ontario\] \<<paul.joe@ec.gc.ca>\>

David Hudak \[Ontario\] \<David.Hudak@ec.gc.ca\>

5\. China Lu Naimeng \< lunaimeng@nsmc.cma.gov.cn\>

6\. European Union (BALTRAD) Ralf Bennartz \<bennartz@aos.wisc.edu\>

7\. Finland Jarmo Koistinen \<jarmo.koistinen@fmi.fi\>

8\. France Nicolas Viltard \<viltard@cetp.ipsl.fr\>

9\. Germany Martin Hagen \<martin.hagen@dlr.de\>

10\. Greece (2) Emmanouil Anagnostou \<manos@engr.uconn.edu\>

Vasso Kotroni \<kotroni@meteo.noa.gr\>

11\. India Raju Garudachar \<raju_garudachar@hotmail.com\>

12\. Israel (2) Daniel Rosenfeld \<<daniel@vms.huji.ac.il>\>

Eyal Amitai \<eyal@radar.gsfc.nasa.gov\>

13\. Italy Eugenio Gorgucci \<e.gorgucci@isac.cnr.it\>

14\. Japan Shuji Shimizu\<shuji.shimizu@jaxa.jp\>

15\. Korea Byung-Ju Sohn \<sohn@snu.ac.kr\>

16\. Netherlands Remko Uijlenhoet \< Remko.Uijlenhoet@wur.nl\>

17\. South Africa Deon Terblanche \<deon@metsys.weathersa.co.za\>

18\. Spain Daniel Sempere-Torres \<sempere@grahi.upc.es\>

19\. Taiwan Ming-Dah Chou \<mdchou@atmos1.as.ntu.edu.tw\>

20\. United Kingdom John Goddard \<j.w.f.goddard@rl.ac.uk\>

21\. United States Matt Schwaller \<mathew.r.schwaller@nasa.gov\>

22\. West Africa Consortium Everette Joseph \<ejoseph@howard.edu\>

**1.0 Overview of GPM Mission**

Globally distributed, continuous, and high-quality measurements of
accumulation, intensity, and temporal evolution of precipitation are
valued for a wide range of basic- and applications-oriented research \--
of international interest and consequence. However, unlike acquisition
of more homogenous meteorological fields such as pressure and
temperature, obtaining high quality precipitation measurements is
particularly challenging due to precipitation's stochastic and rapidly
evolving nature. In general, precipitation systems exhibit spatially
heterogeneous rainrates over local to regional domains, and highly
fluctuating rainrate intensities over time \-- up to large spatial
scales. Thus, it is usual to observe a broad spectrum of rainrates over
a few hours for a given locale or region. For this reason and the fact
that most of the world is not equipped with precision rain measuring
sensors (i.e., reliable raingauges and/or radars), the current rain
measurement of choice for regional to global analysis is obtained from
satellite remote sensing.

The purpose of the International Global Precipitation Measurement (GPM)
Program is to develop a next generation / space-based measuring system
which can fulfill the requirements for frequent, global, and accurate
precipitation measurements \-- continuously acquired along with
well-defined and quantitative metrics of the measurements' systematic
and random errors. The ultimate goal of the associated GPM Mission,
being developed as an international collaboration of space agencies,
weather and hydrometeorological forecast services, research
institutions, and individual scientists, is to serve as the flagship
mission for a variety of international water-related research and
applications programs. These include global water and energy cycle
(GWEC) programs participating in the World Climate Research Program
(WCRP) / Global Energy and Water Cycle Experiment (GEWEX), and basic
research, applications-oriented research, and operational environmental
forecasting programs within individual nations and national consortiums.
Because water cycling and the availability of fresh water resources,
including their predicted states, are of such immense concern to most
nations, and because precipitation is the fundamental driver of all
environmental water issues \-- developing a space-based,
globally-inclusive precipitation measuring system has become a pressing
issue for a large body of nations.

The design and development of the GPM Mission is an outgrowth of
valuable knowledge and published findings enabled by the Tropical
Rainfall Measurement Mission (TRMM) and produced by various U.S.,
Japanese, and European Union (EU) research teams, plus other individual
scientists. Based on TRMM, from consideration of basic physical
principles associated with direct sensing of precipitation from space,
and with a realistic view of economic constraints, it is now recognized
that the GPM Mission must consist of a constellation of satellites, some
dedicated, and some conveniently available from other experimental /
operational missions supported by various of the world's space agencies,
i.e., "satellites of opportunity".

The heart of the GPM constellation is the GPM Core Satellite, under
joint development by NASA and the Japan Aerospace Exploration Agency
(JAXA). As with TRMM, the basic workshare arrangement between NASA and
JAXA is that JAXA will provide the radar and the launch, while NASA will
provide the radiometer, the satellite bus, and the ground segment. The
Core Satellite is the central rain measuring observatory which will fly
both a dual frequency (Ku/Ka-band) precipitation radar called DPR, and a
high resolution, multichannel passive microwave (PMW) rain radiometer
called GMI. The Core Satellite is required to serve as the calibration
reference system and the fundamental microphysics probe to enable an
integrated measuring system made up of eight additional
constellation-support satellites. Each support satellite is required to
carry one or more precipitation sensing instruments, but at a minimum,
some type of PMW radiometer measuring at several rain frequencies.

Fortunately, the GPM constellation has had the welcome attention of the
European Space Agency (ESA), the Italian Space Agency (ASI), and the
Canadian Space Agency (CSA), along with a consortium of European and
Canadian scientists plus other international colleagues, who are seeking
the opportunity for the contribution of a European GPM (EGPM) satellite
whose instrument capabilities would strengthen the core measurement
scheme. This EGPM observatory would be specially outfitted with an
advanced rain radiometer using a mix of window and molecular O~2~
sounding frequencies, and a Ka-band, high-sensitivity (5 dBZ) radar \--
a combination of instruments suitable for measurements of light and warm
rainfall, moderate to heavy drizzle, and light to moderate snowfall. All
these types of precipitation are largely outside the dynamic range of
the Core Satellite's instruments, but are important contributors to the
Earth's water cycle at mid- to high-latitudes, with warm rain and
drizzle very important contributors in the tropics, especially in the
extended marine stratocumulus regions. It is anticipated, based on
mission-life specifications and expected launch dates, that the
time-frame for the Core and EGPM Satellites to support the constellation
architecture is approximately 20010-14 \-- noting this period could be
extended were mission lifetimes to exceed specifications.

The GPM Mission consists of four main components. The first is the space
hardware making up the constellation measuring system as described. The
second is the data information system, referred to as the GPM
Precipitation Processing System (PPS), a system which will reside at the
NASA/Goddard Space Flight Center (GSFC) \-- interconnected to a
distributed data information network (involving such sites as JAXA/EORC
and ESA/EDC sites in Tokyo and Frascati) whose main function would be to
serve regional datas users. The main responsibilities of the NASA PPS
are: (1) to acquire level 0 and 1 sensor data, (2) to produce and
maintain consistent level 1 calibrated / earth located radiometer
brightness temperatures (T~B~s) and radar reflectivities (Zs), (3) to
process level 1 data into consistent level 2 and 3 standard
precipitation products, (4) to disseminate precipitation products
through both "push" and "pull" data transfer mechanisms, and (5) to
assure archival of all data products acquired or produced by the PPS \--
either within the PPS or through suitable arrangements with other data
archive services.

The third mission component, and central to the following report, is the
internationally-organized GPM ground validation (GV) programme, which
will consist of a worldwide network of GV measuring sites and their
associated scientific and technical support organizations. A subset of
these sites are referred to as "GV Supersites", designating that they
will operate in a semi-continuous, near-realtime mode under a
well-defined GV data reporting protocol supported by the GSFC PPS. Other
types of sites will be Standard GV Sites with a main function of
contributing to the GV science program but not required to report
near-realtime data, and Virtual GV Sites (now under consideration by a
consortium of European Union groups affiliated with some nine
countries). A Virtual GV Site consists of a distributed and coordinated
network of sites whose members would selectively operate in either
Supersite or Standard Site mode. The main function of the GPM GV program
will be: (1) to acquire ground-based sensor data relevant to the
validation of and/or comparison with satellite sensor measurements and
standard precipitation product retrievals, (2) to produce, archive, and
publicly make available on the Internet, standard GV products, (3) if a
Supersite, to provide near-realtime error characteristics concerning
instantaneous rainrate retrievals from the core-level satellites (i.e.,
Core and EGPM satellites), consisting of bias, bias uncertainty, and
spatial error covariance information, and (4) if a Supersite, to support
ongoing standard algorithm improvement by reporting significant errors
in instantaneous retrievals from the core-level satellites to scientific
groups authoring and maintaining the standard rainrate algorithms,
including with the reports, essential core (and core-type) satellite and
GV data needed to interpret effectively algorithm breakdowns. Error
characteristics of \~7.5% accuracy and \~20% precision for instantaneous
retrievals \-- which will produce 3-hourly GPM precipitation products
\-- represent projected estimates of the underlying retrieval
uncertainties. These anticipated error factors are based on results from
recent TRMM validation analyses being used to help design the GPM
Mission's International GV Program.

The fourth mission component is the most valuable of the entire mission
\-- that being the people involved, i.e., the collection of individual
scientists, engineers, and program officials making up the various
science teams from participating nations, as well as the oversight
committee / working group infrastructure that will manage and coordinate
the international aspects of the mission. Because the GPM Mission is
expected to be flexible and fluid in design, enabling space hardware
assets to come and go as the situation evolves (referred to as the
"rolling wave" constellation approach), allowing for new and changing
PPS and GV site facilities and capabilities, and accepting that the
underlying scientific effort is a shared responsibility \-- the people
involved will practice international diplomacy as well as adhere to
their fundamental responsibilities and commitments within their own
organizations and sovereign nations.

With these four components, the GPM Mission will have the capability to
provide physically-based retrievals on a global basis, with \~3-hour
sampling assured at any given Earth coordinate \~90% of the time \--
such frequent diurnal sampling made possible by a mixed
non-sunsynchronous / sunsynchronous satellite orbit architecture.
Ultimately, however, it will be the people involved that will
demonstrate how an internationally-sanctioned collective effort can be
used to acquire a long-sought measuring capability of one of the Earth's
most fundamental variables and one of life's most precious commodities.

**2.0 Description of GPM's Ground Validation Programme**

**2.1 Introduction**

The International GV Research Programme of GPM will be extremely
important in achieving mission success because the quality of the
satellite precipitation retrievals, in the eyes of many, will be only as
good as independent assessment and verification will allow. Because
precipitation is a global variable, and globally diverse in nature (as
schematically illustrated in Figure 1), it stands to reason that, to the
extent possible, the GV research program should be globally distributed.
This means at the outset, that just as the space hardware component of
the mission must be international in design because the mission requires
a constellation of low orbiting satellites much too expensive for any
single space agency, the GV component must be international in design
since no single nation can practically deploy (or afford) a global
network of GV measuring sites. Fortunately, as the Abingdonj meeting
demonstrated, there is great interest from a number of world-wide
organizations and individuals in establishing an internationally-based
GPM GV network. Figure 2 provides a site map designating potential
participating nations (in the case of Japan and the United States, two
(2) and three (3) GV sites are anticipated, respectively).

![](media/image2.wmf){width="5.958333333333333in"
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**Figure 1:** GPM's GV strategy requires sampling selection of global
rainfall regime.

![](media/image3.wmf){width="6.429861111111111in"
height="4.033333333333333in"}

**Figure 2:** Current status of potential GPM ground validation site
network.

The importance of a GV research program tailored for the GPM Mission
stems from three basic concerns relevant to precipitation measurement.
The first is measurement uncertainty and the need to quantify
uncertainty in detail, so that users of GPM precipitation retrievals can
interpret their research and applications results with all due caution
and constraint. The second involves the natural inclination to
continually improve the retrieval algorithms used to make the
space-based measurements. This process cannot be done in isolation from
independent precipitation datasets which are needed to assess algorithm
performance, both physically and statistically, and at scales below
those associated with the level 1 satellite measurements.

The third concern is associated with the need for continually improving
the independent ground-based GV measurements themselves. Historically,
ground-based measurements of precipitation have been beset with
difficulties, whether they have been acquired from collection
raingauges, optical raingauges, disdrometers, submerged acoustic
phonics, non-attenuating radars, attenuating radars, long-wave Doppler
profiling radars, or other more specialized sensors. Nonetheless, there
have been impressive engineering innovations applied to ground
precipitation sensors in the last two decades. Wide aperture raingauges
with improved protection from wind effects, drop-counting raingauges,
extended spectrum disdrometers, common aperture / multi-frequency
Doppler profilers, and dual-polarization / dual-frequency radars are
just some of the engineering developments that have produced more
accurate ground-based precipitation measurements (e.g., Bringi and
Chandrasekar 2001). Given this background, it is incumbent that
ground-based sensors continue to improve. Moreover, for the GPM Mission
to be engaged in improving global precipitation datasets, it should
sponsor improvements in independent, ground-based measuring systems \--
an issue that needs attrention within GPM's International GV Research
Program.

GPM's International GV Research Program will require the deployment of a
heterogeneous mix of measuring sites operating under a straightforward
scientific strategy. Ultimately, participating organizations must
represent their own self-interests and concerns. By the same token, the
GPM Mission requires some degree of consistency across the eventual site
network. GPM's GV sites are classified into three types: (1) those sites
which conduct their operations according to their own institutional
requirements, while serving the greater science process by engaging in
GPM's scientific forums and publication processes related to GPM
validation studies \-- this first type of site is referred to as a
"Standard GV Site", designating that its responsibilities represent the
baseline commitment to GPM, (2) those sites which, in addition to the
responsibilities for a Standard GV Site, also routinely report
information to the NASA/GSFC Precipitation Processing System (PPS) on a
near-realtime basis and according to a standardized protocol,
information needed to calculate continuous GPM precipitation retrieval
error characterization (metrics for bias, bias uncertainty, and spatial
error covariance at high spatial resolution ), and to support in a
routine fashion an information exchange process with the PPS designed to
enable continuous improvement of GPM's standard precipitation retrieval
algorithms, accomplished by detecting and reporting to the PPS
significant algorithm failures associated with instantaneous satellite
retrievals found in site overpass data that the PPS will routinely
transmit to the given sites's data processing system \-- this second
type of site is referred to as a "GV "Supersite" \-- designating that it
conducts routine GV data acquisition-processing-reporting operations
using the standard PPS communications protocol for support of error
charicterization and algorithm improvement processes which require
near-realtime operations, and (3) collections of sites which intend to
operate in a coordinated fashion under both Standard GV Site and GV
Supersite modes, but enabling a diverse set of GV foci that enables the
whole to greater than the sum of its parts \-- this third type of site
is referred to as a "Virtual GV Site", designating that it is made up of
a collection of individual sites which coordinate GV coverage of a
region (a group of European Union nations are anticipated to operate in
the Virtual GV Site mode). As evident from Figure 1, these three types
of sites, if most or all participate, would provide excellent sampling
of the variety of precipitation systems distributed over the Earth.

Thus, the design of GPM's International GV Program provides for the
participating organizations to deploy a heterogeneous network of GV
sites on their own terms and with their own preferred instrumentation
\-- and in the event they agree to participate in GV Supersite mode,
they would be required to transmit routine data to GSFC's PPS needed for
retrieval error characterization (i.e., error factors desired at
forecast centers utilizing NWP rainfall data assimilation for optimizing
the assimilation process), and needed for algorithm improvement. Because
of the necessity for routine operations, GV Supersites would also be
required to be affiliated with some type of on-site or remote-site
Science Information Center (SIC). The resultant virtual SIC network
would exchange data with the GSFC node of the PPS, receiving satellite
overpass data from the PPS, while transmitting low bandwidth error
characterization information and algorithm error reports back to the PPS
\-- all according to the standard protocol. Participating scientists and
engineers at any of the sites would be invited, as a matter of course,
to participate in GPM's International GV scientific forums (plus other
forums), and to communicate their relevant scientific findings through
the open literature.

**2.2 Principal Scientific Objectives of International GPM GV Research
Programme**

The main scientific objectives of the GPM GV programme are as follows:

1.  Evaluate and quantify error characteristics, uncertainties, and
    shortcomings in GPM precipitation products through variety of direct
    statistical and physical validation diagnostic methods, as well as
    modeling methods (e.g., environmental prediction using precipitation
    data assimilation, water budget analysis, climate model reanalysis)
    \-- at data latencies desired by GPM's GV client communities, to
    enable optimal use of GPM precipitation retrieval products for
    scientific research and applications.

2.  Improve GPM's physically-based standard precipitation retrieval
    algorithms (designed for satellite radiometer and radar inputs)
    based on comprehensive ground observations of precipitation and
    precipitating storm systems used to provide algorithm error
    detection guidance \-- fostering continuous improvement process by
    use of fluid and low latency data and information communications
    between GV Supersites and GSFC-PPS.

3.  Develop, archive, and make publicly available through Internet,
    standard GV data products applicable for GV research and for
    developing improved methodologies in conducting ground validation
    research \-- and in so doing encourage creation of new GV
    technologies, emphasizing those that lead to higher retrieval
    accuracies, greater precisions, and ultimate greater understanding
    of precipitation's physical processes.

4.  Encourage operational users to confirm usefulness of space-based
    precipitation products based on forecast verification testing,
    hydrometeorological prediction outcomes, agrometeorological modeling
    assessments, climatonomy descriptions \-- and other model-based,
    climatological-based, or descriptive applications.

**2.2.1 GPM's Standard Precipitation Retrieval Algorithms**

One important finding from the TRMM validation programme has been that
simple comparison against conventional surface rainfall data, as derived
from raingauges and scanning rain radars, is not sufficient for
calibrating the TRMM algorithms or for discovering ways to improve the
algorithms. In essence, measurements from space have improved so much
that parameter tuning is no longer satisfactory. Instead, we need a
physically-based validation programme for ensuring radiometrically
consistent rain retrievals.

One of GPM's primary standard level 2 rain retrieval algorithms will be
for the DPR. Since Japan is responsible for the development of the DPR
instrument, it will take the lead on development of algorithms
applicable to DPR measurements. Notably, the standard level 2 algorithm
itself, has not yet been completely specified and is still open to new
ideas.

The DPR actually consists of two radars at Ku-band (13.6 GHz) and
Ka-band (35 GHz). The GPM Ku-band radar will be nearly identical to
TRMM's Ku-band Precipitation Radar (PR), while the Ka-band radar
represents new development. Several types of instantaneous rainrate
profile algorithms are anticipated for development, as a function of the
two different ground swath widths associated with the two distinct scan
angles carved out by the two radars. One algorithm for the Ku-Ka narrow
swath region will fully combine both radar's reflectivity signatures.
Another algorithm can be envisaged for the Ku-band width swath region
which would include extrapolating Ka-band information outside its
narrower swath. Other algorithms might consist of Ku-only, Ka-only, and
perhaps a combined radar-radiometer algorithm involving both Ku/Ka-band
measurements along with GMI measurements.

To support this effort, the GPM GV programme will be needed to assess
the different DPR instantaneous rainrate estimates and to guide the
algorithm developers in improvement of the baseline algorithms. In
general, in comparison to microwave radiometer-based precipitation
retrieval (for either surface rainfall or rainrate profiles),
radar-based precipitation retrieval involves more direct formulations.
Nonetheless, the DPR algorithms will involve a number of model
parameters, the main ones being the bulk variables needed to describe
the underlying drop size distribution (DSD). Using two co-aligned K-band
radars which provide differential reflectivity, two parameters of the
DSD can be obtained, e.g., N~0~ and D~0~ in an inverse exponential
distribution. Other parameters related to make attenuation corrections
due to water vapor and cloud droplets must be assumed in the algorithms.
Accounting for heterogeneous beam filling effects also involves crucial
physical assumptions. Direct validation of the associated parameters
related to these various assumptions will require a different approach
to that used by the TRMM GV programme, and places a greater burden on
the GPM GV programme to enhance the types of sensors and their
utilization in seeking to achieve physical validation of the GPM
standard algorithms

The measurements required for validating GMI radiometer algorithms (and
for other GPM microwave radiometers) are likely to be similar to those
required for validating the DPR algorithms. However, more emphasis will
be needed on describing the detailed 3-dimensional microphysical
structure of the precipitation, including: phases and habits of the
precipitating hydrometeors (e.g., cloud droplets, rain droplets,
pristine crystals, snow crystals, ice aggregates, graupel/hail
particles, and melting ice particles), size distributions of these
hydrometeors, water vapor distribution, and the distinct boundaries of
the cloudy and raining regions. Rain radars (at S-, C-, X-, and K-band)
with polarization diversity and cloud radars (90 GHz) will be able to
provide essential information on some of these parameters. Doppler wind
profiling radars have the potential to derive DSD information aloft
concerning the larger liquid and ice hydrometeors. Knowledge of surface
thermometric and radiometric conditions is also important in
radiometer-based retrieval. There is an analogous surface issue for the
DPR algorithms because they will require alternative knowledge of the
path integrated attenuation (PIA) via the Surface Reference Technique
(SRT). For a 2-radar system, the surface reference technique (SRT)
becomes more complicated, albeit very useful information in the
development of dual-frequency SRT algorithms can be provided from SRT
data already gathered by TRMM. To validate the new SRT algorithms,
independent near-surface measurements of the surface backscattering
cross sections under both rain-free and rainy conditions will be needed.

It is emphasized that surface observations of rainfall from dense
raingauge networks, disdrometers, and scanning ground radars will
continue to be needed. However, to go beyond what has been already
accomplished by the TRMM GV programme, more accurate spatial and
temporal matching of ground and space observations will be needed,
better calibration monitoring of the gauges and radars will be needed,
and better methods of combining the ground measurements based on their
respective strengths will be needed . In order to upscale the GV
observations in both space and time, certain GV sensors, particularly
the dense raingauge networks (and relevant disdrometers), any higher
frequency X- and K-band scanning ground rain radars, and any Doppler
profiling radars, must be embedded in the larger domains associated with
the lower frequency S- and C-band scanning ground rain radars and/or the
wide area/low density raingauge networks.

Validation of snowfall retrievals over continental landscapes,
particularly for dry snow, is another important GV issue. Even on the
ground, obtaining snowfall water equivalence observations with ground
sensors is difficult. Thus, one or more "Snow Supersites" will be
needed. Notably, estimation of wet snowfall over ocean, which is
considered a more tractable retrieval problem, has been a difficult with
TRMM measurements. Thus, newer retrieval methodologies for the GPM
Mission will be required.

For microwave radiometer-based rainrate profile retrievals, one evolving
methodology involves "type/regime characterization" of precipitation
systems dependent on a cloud resolving model (CRM) producing radiometer
brightness temperature synthesis using a coupled microwave radiative
transfer model (RTE model). For this algorithm approach, the global
diversity of the GPM GV site network will become the most important
factor.

Finally, it should to be recognized that the validation of 3-hourly rain
maps, assembled from measurements obtained from the various
constellation satellites, will require a different GV methodology than
appropriate for instantaneous rainfall products produced by the DPR and
GMI, plus the other microwave radiometers. In the case of TRMM,
comparisons with blends of ground and satellite data (such as GPCP
products) were performed. Presumably, an analagous approach will be
needed for the GPM Mission.

**2.2.2 NWP as GV Evaluation Tool**

Improvements made during the last decade to the quality of forecasts
produced by numerical weather prediction (NWP) models in operational and
experimental meteorological centers have been the result of several
factors. Greater computing resources have enabled increased horizontal
and vertical resolutions and therefore have allowed a better description
of small-scale processes such as cloud and precipitation formation.
Another factor has been better specification of initial conditions to
start both deterministic and ensemble forecasts. The definition of
"best" initial state of a NWP model is performed in operational centers
within a data assimilation system. The role of a data assimilation
system is to optimally combine short-range forecasts (typically between
6 and 12 hours) and meteorological observations covering a 6 to 12-hour
window. This analysis provides an improved description of the state of
the atmosphere on the model grid at a given time. Based on these
techniques and the concomitant increases in data, forecast skill scores
on large-scale dynamical fields (such as geopotential height at 500 hPa)
have been significantly improved during the recent years, particularly
in the Southern Hemisphere (Simmons and Hollingsworth 2001).

The assimilation of observations related to the water cycle in cloudy
and rainy regions can provide improved initial humidity fields that can
lead to improved forecasts of clouds and rain. This is associated with
the dominant role of latent heat release produced by cumulus clouds on
tropical dynamics and on extra-tropical severe storms. A major challenge
for data assimilation originates from the high spatial and temporal
variability of clouds and rain, since current systems are designed for
atmospheric variables having larger spatial scales (\>500 km) and lower
temporal variability (\>6 hours). Despite these limitations, the
assimilation of precipitation observations has been under investigation
during the last twenty years.

With the advent of 3D and 4D variational assimilation systems, it is now
possible to include rainfall rates in the analysis like any other kind
of observation \-- despite the more complex cloud and rain microphysical
processes that are involved. For example, the National Centers for
Environmental Prediction (NCEP) has recently introduced operationally an
assimilation of satellite derived rain rates from SSM/I and TMI in their
3D-Var system. Along the same lines, ECMWF is developing a methodology
to allow the assimilation of precipitable water in rainy areas in their
4D-Var assimilation system. A number of preliminary studies (e.g.,
Marécal and Mahfouf 2002) have demonstrated that analyses and forecasts
can be improved by assimilating such information from either retrieved
rain rates (Mahfouf et al. 2003), or directly from observed microwave
radiances (Moreau et al. 2003).

With this background, it is evident that a NWP system (dynamical model,
physics packages, and data assimilation scheme) offer several ways to
evaluate the quality of precipitation data:

-   Direct comparison of model fields with observations since model
    fields are obtained from consistent global physical process modeling
    and constrained by large observational data volumes.

-   Improvement of analyses when satellite radiometer-based cloud and
    precipitation data are assimilated:

> \- directly, through comparison with standard validation measurements
> (e.g., from raingauges, ground-based radars, spaceborne radars);
>
> \- indirectly, through comparison with other cloud/rain-related
> observations (e.g., infrared and/or passive microwave radiances).

-   Improvement of forecasts when cloud/precipitation data are
    assimilated:

> \- globally, with forecast skill scores of key meteorological
> parameters;
>
> \- regionally, with event-related evaluations (e.g., referring to
> tropical cyclone track forecasts).

**2.2.3 Hydrometeorological Modeling as GV Evaluation Tool**

Hydrometeorological modeling refers to quantitative precipitation
modeling (QPF) and its application to land hydrometeorological models.
In using this type of modeling for GPM GV purposes, the following
approaches are recommended:

[First]{.underline}, a cloud-resolving atmospheric model (CRM), i.e., a
primitive equation model using nonhydrostatic dynamics and detailed
physics, particulary for: (a) boundary layer flux and turbulence
processes, (b) solar and infrared radiative transfer and heating/cooling
rates, and (c) explicit cloud microphysical processes, is used to
assimilate surface/upper-air satellite-based and/or radar-based
precipitation measurements \-- or latent heating estimates derived from
these measurement.

[Second]{.underline}, a physically-based and detailed land
hydrometeorology model (HYDROMET) is used for estimating hydrological
responses to precipitation (such as soil moisture build up,
evapotranspiration, runoff, and other canopy/soil water storage and
exchange processes) over selected catchments utilizing detailed digital
soil type/texture and land-use/land-cover information.

[Third]{.underline}, the simulated rainfall accumulations from the
coupled CRM-HYDROMET model over various integration periods are
validated against surface measurements of hydrological variables
including precipitation and stream discharges. Such an example is shown
in the diagrams presented in Figure 3 for two rainfalls events from
Supertyphoon Herb (1996) and Typhoon Nari (2001) over the Reservoir
Shiehmen catchment in Taiwan. Once a validated and accurate CRM-HYDROMET
modeling system is developed using the above recommended approaches, it
can be can applied over different catchments, ultimately using *in situ*
hydrological measurements to validate GPM rainfall, hydrometeor
profiles, and latent heat generation. The validated modeling system can,
in turn, be used with GPM precipitation as inputs to better estimate
hydrological cycle processes within the selected catchment. The
validated modeling system can also be used for QPF and other related
hydrological applications such as flood warning and water resources
management.

**2.3 Organizational Structure**

To achieve the above objectives, we need coordination between a
widespread body of research and operational organizations. In addition
to the routine observational programs being managed by a diversive set
of meteorological and hydrological agencies, a number of national and
multi-national precipitation system study projects are planned or are
already underway. We should encourage and coordinate information and
data exchange between these programs and projects with repect to the GPM
GV programme which will be responsible for management of
information/data exchage vis-à-vis GPM's network of GV sites, according.
This process should be conducted within a well-defined international
framework.

![](media/image4.wmf){width="4.574305555555555in"
height="1.9819444444444445in"}

![](media/image5.png){width="4.677777777777778in"
height="1.5298611111111111in"}

**Figure 3:** Lifecycles of observed and simulated rainfalls events for
1996 Supertyphoon Herb (upper diagram) and 2001 Typhoon Nari (lower
diagram) over Reservoir Shiehmen catchment in Taiwan.

One approach to achieve the desired coordination is to form an
international GV Coordination Working Group within GPM's international
framework. This group would oversee:

-   management and coordination of information/data exchange between
    precipitation-related observational programs and projects, and GPM's
    GV programme including its network of GV sites

-   identification and summarization of advantages and deficiencies in
    all observations used for GPM validation purposes

-   development of effective mechanisms for direct interactions with GPM
    algorithm developers

-   creation of GPM GV data management and data dissemination policy

-   definition of effective communications protocol for data exchange
    between GPM GV sites

**2.4 GV Measurement Requirements**

It is anticipated that data collected by international partner GV sites
will be used for multiple applications in GPM ground validation. These
applications will include evaluation of satellite estimates of such
phenomena as: (a) precipitation existence, (b) surface rainfall
accumulation, (c) vertical structure of rainrate, (d) vertical structure
hydrometeor densities and DSD properties, (e) precipitation type (i.e.,
rain, snow, melting ice), (f) relative pattern of precipitation
intensity, and (g) vertical profile of latent heating.

The greatest bandwidth of GV data will come from scanning S-, C-, X-,
and K-band radar observations, however many other lower bandwidth but
important GV observations will be produced, including measurements from:
(a) raingauges, (b) disdrometers, (c) radiosondes, (d) instrumented
towers and ballon-sondes, (e) various upward-viewing radiometers,
high-frequency radars, and Doppler profiling radars, (f) ceilometers and
sky cameras, (g) downward viewing K-band radars, and (h) other
specialized observations. Analyses and short-term forecasts from NWP
models will provide estimates of 4-dimensional temperature, humidity,
and winds \-- plus other key 4D model outputs. Each individual partner
GV site would be expected to acquire its own specific combination of GV
datasets, and then be prepared to contribute those data and data
products they have approved for release for general use, rather than
prescribe a \"one size fits all\" specification for the GPM GV
programme.

Specific information concerning the GV datasets, including details of
the instrumentation, spatial and temporal sampling characteristics,
calibration or other conversion factors, analysis or averaging schemes
applied to the data, and etc., will be required to use these data
effectively and accurately by the user community. Recognizing that any
of the GV data are, at best, only estimates of the true physical state,
one additional requirement will be that the GV data be accompanied by
reasonable descriptions and estimates of their known error
characteristics.

We recognize that the absolute calibration of GV data, particularly
radar reflectivity and differential reflectivity variables, may be
revised after data are collected and recorded. It is recommended that
partner sites send detailed records of calibration estimates to the GPM
GV archive and stabilize and automate calibration to the degree
possible. It is also recommended that GV products minimize dependence on
absolute calibration values.

In order to maximize the utility and flexibility of the archived GV
data, the data need to be available in a format that facilitates
processing and reprocessing for diverse applications by many
investigators over a period of years. It is recommended that the radar
data be available in a polar coordinate format that preserves
information on the azimuth angle relative to true north, elevation
angle, and range gate spacing. Data should be archived either in a
public domain format or a format that is readily transferable into a
public domain format.

Data of greatest interest to the GPM GV programme falls into several
categories:

1.  data obtained during any precipitation event,

2.  data obtained during overpasses of GPM Core or Constellation
    Satellites,

3.  data obtained during overpasses of GPM Core or Constellation
    Satellites \-- with precipitation.

It is important to note that many overpasses will not have coincident
precipitation events and many precipitation events will not have
coincident overpasses. The most valuable subset of data for GV is
represented by category (3) which is the intersection of categories (1)
and (2). A satellite overpass is nearly instantaneous and represents a
snapshot of a precipitation event. The next most desired category of
data is category (1) which will provide information on regional
precipitation climatology, storm structure, evolution, and satellite
temporal sampling errors. It is anticipated that a subset of
precipitation events, such as those that lead to flooding, may be of
high joint interest among the GPM GV partners. The types of high
interest precipitation events need to be identified in collaboration
with the international partners and prioritized for storm duration data
collection. There is also value to GV in the subset of overpasses
without precipitation since the unambiguous absence of precipitation can
help constrain satellite algorithm parameters pertaining to
precipitation existence.

To be considered as an international partner GPM GV site, it is
recommended that at minimum the site contribute operational radar and
on-site gauge (rain/snow) data to the archive with at least 80%
availability. It is recognized that information from research radars
will have lower availability, depending, for example, on the degree of
automation of data collection, levels of funding and competing
requirements. It is recommended that, as a minimum, category (3) data
should be available from research radars for at least 50% of significant
events.

Ideally, the partner operational radar and on-site raingauge data sets
are to be deposited at the designated archive within 48 hours of data
collection to allow for rapid tuning and/or monitoring of the
performance of the space measurement. Near realtime GV data usage, such
as space-ground real time synergy, will require near realtime GV data
delivery. Other sources of GV data, for example, raingauge observations
from national cooperative networks and data from research radars, may
not be available so quickly, although partners should strive to submit
supporting GV data within a 2-week time frame. Some delay may be
acceptable for the off-line validation or parameter tuning in the
algorithms. It would be valuable to set agreed and realistic targets for
delivery of data, tailored to each site and dataset, so that the user
community can have a reasonable expectation of when data will become
available. For consistency among sites and with WMO data sets, all GPM
GV data sets should utilize UTC time and metric units.

**2.5 GV Data Policy**

It is recommended that the data policy for the GPM GV Programme should
abide by the following three requirements:

1.  GV data should be made available to research community.

> It is understood that each country/organization/agency has its own
> data policy, background, and operational constraints. However, an open
> data policy is essential for the maximum utilization and improvement
> of the space data. The GPM data will be global in nature, and thus
> validation in many regions and countries will be important. Currently,
> discussion for the Global Earth Observation (GEO) summit is underway.
> There, the open data policy has been strongly promoted.

2.  Delay of GV data transmission should be minimized.

3.  Level of availability of GV data requires further discussion.

> For example, full volume scanning radar data are generally required.
> However, some facilities may have difficulty in providing this type of
> data because of limiting constraints such as manpower shortage. Some
> agencies may not have enough financial support for continuous GV data
> acquisition and data processing. Operational agencies may provided for
> continuous GV operations while research organizations may have
> difficulties in providing this service. All of these issue will
> require futher deliberation during future International GPM GV
> Workshops.

**2.6 Multi-National, Multi-Regional, & Multi-Agency Sites**

**2.6.1 Concept of Virtual GV Site**

*\[In progress.\]*

**2.6.2 European Virtual Supersite**

Due to the political structure in Europe there are several national or
regional weather services, research agencies and universities. Various
sites are operated in Europe which are suited for ground validation in
the scope of GPM and the European contribution EGPM. In addition weather
radar networks are operated in all countries and data are exchanged
within Europe. Europe offers a wide range of different climatic zones
and precipitation systems ranging from deep convection to baroclinic
frontal systems and snow regions.

![](media/image6.jpeg){width="3.5311023622047246in"
height="3.644488188976378in"} 4). These sites are equipped with
excellent instrumentation. However, not all of the sites can offer a
complete set of instruments as would be anticipated for a supersite.
Financial constrains can limit upgrading of the sites. Currently no
transnational instrumented observation sites are planned. Also, not all
of the proposed sites are located in regions where precipitation is
observed with sufficient frequency during the year. It will be not
possible with the individual sites to cover all of the required features
necessary for a physical ground validation within GPM and EGPM. It is
expected that the sites have strengths in some points and will be able
to provide sufficient information for the retrieval of the error
structure for specific precipitation situations and climatic conditions.

In order to benefit from the research strengths of the existing
instrumentation as well as the scientists associated with the
programmes, the best strategy toward a ground validation program would
be an integrated approach where all these ground validation sites are
tied together to a distributed or virtual ground validation supersite.

The concept of a distributed or virtual supersite will be based on a
networking infrastructure, both physical and organizational. Physical
networking consists of the exchange of data and routines. It is
envisaged to exchange instruments for calibration and intercomparison
campaigns. Several institutions operate mobile radars and other
instruments. Those instruments and radars should be available for
focused observation campaigns at any of the existing sites or in other
regions of interest. These could be areas or precipitation systems where
the determination of the complete error structure is not possible with
the existing instrumentation. Organizational networking means a
structure where the participating site mangers, the national weather
services and GPM and EGPM representatives will be presented. This
network and the respective steering committee has the task to coordinate
the activities within the European sites. It should be envisaged that
financial resources will be available through European agencies and
their supporting programmes. Besides keeping an inventory of available
instruments and their quality, it will be necessary to monitor the error
structure at each of the sites. Recommendations for measurement
strategies, further instrumentation, coordinated projects and field
campaigns will be made by the committee on the basis of the observed
error structures or scientific needs. Field campaigns will also be
necessary to gain sufficient information about the quality of
operational weather radar networks. Currently each service runs
different scanning strategies and data evaluation algorithms. The
combination of weather radar networks essentially covers the whole of
Europe. Monitoring their quality at the supersites will considerably
increase the potential area for ground validation.

In summary the concept of a distributed or virtual supersite will
increase the observational area and thus increase the number of
satellite overpasses for various regions and precipitation systems.
Through the networking activities it will be possible to provide a
maximum of information even though not all sites are fully instrumented.

**2.6.3 NOAA Hydrometeorological Testbed Program**

*\[In progress.\]*

**2.6.4 DOE-ARM Southern Great Plains Site**

The Department of Energy's Atmospheric Radiation Measurement (ARM)
program ([www.arm.gov](http://www.arm.gov/)) operates Climate Research
User Facilities (CRUFs) to study the effects of clouds on global climate
change. The largest and best-instrumented ARM CRUF is located in the
Southern Great Plains (SGP) of the United States. The SGP ARM CRUF,
which is the largest and most extensive climate research field site in
the world, consists of in situ and remote-sensing instrument clusters
arrayed across approximately 55,000 square miles (143,000 square
kilometers) in north-central Oklahoma. The heart of the SGP site is the
heavily instrumented Central Facility located on 160 acres of cattle
pasture and wheat fields southeast of Lamont, Oklahoma. The central
facility contains state-the-art cloud profiling remote sensors, an
extensive array of surface radiation sensors, and a wide variety of
sensors that provide supporting information about the local atmospheric
state. Boundary and extended facilities that contain subsets of the
central facility information are distributed over the balance of the ARM
SGP CRUF. The ARM SGP CRUF lies within the Arkansas Red River Basin and
contains two smaller, experimental watersheds that have been used in
past hydrologic studies: the Little Washita (operated by Department of
Agriculture) and the Walnut River Watershed.

The ARM SGP CRUF will be used to study precipitation processes and
feedbacks in support of the NASA GPM G/V program. Techniques have been
developed by ARM that enable the data from multiple sensors (passive and
active) to be combined to form best estimates of the location of clouds
within the column and the entire ARM CRUF domain. These data are used to
produce estimates of the microphysical and radiative properties of the
clouds. In the latter case, ARM currently produces estimates of the
Broad-band Heating Rate Profile (BBHRP) for the column above the central
facility and the entire SGP site. These heating rate profiles help
quantify radiative feedbacks between clouds and larger scale
circulation, and between radiation and precipitation processes.

Evaluation of the atmospheric water budget, including precipitation,
over SGP ARM CRUF requires information about the large scale forcing in
the region. This forcing can be estimated using variational analysis
techniques developed by ARM, which are now operational. The variational
analysis product quantifies water vapor concentration and distribution,
as well as advection, along with a wide variety of additional forcing
information. These analyses are necessary to achieve closure in the
atmospheric water budget, which is essential for precipitation process
research.

Contained within the ARM SGP ACUF is the Atmospheric Boundary Layer
Experiment (ABLE) site. The ABLE site is well suited for NASA GPM
studies because it routinely operates a set of atmospheric
instrumentation in the Walnut River Watershed (WRW). The WRW has an area
of about 75 km by 100 km, which is two orders of magnitude smaller than
the ARM SGP site. It is a sufficiently small, nearly closed catchment
basin containing a moderate level of ecosystem diversity, which is
amenable to computing many of the components of the hydrological budget.
ABLE has supported two major field campaigns on boundary layer
meteorology by the Cooperative Atmosphere-Surface Exchange Study (CASES)
consortium of scientists (LeMone et al. 2000). Instrumentation operated
routinely for DOE at the ABLE site includes a network of rain gauges,
surface energy components at two locations, soil moisture profiles in
several locations, net ecosystem exchange of carbon at an Ameriflux
site, and boundary layer radar wind profilers at three locations. While
the ABLE site is somewhat removed from the ARM CRUF central facility, it
is a valuable source of additional information for NASA GPM G/V
activities.

In summary, the ARM SPG CRUF provides a unique opportunity to extend
NASA GPM capabilities through validation and process research. ARM is
well equipped to contribute significantly in both areas.

**2.7 GV System Design**

**2.7.1 Copyleft and GNU General Public License**

GPM GV partners have many activities in common. Similar types of
observations are recorded, converted into common formats,
quality-controlled, and processed into end-user products. If freely
available, some existing software could either be used as is or adapted
for many GPM GV applications. A mechanism is needed to facilitate the
use and modification of source code among partner facilities while
preserving the rights of the program's authors.

Uncopyrighted source code can be shared and improved upon but has the
disadvantage that anyone can make a few changes to it and then convert
the program into a proprietary software product.

Copyleft is a general method for making a software program into free
software and requiring all modified and extended versions of the program
to be free software as well. A program that is copylefted contains a
copyright statement by the author and distribution terms. The
distribution terms constitute a legal instrument that gives everyone the
rights to use, modify, and redistribute the program's code or any
program derived from it but only if the distribution terms are
unchanged. As part of the terms of the license, the source code must be
freely available for use, modification, and redistribution.

The GNU General Public License
(http://[www.gnu.org/copyleft/gpl.html](http://www.gnu.org/copyleft/gpl.html))
is a specific means of implementing copyleft. GNU provides distribution
terms text for insertion into source code to implement the General
Public License. The distribution terms text remains in all subsequent
versions of the source code. Modified files must also contain prominent
notices stating the author and date of any change.

An existing software library package, the TRMM Office Radar Software
Library
(<http://trmm-fc.gsfc.nasa.gov/trmm_gv/software/rsl/index.html>),
contains general functions for reading, writing, and manipulating radar
data. This package is published under the GNU General Public License and
is the foundation of many TRMM GV product algorithms. Other groups are
encouraged to copyleft their software to facilitate exchange and
adaptation of source code among GV partners.

**2.7.2 Validation System Design & Integration: International GV
Perspective**

**A. Introduction:** Development of the Ground Validation system from
"*System Engineering*" principles enables, a "***top down***" flow of
requirements into the GV system. These can be traced to the formulation
of the GPM mission within the context of the Global Water and Energy
Cycle. The key elements of the GPM program that will provide the driver
for the GV system are essentially the "mission goals".

The purpose of this section is to develop international GPM-GV system
design methodologies so that it fits well within the overall GPM system.
The term " validation" itself is a key aspect of system engineering "
termed System Validation". Thus the ground validation program can be
readily seen as satisfying one of the key elements of the system
engineering principles for the GPM system.

Validation can be seen either as a subsystem of the GPM system or an "
important system engineering process" for the GPM, because every system
has to be validated. In order to develop the design aspects of
international GV so that it satisfies both aspects, several system
engineering terminologies are defined in the GPM-GV context. In addition
the GPM-GV system should be designed to provide the latitude needed as
part of any scientific discovery process. Just as the GPM mission, the
GV part of it also may envision many scientific discoveries and
technical developments.

The GPM-GV system is an assembly of elements such as remote sensors and
in-situ devices to realize the overall " validation function" that could
not be achieved by an individual element alone. Each element of GPM-GV
may satisfy an individual requirement, but the overall system provides
the " collective action" of system validation. We should be able to
develop " minimum set of " elements necessary along with desirable
properties for risk mitigation. Development of GPM-GV system should
include:

a.  definition of exact functions to be performed by system as dictated
    from GPM system,

b.  examination of ability to perform system function, accounting for
    physical limitations, availability of resources, and capabilities,

c.  development of GPM GV system architecture and define hierarchy of
    subsystems,

d.  definition of procedures that can be used to test functionality,

e.  system integration.

f.  demonstrating required performance and operation of system
    throughout its life, including maintenance and upgrades.

**B. Essential Features of GPM-GV System:** The essential features of
the GPM-GV system can be divided into four parts namely:

a.  ***System Function Definition:*** These include our current
    determination of what we want the GPM-GV system to do. These lists
    can be constructed from the GPM system goals. List of such functions
    are as follows:

> i\. validation of GPM as a system that can be done from ground, such
> as GPM sensor system calibration,
>
> ii\. validating and assisting GPM in quantifying space-time variation
> in rainfall, relationship between rain microphysics/latent heating/DSD
> properties,
>
> iii\. validating and assisting GPM in accurate, precise, frequent &
> globally distributed measurements of instantaneous rainrate & latent
> heat release,
>
> iv\. validating and assisting GPM in error characterization of
> precipitation retrievals,
>
> v\. validating and assisting GPM in frequent sampling & complete
> continental coverage of high resolution rainfall measurements
> including snowfall, hazardous flood forecasting and fresh water
> resources prediction.

b.  ***Communications:*** The communication aspects of the GV system
    specially establishes the protocols of who communicates with who. Is
    there inter-site or inter-process communication? Protocols as to GV
    system communications with GPM satellite algorithm system, as well
    as communication between GV sites and hierarchy of subsystems are
    established here. Data communications is a very important part,
    especially for the international aspects of the GV programme.

**C. Requirements Development and Users:** The international GPM/GV
system is created to meet the goals of the GPM system. Establishing the
requirements is a " crucial step" in the process. Users of the GV system
include, the main GPM system, the scientific community and the GPM-GV
site scientists. A user is anyone who plays role in any stage of the
life cycle and not just the end user. In addition because of the
scientific nature of the GPM mission, the requirement document for GV
subsystem needs to be fine tuned as the needs of the global partner
communities, and scientific understandings change over time. The
architecture of the GPM-GV system needs to be able to accommodate these
changes. There is a separate requirements document being prepared for
GPM-GV. The requirements can be broken up into different levels as
described below.

Special international considerations in the GPM-GV requirements process,
such as environmental, political and competitive factors. If these need
to be considered they must be included in the requirements document.
Examples may be U.S. GPM-GV will not be able to accommodate more than
two sites. Additional example can be EU GPM GV site will be a
distributed site.

The following categories of function requirements, stipulated with
international GPM GV in mind, would help ensure most of the lower level
detailed requirements are captured:

a.  ***Performance Defining What GPM GV System Must Do:*** This
    requirement must come from goals where functional requirements could
    form level 1 system requirements. Suggested set of these
    requirements for GPM GV system are as follows:

> i\. make measurements to assist in validating and refining physical
> formulations used for satellite algorithms,
>
> ii\. provide error characterization of precipitation retrievals,
>
> iii\. make better measurements of local precipitation than satellite,
>
> iv\. observe space and time characteristics of precipitation at local
> scales better than satellite,
>
> v\. assist in validating microphysical and DSD assumptions in
> retrievals and models,
>
> vi\. assist in validating full scale observations of continental
> rainfall and snowfall,
>
> vii\. assist in validating hydrometeorological applications such as
> flood forecasting.

b.  ***Special Constraints:*** These requirements may include ensuring
    coverage to, say, continents, oceans, and mountainous regions. They
    may also include ensuring measurements of both rainfall and
    snowfall.

c.  I***nterface Requirements of International GV Programme with rest of
    GPM:*** These requirements will ensure that GPM GV 's role in issues
    such as algorithm development are being made part of system design
    process.

d.  ***Ease of User Access:*** These requirements would be used to
    define data access \-- communications again being able to trace to
    system goals. For example, it should be straigthtforward to check if
    functionalities are being met.

e.  ***Life Cycle:*** These requirements could specify, for example,
    when international GPM GV sites must start operating.

**D. International GPM GV System Architecture:** Establishing the
architecture is perhaps the most important process in addition to
establishing requirements, in development of the GPM GV system. The
architecture building is typically a visionary and creative process,
that ensures all future changes can be implemented without fundamentally
breaking the architecture. The architectural design creates the form of
the international GPM GV system. There are a few important features that
must be envisioned in the GPM-GV system architecture as given below:

a.  integration of heterogeneous remote sensor and *in situ* data from
    around globe,

b.  incorporation of theoretical information principles in
    distinguishing and assimilating multi-sensor environments; as
    example, information from single raingauge in isolated area may be
    more important than information from similar raingauge co-located
    with radar,

c.  developing strategy how subsystems should interact, thereby defining
    communications architecture,

d.  modularity for upgrades,

e.  reliability and risk.

The precipitation measurement systems in the earth domain (as opposed to
space) include, ground based and airborne radars, in-situ measurement
devices such as disdrometers, rain gages and airborne measurement
probes. In addition airborne radars are also available for precipitation
measurement. Based on the technical expertise developed in traditional
disciplines, these observations could be divided into " horizontal
thrust areas" such as remote sensing instruments, *in situ*
observations, cross-platform simulation and modeling, and outreach. The
international GPM GV super sites can then be seen as "vertical
integration" sites across the thrust areas. Such a "cross discipline"
integration will be an important task of a GV Supersite manager (that
encompasses, all three parts . This process also defines a GV Supersite
that should perhaps do all four parts. A GV Supersite could be defined
as one that addresses all functionalities listed above. Figure 5
schematically illustrates the horizontal thrust areas (classical
disciplines) and vertical integration of these thrust areas at four
hypothetical GV Supersites, while Figure 6 schematically illustrates a
tentative GV architecture.

**2.8 Web Site for International GV Coordination**

As discussed earlier, the primary ground validation of GPM products will
make use of observations of precipitation and related quantities from a
number of well instrumented \"super-sites\" located in several countries
around the globe. The detailed ground validation work will be done by
the organizations providing the GV data, that is, in a *distributed*
rather than a centralized fashion. The GV data will be openly available
to the GPM community, so theoretically any center could validate
satellite products using data from other sites. Realistically speaking,
centers would most likely focus their efforts primarily on their own
validation site(s).

![](media/image7.wmf)

**Figure 5:** Technical discipline areas and vertical integration of
these activities at GV Supersites.

![](media/image8.wmf)

**Figure 6:** Architectural overview of GPM and suggested GV
architecture.

The experience of the TRMM ground validation program was that it was not
possible to enforce a set process for calibrating GV data and conducting
identical satellite product validation at *all* sites. No two sites were
exactly the same, and so different validation methods were employed in
different places. This will also be the case for GPM GV. Rather than
prescribe some \"lowest common denominator\" product generation, we
believe it is better to let each center produce its own optimally
calibrated and quality-controlled reference data, and use these to
evaluate the GPM satellite products.

Given the distributed nature of GPM GV, there is a need to coordinate
and assemble the GV results from various international sites into a
larger view. Ideally, these results could be accessed via a GPM GV
\"Validation Central\" web site that would not only give an overview of
the performance of the GPM algorithms and products across the range of
GV sites, but also provide a forum for discussion of the results.

Advantages of such an international GV web site would include:

a.  algorithm developers, GV providers, and GPM product users would be
    able to get \"big picture\" concerning GPM performance,

b.  information concerning GPM performance across variety of
    precipitation regimes would help ensure that satellite products are
    used appropriately,

c.  results would be shared much faster than normally possible via
    international meetings,

d.  errors would be detected and fixed more quickly,

e.  broader discussion of validation results would enable greater
    improvements in satellite algorithms, and possibly also in reference
    data,

f.  GV scientists would easily view and share validation methods,

g.  GPM would be ensured improved visibility and accountability.

**3.0 Working and Summary Group Reports (De-tersed)**

**3.1 Working Group Reports**

**3.1.1 WG#1a: Retrieval Error Characterization**

**Team**

E. Ebert (Chair), T.L'Ecuyer (Raporteur), *\[remainder to be compiled\]*

**A. What is meant by \"error\"?** The total error of GPM products will
have contributions from temporal and spatial sampling errors,
precipitation detection errors, and algorithm errors. The GV program
will make use of research done for TRMM and other programs to try to
quantify the relative contributions of each type of error.

The actual satellite error is further augmented by a component due to
errors in the reference data itself. It will be difficult, maybe
impossible, to untangle the error in the reference data from that of the
satellite estimates. *[The GV program must supply uncertainty estimates
not only for the satellite estimates but also for the reference data
itsel]{.underline}f,* and provide detailed information on how the
uncertainty estimates are derived.

**B. Error characterization requirements:** While the working group did
not wish to specify a list of particular validation statistics, we did
discuss some fundamental requirements for particular user groups. At the
most basic level, *[precipitation detection errors]{.underline}* must be
quantified in terms of critical thresholds and frequency of occurrence.

**B.1. Error characterization requirements for climate research**:
involve estimates of *[bias errors]{.underline}*. The imperfect quality
of the GV data may not allow us to say whether low amplitude behavior of
satellite estimates (long-term trends, for example) are reliable.
Research will be needed to determine the temporal and spatial scales for
which bias estimates are possible.

**B.2. Error characterization requirements for data assimilation in NWP
models:** involve estimates of *[random errors]{.underline}* (+/- *σR*)
in the satellite products (which could be rain rate, brightness
temperature, reflectivity, liquid water content, etc., depending on how
the assimilation is done). In particular, this means estimating the
diagonal and off-diagonal elements of the error covariance matrices. The
GV program will address this requirement by computing the error
covariance structures at GV sites and exporting those estimates to a
more global scale using the combined DPR and GMI observations. The
question remains as how to best extend these error estimates to the
radiometers on the constellation satellites.

**B.3. Error characterization requirements for nowcasting:** involve
estimates of occurrence of *[extreme (unacceptable)
errors]{.underline}*.

**B.4. Finally, error characterization requirements for algorithm
developers:** were acknowledged to be very complex but were not
discussed in detail, as the group ran out of time. Algorithm developers
will need to work closely with GV providers to ensure their needs are
met.

**C. Stratification of error characterization results into homogeneous
subsets:** according to (for example) latitude bands, season,
land/ocean, and storm type will help provide more robust estimates of
spatially and temporally varying uncertainties.

**D. Particular topics where GV can make big difference:** In addition
to \"standard\" validation, there are some areas where GV can make a big
difference in improving the quality of GPM products. One would be to
establish the limits of the sensors for precipitation detection (e.g.,
what is the sensor\'s sensitivity and how does that depend on the
spatial and temporal resolution of the data or product?). The GV program
should be able to characterize the low-rainrate end of the rainfall
distribution and its regional distribution (through surface and remote
instrumentation and CloudSat). GV data will be particularly useful in
the evaluation of GPM products for extreme events, the evaluation of
rainfall spectra, and the characterization of multi-scale variability.
It can also provide information for use in the satellite algorithms e.g.
*a priori* databases, physical assumptions such as DSD, freezing level,
beamfilling, etc.

**E. Processing and dissemination of error information:** The detailed
local error characterization will be done on a site by site basis by GV
participants, while the Precipitation Processing System (PPS) will be
responsible for applying the global error characterization model(s) to
the full GPM satellite dataset and supplying the error estimates to the
end user.

**F. GV data latency:** Timeliness of the GV data and error
characterization is an important issue. The more quickly these become
available, the more effective they will be for the algorithm developers
and GPM product user community. Is basic-level near-real-time (days or
even hours) GV possible or practical? If so, errors detected by the GV
processing could be used as an early-warning system for satellite (or
GV) product quality. More detailed error analysis products would not be
subject to such stringent timeliness requirements.

**3.1.2 WG#2a: Regional Mapping of GV Error using Supersite Network**

**Team**

M. Hagen (Chair), R. Cifelli (Raporteur), *\[remainder to be compiled\]*

**A. Error transfer from local to regional scale:** The topic of this
working group was the discussion of the question: "How can we transfer
the error assessed at a supersite to sites outside the radar range?"

**B. Precipitation classification:** It was agreed that one solution
could be the classification of precipitation in a number (say 20)
different types. The classification based on precipitation types seems
more appropriate than a classification based on climate regimes.
Precipitation types are defined by instantaneous observations, whereas
climate regimes are defined on a long-term basis. If the error
characteristics have been studied for a given precipitation type at a
supersite it is assumed that the error characteristics for that type can
be transferred outside the supersite range. Further validation will be
performed at other ground validation sites observing the same
precipitation type in order to verify the error characteristics. It is
not expected that any supersite can observe all precipitation types.
Therefore, additional field observing programmes (FOP's) can be
initiated to determine the error characteristic in other regions not
covered by a supersite. FOP's can also be used to redefine precipitation
classification.

**C. Definition of precipitation types:** The definition of the
precipitation types should be based upon the GPM microwave imager (GMI),
since this instrument measures much more indirectly compared to the
dual-frequency precipitation radar (DPR). Also, the temporal and spatial
coverage by GMI is much higher than with the DPR. The classification has
to be developed in close cooperation with the GPM rain retrieval
algorithm developers. Their input is also needed for the enhancement and
refinement of the classification. The classification can be based on
physical parameters, like rain layer depth, ice layer depth, melting
layer intensity, etc., or on statistical observations.

**D. Land and ocean differences:** It is assumed that the classification
has also to consider land and ocean differences, since GMI will perform
differently there. It was also noted that it will be difficult to assess
the error in costal regions (problems with GMI algorithms are expected
there) and in mountainous regions (ground validation by radar or gauge
is difficult). Most difficult will be shallow snow layers since they
cannot be observed by ground based radars except at close distances, nor
by gauges, and even the DPR will not see them.

**3.1.3 WG#3a: New Challenges and Ideas for GV Research**

**Team**

V. Chandrasekar (Chair), E. Gorgucci (Raporteur), L. Facheris, J.D.
Fuentes, D. Hudak, H. Hanado, A. Illingworth, P. Hwang, V. Levizzani, C.
Matzler, A. Mugnai, H. Russchenberg, and M. Schoenhuber

**A. Sources of new challenges**

a.  transition from TRMM to GPM eras:

> i\. system engineering
>
> ii\. rainfall characterization
>
> iii\. microphysics/hydrometeor identification/quantification

b.  global integration.

**B. New challenges and ideas for GV research**

a.  ground radar community should go to drawing board, think out of box,
    and come up with solutions to snowfall remote sensing,

b.  research into characterizing tail of snowfall distribution,

c.  characterize remote sensing of mixed phase precipitation,

d.  microphysical/electromagnetic model validation for remote sensing of
    ice phase (combine with airborne experiments),

e.  light precipitation (fully characterized by GV),

f.  what about precipitation not reaching ground (more common at mid and
    high latitudes) \-- should GV charaterize this type of
    precipitation?,

g.  GV observational research to validate cloud models,

h.  system integration.

i.  

**3.1.4 WG#4a: GV Opportunities for Operational Raingauge/Radar
Networks**

**Team**

R. Ferraro (Chair), C. Kidd (Raporteur), *\[remainder to be compiled\]*

**A. Current status of operational raingauge & radar networks**

a.  USA: daily raingauge and radar currently used (www); 158 NEXRADs
    over US; Doppler 6-10-min scans; Wind profiler networks; USGS
    gauges,

b.  UK: good daily raingauge and radar network -- access?,

c.  Europe: radar data accessible (UK RAL/BADC),

d.  Global GTS: 3-hourly raingauge (US ftp),

e.  Scandinavia: Baltex radar/raingauge data, high latitudes (55-68N),
    vertical profiles, raingauge adjusted,

f.  Spain: raingauge and C-band radar data -- coastal SE: (www)

g.  Others: it would be worthwhile for GPM to compile detailed inventory
    of datasets with relevant information (URLs, POCs, etc.)

**B. "Value added" potential**

a.  error characterization:

> i\. different time scales
>
> ii\. different spatial scales
>
> iii\. meteorology (rain intensity / wind)
>
> iv\. raingauge accuracy (single/multiple-colocated collectors)

b.  common methodology:

> i\. metadata
>
> ii\. standards
>
> iii\. checklists \-- possible errors and corrections

**C. Data delivery**

a.  data access: ftp, www?

b.  data format: common data formats for different data types (radar
    from US, UK, etc)

c.  data latency: routine delivery and time delay

d.  data documentation: comprehensive information on data, POC,
    decoders/software

e.  data display issues \-- reference gifs/jpegs

f.  data archive by operational agencies for raungauge/radar datasets
    required

**D. Obstacles**

a.  time zones and daily data for raingauges

b.  cooperation between organizations/states/countries

c.  minimum detectable rainrates

d.  low level precipitation below radar's minimum tilt angle

e.  radar Z-R relationships

**E. GPM possibilities**

a.  radar:

> i\. NEXRAD: priorities for polarimetric upgrade?
>
> ii\. local media radars

b.  raingauge networks:

> i\. standardization
>
> ii\. error improvements (multiple colocated raingauges)
>
> iii\. automated networks

c.  utilization of other snowfall measurements/precipitation gauges

d.  international cooperation \-- politics/WMO

**F. Concluding note**

Operational networks should be seen as a key element of any GPM GV
campaign by providing the framework and wider context that encompass the
GV Supersites.

**3.1.5 WG#1b: International GPM GV Organizational Requirements**

**Team**

V. Levizzani (Chair), R. Lawrence (Raporteur), I. Bibyk, R. Calheiros,
L. Facheris, R. Ferraro, J. Goddard, E. Gorgucci, C. Kidd, M. Kitchen,
K. Nakamura, J.C. Nam, M. Ralph, G. Roth, H. Russchenberg, and D. Yang

**A. Complete inventory of existing sites**

location

instrumentation (existing + planned)

site availability prior to launch

scope of site

characterization of sites: e.g., core site, secondary site, other

**B. Sites to be established**

National activities for establishing GPM GV facilities

National and International research projects

**C. Additional support for GPM GV**

need to encourage other countries to fill existing gaps

**D. Northern latitude sites**

needed for snowfall retrieval validation

**E. Field campaigns and temporary sites**

to be established based on special needs

**F. Site coordination**

requires significant interactions

**G. Country/site/institution participation**

motivation needed

need for communicating benefits

coordination with WMO, e.g., GEO

**H. Set up of protocol for GPM GV site definition**

**I. Data delivery: realtime or near-realtime issues**

e.g., error characterization for data assimilation purposes or special
applications

**J. Global change understanding poses less stringent data delivery
timing**

e.g., precise "measurements" required for IPCC as opposed to "rough
estimates" for GEWEX

**K. Data availability**

free and open exchange of scientific data

**L. Potential sites with high-quality research and/or operational
radars**

AUSTRALIA Brisbane & Darwin

BRAZIL Sao Paulo & SIVAM radar network in Amazon

CANADA Montreal and southern Canadian radar network

CHINA TBD

EU BALTEX radar network, Cabauw, Catalunya radar network, Chibolton,
Oberpfaffenhofen, Palaiseau & southern France radar network, Rome &
Italian radar network

GREECE TBD

INDIA ISRO's southern India radar sites

ISRAEL TBD

JAPAN Okinawa & Wakkanai

KOREA South Korean radar network

RMI Kwajalein's K-POL site

SOUTH AFRICA TBD

TAIWAN Taiwanese radar network

USA ARM-SGP NEXRAD-Pol, Barrow NEXRAD, California NEXRADs, Colorado
CHILL & S-POL radars, Florida NEXRADs, Texas NEXRADs, Wallops Island
N-POL radar

WEST AFRICA AMMA radar network

**3.1.6 WG#2b: Scientific Goals of GPM GV Research Program**

**Team**

K. Okamoto (Chair), P. Hwang (Raporteur), B. Goodison, C.V.
Chandrasekar, R. Cifelli, J.D. Fuentes, R. Hood, D. Hudak, A. Mugnai,
E.A. Smith, C.H. Sui, A. Tokay, and R. Uijlenhoet

Scientific goals of GPM GV Research Program are to develop and improve
an international strategy to measure and validate precipitation over a
range of time and space scales over the globe. Its scope covers: 1.
algorithm, 2. water budget, 3. NWP, 4. data assimilation, 5. etc.

**A. GV research to improve precipitation measurement contributes to:**

-   algorithm improvement

-   hydrometeorological process modeling

-   new measuring systems

-   ground remote sensing and i*n situ* measurement of snow

-   cloud life cycle processes related to precipitation systems

-   improvement of surface emission and scattering characterization

-   improvement of numerical models

**B. Better understanding of error characterization in near-realtime:**
for GPM space-borne sensor products.

**C. Development of scientific methodology:** to integrate and interpret
heterogeneous globally distributed GV data.

**3.1.7 WG#3b: Accuracy Requirements**

**Team**

P. Bauer (Chair), J. Schulz (Raporteur), *\[remainder to be compiled\]*

**A. General remarks**

-   Major point in describing accuracy requirements is understanding of
    processes instead of only giving accuracy thresholds and goals for
    surface rain rate. For instance, GV is for validating mm/h but it is
    more important to validate processes, e.g. accuracy of 0.1 mm/h at 2
    mm/h rain rate means different things in different areas. Number of
    constraints of problem is most relevant part, accuracy of DSD, LWC,
    etc.

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-   Can accuracy of GV and satellite products be defined in same way?

-   We need error distributions!

-   Situation classification scheme.

-   Define interface between science and engineers, i.e.. put scientific
    profile into work. What is minimum set of instruments needed for
    achieving required accuracy, e.g., with radar, are polarization and
    Doppler capabilities needed?

-   Do we need models to fill gaps of information?

-   Accuracy in relation to different applications?

-   Is there accuracy limit? \[This question has to be answered because
    decisions to spend money are at stake.\]

**B. Retrieval error sources**

Instrument dependent:

-   sensitivity (detection)

-   calibration

-   sampling (temporal)

-   Matching / representativity

-   transformations between parameters (linearity, unknown physics)

-   scene dependence

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-   natural variability

-   geophysical noise

-   geophysical bias (climatic anomaly; El Niño)

Do we need models to fill gaps of information?

Empirical methods like trend analysis to beat errors down in successive
levels are needed. From methodological side, is it solved by additional
information inserted at different levels?

Should a priori knowledge, e.g. more rain during El Niño year, go into
analysis?

Requirements depend on quality of GV data.

**C. Information level**

-   spatial and temporal sampling/coverage (includes accumulation),
    correlations

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-   secondary parameter: RR, Q2, snowfall accumulation (δSF)

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```
-   primary parameter: T, q, N(D), rho(D),

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-   calibrated measurement and sensitivity: Ze, TB, ....

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-   detection, sensitivity, classifiction

**D. Methodology to estimate accuracy**

-   long time series analyses

-   spatial distribution analyses

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-   error modelling

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-   hardware design (e.g., use of polarization radar)

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-   experiment design:

i\. case studies

ii\. processes

iii\. extra data (e.g., use of IOPs)

iv\. use of models

**Table 1:** *\[title needs to be inserted\]*.

+------------------------+------+-------+-------+--------+---+-----+
| *                      | **P  | *     | **H   | **     | * | **  |
| *Applications/Accuracy | roce | *Algo | ydrol | Nowcas | * | Cli |
| Requirements**         | ss** | rithm | ogy** | ting** | N | mat |
|                        |      | Va    |       |        | W | e** |
|                        | *    | lidat |       |        | P |     |
|                        | *Stu | ion** |       |        | * |     |
|                        | dies |       |       |        | * |     |
|                        | \*** |       |       |        |   |     |
+------------------------+------+-------+-------+--------+---+-----+
| **Detection            | \+   | \+    | \+    |        |   |     |
| Sensitivity**          |      |       |       |        |   |     |
+------------------------+------+-------+-------+--------+---+-----+
| **Calibrated           | \+   | \+    |       |        | \ |     |
| Measurement and        |      |       |       |        | + |     |
| Sensitivity: e.g., Ze, |      |       |       |        |   |     |
| TB, ....**             |      |       |       |        |   |     |
+------------------------+------+-------+-------+--------+---+-----+
| **Primary Parameter:   | \+   | \+    |       |        |   |     |
| e.g., T, q, N(D),      |      |       |       |        |   |     |
| r(D)**                 |      |       |       |        |   |     |
+------------------------+------+-------+-------+--------+---+-----+
| **Secondary Parameter: | \+   | \+    | \+    | \+     | \ |     |
| e.g., RR, Q2, SF       |      |       |       |        | + |     |
| accumulation (dSF)**   |      |       |       |        |   |     |
+------------------------+------+-------+-------+--------+---+-----+
| **Sampling/Covering/** | \+   |       | \+    |        | \ | \+  |
|                        | Only |       |       |        | + |     |
| **Correlations**       | samp |       |       |        |   |     |
|                        | ling |       |       |        |   |     |
+------------------------+------+-------+-------+--------+---+-----+

\*Mesoscale Models Parametrization improvements

Global Models

General understanding Microphysics

Radiative Transfer

Electromagnetic issues

Matrix entry A13 (hydrology/detection) sensitivity limit vs.
pdf(parameter).

Matrix entry A32 Parameters for algorithm developer: Full set of N(D) is
required ( mean and variances are not enough).

Matrix entry A55 (NWP/sampling) need error covariance,

Off diagonal terms

Matrix entry A56 (Climate/sampling), gauges at a sufficient density for
pinning down bias errors.

**3.1.8 WG#4b: Basic Radar Products & Implications for Observation
Strategy**

**Team:**

S. Yuter (Chair), J. Koistinen (Raporteur), S. DiMichele, M. Hagen, A.
Illingworth, S. Shimizu, and D. Wolff

**A. Summary:** Working Group 4b made recommendations for GV partner
local radar products and associated observation strategies. Three
general categories of products are described: text products summarizing
information on the statistical characteristics of the radar data and
derived parameters, 2D products providing maps of the horizontal
variability of near surface radar observed and derived parameters, and
3D products describing volumetric echo structure. Regional composites
could include products based on several of the 2D and 3D single radar
products. Several types of time-integrated 2D and 3D products are also
recommended. A brief discussion of useful ancillary data from other
sources and remaining challenges concludes the report.

**B. Background:** The recommended GV radar products address the
scientific objectives defined at the GPM GV Working Group meeting in
Seattle, Washington in February 2002 (Yuter et al. 2002). These
objectives are:

a.  determination of minimum detectable surface precipitation rate,

b.  classification of precipitation in (x,z) and (x,y) dimensions into
    hydrometeor categories such as rain, snow, mixed, and graupel/hail,

c.  classification of 3-dimensional precipitation structure,

d.  determination of spatial pattern of surface precipitation intensity,

e.  quantitative estimation of surface precipitation rate,

f.  description of errors associated with each of above items (a-e).

During the October 2003 Precipitation Measurement Missions meeting in
Greenbelt, Maryland, tasks related to the evaluation of the satellite
estimated vertical profile of latent heating were added to the GPM GV
responsibilities. The specific objectives for latent heating validation
are still being defined but include collection of volumetric horizontal
divergence data and classification of radar echo into convective and
stratiform precipitation components.

The working group focused on potential GV products associated with
surface-based scanning radars including S-band, C-band or X-band Doppler
polarimetric and non-polarimetric radars. Based on presentations at the
meeting, potential GV partner radars include a mixture of operational
radars with fixed scan strategies and research radars with flexible scan
strategies. It is anticipated that logistical, geographical, and
operational constraints will limit partner radars to data collection for
a subset of the recommended products. The full list of recommended
products in this document represents a superset of products from a
variety of radar types and locations.

**C. General recommendations:** These recommendations represent the
consensus of the working group:

1.  It is vital that information on uncertainties be routinely included
    with every GV observed and derived product.

2.  Polar coordinate data from participating radars will be archived and
    available for use by all GV partners (see Section 3).

3.  Cartesian products are easier to compare to satellite data than
    polar coordinate data since range dependencies can be minimized when
    Cartesian grid is appropriately scaled for radar characteristics and
    maximum product range. Since some interpolation schemes can
    introduce artifacts and degrade information, common high quality
    objective interpolation methodology needs to be agreed upon and
    adapted to ensure quality and consistency among Cartesian products
    from different sites.

4.  For all GPM applications, snow accumulation should be expressed in
    units of equivalent liquid per unit time. Snow accumulation depths
    vary with crystal shape and temperature and hence are difficult to
    compare among sites and storms.

5.  Observed products such as radar reflectivity should have
    non-meteorological echoes identified with bad quality flag and
    confidence level. Non-meteorological echoes should be removed before
    derived products are calculated.

**D. Archival of original radar measurements:** Polar coordinate radar
data represent a key data set for GV. All other products are derived
(and reprocessed) from the originally recorded polar data. It is vital
to the success of GV that the originally recorded radar data be archived
and accessible. The archived format should either be a public domain
format or one that is readily transferable to a public domain format.
The archived polar coordinate data must preserve information on the
azimuth angle relative to true north, the elevation angle, and the range
gate spacing.

To be of value for error characterization products utilized by
operational users, GV radar data needs to be available soon after data
collection. Ideally, partner radar data should be deposited at the
designated GV archive within 48 hours of data collection. It is
recognized that some radar data sets may not be available within 48
hours. These data sets will be valuable for detailed analysis and
climatological applications which have less stringent latency
requirements.

Quality control (QC) should be applied to the polar coordinate data
prior to processing of derived products. Local knowledge should be
applied as much as possible in the removal of non-meteorological echoes
especially for QC parameters which vary with space and time. GPM GV may
find it useful to apply a second round of QC if it is capable of
detecting additional non-meteorological echoes or if the automated
national system does not include advanced QC techniques.

Distinguishing pixels with no precipitation from those with lost
precipitation signal will likely be a demanding task. The latter
category includes beam blocking due to mountains which can vary with the
thermodynamic profile and radar beam overshooting of shallow
precipitation at long ranges which can vary storm to storm. Individual
quality factors at each pixel could be summed into a general quality
class flag.

**E. Text products:** The purpose of text products is to provide an easy
to use summary of radar observed and derived products. Likely
applications of text products are to identify times of interest for
detailed study within the GV data sets, and for comparison of basic
statistics among the GV sites, GPM satellites, and regional model
output.

**F. 2D near-surface scan products:** The purpose of 2D near-surface
scan products is to document the horizontal variability of observed and
derived parameters. 2D products are based on a single low-level
elevation angle PPI scan (≤ 1°). These products are distinguished from
3D

**Table 2:** Recommended text products. By definition, all products
contain information on uncertainties of constituent variables.

  ----------------------------------- -----------------------------------
  **Name**                            **Description**

  Precip area above Z thresholds      X km^2^ of precip within radar
                                      domain of Y km^2^ for Z thresholds
                                      of 0, 10, 20 dBZ

  Surface precipitation types present Rain, snow, mixed, graupel/hail

  Presence of distinct melting layer  Yes or No in volume

  Rain layer depth                    km -- average, standard deviation,
                                      min, max within volume

  Ice layer depths for Z thresholds   km - average, standard deviation,
                                      min, max within volume for Z
                                      thresholds of 0, 10, 20 dBZ

  Echo top height for Z thresholds    km -- average, standard deviation
                                      for Z thresholds of 0, 10, 20 dBZ

  Attenuation correction (X- and      Whether attenuation correction is
  C-band radars)                      applied and some information on its
                                      application.

  Coincident GPM Core and             Time, distance to nadir, ascending
  Constellation Satellite overpasses  or descending and name of satellite

  Z, (ZDR) calibration                Offset and its uncertainty versus
                                      recorded data
  ----------------------------------- -----------------------------------

*[Notes on text products]{.underline}*

-   *Suggested Z thresholds include values below and above expected GPM
    core satellite DPR sensitivity.*

-   *Echo top height is dependent on radar sensitivity and scan strategy
    which varies from radar to radar. Hence echo top height statistics
    will be difficult to compare among sites.*

products which require volume scans, i.e. a set of PPIs at different
elevation angles. Applications of 2D products include comparison with a
wide range of satellite intermediate and final map products.

All the products on the table below are recommended to be on an
objectively interpolated Cartesian grid (Trapp and Doswell 2000). Since
radar characteristics such as beam width and the maximum usable product
range vary among radars and precipitation vertical structures, the
optimal Cartesian grid resolution and size may be radar and seasonally
specific.

When multiple coordinated radars are available within a region, some of
the 2D map products below may be able to be produced as regional
composites (Section 8).

As part of GV site documentation, a detailed map is needed of the
surface background types in terms of water, land, and potentially
land-surface type (urban, forest, grassland etc) for each pixel in the
2D Cartesian grid.

**G. 3D volume scan products:** 3D products require volume scans
containing several elevation angles. These products document the 3D
variability of observed and derived parameters. Some of these products
are 2D maps derived from volumetric data. The working group decided it
made more sense to group products by type of radar scan needed to
produce them as compared to their

**Table 3:** Recommended 2D products where QC indicates
quality-controlled variable. By definition, all products contain
information on uncertainties of constituent variables.

+-----------------------------------+-----------------------------------+
| **Name**                          | **Description**                   |
+-----------------------------------+-----------------------------------+
| QC-Z long range surveillance scan | Cartesian map of observed         |
|                                   | reflectivity based on low PRF     |
|                                   | surveillance scan at low          |
|                                   | elevation angle                   |
+-----------------------------------+-----------------------------------+
| QC-observed radar variables       | Cartesian map of each of observed |
| within lowest tilt of volume scan | parameters which serve as input   |
|                                   | for derived 2D products           |
+-----------------------------------+-----------------------------------+
| Location of non-meteorological    | Diagnostic map \--                |
| echoes                            | non-meteorological echo tagged    |
|                                   | with bad quality flag and         |
|                                   | confidence (may be incorporated   |
|                                   | into QC-Z and QC-observed         |
|                                   | products)                         |
+-----------------------------------+-----------------------------------+
| Attenuation correction            | Diagnostic PPI scan showing       |
|                                   | attenuation correction values in  |
| (X- and C-band radars)            | dBZ at each polar coordinate      |
|                                   | pixel                             |
+-----------------------------------+-----------------------------------+
| Range where radar beam overshoots | Diagnostic map of usable radar    |
| precipitation                     | range for each volume \-- of      |
|                                   | particular interest for shallow   |
|                                   | precipitation                     |
+-----------------------------------+-----------------------------------+
| Precipitation echo locations      | Derived Cartesian map \--         |
|                                   | existence of precip echo for      |
|                                   | various Z thresholds (say 0, 10,  |
|                                   | 20 dBZ) (for some applications    |
|                                   | mm/h thresholds may be useful)    |
+-----------------------------------+-----------------------------------+
| Surface precipitation by          | Derived Cartesian map of          |
| hydrometeor type                  | estimated surface values,         |
|                                   | including rain, snow, mixed rain  |
|                                   | and snow, graupel/hail (of        |
|                                   | particular interest in            |
|                                   | midlatitudes)                     |
+-----------------------------------+-----------------------------------+
| Convective and stratiform         | Derived Cartesian map \--         |
| precipitation                     | objective classification of radar |
|                                   | echo regions (of particular       |
|                                   | interest in tropics for use in    |
|                                   | partitioning latent heating)      |
+-----------------------------------+-----------------------------------+
| R derived from Z                  | Derived Cartesian map of          |
|                                   | estimated surface precip          |
|                                   | intensity (rainrate or snowfall)  |
|                                   | based on reflectivity, scan       |
|                                   | geometry, and storm structure     |
|                                   | without use of polarimetric       |
|                                   | parameters (vertical profile      |
|                                   | correction applied to each pixel  |
|                                   | should be included as field in    |
|                                   | this product)                     |
+-----------------------------------+-----------------------------------+
| Hybrid R                          | As above except including         |
|                                   | available polarimetric variables  |
|                                   | as appropriate                    |
+-----------------------------------+-----------------------------------+

*[Notes on 2D products]{.underline}*

-   2D maps include products representing both data at height of radar
    beam and estimates of real ground/sea surface value derived from
    measurements at height of radar beam \-- which is always above
    surface. Precipitation type and rainrate will be compared to
    surface-based *in situ* measurements. T hese categories of map
    products are, by definition, estimates of surface values which take
    into account vertical profile of precipitation.

-   Overlaying surface precipitation intensity and surface precipitation
    hydrometeor type maps will distinguish snow rates from rainrates.

-   Using -10 dBZ threshold within 50-km range of radar would be useful
    for precipitation echo locations in snow.

-   Depending on how GV convective/stratiform classification algorithm
    is modified for GPM, it may become 3D product. Current TRMM GV
    convective stratiform product is given on 2 x 2 km horizontal
    resolution Cartesian grid to 150 km range based on information in
    lowest tilt of radar volume scan (Steiner et al. 1995). Algorithm
    parameters are tuned for particular precipitation climatology and
    radar with volumetric data (Yuter and Houze 1997). Current TRMM PR
    convective stratiform algorithm utilizes combination of horizontal
    (5 x 5 km) and vertical (250 m at nadir) precipitation echo
    information (Awaka et al. 1998).

-   Maximum range that hybrid techniques for estimating R can be
    successfully applied is subject of active research within radar
    community. Within literature, these techniques are often restricted
    in range compared to non-polarimetric methods.

output format. For example, echo top height is a 2D map but 3D data are
required to derive it so it is classified as a 3D product.

Primary applications are comparison to 3D observed and derived products
from the DPR and for assessment of physical assumptions regarding the 3D
storm structure used in estimating surface precipitation from satellite
passive microwave observations. Divergence products are for evaluation
of satellite-derived latent heating estimates.

With the exception of the RHI product (see notes below) and the VVP and
VAD products, the balance of products in the Table 4 are recommended to
based on data objectively interpolated to a 3D Cartesian grid. See
comments on 2D products (Section 5) regarding grid resolutions and
sizes.

**Table 4:** Recommended 3D products where QC represents quality
controlled variable. By definition, all products contain information on
uncertainties of constituent variables.

+-----------------------------------+-----------------------------------+
| **Name**                          | **Description**                   |
+-----------------------------------+-----------------------------------+
| RHI along satellite track during  | For comparison to DPR obs,        |
| GPM Core Satellite overpasses     | satellite-derived attenuation     |
| with precipitation                | correction, and D~o~              |
+-----------------------------------+-----------------------------------+
| QC-observed radar variables       | 3D Cartesian volume of observed   |
| within volume                     | parameters \-- which serve as     |
|                                   | input for derived Cartesian 3D    |
|                                   | products                          |
+-----------------------------------+-----------------------------------+
| Location of non-meteorological    | Diagnostic 3D volume \--          |
| echoes                            | non-meteorological echo tagged    |
|                                   | with bad quality flag and         |
|                                   | confidence (may be incorporated   |
|                                   | into QC-observed products)        |
+-----------------------------------+-----------------------------------+
| Attenuation correction            | Diagnostic PPI volume showing     |
|                                   | attenuation correction values in  |
| (X- and C-band radars)            | dBZ at each polar coordinate      |
|                                   | pixel                             |
+-----------------------------------+-----------------------------------+
| Echo top                          | Derived Cartesian map of maximum  |
|                                   | height of precip echo for various |
|                                   | Z thresholds (say 0, 10, 20 dBZ)  |
+-----------------------------------+-----------------------------------+
| Rain layer height                 | Derived Cartesian map \--         |
|                                   | expected to vary across           |
|                                   | baroclinic fronts                 |
+-----------------------------------+-----------------------------------+
| Hydrometeor classification        | Derived Cartesian 3D volume \--   |
|                                   | echo volume pixels classified by  |
|                                   | hydrometeor type (requires        |
|                                   | polarimetric parameters)          |
+-----------------------------------+-----------------------------------+
| Vertically integrated LWC and IWC | Derived Cartesian map of          |
|                                   | vertically integrated values      |
|                                   | based on Z or polarimetric        |
|                                   | parameters                        |
+-----------------------------------+-----------------------------------+
| Velocity Volume Processing (VVP)  | Derived profiles based on         |
| \-- yields profiles of horizontal | cylindrical volume of radial      |
| winds, divergence, and Z          | velocity and Z data within 30-40  |
|                                   | km range of radar                 |
+-----------------------------------+-----------------------------------+
| Velocity Azimuth Display (VAD)    | Derived profile based on conical  |
| \-- horizontal wind and           | volume of radial velocity data    |
| divergence profiles               | within precip echo                |
+-----------------------------------+-----------------------------------+
| CFADs of Z by category            | Derived array of joint frequency  |
|                                   | distribution with height of Z for |
|                                   | categories of precip echo within  |
|                                   | 3D Cartesian volume               |
+-----------------------------------+-----------------------------------+
| Vertical profiles of Z by         | Derived from precip echo within   |
| category                          | 3D Cartesian volume               |
+-----------------------------------+-----------------------------------+
| CFADs of horizontal divergence by | Derived array of joint frequency  |
| category for multi-Doppler or     | distribution with height of       |
| bistatic sites                    | divergence for categories of      |
|                                   | precipi echo within 3D Cartesian  |
|                                   | volume                            |
+-----------------------------------+-----------------------------------+
| Vertical profiles of horizontal   | Derived from precip echo regions  |
| divergenceby category for         | within 3D Cartesian volume        |
| multi-Doppler or bistatic sites   |                                   |
+-----------------------------------+-----------------------------------+

####### Notes on 3D products

-   Working group makes strong recommendation to obtain RHIs parallel to
    GPM Core Satellite track within DPR K~u~-band swath. To be of most
    value, largest dimension of GV radar's effective beamwidth should
    not exceed ground resolution of DPR instrument. Only subset of GV
    partner radars will have operational flexibility to obtain these
    RHIs. Applications of this RHI product may require both polar
    coordinate and objectively interpolated Cartesian versions.

-   Echo top height (see notes in Section 4). Also, -10 dBZ threshold
    would be useful within 50-km range of radars with sufficient
    sensitivity.

-   Rain layer height is similar but not identical to bright band
    height. Rain layer height is parameter used in radiative transfer
    calculations.

-   Contoured frequency by altitude diagrams (CFADs, Yuter and
    Houze 1995) of Z by categories are current TRMM GV product. Their
    purpose is to provide concise information on frequency distribution
    with altitude of Z such as skewedness, modes, min, and max etc.

-   Categories of precipitation for profiles and CFADs include
    combinations of total, convective, and stratiform precipitation
    components with surface types of land, ocean, coastal, and all used
    for TRMM. For GPM, additional categories are added for midlatitude
    sites related to surface precipitation types such as rain, snow,
    mixed, and graupel/hail.

-   Quality of VVP (Waldteufel and Corbin 1979; modified by Koscielny et
    al. 1982) and VAD (Lhermitte and Atlas 1961; Browning and
    Wexler 1968) products is function of volume scan strategy, i.e.,
    number and spacing of elevation angles and maximum elevation angle,
    and how well assumption of horizontal homogeneity holds within
    analyzed volume. Stratiform precipitation, which is more uniform in
    horizontal, usually yields higher quality VVP and VAD output than
    convective precipitation. In practice, these products are usually
    derived for subset of scanned volume less than 50-km range from
    radar.

**H. Time-integrated products:** The working group recommends the use of
only two accumulation time periods which can be combined by users into a
variety of customizable time scales such as 5-day, calendar months,
30-day periods, seasonal, etc. The two recommended time scales are:

-   24 hours (0000 UTC-2359 UTC)

-   storm duration

Storm duration may be difficult to define precisely. We suggest
guidelines be developed for GPM GV on this topic. Based on working group
discussions and the current TRMM products, the time-integrated products
identified in Table 5 are suggested.

**Table 5:** Recommended time-integrated products for both 24 hour and
storm duration time periods (see above discussion concerning
precipitation categories). By definition, all products contain
information on uncertainties of constituent variables.

  -----------------------------------------------------------------------
  **Name**

  Rainfall accumulation maps in units of mm height per m^2^ area

  Snowfall accumulation maps in units of equivalent liquid mm height per
  m^2^ area

  Accumulated vertical profiles of Z by precipitation category

  Accumulated CFADs of Z by precipitation category
  -----------------------------------------------------------------------

Included with all time integrated products should be information on the
time interval between the radar scans used to compute the product. The
time interval between low level scans should ideally be ≤ 5 min. For
each time-integrated product, information on data gaps and the
associated confidence level are also needed. For example, for days with
no data gaps or if the radar was taken down during a non-precipitating
period for scheduled maintanence, the confidence that the 24 hour total
represents the actual accumulation would be high. In contrast, if the
radar broke down in the middle of a storm, the confidence would be low.
Note that confidence level in this context relates to temporal sampling
gaps. Information on the total uncertainty of the time-integrated
products based on their sampling interval and on the uncertainties in
the instantaneous precipitation rate and Z products is also needed.

**I. Regional composite products:** Regional composite products based on
data from multiple coordinated radars (Michelson et al. 1999, Raschke et
al. 2001, Koistinen and Michelson 2002) have the benefits large area,
overlapping coverage, and often enhanced quality compared to single
radar products. Since these data are likely to be processed and
reprocessed for multiple applications, data arrays are needed for GPM GV
applications. Potential regional composite products may be able to be
adapted from a subset of the 2D and 3D products discussed in Sections 5
and 6.

**J. Ancillary data:** The working group briefly discussed several other
types of surface-based measurements that would add significant value to
the weather radar observations. These are:

-   Ceilometer-measured cloud-base heights

-   Vertical profiles of liquid and ice water contents from cloud
    radars.

Additionally, NWP outputs for the GV radar domain including the hourly
thermodynamic profile above each site, 3D winds, and cloud and rain
parameters would be very useful to have in a form that facilitates
comparison with the radar products. It is recommended that the NWP
outputs over the GV sites data be developed as a GV product and archived
with the local radar site products.

**K. Some remaining challenges:** The successful validation of
satellite-derived snow estimates requires progress on several challenges
in snow measurement from the ground. Current methods for estimation of
snow rate from observed radar reflectivity are widely considered to be
unreliable. A research focus on this problem is needed in order to
characterize and potentially reduce uncertainties to acceptable levels
for GPM applications. Another important challenge is the validation of
light snow rates which is difficult with current instruments. Some new
instruments including the DRI/NCAR hotplate and weighing gauges by
Geonor and OTT need to be tested for GPM applications and their
uncertainties characterized under a range of conditions.

In the course of writing up this report, several issues arose which will
need to be addressed at future meetings:

-   Given differences in radar beam widths and maximum usable range, to
    what degree should Cartesian product grid resolutions and sizes be
    standardized among partner radars.

-   Where is responsibility for removal of non-meteorological echos in
    observed radar parameters? Are they to be flagged at local sites
    before data are sent on to GV archive or should QC be performed on
    archived data prior to product processing? It may be difficult to
    require standardized QC methodology to be performed by operational
    radars.

**3.2 Summary Group Reports**

**3.2.1 Potential GV Site Concept**

**A. What is a GPM GV site required to do?**

a.  provide primary inputs into GV process

> i\. reflectivity calibration
>
> ii\. spatial information (horizontal and vertical, bright band,..)
>
> iii\. rainfall rate and snowfall
>
> iv\. DSD properties

b.  provide additional physical inputs

> i\. cloud properties
>
> ii\. PBL structure including initiation of convection and turbulence
>
> iii\. radiation and energy exchanges

c.  address different climate types

> i\. high latitudes
>
> ii\. mid latitudes
>
> iii\. tropics
>
> iv\. complex orography
>
> v\. maritime, continental, and coastal areas

d.  address different dominant rainfall types

> i\. convective rainfall
>
> ii\. stratiform rainfall
>
> iii\. drizzle and warm rainfall
>
> iv\. snowfall and other frozen forms of precipitation

A core grouping of GPM GV sites should be operated continuously.
However, available resources and seasonality of certain phenomena should
be part of this consideration.

**B. Field campaigns at certain sites will be desirable**

a.  to bring together instruments of opportunity

b.  to be phased and colocated with international experiments being
    planned independently (e.g., AMMA)

**C. Primary infrastructure for each GV site**

a.  although different sites will concentrate on different instrument
    suites, minimal instrumentation shuold include:

i\. rainfall: calibrating raingauges, disdrometers, and at least one
operational or dedicated research radar (S- or C-band) which is close to
GV site, with 2-km resolution, preferably with full polarization for
detailed studies, and capability for volume scanning

> ii\. snowfall: scanning (X-band) radar, heated plates and snow gauges,
> and optical forward scattering devices (e.g., Parsivel, 2D video
> disdrometer)

b.  high capacity internet connection

c.  data archive containing at least several Terabytes

**D. Secondary infrastructure for each GV site**

a.  Doppler wind profiling radar (preferably dual-frequency)

b.  Lidars - aerosol, PBL, water vapor, thin clouds (supercooled layers,
    ice crystals)

c.  cloud radars (94 GHz) for LWCs/IWCs

d.  upward pointing X- or K-band Doppler radar (rainrates, bright band,
    DSD, latent heating)

e.  upward pointing microwave radiometer for LWP and ground-equivalent
    measurements vis-a-vis satellite radiometers

f.  SW/LW radiometers for radiative fluxes and energy budget analysis

g.  PBL instrumentation, sonic anemometers, flux towers

h.  microwave link for path integrated rain rate

**E. Desirable characteristics of each GV site**

a.  network-embedded so that natural upscaling of products can be
    implemented

b.  flexibility to derive necessary parameters, e.g., not all
    operational networks can provide Z rather than R

**F. Finally, each GV site requires**

a.  to be "officially" designated

b.  to be appointed with clear attribution of duties, e.g., rain, snow,
    cloud-aerosol interactions, etc. \-- because:

> i\. national or international organizations will be funding site
> activities
>
> ii\. funding organization must be clearly motivated
>
> iii\. benefits to funding organization must be clearly evident

**3.2.2 Country, Region, and Agency Site Readiness**

In order to obtain an initial perspective of each county's readiness
insofar as GV instrumentation infrastructure, ad hoc selected
representatives from each country in attendence (or that had been
invited to attend but could not) were asked to prepare brief summaries
of the most likely current (or future) GV instrumentation that might be
applicable for the GPM GV site network. The national summaries are
presented in section 4.2. It should be cautioned that these summaries
are not necessarily complete or fully accurate. Instead, they represent
an attempt by the selected representatives to provide a rough estimate
of infrastructure assetts.

**4.0 GV Site Status and Future Plans**

**4.1 Nation by Nation Summaries**

The following 21 sub-sections provide brief summary descriptions of
current GV and anticipated GPM GV capabilities and activities in each of
the 21 countries represented at the Abingdon Workshop through invitation
to the meeting (17 of 21 national representatives or groups of
representatives were able to attend).

2.  ***Australia***

**GPM Ground Validation In Australia**

GPM ground validation in Australia will be conducted using a two-pronged
approach. In northern tropical Australia, the Bureau of Meteorology has
a well-instrumented climate monitoring station at Darwin (12S, 131E).
Within a (200 km)^2^ region there are two C-band radars (one Doppler and
one dual-polarized), a 50/920 MHz profiler, a disdrometer, a C-scale
network of 25 rain gauges, half of which are co-located with automatic
weather stations, and a mesoscale rain gauge network with a large number
of gauges. In addition the Department of Energy maintains an Atmospheric
Radiation Measurement program (ARM) Tropical Western Pacific site at
Darwin, with a complete array of instrumentation for measuring
meteorological, cloud, and radiative conditions (for details please see
<http://www.arm.gov/docs/sites/twp/darwin.html>). The Darwin
observations have been used

![](media/image9.png){width="6.309722222222222in"
height="3.8055555555555554in"}

**Figure 7:** Large-scale validation for one of GSFC\'s real-time
TRMM-based algorithms.

extensively to validate TRMM satellite precipitation estimates, and have
the advantage of being able to sample both maritime and continental
convection. An additional site will be developed near Brisbane (27S,
153E) employing an S-band dual polarization, dual frequency radar and
associated rain gauge observations.

In addition to the above \"supersite\" approach, a national scale
validation will be conducted using the Bureau of Meteorology\'s
operational daily rain gauge analysis, based on \~1000 observations
(real-time), or \~5000 observations (a few months after real time). An
example of large-scale validation for one of GSFC\'s real-time
TRMM-based algorithms is shown in Figure 7 Validation can easily be
extended to monthly and seasonal time scales. On sub-daily time scales,
the Bureau is developing an hourly gauge-calibrated radar rainfall
analysis at 1 km spatial resolution. This product will be used to
validate the space-time structure of the satellite rainfall fields,
including the representation of the diurnal cycle.

2.  ***Austria***

**Ground Validation Site Status and Future Plans -- IAS, JOANNEUM
RESEACH, Graz, Austria**

IAS, the Institute of Applied Systems Technology (director Prof. O.
Koudelka), looks back onto a three decades lasting tradition in
investigating and modelling tropospheric effects on radio wave
propagation. Especially the Radar and Propagation Research Group (head
Prof. W.L. Randeu) has accumulated extensive experience and tools most
relevant also for GPM ground validation work. A dual-polarisation,
frequency-agile C-band research weather radar has been developed and set
up in cooperation with ESA / ESTEC, data analysis includes e.g. rain
retrieval algorithms, rain cell and melting layer studies, comparison of
satellite- and radar-derived rainfall rates. Ground validation work in
Graz is deemed to be of special importance because of the surrounding
mountainous terrain and the more continental Austrian type of climate.

**Present status of site:** Whereas the C-band weather radar would need
some refurbishment, instrumental observation presently focuses on
acquiring precipitation microstructure data using the imaging
2D-Video-Distrometer (2DVD), two units are in operation. Furthermore all
Austria is covered by four routine operation weather radars (C-band, 5
minutes refresh time) and by a dense raingauge network, a close
relationship to the operators exists. To measure cloud base, a Lidar is
in operation. IAS runs projects investigating precipitation particle
scattering amplitudes, including irregularly shaped and mixed-phase
particles (snowflakes and ice crystals). Relevant modelling work is
supported using data from the imaging 2D-Video-Distrometer units.

**Future plans:** Refurbishment of the research weather radar station is
being discussed at the moment, including possibly to set up a Ka-band
radar, also allowing observations of cloud formation processes. Within
the closer range of the radar ( \< 15 km ) the following would be of
interest:

\- detailed analysis of precipitation events over the city of Graz

\- comparisons with 2DVD units along a mountain height profile,
including ice and snow scattering

\- set up of auxiliary instruments for measurement of atmospheric
radiation

\- operation of a 1280 MHz Windprofiler (retrieving vertical profiles of
wind and turbulence, co-sited with the pulsed LIDAR)

Thus it is prediction, explanation and verification of satellite
measurements, to be done in the specific climatic and topographic
situation of Graz. Figure 8 provides a schematic illustration.

In the last two years Austria has suffered both -- severe flooding and
drought. IAS is fully aware of the importance of relevant observations
and research.

![](media/image10.png){width="4.497916666666667in"
height="3.7319444444444443in"}

**Figure 8:** Schematic illustration of IAS plans for GV research in
Graz, Austria.

3.  ***Brazil***

**GPM Ground Validation in Brazil**

Ground validation activities in Brazil, in support of precipitation
measurements to be performed by GPM satellite constellation, are being
considered mainly by universities, research institutions and government
agencies/organizations. Both ground based measurements and research
aspects are contemplated in those activities. They are briefly
approached below.

**Ground based measurements:**

a\) Weather radars - In general, presently existing radars fall into the
two governmental level groups, i.e, federal and state. At the Federal
level are the SIV AM (System for the Surveillance of the Amazon) with 10
S-band Doppler systems, the Air Force network also with 10 S-band
Doppler radars, the Federal University of Pelotas with one S-band
Doppler system which will undergo a major up-date/up-grade in the near
future to resume operations and the University of Alagoas with an old
non-coherent C-band to which a Doppler capability is to be added as part
of a modernization of the system. The State level systems are the
three-set network in São Paulo featuring two S-band Dopplers and one
non-coherent 10 cm system, the Simepar (Meteorological System of the
State of Paraná) radar which is a 10 cm Doppler deploying a 1 degree
beam-width antenna (all the others have a 2-degree beam) and the State
of Ceara X-band.

b\) Raingages - There are several operators of raingages in the country,
both of government and private nature. Synoptic totals only and
recording gages integrate the existing networks with different relative
numbers of each type. In the State of São Paulo, for instance, there is
an approximate ratio of 3:1 (totaling/recording) for the hydrological
system network. Examples of main networks are presented in the sequence.

-   Paraná State network: about 120 recording gages, a substantial
    portion of it within the Simepar 240 km radar range.

-   São Paulo State network: more than 300 recording gages (within radar
    240 km radar range since the radar coverage practically spans the
    whole State).

Among the countrywide networks, there is a comprehensive system for
agrometeorological purposes, comprising about 2400 daily total gages.

**Research efforts:** Universities and research organizations are
carrying out, or planning, developments related to the GPM program. Some
of those efforts are specifically envisaging validation issues. On going
research on this can be found, for instance, in the Universities of São
Paulo (USP) and of the State of São Paulo (UNESP), and the National
Institute for Space research (INPE).

Topics include measurement strategies, matching procedures for data
comparison from different sensors, sampling characteristics, retrieval
algorithms, validation through end-products (e.g. catchment response,
equivalent latent heat release/NWP), etc.

Among a few preliminary results already obtained using radar data are
climatologically consisted Tb-Z(R) relationships.

**Comments:** A number of instruments of direct interest for validation
are planned for deployment in the near future. This is the case with a
dual-polarization, Doppler X-band radar which will operate in the
metropolitan area of the city of São Paulo and a new S-­band Doppler,
prepared for later addition of dual-polarization capability, which will
be installed somewhat away from the São Paulo metro area. They will work
coupled to a micronet of 20 automatic weather stations covering the bulk
of metro São Paulo. The synergistic observations with these systems is
expect to provide particularly accurate precipitation estimates,
invaluable for satellite rainfall validation. The above mentioned
systems are originally specified to integrate the Hydrometeorological
System of the State of São Paulo (SIHESP), which is now under
development. In this sense, is also emblematic the establishment of a
statewide telemetering raingage network, in the context of the SIHESP
project. Strict quality control procedures to be implemented should
provide quite reliable data, of particular value for validation.
Dedicated validation sites being/to be implemented for specific
programs - as is the case for the Aqua polar platform - are another
relevant potential support for the GPM GV. On the other hand,
experiments of opportunity offer many possibilities for validation data
base.

The TroCCiBras/Troccinox (Tropical Convection, Cirrus and Nitrogen
Oxides Experiment/Brazil) and Hibiscus field campaigns, developed during
the January-­March, 2004 period based in Bauru-São Paulo is a good
example.

Data then obtained, such as hydrometeor population in the upper portion
of heavy rain clouds, are basic for validating satellite rainfall
microwave radiometry.

While much representative, information here provided are - as stated -
only examples of ongoing/planned activities on the GPM GV theme and,
thus, is far from exhaustive. Also, it is naturally biased towards the
projects carried out by, and those close to, the rapporteurs.

**Outlook:** Some actions are now being initiated to organize the
knowledge about GPM related activities in Brazil, of which GV is a major
issue. Synergism is being sought among those involved. A much complete
survey of GV GPM possibilities in Brazil should emerge soon, among the
first results of those actions.

While issues about spacecrafts and sensors here for GPM are at most very
speculative as of now, one would not say this is out of question.
Although in a much different context, a meteorological payload has
already been considered for a future Brazilian geo-stationary satellite.

2.  ***Canada***

**Canadian Ground Validation Opportunities**

Canada is a vast northern country consisting of diverse meteorological
and precipitation regimes. Snow constitutes a significant portion of the
annual precipitation. Observation systems within Canada are designed to
measure all precipitation types and in severe environments. In a very
broad sense, (i) snow constitutes a greater proportion of the
precipitation with increasing latitude and distance from coastal
regions, (ii) continental snow systems tend to have lighter snowfall
rates than coastal systems, (iii) lake effect snow falls can create
localized highly variable long lived precipitation patterns, (iv) Arctic
tends to be uniformally light.

There are several unique ground validation opportunities for GPM in
Canada.

-   The operational Canadian Nipher shielded gauge has been shown to be
    the most effective of the operational snow gauges in use worldwide.
    It has been extensively studied and wind corrections are readily
    available.

-   The Canadian Radar Network consists of thirty C-Band Doppler radars
    and one S-Band Doppler radar. The radars are highly sensitive to
    snow -- typically they have a sensitivity of -40 dBZ at 1km range.
    The radar network is set up to detect low level precipitation
    systems: (a) Eleven of the radars are equipped with 0.65^o^
    beams. (b) Negative elevation angles are used in winter. Both are
    designed to better detect and estimate low level snow fall.

-   As part of the Automatic Weather Observation System, 95
    Precipitation Occurrence Observation Sensor (POSS) are operational.
    While they are currently tasked to report on the occurrence of
    precipitation, they have the capability to estimate precipitation
    type, precipitation rate (including snowfall), and particle size
    distributions on a minutely basis. Processing is in place to
    retrieve these parameters but telecommunication modifications are
    needed to retrieve them.

-   The Canadian Mesoscale Observation Testbed (C-MOST) is centred
    around the Montreal area and consists of a UHK, VHF profilers, Xband
    Vertically pointing Doppler radar, polarization S Band radar and
    mesonet surface observations including POSS and snow gauges. This
    site is influenced by east coast weather systems and tends to have
    higher snowfall rates.

-   Canada produces Snow Water Equivalent maps on a routine basis using
    satellite radiometric measurements. These maps were developed
    through extensive research and have been validated in various
    regions in Canada.

-   Several instrumented sites are available besides the CMOST site. A
    possible western site which is influenced by continental systems and
    lighter precipitation rates is located near Bratt's Lake. It is
    located in a flat region of the country. The Centre for Atmospheric
    Research (CARE) is a instrumented precipitation sensor research site
    near Toronto that is influence by Lake Effect snow falls. Radisson,
    Quebec is a site established by Quebec Hydro for precipitation and
    snowpack research. It is influenced by Lake Effect snows from Hudson
    Bay. Several Arctic sites (Alert, Resolute) may also be possible if
    established in collaboration with other research programs. The
    Environment Research Aircraft Facility is an airborne microphysical
    and remote sensing facility used to study precipitation processes.

    2.  ***China***

**Potential Applications of MVRI on Precipitation Retrieval and its
Validation**

Compared with conventional raingauge and radar observations, the
Meteorological satellites could provide real-time rainfall information.
In addition, satellite derived rain products are the only available
precipitation datasets over oceans and remote areas where there are lack
of conventional rainfall measurements. China has a plan to launch the
Microwave Radiation Imager (MVRI) onboard FY-3 satellite in the near
future. MVRI is a multi-frequency conical scanning microwave imager,
with horizontal/vertical (H/V) polarization channels similar to the
Special Sensor Microwave Imager (SSM/I). A research project has been
established to explore a precipitation retrieval technique using MVRI
measurements. This rain retrieval algorithm could be ready in 2006. A
statistic approach using scattering index has been developed with SSM/I
data and synthetic retrieval tests using MVRI are in progress.
Meanwhile, NSMC is developing a physical precipitation retrieval
algorithm that is expected to lead to better rainfall retrievals.

NSMC, a meteorological satellite operational center in China, is
interested in participating in the global precipitation measurement
(GPM) project. There are large variations of precipitation over China.
For example, the annual precipitation is about 50 mm in the northwest
part of Tibetan plateau, while it is over 2000 mm in the southeast
region of China. With these extreme climate rainfall zones, China is in
effort to achieve better precipitation measurements both in time-space.
Since ground validation (GV) program is always very important in
satellite rainfall measurements, NSMC also has a GV program with the
FY-3 project. The existing raingauge observation network is very good in
China and the increasing ground Doppler radar coverage could provide
additional rain measurements. These observations should provide a good
opportunity to conduct GV activities. They are not only important to
FY-3 project, but also useful to GMP project. NSMC would like to be one
of the partners in the GPM family to exchange information and contribute
to the GPM. FY-3 project is expecting to use GPM core satellite
measurements for its GV program and seeking opportunities to participate
in the GPM GV Research Program.

Great successes in precipitation retrieval have been made since the
launch of TRMM and more accurate rainfall observations are expected in
the GPM era. There are huge potential applications with the GPM and the
FY-3 polar orbiting meteorological satellite measurements in China.
China is preparing to collaborate with communities of satellite
observations and to contribute to better global precipitation
observations.

3.  ***Finland***

**Possibilities for GPM Validation in Finland**

Finland is located in the boreal forest zone between latitudes 60 N and
70 N and has a severe snowfall climate. The number of snow cover days
varies from 100 in the southwestern archipelago to 220 in Lapland. Mean
annual precipitation is 400-700 mm. Snow has many socioeconomic impacts,
e.g. the average winter season road snow clearance costs are 100 million
Euros. The Finnish Meteorological Institute (FMI) is willing to act as a
partner in the GPM validation, especially snowfall, by providing
reference data and research cooperation. As the launches of GPM and EGPM
will hopefully take place around 2008 and later, this document can not
describe in detail the future validation equipment but only give an
overview of the possibilities. A more detailed observational plan can be
created later.

Finland has good experience in the remote sensing of snow water
equivalent and snow depth on the ground. Therefore FMI and the Finnish
Environment Institute (SYKE) are going to take responsibilities of these
issues in the EUMETSAT Hydro-SAF, which is under preparation (a summary
of remote sensing of snow on the ground is given by Pylkkö et al.,
2003). The ground snow depth estimated from satellites could be used as
a reference for long period GPM accumulation measurements.

The main validation data will be obtained from the weather radar
measurements, radio soundings and from surface sensors. The operational
radar network consists of 7 (8 in 2006) C-band Doppler radars from which
the polar measurement data (typically 4-10 elevation angles, 360 azimuth
angles, 500 range bins, 5-15 minute time intervals) is archived already
now. We have developed e.g. methods for the network composites to
correct underestimation of surface precipitation due to the shallow
vertical profiles of reflectivity (VPR) in snowfall and real time
spatial adjustment of the Z-R/Ze-S relation according to the actual
hydrometeor water phase at each measurement bin. Reliability masks for
radar products are under development. Summary of the long experience in
radar-based snowfall measurements at FMI can be found in Koistinen et
al. (2003).

As an example of radar data the following image, Figure 9, presents the
cumulative distribution function of the radar reflectivity factor at
ground (sfc) and at the heights of 2000 m and 4000 m above ground based
on 54 000 measured VPRs in snowfall during a 12 month period. The curves
indicate that serious care must be given to the sensitivity of the
K-band precipitation radars in the GPM/EGPM-program.

We have also good possibilities to perform regional precipitation
validation widely as a North European cooperation applying the
high-quality gauge-radar integrated BALTEX precipitation products,
covering major part of the Baltic sea catchment area with more than 30
radars, see Koistinen and Michelson(2002) an d
<http://www.gkss.de/baltex/baltex_frame_builder.html> (path: Data and
Data Centers, BALTEX Radar Data Center, Products).

![](media/image11.png){width="3.779861111111111in"
height="2.692361111111111in"}

**Figure 9:** Cumulative distribution function of the radar reflectivity
factor at ground (sfc), 2000 m, and 4000 m above ground based on 54 000
measured VPRs in snowfall during a 12 month period.

Snowfall measurements at ground are obtained from snow courses, from
ordinary gauges with wind shields and from sensitive weighing gauges
(OTT or Geonor). A well equipped ground reference site has two options,
depending on the actual latitude coverage of the GPM sensors: (1)
Sodankylä, and (2) Helsinki-Jokioinen. Sodankylä (67 N) has 200 snow
cover days/year and is already heavily equipped with appropriate
meteorological sensors as it is a WCRP/GEWEX CEOP validation station,
see <http://www.joss.ucar.edu/ghp/ceopdm> and
<http://www.fmi.fi/research_polar/polar_2.html> .

Helsinki-Jokioinen (60-61 N) is a bimodal station, which has less
frequent snow (150 days) and no masts for flux measurements but, on the
other hand, windprofilers and quite obviously a polarimetric C-band
research and test radar as well as a mesoscale testbed with lot of
surface AWS sensors. All these additional measurements compared to the
Sodankylä site are taken care as a cooperation by FMI, University of
Helsinki and Vaisala company. Jokioinen acts as a WMO test site for a
large collection of solid precipitation gauges.

4.  ***France***

**Cevennes-Vivarais Mediterranean Hydrometeorological Observatory**

The \"Cévennes-Vivarais Mediterranean Hydro-Meteorological Observatory\"
(OHM-CV is the French acronym, see the web site:
http://www.lthe.hmg.inpg.fr/OHM-CV/index.html) is a research initiative
aimed at improving the understanding and modelling of the intense
Mediterranean rain events that frequently result in devastating
flash-floods in the South of France (e.g., Nîmes 1988, Vaison la Romaine
1992, Aude 1999, Gard 2002, Cévennes 2003) like in other Mediterranean
countries. The OHM-CV has received the label of "Environment Research
Observatory" (ORE) from the French Ministry of Research in 2002. A
primary objective of the observatory is to bring together the skills of
meteorologists and hydrologists, modellers and instrumentalists,
researchers and practitioners, to cope with these rather unpredictable
events.

Due to the difficulties in observing extremes, the OHM-CV observation
strategy is comprised of three complementary lines: (i) detailed,
long-lasting and modern hydro-meteorological observation over part of
the region of interest, the Cévennes-Vivarais region; (ii) post-flood
investigation after all the extreme events occurring over the entire
French Mediterranean region and (iii) use of historical and
palaeo-hydrological information available on past floods. The first
observation strategy, with the Cévennes-Vivarais pilot site, is of
special interest for the GPM project. Over this 160 x 200 km2
flash-flood prone region (Figure 10), the operational
hydro-meteorological observation system is already very rich with three
weather radar systems of the Météo France ARAMIS network, 160 hourly
rain gauges, 400 daily rain gauges and 45 stage and discharge stations
over the main right bank tributaries of the Rhône river.

An on-going action of the OHM-CV is devoted to the creation of a data
base for research by collecting and critically analysing the operational
data for a period of more than 10 years, starting in 2000. Several
concerted actions are also realized by the research/operational
communities in order to progressively upgrade the Cévennes-Vivarais
observation system. For instance, (1) the usefulness of a volume
scanning strategy for meteorological and hydrological applications is
being tested with the Bollène and Nîmes weather radar systems, (2)
experiments are realized to assess the potential of GPS for measuring
the water vapour inflow into the Cévennes-Vivarais region, (3) remote
sensing techniques are being developed for measuring the river
discharges during floods. Besides these observation and instrumental
activities, high-resolution non-hydrostatic meteorological models and
rainfall-runoff distributed models are developed and evaluated, prior to
their further coupling with the ultimate objective of obtaining an
integrated forecast of the phenomena of interest.

![](media/image12.png){width="3.9298611111111112in"
height="3.1222222222222222in"}

**Figure 10:** Cévennes-Vivarais Mediterranean Hydrometeorological
Observatory. Coloured map shows topography (in m ASL), while 3 weather
radars are indicated by crosses and 40-km range indicators. Black
circles and triangles give locations of 1-hour raingauge network.

5.  ***Germany***

**GPM Ground Validation in Germany**

In Germany ground validation for GPM is available through the national
weather service, Deutscher Wetterdienst (DWD) and through other local
research organizations.

![](media/image13.png){width="3.201388888888889in" height="3.625in"}

DWD operates a network of 16 C-band Doppler weather radars. The network
is dense and almost whole Germany is covered within the 120 km range of
the radars. The radars run volume scans every 15 minutes and provide
various products for the end users. In addition a special high
resolution precipitation scan is performed every 5 minutes at each radar
and data are available as hourly and daily sums. DWD also operates an
additional radar at the radar research laboratory on top of
Hohenpeißenberg Mountain. This radar is operated independent from
operational constrains. This radar will be upgraded to a polarimetric
radar within the next years. Through co-operation with state water
authorities a dense automatic rain gauge network is jointly operated in
Southern Germany. DWD runs projects together with hydrological
institutions to provide real-time calibration of radar measured
precipitation with rain gauges.

Besides the operational nationwide precipitation measurements by DWD, at
the time three locations have been identified to act as ground
validation site. These are:

-   **Bonn**: The University of Bonn operates a X-band weather radar.
    Cooperation exists with local operators of rain gauges. The
    institute also operates a multi-frequency radiometer which is suited
    to retrieve the liquid water path and other atmospheric properties.
    Rain gauges, disdrometer and vertical pointing rain radars are also
    available.

-   **Lindenberg**: At the Lindenberg observatory the DWD runs
    operational and research instruments mainly for boundary layer
    research. Active and passive remote sensing instruments like wind
    profilers, RASS, vertical pointing rain radar, radiometer,
    ceilometer are available.

-   **Oberpfaffenhofen**: The Institute of Atmospheric Physics at the
    German Aerospace Center (DLR) operates at Oberpfaffenhofen a
    polarimetric Doppler research weather radar. The radar is
    supplemented with a bistatic Doppler radar network, which enables
    the retrieval of the 3D wind vector field. Within the range of the
    radar data from the dense rain gauge network of DWD are available.
    In close range to the radar the DWD operates two radars:
    Hohenpeißenberg and Munich. Additional instruments are various lidar
    systems, ceilometer, disdrometer and high resolution rain gauges. A
    mobile Ka-band cloud radar is planned. DLR operates several research
    aircraft. With the DLR radar different climatic zones are covered,
    flat plane (500 m MSL) and high Alpine mountains (3000 m MSL). A
    German research station at the Zugspitze (2964 m MSL) can be used
    for additional measurements within snow.

    2.  ***Greece***

**GPM Ground Validation in Greece**

*\[To be completed\]*

3.  ***India***

**Ground Validation for Global Precipitation Mission in India**

Ground Validation of Spaceborne Precipitation sensors was conducted in
India in the context of Tropical Rainfall Measuring Mission (TRMM)
.Units of Indian Space Research Organization (ISRO) such as Radar
Development Cell (RDC), National MST Radar Facility (NMRF) , Gadanki,
Space Applications Centre (SAC), have contributed to this effort. The
following set of instruments participated in the ground validation
activities:

1.  S-Band Doppler Weather Radar ( called Megha-2700) established at the
    south eastern coast of India. This radar is located strategically to
    monitor the tropical cyclone systems.

2.  MST Radar a VHF profiler established at Gadanki village.

3.  Co-located instruments such as disdrometer, Optical Rain Gauge and a
    Lower Atmospheric Wind Profiler - LAWP (L-Band Profiler) were used
    for characterizing tropical rainfall.

Modeling studies were undertaken at Space Applications Center,
Ahmedabad. All the above instruments were managed by ISRO. India
Meteorological Department (IMD) was supported by NASA for Ground
Validation efforts by upgrading (IMD'S) existing Weather Radar at
Karaikkal, to a digital receiver and recording system. Comparison of the
aerial rainfall retrievals from the horizontally scanning DWR with the
vertically profiling precipitation radar from TRMM as well as TMI were
made. Efforts were made to deduce drop size distribution from the L-Band
Profiler including comparison with the disdrometer data.

Recently a team from NASA visited India in connection with the Ground
Validation for GPM. Based on the discussions held with the NASA team, a
consolidated proposal on Ground Validation is being submitted for which
ISRO will be the lead agency, with participation from the concerned
Centres and Units of ISRO as well as other interested agencies at the
national level including IMD and university groups to contribute towards
the Ground Validation Program of GPM. It is also relevant to state that
ISRO is planning to launch a multifrequncy radiometer space craft called
Meghatropques,( a collaborative project CNES) that will likely form one
of the constellation satellites for GPM. Ground validation efforts for
this spacecraft are also consistent with those for GPM.

The instrumentation systems which will be participating in the Ground
Validation Program as of now are following:

1.  DWR Megha - 2700 developed by ISRO-- RDC for IMD and located at
    SDSC, SHAR along with co-located supporting instruments such as rain
    gauge and disdrometer (supplied by Centre for Earth Sciences,
    Thiruvananthapuram). It is also proposed to upgrade this DWR into a
    dual-polarization system.

2.  The DWR system located at Chennai namely Gematronik 1500 of IMD.
    This system operates at horizontal polarization only. It is proposed
    to conduct certain dual Doppler retrievals using this Radar along
    with DWR- Megha 2700 located at SDSC SHAR.

3.  The MST Radar operating at 53 MHz and its co-located facilities
    including Lower Atmospheric Wind Profiler (LAWP) operating at 1357
    MHz, an optical rain gauge and disdrometer, from National MST Radar
    Facility, Gadanki.

4.  It is also proposed that one existing C-Band Radar located at Thumba
    Equatorial Rocket Launching Station, Vikram Sarabhai Space Centre,
    Thirvanathanpuram will be converted into a dual-polarized Weather
    Radar in the foreseeable future. This Radar will be supported by a
    number of existing rain gauge stations in and around
    Thiruvanathanpuram.

India gets its rainfall mainly through monsoons starting from early June
till end of November with a break in monsoon occurring sometime towards
the end of August. The onset of South West monsoon is seen over the
Kerala coast which will be detected by the C-Band Weather Radar and the
aerial rainfall estimation will be made. The East coast of Southern
India will be visited by the North East monsoon in the months of October
to December. The rainfall during this North East monsoon will be
measured by the DWR's located at SHAR and Chennai along with Profilers
at Gadanki. There will also be a number of pre-monsoon thunder showers
occurring inland especially over Gadanki which will also be
characterized by the planned measurement systems. In addition the radars
will provide continuous coverage over the annual tropical cyclone
season.

Currently all the Radar systems and other instruments have stand alone
data recording and analysis facilities. A proposal to network the data
obtained from each instrument will be worked out to enable archival at a
Central location (TBD) for Ground Validation and co-related processing
of the data obtained from each sensor. It is expected that this network
operation of precipitation measuring instrumentation systems would
result in providing a very effective validation program for
precipitation over South India to support the GPM Mission. In addition
modeling and data analysis studies at SAC with data from this network
will provide an important component.

2.  ***Israel***

**Ground Validation Activities in Israel**

Israel is a small country with little territorial coverage to offer
surface ground validation in the old sense. This realization became
apparent with respect to TRMM. Instead, Israel will continue
contributing to validation of space borne retrieved cloud
microstructure, precipitation forming processes and the way these
processes are affected systematically by differences in the
thermodynamic and aerosol composition of the troposphere. These cloud
properties are inherently important to GPM, as demonstrated recently by
Rosenfeld and Ulbrich (2003). They have shown that cloud microstructure
can profoundly affect the rain drop size distribution in a way that can
cause systematic biases in radar and passive microwave estimated
rainfall by factors \> 2. Such biases would be smaller with the dual
frequency radar on the mother GPM satellite. But application of these
principles to the rest of the GPM constellation has the potential of
large improvement of the accuracy of the rainfall measurements on a
global scale.

The two main assets for that in Israel are: (1) a King-Air C90 cloud
physics research aircraft, with cloud physics and aerosol probes, and
(2) an explicit microphysics cloud model (The Hebrew University Cloud
Model, developed by Prof. Alexander Khain), to be used for simulating
the clouds and precipitation that are validated by the aircraft
measurements, and apply a forward radiative transfer model for
calculating the radiative signatures that should be seen by the GPM
constellation.

![](media/image14.png){width="5.733333333333333in" height="3.825in"}

**Figure 12:** Picture of Israeli cloud physics aircraft, with aerosol
and precipitation probes under wings, and aerosol-sampling intake on
top.

3.  ***Italy***

**GPM Italian GV Site**

**Introduction:** Italian climate is a typical Mediterranean one. As far
as precipitation is concerned, yearly amount varies from 2000 mm (Alps
and Apennines) to 400 mm (Islands and Southern Italy). Most rainy season
is fall, while precipitation is scarce during summer, which is not,
however, totally dry (in Rome: 33 rainy days in winter, 29 in spring and
fall, and 12 in summer). Peaks precipitation intensities are recorded
during fall and summer storms. Intense precipitation often occurs in
narrow cost lines bounded by mountains, which are thus exposed to high
hydrogeological risk. Due to its position in the Mediterranean Sea and
the complexity of its territory, climate of Italy is not homogeneous;
anyway, Rome can be considered a significant representative sample of an
"average" Mediterranean climate of Italy.

**Infrastructures for GV:** The Italian GV validation infratructure will
be built upon the CNR-ISAC atmospheric observatory in Rome, the CNR-ISAC
Polar 55C weather radar, sited in Rome and the Italian meteo radar
network through its focal point at CIMA in Savona, which collect also
real time data from about 750 rainfall gauge station in Italy.

**CNR-ISAC atmospheric observatory in Rome:** The site is located in the
central part of Italy, 30 km northeast of the coast of the Tyrrehnian
Sea and 20 km southeast of Rome. This position makes this site very
representative of the Mediterranean climate and suitable for studying
the interaction between the local and the mesoscale circulation, the
sea-land transition influence in the formation of precipitation, and for
observing precipitation in an urban area of huge importance such as the
city of Rome. The infrastructure, easily accessible, is provided with
laboratories and open areas were most the equipment is installed.

Two large open areas are available for instrumentation: a 2300 m2 grass
field and the 500 m2 roof of the main building of the Institute. VHF
radar wind profiler for clear air wind observation, sodar, minisodar,
lidar (a multiple receiver system utilizing simultaneously the
Rayleigh-Mie and Raman techniques to profile aerosol, temperature and
water vapor), micrometeorological mast, radiometric stations, automatic
weather station and microlidar, are installed in the open field; while
the Polar 55C C-band weather radar and the 60 GHz temperature profiler
(MTP5) are installed on special structures on the roof of the building.
An HRPT satellite reception station is also running. Available
instrumentation will possibly be improved for GV activities through
ground-based radiometer and/or dual frequency radar.

Additional instrumentation in the area of Rome, which could be
potentially adopted for GV, includes also the telemetered raingauge
network owned by several public bodies and managed by the Italian
Hydrologic and Oceanic Service which is constituted by 37 gauges with a
density of 1/14.8 km2 and the sounding station of Italian Meteo Services
located within 30 km from the Polar 55C radar.

**Polar 55C weather radar:** Many of the envisioned radar GV activities
are centered on the Polar 55C research radar, a coherent C-band, dual
polarization radar developed by Italian National Research Council. The
radar system operated from 1991 and 2001 near Florence (Italy) also for
the need of Mesoscale Alpine Programme. The system was installed in 2001
in the Rome Site and upgraded in 2002 with a new digital receiver. With
the current configuration, it can provide measurements of the
reflectivity factor at horizontal polarization, the differential
reflectivity, the mean and standard deviation of the Doppler velocity,
and, finally, the specific differential phase. The coverage of Polar 55C
includes a portion of the Thyrrenian Sea, the city of Rome and a portion
of the west side of Appennine range. The favorable position of the Polar
55C, close to a major urban area and to the Thyrrenian Sea, is
particularly useful to use polarimetric radar data to highlight the
contributions of land-sea interaction and of urban areas in the cloud
and precipitation formation mechanisms in a regional model.

**Italian radar network:** The Italian radar network has been planned by
the Dipartimento di Protezione Civile (the Italian Civil Protection
Department). Real time data from the network will be collected by DPC
and by CIMA in Savona. A competition is, at present, open to select the
manufacturer and the number, out from a total of 14 planned, of new
radars to be installed in this first round. This plan, aims at a)
providing adequate and homogeneous coverage of the Italian territory; b)
integrating in the network the coverage provided by the 12 existing
radars managed by Regional authorities and the 6 managed by the Italian
Air Force, and c) to establish a common framework for the optimal use of
all Italian operational weather radars. The 14 new installations will be
equipped with C-band radar with doppler and polarimetric capabilities.
The network is expected to be operational from the end of 2004 with 8
new installations and a satellite based data communication system.

![](media/image15.png){width="3.511111111111111in"
height="2.3006944444444444in"}

**Figure 13:** Antenna array of VHF wind profiler (foreground) and
offset fed paraboloid antenna of Polar 55C weather radar (background) at
Rome CNR-ISAC site.

![](media/image16.png){width="4.302777777777778in" height="5.18125in"}

**Figure 14:** Existing weather radar sites for Italy along with 14 new
Polarimetric Doppler radar system sites planned by DPC.

**Table 6:** Location of existing weather radars in Italy belonging to
Regional Authorities. "Site" names (with respective Province
abbreviation within brackets) are those pictured in Figure 13 and 14.
Main specifications are also given in terms of manufacturer, Doppler
capability, operating frequency band, dual polarization option,
beamwidth and radome presence. Current status is referenced to 31
December 2001. Membership to METEONET Italian network is also noted.

+----------------------------+---------------------+-------------------+
| **Weather Radar Site**     | **Main              | # Current status  |
|                            | Specifications**    |                   |
+----------------------------+---------------------+-------------------+
| Name: San Pietro Capofiume | Manufacturer:       | Operational;      |
| (BO)                       | **ALENIA-SMA**      |                   |
|                            |                     | member of the     |
| Owner: ARPA Emilia Romagna | Doppler: **YES**    | Italian           |
|                            |                     |                   |
| Site: Lat. 44°39'22'',     | Band: : **C**       | METEONET network  |
| Lon. 11°37'26''            |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 11 m             | **YES**             |                   |
|                            |                     |                   |
|                            | Beamwidth: **0.9°** |                   |
|                            |                     |                   |
|                            | Radome: **NO**      |                   |
+----------------------------+---------------------+-------------------+
| Name: Monte Grande - Teolo | Manufacturer:       | Operational;      |
| (PD)                       | *                   |                   |
|                            | *EEC**-**ERICSSON** | member of the     |
| Owner: ARPA Veneto         |                     | Italian           |
|                            | Doppler: **YES**    |                   |
| Site: Lat. 45° 21' 46'',   |                     | METEONET network  |
| Lon. 11° 40' 25''          | Band: **C**         |                   |
|                            |                     |                   |
| Altitude: 472 m            | Dual polarization:  |                   |
|                            | **NO**              |                   |
|                            |                     |                   |
|                            | Beamwidth: **1°**   |                   |
|                            |                     |                   |
|                            | Radome: **YES**     |                   |
+----------------------------+---------------------+-------------------+
| Name: Spino d'Adda (CR)    | Manufacturer:       | Operational;      |
|                            | **ALENIA**          |                   |
| Owner: CNR                 |                     | member of the     |
|                            | Doppler: **YES**    | Italian           |
| Manager: PoliMI            |                     |                   |
|                            | Band: **S**         | METEONET network  |
| Site: Lat. 45° 24' 00'',   |                     |                   |
| Lon. 9° 30' 00''           | Dual polarization:  |                   |
|                            | **NO**              |                   |
| Altitude: 80 m.            |                     |                   |
|                            | Beamwidth: **2°**   |                   |
|                            |                     |                   |
|                            | Radome **NO**       |                   |
+----------------------------+---------------------+-------------------+
| Name: Fossalon di Grado    | Manufacturer:       | Operational;      |
| (GO)                       | **ALENIA-SMA**      |                   |
|                            |                     | member of the     |
| Owner: ARPA Friuli Venezia | Doppler: **YES**    | Italian           |
| Giulia                     |                     |                   |
|                            | Band: **C**         | METEONET network  |
| Site : Lat. 45° 43' 40'',  |                     |                   |
| Lon. 13° 28' 00''          | Dual polarization:  |                   |
|                            | **YES**             |                   |
| Altitude: 25 m.            |                     |                   |
|                            | Beamwidth: **0.9°** |                   |
|                            |                     |                   |
|                            | Radome: **NO**      |                   |
+----------------------------+---------------------+-------------------+
| Name: Preturo (AQ)         | Manufacturer:       | []{.mark}         |
|                            | **EEC-ERICSSON**    |                   |
| Owner: Regione Abruzzo -   |                     | Operational;      |
| CETEMPS                    | Doppler: **YES**    |                   |
|                            |                     | External member   |
| Site: Lat. 42° 22' 48'',   | Band: **C**         | of the Italian    |
| Lon. 13° 19' 12''          |                     | METEONET network; |
|                            | Dual polarization:  | to be moved to M. |
| Altitude: 680 m.           | **NO**              | Midia             |
|                            |                     |                   |
|                            | Beamwidth: **1.6°** |                   |
|                            |                     |                   |
|                            | Radome **YES**      |                   |
+----------------------------+---------------------+-------------------+
| Name: Monte Macaion (BZ)   | Manufacturer:       | Operational;      |
|                            | **EEC-ERICSSON**    |                   |
| Owner: Autorità di bacino  |                     | member of the     |
| dell'Adige                 | Doppler: **YES**    | Italian           |
|                            |                     |                   |
| Manager: Province di       | Band: **C**         | METEONET network  |
| Trento e Bolzano           |                     |                   |
|                            | Dual polarization:  |                   |
| Site : Lat. 46° 29' 44'',  | **NO**              |                   |
| Lon. 11° 12' 37''          |                     |                   |
|                            | Beamwidth: **1°**   |                   |
| Altitude: 1890 m.          |                     |                   |
|                            | Radome: **YES**     |                   |
+----------------------------+---------------------+-------------------+
| Name: Bric della Croce     | Manufacturer:       | Operational;      |
| (TO)                       | **ALENIA**          |                   |
|                            |                     | member of the     |
| Owner: Regione Piemonte    | Doppler: **YES**    | Italian           |
|                            |                     |                   |
| Site: Lat. 45°1'53'', Lon. | Band: **C**         | METEONET network  |
| 7°43'59''                  |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 720 m            | **NO**              |                   |
|                            |                     |                   |
|                            | Beamwidth: **1°**   |                   |
|                            |                     |                   |
|                            | Radome: **YES**     |                   |
+----------------------------+---------------------+-------------------+
| Name: Monte Rasu Bono (SS) | Manufacturer:       | To be tested;     |
|                            | **ALENIA-ERICSSON** |                   |
| Owner: Regione Sardegna -  |                     | Not operational.  |
| SAR                        | Doppler: **YES**    |                   |
|                            |                     |                   |
| Site: Lat. 40° 25' 21'',   | Band: **C**         |                   |
| Lon. 9° 00' 19''           |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 1259 m.          | **YES**             |                   |
|                            |                     |                   |
|                            | Beamwidth:          |                   |
|                            | **0.95°**           |                   |
|                            |                     |                   |
|                            | Radome: **YES**     |                   |
+----------------------------+---------------------+-------------------+
| Name: Monte delle Rose     | Manufacturer:       | Tested;           |
| (PA)                       | **EEC-ERICSSON**    |                   |
|                            |                     | Not operational.  |
| Owner: Regione Sicilia     | Doppler: **YES**    |                   |
|                            |                     |                   |
| Site: Lat. 37° 39' 14'',   | Band: **C**         |                   |
| Lon. 13° 25' 06''          |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 1436 m.          | **NO**              |                   |
|                            |                     |                   |
|                            | Beamwidth: **0.9°** |                   |
|                            |                     |                   |
|                            | Radome: **YES**     |                   |
+----------------------------+---------------------+-------------------+
| Name: Colle Settepani (SV) | Manufacturer:       | Testing phase;    |
|                            | **ALENIA-SMA**      | operational       |
| Owner: Regioni Liguria e   |                     | within the middle |
| Piemonte                   | Doppler: **YES**    | of 2002.          |
|                            |                     |                   |
| Site: Lat. 44° 14' 57'',   | Band: **C**         |                   |
| Lon. 8° 11' 55''           |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 1387 m.          | **YES**             |                   |
|                            |                     |                   |
|                            | Beamwidth: **1°**   |                   |
|                            |                     |                   |
|                            | Radome: **YES**     |                   |
+----------------------------+---------------------+-------------------+
| Name: Gattatico (RE)       | Manufacturer:       | Testing phase;    |
|                            | **ALENIA-SMA**      | operational       |
| Owner: DSTN                |                     | within the middle |
|                            | Doppler: **YES**    | of 2002.          |
| Manager: ARPA Emilia       |                     |                   |
| Romagna                    | Band: **C**         |                   |
|                            |                     |                   |
| Site: Lat. 44° 47' 29'',   | Dual polarization:  |                   |
| Lon. 10° 29' 57''          | **YES**             |                   |
|                            |                     |                   |
| Altitude: 34 m.            | Beamwidth: **0.9°** |                   |
|                            |                     |                   |
|                            | Radome: **NO**      |                   |
+----------------------------+---------------------+-------------------+
| Name: Loncon (VE)          | Manufacturer:       | To be installed   |
|                            | **EEC-ERICSSON**    | within the        |
| Owner: ARPA Veneto         |                     | beginning of 2003 |
|                            | Doppler: **YES**    |                   |
| Site: Lat. 45° 41' 12'',   |                     |                   |
| Lon. 12° 47' 12''          | Band: **C**         |                   |
|                            |                     |                   |
| Altitude: 14 m.            | Dual polarization:  |                   |
|                            | **NO**              |                   |
|                            |                     |                   |
|                            | Beamwidth: **0.9°** |                   |
|                            |                     |                   |
|                            | Radome: **YES**     |                   |
+----------------------------+---------------------+-------------------+

**Table 7:** Location of existing weather radars in Italy belonging to
Italian Air Force. "Site" names (with respective Province abbreviation
within brackets) are those pictured in Figure 13 and 14. Main
specifications are also given in terms of manufacturer, Doppler
capability, operating frequency band, dual polarization option,
beamwidth and radome presence. Current status is referenced to 31
December 2001.

+----------------------------+---------------------+-------------------+
| **Weather Radar Site**     | **Main              | # Current status  |
|                            | Specifications**    |                   |
+----------------------------+---------------------+-------------------+
| Name: Brindisi (BR)        | Manufacturer:       | Not operational   |
|                            | **ALENIA**          |                   |
| Owner: Aeronautica         |                     |                   |
| Militare Italiana          | Doppler: **YES**    |                   |
|                            |                     |                   |
| Site: Lat. 40° 38' 00'',   | Band: **C**         |                   |
| Lon. 17° 57' 00''          |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 25 m.            | **YES**             |                   |
|                            |                     |                   |
|                            | Beamwidth: **0.9°** |                   |
|                            |                     |                   |
|                            | Radome: **NO**      |                   |
+----------------------------+---------------------+-------------------+
| Name: San Giusto (PI)      | Manufacturer:       | Operational       |
|                            | **ALENIA**          |                   |
| Owner: Aeronautica         |                     |                   |
| Militare Italiana          | Doppler: **YES**    |                   |
|                            |                     |                   |
| Site: Lat. 43° 40' 47'',   | Band: **C**         |                   |
| Lon. 10° 38' 24''          |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 25 m.            | **YES**             |                   |
|                            |                     |                   |
|                            | Beamwidth: **0.9°** |                   |
|                            |                     |                   |
|                            | Radome: **NO**      |                   |
+----------------------------+---------------------+-------------------+
| Name: Grazzanise (NA)      | Manufacturer:       | Operational       |
|                            | **PLESSEY**         |                   |
| Owner: Aeronautica         |                     |                   |
| Militare Italiana          | Doppler: **NO**     |                   |
|                            |                     |                   |
| Site: Lat. 41° 02' 59'',   | Band: **C**         |                   |
| Lon. 14° 04' 12''          |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 30 m.            | **NO**              |                   |
|                            |                     |                   |
|                            | Beamwidth: **1.5°** |                   |
|                            |                     |                   |
|                            | Radome: **NO**      |                   |
+----------------------------+---------------------+-------------------+
| Name: Istrana (VE)         | Manufacturer:       | Operational       |
|                            | **PLESSEY**         |                   |
| Owner: Aeronautica         |                     |                   |
| Militare Italiana          | Doppler: **NO**     |                   |
|                            |                     |                   |
| Site: Lat. 45° 40' 47'',   | Band: **C**         |                   |
| Lon. 12° 05' 59''          |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 30 m.            | **NO**              |                   |
|                            |                     |                   |
|                            | Beamwidth: **1.5°** |                   |
|                            |                     |                   |
|                            | Radome: **NO**      |                   |
+----------------------------+---------------------+-------------------+
| Name: Trapani (TP)         | Manufacturer:       | To be installed   |
|                            | **PLESSEY**         |                   |
| Owner: Aeronautica         |                     |                   |
| Militare Italiana          | Doppler: **NO**     |                   |
|                            |                     |                   |
| Site: Lat. 37° 55' 12'',   | Band: **C**         |                   |
| Lon. 12° 30' 00''          |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 30 m.            | **NO**              |                   |
|                            |                     |                   |
|                            | Beamwidth: **1.5°** |                   |
|                            |                     |                   |
|                            | Radome: **NO**      |                   |
+----------------------------+---------------------+-------------------+
| Name: Decimomannu (CA)     | Manufacturer:       | To be installed   |
|                            | **PLESSEY**         |                   |
| Owner: Aeronautica         |                     |                   |
| Militare Italiana          | Doppler: **NO**     |                   |
|                            |                     |                   |
| Site : Lat. 39° 21' 00'',  | Band: **C**         |                   |
| Lon. 8° 58' 12''           |                     |                   |
|                            | Dual polarization:  |                   |
| Altitude: 30 m.            | **NO**              |                   |
|                            |                     |                   |
|                            | Beamwidth: **1.5°** |                   |
|                            |                     |                   |
|                            | Radome: **NO**      |                   |
+----------------------------+---------------------+-------------------+

**Table 8**: Locations of 14 new Polarimetric Doppler radar systems
planned by DPC. "Site" names are those pictured in Figure 13 and 14.
"Zone" indicates geographical area, while "Region" is related to
respective regional Authority.

+-------------+-------------+-----------+---------+---------+--------+
| **SITE**    | **ZONE**    | *         | **LAT   | **LONG  | **AL   |
|             |             | *REGION** | ITUDE** | ITUDE** | TITUDE |
|             |             |           |         |         | (m)**  |
|             |             |           | **(     | **(     |        |
|             |             |           | ED50)** | ED50)** |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Monte    | Friu        | Friul     | 46°     | 13°     | 1641   |
| Mataiur***  | li/Slovenia | i-Venezia | 12'46'' | 31'50'' |        |
|             |             | Giulia    |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Monte Le | Tos         | Toscana   | 43°     | 10°     | 1026   |
| Pizzorne*** | cano/Ligure |           | 57'46'' | 36'40'' |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Monte    | Medio       | Marche    | 43°     | 12°     | 976    |
| Pa          |             |           | 38'17'' | 44'59'' |        |
| ganuccio*** | Adriatico   |           |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***M.       | Toscana     | Toscana   | 43°     | 11°     | 1051   |
| Poggio di   |             |           | 07'38'' | 00'18'' |        |
| Montieri*** | Litoranea   |           |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Monte    | Appennino   | Umbria    | 42°     | 12°     | 1428   |
| Serano***   |             |           | 51'36'' | 47'59'' |        |
|             | Centrale    |           |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Il       | Abruzzo     | Abruzzo   | 41°     | 14°     | 692    |
| Monte***    |             |           | 56'22'' | 37'15'' |        |
|             | Adriatico   |           |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Piana di | Puglia      | Puglia    | 41°     | 15°     | 1022   |
| M           |             |           | 43'23'' | 41'18'' |        |
| ontenero*** | Set         |           |         |         |        |
|             | tentrionale |           |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Monte    | Campania    | Campania  | 40°     | 14°     | 877    |
| Comune***   |             |           | 37'51'' | 27'38'' |        |
|             | Penisola    |           |         |         |        |
|             | Sorrentina  |           |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Monte    | Basilicata  | B         | 40°     | 15°     | 1354   |
| Li-Foi***   |             | asilicata | 38'16'' | 41'32'' |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Località | Puglia      | Puglia    | 39°     | 18°     | 211    |
| Casarano*** |             |           | 59'51'' | 11'34'' |        |
|             | Meridionale |           |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Monte    | Calabria    | Calabria  | 39°     | 16°     | 1708   |
| Pett        |             |           | 22'15'' | 37'07'' |        |
| inascura*** | Ionica      |           |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Monte    | Calabria    | Calabria  | 38°     | 16°     | 1423   |
| Pecoraro*** |             |           | 31'33'' | 20'46'' |        |
|             | Tirrenica   |           |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Monte    | Sardegna    | Sardegna  | 39°     | 09°     | 1261   |
| Armidda***  | Meridionale |           | 52'59'' | 29'42'' |        |
+-------------+-------------+-----------+---------+---------+--------+
| ***Monte    | Sicilia     | Sicilia   | 37°     | 14°     | 960    |
| Lauro***    |             |           | 07'04'' | 49'41'' |        |
|             | Meridionale |           |         |         |        |
+-------------+-------------+-----------+---------+---------+--------+

4.  ***Japan***

**GPM Ground Validation in Japan**

*\[to be completed\]*

5.  ***Korea***

**GPM Ground Validation in Korea**

Korea is located in between continental and maritime weather regime,
influenced by the North Pacific high during the summer and by the
Siberian high during the winter. As summer approaches a rainfall zone
develops over northern China, Korea, and Japan from mid-June to late
July. Northward shift of the anticyclone is also noticed during this
period. This abrupt northward advance of monsoon front is thought to be
phase-locked signal with an intraseasonal oscillation. The formation of
a new rainfall area is regionally known as the *Changma* in Korea.

Formation of deep convective clouds and heavy rainfall events are quite
often during this rainy season. Rain system is thought to be rather
complicated due to the presence of complex terrain in the Korean
peninsula in which mountains range from the northeast to the middle
south Korea. During the winter period, precipitation is often associated
with the lake effect of the Yellow Sea when northerly and north-westerly
flows are prevalent. Thus Korea experiences various forms of
precipitation, providing an ideal validation site examining rain
products retrieved under various conditions. Valuable information on
rainfall characteristics can be obtained by carefully analyzing
measurements from already equipped over the Korean peninsula. Followings
are instruments which may be used for the GV purposes.

**Raingage network**: Korea has a long history in measuring
precipitation, which dates back to 14^th^ century when the world's first
raingage was invented and had been used for regular observation until a
modern rain gauge was introduced in later 19^th^ century. Estimating the
precipitation over the peninsula, Automated Weather Station (AWS)
network is established by the Korean Meteorological Administration
(KMA). The network consists of 536 uniformly distributed (approximately
40 gauges per 1-degree box), 0.5-mm resolution, automatically
reporting-tipping raingages, continuously operated by the KMA. Figure 15
depicts the geographical distribution of the AWS network in which
one-minute rain estimates are reported.

**Radar network**: Since the first S-band radar was stationed at the top
of the Kwan-ak mountain of Seoul in 1969, the radar network is
established covering the most of Korean peninsula. They consist of
C-band Doppler radars installed at Gosan in Jeju island, Donghae,
Gunsan, Chungsong, and Baekryungdo and S-band Doppler radars installed
at Jindo, Kwanaksan, Chulwon, and Busan. These radar network may be used
for validating GPM rainfall products, in conjunction with raingage
observations. The radar for the research is different from the
operational radars in terms of frequency, polarization and mobility,
using X-band Doppler with the dual polarization capabilities installed
at a trailer.

**National Center of Intensive Observation of Severe Weathers**:
Enhancing our understanding of heavy rainfall system in summer and
improving model prediction capability, one observatory is established
for intensive data observations, in particular, for severe weather in
summer associated with typhoon and Changma. Also aimed are long-term
monitoring of surface fluxes for improvement of physical processes
between land surface and atmosphere, and study on the formation and
development mechanism of heavy rainfall system. Main instruments are 1.3
GHz-WPR, Autosonde (Vaisala), micro rain radar, optical rain gage,
X-band Doppler radar. A 20m flux tower is available. Detailed
description for the instruments is given in the following Table 9.

![](media/image17.png){width="3.70625in" height="3.754166666666667in"}

**Figure 15:** Automated Weather Station(AWS) raingauge network over
Korean peninsula.

**Table 9:** Meteorological equipment installed at National Center for
Intensive Observation of Severe Weather.

+---+-------------+--------------------+-----------------------+--------+
|   | **Meteo     | **Observation      | **Application**       | **In   |
|   | rological** | Elements**         |                       | stalla |
|   |             |                    |                       | tion** |
|   | **          |                    |                       |        |
|   | Equipment** |                    |                       |        |
+---+-------------+--------------------+-----------------------+--------+
| 1 | >           | > Wind direction,  | Producing one-minute  | > Dec  |
|   |  1.3GHz-WPR | >                  | profile of vertical   | ember, |
|   | >           | > Wind speed       | and horizontal wind   | > 2002 |
|   | >           |                    |                       |        |
|   |  (Sumitomo, |                    |                       |        |
|   | > Japan)    |                    |                       |        |
+---+-------------+--------------------+-----------------------+--------+
| 2 | > Autosonde | > Pressure,        | Producing             | > Ja   |
|   | >           | > Temperature,     | three-hourly          | nuary, |
|   | > (Vaisala, | > Relative         | upper-air observation | > 2002 |
|   | > Finland)  | > humidity, Wind   | data                  |        |
+---+-------------+--------------------+-----------------------+--------+
| 3 | > Micro     | > Reflectivity,    | Producing vertical    | > May, |
|   | > Rain      | > Rain rate,       | profiles of rain      | > 2002 |
|   | > Radar     | > Liquid water     | rate, LWC and drop    |        |
|   | >           | > content(LWC),    | size distribution     |        |
|   | >           | >                  |                       |        |
|   |  (Met-Tech, | > Drop size        |                       |        |
|   | > Germany)  | > distribution     |                       |        |
+---+-------------+--------------------+-----------------------+--------+
| 4 | > Optical   | > Rain rate        | Producing information | > May, |
|   | > Rain      |                    | to distinguish        | > 2002 |
|   | > Gauge     |                    | between rain and snow |        |
|   | >           |                    | and precipitation     |        |
|   | > (STCI,    |                    | intensity             |        |
|   | > USA)      |                    |                       |        |
+---+-------------+--------------------+-----------------------+--------+
| 5 | 20 m Flux   | Net radiation,     | Producing sensible,   | July,  |
|   | Tower       | Wind, CO₂and H₂O   | latent, radiative     | 2002   |
|   |             | concentration.     | fluxes over the land  |        |
|   | (ADTEC      | Soil temp.         | surface               |        |
|   | ,Korea)     |                    |                       |        |
+---+-------------+--------------------+-----------------------+--------+
| 6 | X-Band      | Reflectivity,      | Producing             | Nov    |
|   | Doppler     | Radial velocity,   | reflectivity and wind | ember, |
|   | Weather     | G-DR(Differential  |                       | 2002   |
|   | Radar       | reflectivity)      |                       |        |
|   |             |                    |                       |        |
|   | (EEC, USA)  |                    |                       |        |
+---+-------------+--------------------+-----------------------+--------+

6.  ***Netherlands***

**Cabauw Experimental Site for Atmospheric Research in Netherlands**

The Cabauw Experimental Site for Atmospheric Research (CESAR) is the
Netherlands' national atmospheric remote sensing facility, located near
the village of Cabauw, approximately 20 km SW of Utrecht
([http://www.cesar-observatory.nl](http://www.cesar-observatory.nl/)).
CESAR is operated by a consortium of major universities and research
institutes involved in experimental research towards
cloud-aerosol-radiation interactions, atmospheric composition,
precipitation, and land surface-atmosphere interactions. Close
collaboration exists with several foreign research groups, particularly
from Germany. The observational facility is being used for process
studies of atmospheric and land surface processes, monitoring of
long-term tendencies in climate parameters, the development of new
measurement techniques, the validation of satellite observations, and
the training of young scientists. The central theme of CESAR is *sensor
synergy* for atmospheric profiling and water/energy budget studies via
both (ground-based) remote sensing and in situ observations.

The Cabauw site, with its 213 m meteorological tower, has been the
experimental research facility of the atmospheric research group at the
Royal Netherlands Meteorological Institute (KNMI) since the early 1970s
(<http://www.knmi.nl/onderzk/atmoond/cabauw/cabauw.html>). In the
framework of CESAR, the original collection of ground-based in situ and
remote sensing instruments has been upgraded to enable the study of
cloud-aerosol-radiation interactions, atmospheric composition,
precipitation, and land surface-atmosphere interactions (Table 10).
CESAR has been operational since the summer of 2001. Since then, it has
been the center stage of several international measurement campaigns:
Baltex Bridge Cloud Campaigns 1 and 2 (BBC1, 2); CESAR Rainfall
Experiment 2002 (C-Rex'02). Currently, hydrological research efforts are
going on to close the water budget of several polder areas that surround
the Cabauw site through detailed measurements of the inputs
(precipitation, groundwater), outputs (discharge, evaporation) and
storage changes (open water levels, unsaturated zone). Ultimately, such
polders could act as huge (\~25 km^2^) rain gauges. In summary, CESAR
will provide unique opportunities for ground validation research related
to GPM.

**Table 10:** Research instrumentation available at CESAR.

+-----------------------+-----------------------+-----------------------+
| Remote Sensing        | *In Situ* Instruments | *In Situ* Instruments |
| Instruments           |                       |                       |
|                       | *measurement tower*   | *ground-based*        |
+-----------------------+-----------------------+-----------------------+
| 1 GHz wind profiler   | SJAC                  | Radiosonde            |
|                       |                       |                       |
| 3 GHz rain / cloud    | Optical particle      | 20 Rain gauges        |
| radar                 | counter               |                       |
|                       |                       | 3 Disdrometers        |
| 10 GHz rain radar     | FSSP-95               |                       |
|                       |                       | TDR soil moisture     |
| 35 GHz cloud radar    | Nephelometer          | sensors               |
|                       |                       |                       |
| 94 GHz cloud radar    | Sonic anemometer      | Groundwater tubes     |
|                       |                       |                       |
| 2 doppler weather     | Infrared fluctuation  | Discharge             |
| radars                | meter                 | measurements          |
|                       |                       |                       |
| Ceilometer            | Gas analyzer          | Operational gauge     |
|                       |                       | networks              |
| Non-scanning lidar    | Aethalometer          |                       |
|                       |                       |                       |
| Raman lidar           | Sun photometer        |                       |
|                       |                       |                       |
| Scanning lidar        | Humidograph           |                       |
|                       |                       |                       |
| UV Radiometer         | Wind sensor           |                       |
|                       |                       |                       |
| IR radiometer         | Temperature sensor    |                       |
|                       |                       |                       |
| Microwave radiometer  |                       |                       |
|                       |                       |                       |
| 42 GHz beacon         |                       |                       |
| receiver              |                       |                       |
|                       |                       |                       |
| GPS receiver          |                       |                       |
|                       |                       |                       |
| Scintillometer        |                       |                       |
| (X-LAS)               |                       |                       |
|                       |                       |                       |
| Pyranometer           |                       |                       |
+-----------------------+-----------------------+-----------------------+

![](media/image18.png){width="6.184027777777778in"
height="4.557638888888889in"}

**Figure 16:** Daily rainfall stations (\~300) and radar range markers:
75-km around operational KNMI C-band doppler radars in De Bilt and Den
Helder and 30-km around planned X-band weather surveillance radar
SOLIDAR (scanning radar which will be mounted on top of meteorological
tower at Cabauw).

![](media/image19.png){width="5.584027777777778in"
height="2.5347222222222223in"}

**Figure 17:** Rainfall instrumentation during CESAR Rainfall Experiment
2002 (C-Rex '02) that took place at Cabauw site between 1 September and
31 December 2002.

7.  ***South Africa***

**Ground Validation Facilities in South Africa**

The South African Weather Service (SAWS) has entered into a new research
and development project with the Water Research Commission for the
development of integrated rainfall estimation over Southern Africa. This
project builds on a previous initiative called the Spatial Interpolation
and Mapping of Rainfall (SIMAR), which produced integrated rain gauge,
radar and satellite rainfall products. The new project is undertaken in
partnership with the University of Natal and includes a capacity
building component as well as the integration of Meteosat Second
Generation (MSG) data and products.

The SAWS has developed a system to automatically log and communicated
data from tipping bucket rain gauges via the SMS service of the cell
phone network. In the attached figure this system is shown. A network of
these real-time automated rain gauges has been deployed over the
continental interior region of the country, which is also well covered
by S-band radar. In the near future a similar network will be deployed
over the eastern coastal areas where the characteristics of rainfall is
quiet different. These networks will provide the ideal opportunity to
verify other rainfall estimation techniques.

The SAWS and other South African partners have also been successful to
obtain funding as part of the PUMA Outlook Activities to ensure MSG
product development and implementation in South Africa. One of the
components of this project is also rainfall estimation verification and
development.

![](media/image20.png){width="6.052777777777778in"
height="3.7381944444444444in"}

**Figure 18:** Schematic diagram of realtime raingauges.

8.  ***Spain***

**Catalunya GV Site Status and Future Plans**

METEOCAT and GRAHI-UPC have proposed Catalunya as a validation supersite
for GPM mission.

The supersite design will be based on a dense C-band radar network
complemented by a raingauge network and other hydrometeorological
measurements, operationally working 24/24 hours 365 days per year. This
configuration will allow us to have a region of about 15000 km^2^ in
which any volume of space will be measured by 3 different radars at the
same time, available operationally. Also 3 super dense GPM pixels (5
raingauges+disdrometer in a 4 by 4 km box) are planned to be equipped in
the surroundings of Barcelona to study the variability inside a GPM
pixel.

The strong collaboration between Meteocat (who will operate the
supersite), the GRAHI (who will carry out the studies and develop the
processing algorithms and operational tools) and other operational
agencies as the Water Agency of Catalunya (ACA) the Sewer management
company (CLABSA) and the Spanish National Meteorological Institute
(INM), is the base of the supersite potentiality.

![](media/image21.jpeg){width="3.6951388888888888in"
height="2.161111111111111in"}

**Figure 19:** Catalunya GV Supersite region.

The strong collaboration between Meteocat (who will operate the
supersite), the GRAHI (who will carry out the studies and develop the
processing algorithms and operational tools) and other operational
agencies as the Water Agency of Catalunya (ACA) the Sewer management
company (CLABSA) and the Spanish National Meteorological Institute
(INM), is the base of the supersite potentiality.

The regional government of Catalunya has announced its compromise with
the GPM mission (press conference of 25 November 2003), and the
acceptation of the invitation received from NASA to prepare a
demonstration project of the supersite:
[http://www.grahi.upc.es/menu/GPM/index_gpm.htm .]{.underline} The
project have also received the support of the EC, by the way of the R+D
project VOLTAIRE (EVK2-2002-CT-00155) to design the setup of the
supersite, and of the Catalan Science Foundation to run the
demonstration project, and it is part of the validation program included
on the EGPM project, presently in stage A at ESA.

In occasion of the World Meteorological Day (23 March 2004) the Catalan
government (the minister of Environment) will formally confirm the
commitment of the regional government with the GPM mission driving a
validation supersite at Catalunya.

9.  ***Taiwan***

**GPM Activity in Taiwan**

The radar and surface rain-gauge network in Taiwan (see Figure 20) are
maintained by the Central Weather Bureau (CWB). The facility is the
central component of the CWB quantitative precipitation
estimate/prediction (QPE/F) projects that consists of the following:

1.  Measurements are being made by the Radar network (see Figure 20)
    with observation frequency: 6-10 min. A QC procedure is first
    applied to the raw measurements to remove ground and sea clutters,
    solitary and strip echoes. Then, a vertical Z-profile adjustment is
    performed to extrapolate the Z values from the lowest scanning level
    to surface.

2.  Surface precipitations are measured at the automatic rain gauge
    stations (see Figure 20) with observation frequency: at least 10
    min.

3.  The QPE project utilizes measurements by radars, GIS, satellite, and
    lightening, together with a regional model to derive gridded surface
    precipitation data through the following procedures: i) quality
    control of gauge data (hourly rainfall), ii) local biases calculated
    at each gauge station, iii) objective analysis of biases onto the
    QPE grid, iv) adjust of the hourly QPE precipitation products, v)
    accumulations are based on the local bias adjusted QPE, vi) local
    Gauge Adjusted Radar QPE, vii) adaptable Z-R relationships, viii)
    improvement of a regional model utilizing the gridded rainfall data.

Compliment to the CWB facility, the National Central University has a
S-band polarimetric/Doppler radar, a VHF radar, disdrometers, and
Integrated Sounding System (ISS). The facility at the NCU represents the
achievement of a group of faculty members who have devoted to the radar
and rainfall research for the past ten or more years. This group of
scientists also participated in the TRMM project and performed the
following research: 1) quality control of radar and raingauge data, 2)
radar rainfall estimate algorithms development, 3) mesoscale dynamics of
precipitation system study, 4) SCSMEX experiment, 5) new instruments
development.

In addition to the above facility and research activities, many
scientists in Taiwan are interested in the GPM GV project. At the first
stage of the Taiwan participation in the GV project, the following teams
have been identified:

• [The Central Weather Bureau]{.underline}

> The CWB will continue the improvement of QPE and QPF projects through
> the following:
>
> 1\) Develop the QC and QA procedures for its surface rainfall
> measurements
>
> 2\) Adjust radar Z-R relations using the surface rainfall data
>
> 3\) Improve 0\~2hr QPF product through a statistical analysis of the
> radar data
>
> 4\) Improve 2\~12hr QPF product through a data initialization and
> assimilation system

• [NCU Radar Team]{.underline}

> This project will carry out the following research:
>
> 1\) Develop rainfall algorithm with multiple instruments at
> NCU including polarized radar, disdrometers, Integrated Sounding
> System-ISS profiler radar
>
> 2\) Perform ground truth validation of rainfall from multiple
> instruments
>
> 3\) Study dynamics and microphysics of precipitation systems

• [Satellite Team]{.underline}

> This team will perform satellite rainfall retrievals using TRMM/TMI/PR
> & NOAA/AMSU and ground validation using rain gauge data

• [QC/QA Raingauge and Hydrological Data]{.underline}

> This project will perform a QC/QA analysis of rain gauge data and
> Spatial Interpolation of Hydrological Data through the following:
>
> 1\) Rainfall QC
>
> 2\) Conduct careful cross-check of rainfall against downstream flow
> data;
>
> 3\) Implement pixel-average-rainfalls (PAR) estimation based on the
> spatial variation characteristics of rainfall data;
>
> 4\) Evaluating the performance of existing raingauge network based on
> information entropy and geostatistics.

![](media/image22.jpeg){width="2.988888888888889in"
height="3.2930555555555556in"}![](media/image23.png)

**Figure 20:** Locations and spatial coverage of surface radars (left
panel) and surface rainfall stations (right panel) installed by Central
Weather Bureau . Triangle indicates position of NCU site. By 2005,
Polarimetric/Doppler radar will be set up at this location.

2.  ***United Kingdom***

**Ground Validation within United Kingdom**

The UK ground validation will cover Southern England and utilise
instrumentation and knowledge from the Met Office, the CCLRC Chilbolton
Facilities for Atmospheric and Radio Research (CFARR), and the
Department of Meteorology at the University of Reading. The climate in
the UK is maritime and temperate; the average annual rainfall in
Southern England is about 900 mm, spread uniformly through the year.

The UK Met Office operates a Radar network that covers most of the
Southern UK at 1 and 2km resolution (Figure 21). The Radars provide
continuous rainfall measurements 24 hours a day under an automated
system, which executes reflectivity scans at eight elevations every five
minutes. CCLRC operates the world renowned CFARR which hosts the
Chilbolton Advanced Meteorological Radar (CAMRa) (see Figure 22).

  -------------------------------------------- ------------------------------------------------------
  ![](media/image24.wmf)                       ![](media/image25.jpeg){width="2.3409722222222222in"
                                               height="2.477777777777778in"}

  **Figure 21:** UkK Met Office radar network. **Figure 22:** 25-metre fully steerable radar at
                                               CFARR.
  -------------------------------------------- ------------------------------------------------------

CAMRa is a 3GHz polarisation-Doppler fully scanning S-band radar with a
0.25^o^ beam width. Attenuation is low at this frequency, and
precipitation data can be accurately recorded to about 100 kilometres
range. It transmits and receives both horizontal and vertical
polarisation, and records full reflectivity and phase information.
Products include reflectivity, differential reflectivity, Linear
depolarisation ratio, radial velocities, spectral width, and correlation
parameters. The CAMRa radar would primarily be used to provide detailed
vertical structure of individual events, including melting layer heights
and storm dynamics, while the Met Office network will provide accurate
information on the horizontal precipitation structure. The Met Office
FAAM Bae146 aircraft (Figure 23) would also be available for campaigns,
to develop remote sensing techniques, improve understanding of physical
processes and help develop model parameterisations.

Within a one hundred kilometre range of Chilbolton, the Met Office have
at least 19 rain gauges, while more data could also be obtained from the
Environment Agency's raingauge network. Located at CFARR is a suite of
rain gauges consisting of; Rapid Response Drop Counting rain gauges, an
Optical gauge, a Joss Disdrometer, a Tipping Bucket rain gauge and a
self-syphoning capacitance gauge. Located 8km SSE of CAMRa is CFARR's
remote site Sparsholt which operates a Disdrometer, Tipping Bucket
Raingauge and a Rapid Response drop counting gauge.

Sharing the 25 metre dish with CAMRa is a 1275 MHz Clear-air Radar,
ACROBAT, used to study frontal dynamics, urban meteorology and cloud
physics. Chilbolton also operates two zenith pointing cloud radars,
Galileo at 94GHz and Copernicus at 35 GHz, a UV Raman Lidar, an IR
ceilometer, visible and IR radiometers, a cloud camera and a met
station. These provide routine quality controlled products such as
target classification, cloud fraction, ice water content, liquid water
content, turbulent kinetic energy dissipation rate and temperature.

![](media/image26.jpeg){width="6.459722222222222in"
height="4.3277777777777775in"}

**Figure 23:** UK FAMM BAe 146 aircraft.

Within a one hundred kilometre range of Chilbolton, the Met Office have
at least 19 rain gauges, while more data could also be obtained from the
Environment Agency's raingauge network. Located at CFARR is a suite of
rain gauges consisting of; Rapid Response Drop Counting rain gauges, an
Optical gauge, a Joss Disdrometer, a Tipping Bucket rain gauge and a
self-syphoning capacitance gauge. Located 8km SSE of CAMRa is CFARR's
remote site Sparsholt which operates a Disdrometer, Tipping Bucket
Raingauge and a Rapid Response drop counting gauge.

Sharing the 25 metre dish with CAMRa is a 1275 MHz Clear-air Radar,
ACROBAT, used to study frontal dynamics, urban meteorology and cloud
physics. Chilbolton also operates two zenith pointing cloud radars,
Galileo at 94GHz and Copernicus at 35 GHz, a UV Raman Lidar, an IR
ceilometer, visible and IR radiometers, a cloud camera and a met
station. These provide routine quality controlled products such as
target classification, cloud fraction, ice water content, liquid water
content, turbulent kinetic energy dissipation rate and temperature.

All the data gathered at CFARR are quality controlled and converted to a
standard data format, NetCDF. This data is released through the British
Atmospheric Data Centre (BADC), <http://badc.nerc.ac.uk/> , which caters
for thousands of users, both from within the UK and from overseas.

3.  ***United States***

**Ground Validation within United States**

***Summary of Continental GPM Supersite Concept***

Consensus from the TRMM Science Community calls for developing a NASA
GPM continental supersite in north central Oklahoma. This will be
accomplished by augmenting the existing Atmospheric Radiation
Measurement (ARM) program Cloud and Radiation Testbed (CART) site with
precipitation observing platforms. The combined suite of ARM and GPM
instruments at the CART site is intended to provide an unprecedented set
of cloud and precipitation observations in one location. Current
instrumentation at the ARM CART site includes:

-   Continuous ground based monitoring (AOS) and occasional aircraft
    profiling of aerosols

-   Radiosonde launches (up to 4 per day)

-   Column water vapor and cloud liquid water (MWR)

-   Vertical profiles of water-vapor, cloud and aerosol-related
    quantities (Raman Lidar)

-   50 and 915 MHz Wind Profiler and RASS

-   35 GHz vertically pointing radar (MMCR)

-   Cloud base height (Vaisala Ceilometer)

-   Cloud base and PBL height (Micropulse Lidar)

-   Eddy Correlation Flux Surface Bowen Ratio measurements

-   60 m meteorological tower, precipitation and snow depth gauges

With regard to required instrumentation for precipitation measurements
at the Continental GPM site, a consensus has been reached that both an
S-band polarimetric radar and a dense rain gauge network (and
disdrometers) be established. It is expected that additional
instrumentation will be determined over the next year. During the TRMM
Science meeting in October 2003, a break-out session on needs and
requirements of the NASA GPM Continental Supersite was held and the
following action items and recommendations were the outcome of that
session:

-   TRMM ground validation (GV) provides a useful roadmap for GPM
    validation.

-   Discussed concept of "rainfall regime": can expected "physics" of
    precipitation in footprint of TRMM/GPM/ground based radar (D~o~, Z
    profile), be described or linked to routinely available data like
    low level winds, reconstructed soundings, aerosol observations, etc?

-   Recommend that work on regime classification continue since it would
    provide useful guidance to satellite algorithm developers (e.g., in
    regime xxx, use Z-R relation yyy...).

-   Conduct a design study that would lead to a rain "standard" at the
    OK ARM CART site for use in the pre-GPM era consisting of dense
    gauges, distrometers, and a dual-wavelength profiler. This would be
    the accepted precipitation metric. Involve polarimetric radars for
    detailed intercomparison as these radars will be used in other
    locations for GV within the GPM era. Radars are transfer standard. S
    and X-band polarimetric systems are required.

-   Assess the role of the central. Florida gauge/radar network as well
    as the Wallops Is. Rain measuring facility in both the GPM
    pre-flight era and mission era. These sites have excellent
    capabilities and would provide for additional precipitation regimes
    to be identified and quantified. Also, when same regime is
    identified between two sites, we need to verify that they have the
    same physical characteristics (rain pdf Do, etc)

-   Algorithm developers will need to work closely with GV team and help
    design required measurements for GV.

-   It was recognized that validation for the dual precipitation radar
    (DPR) may require several detailed field campaigns that would
    provide information on vertical structure of the drop size
    distribution (DSD).

-   We have a recognized gap in our ability to routinely measure
    characteristics of ice aloft---mixing ratio, particle size
    distribution, density. Supercooled liquid water (SLW) is also
    problematic due to its transient nature and we should investigate
    radiometric techniques for use in GPM GV. Also, investigate the use
    of UAV's to carry out routine measurements of SLW and ice aloft.

-   GV design must capture multi temporal and spatial scales of
    precipitation variability.

![](media/image27.jpeg){width="6.429861111111111in"
height="4.822222222222222in"}

**Figure 24:** Location of proposed NASA GPM continental GV Supersite
with respect to surrounding observational network and design concept for
precipitation measurements at Supersite.

![](media/image28.jpeg){width="5.459722222222222in" height="3.0in"}

**Figure 25:** Flow chart illustrating concept for GV and satellite
algorithm team interaction.

***Kwajalein Atoll, Republic of Marshall Islands (Location: 8.7°N ;
167.7°E)***

**Overview:** Kwajalein Atoll is part of the Republic of the Marshall
Islands (RMI). The nation consists of a group of atolls that lie halfway
between Hawaii and Papua New Guinea (Figure 26). Kwajalein Island is the
largest and southernmost island within Kwajalein Atoll. The island is
less than 15 sq km in area and the highest point is less than 10 m above
mean sea level. Formerly an American protectorate, the RMI entered into
a Compact of Free Association with the United States upon independence
in 1986. The agreement guaranteed the continued American use of the
Reagan Test Site (RTS) of the US military. The island is accessible by
commercial airline and military transport.

Researchers have conducted meteorological experiments from Kwajalein for
several decades. Recent activities include KWAJEX (Yuter et al., 2004)
which took place in 1999, and ongoing radar and rain gauge data
collection since 1998 as part of NASA TRMM Ground Validation (Schumacher
and Houze 2000). Kwajalein receives on average \~2600 mm of rainfall
each year. Its location at 8.7° N is on the northern boundary of the
mean location of the west Pacific ITCZ. Precipitation is highly seasonal
(Figure 27), and varies with the seasonal oscillation of the ITCZ. Much
of the precipitation is associated with deep convective cloud systems,
which are modulated by both coherent wave motions trapped in the
tropical waveguide and tropical depression-like disturbances (Sobel et
al. 2003). Approximately three-quarters of the island's precipitation
occurs between May and November (Figure 27), but measurable
precipitation occurs on 50-70% of days all year round (Figure 28).

Kwajalein Island has a permanent Doppler dual polarization S-band radar
facility (Table 11) originally developed for US Army and FAA and
upgraded by NASA for TRMM Ground Validation applications. Radar coverage
spans 360 degrees and is virtually unimpaired over marine waters. The
current nominal scan strategy for the radar was developed to optimize US
Army, FAA, and NASA Ground Validation applications and has significantly
higher vertical resolution than NWS NEXRAD scans. Upper air soundings
are obtained twice daily at 0 and 12 UTC with a GPS radiosonde system.
In support of NASA TRMM, rain instruments have been installed on several
islands including a 500-m scale array of tipping bucket gauges on Roi-
Namur and Joss-Waldvogel disdrometers on Kwajalein and Roi-Namur (Table
12). The US Army contract for weather operations at RTS including the
S-band radar changed in October 2003 from Aeromet Inc. of Tulsa, OK to
3D Research Corporation of Huntsville, AL.

**Table 11:** Characteristics of Kwajalein S-band Doppler dual
polarization radar.

+------------------------------+---------------------------------------+
|                              | **Kwajalein S-band**                  |
+------------------------------+---------------------------------------+
| **Model**                    | Modified DWSR-93S                     |
+------------------------------+---------------------------------------+
| **Wavelength**               | 10.71 cm                              |
+------------------------------+---------------------------------------+
| **Peak transmit power**      | 250 kW horizontal                     |
|                              |                                       |
|                              | 250 kW vertical                       |
+------------------------------+---------------------------------------+
| **Pulse duration (µsec)**    | 0.7                                   |
+------------------------------+---------------------------------------+
| **Minimum detectable         | -108 dBm                              |
| signal**                     |                                       |
+------------------------------+---------------------------------------+
| **Antenna gain**             | \~45 dB                               |
+------------------------------+---------------------------------------+
| **PRF**                      | variable 393-960 Hz                   |
+------------------------------+---------------------------------------+
| **Polarization**             | Horizontal and vertical               |
+------------------------------+---------------------------------------+
| **Beamwidth**                | 1.12°                                 |
+------------------------------+---------------------------------------+
| **Antenna and radome         | 8.23 m parabolic dish, 11.5-m sphere  |
| dimensions**                 |                                       |
+------------------------------+---------------------------------------+
| **Antenna height**           | 24.8 m above MSL                      |
+------------------------------+---------------------------------------+
| **Maximum scan speed**       | 16 °/sec                             |
+------------------------------+---------------------------------------+
| **Elevation range**          | -0.4 to 90.5°                         |
+------------------------------+---------------------------------------+
| **Recorded radar variables** | Z~H~, V~r~, SW, Z~DR~, ρ~HV~, φ~DP~   |
+------------------------------+---------------------------------------+
| **Radar processor and        | Sigmet RVP7, RCP02, and IRIS software |
| software**                   |                                       |
+------------------------------+---------------------------------------+

**Table 12:** Rain instrumentation at Kwajalein Atoll. Tipping bucket
gauges were installed on outlying non-RTS islands in 1998-99 under
agreement with RMI weather service and NWS, but those gauges reported
only sporadically at first and more recently not at all. Instruments in
this table are all on RTS-controlled islands.

+--------+-------------------+--------------+-------+----------------+
| **Is   | **Qualimetrics    | **Jo         | **    | **Within**     |
| land** | tipping bucket**  | ss-Waldvogel | Range |                |
|        |                   | d            | f     | **clutter      |
|        | **with MadgeTech  | isdrometer** | rom** | pattern of     |
|        | logger**          |              |       | lowest radar   |
|        |                   | **with       | **    | scan (0.4°)**  |
|        |                   | logging on   | radar |                |
|        |                   | PC**         | (     |                |
|        |                   |              | km)** |                |
+--------+-------------------+--------------+-------+----------------+
| Kwa    | 2 in pair         | 1 within     | 0     | Yes            |
| jalein |                   | hedge        |       |                |
|        |                   | shelter      |       |                |
+--------+-------------------+--------------+-------+----------------+
| Carlos | 2 in pair         | \-           | 15    | Yes            |
+--------+-------------------+--------------+-------+----------------+
| Meck   | 2 in pair         | \-           | 30    | Yes            |
+--------+-------------------+--------------+-------+----------------+
| Legan  | 2 in pair         | \-           | 33    | Intermittent   |
+--------+-------------------+--------------+-------+----------------+
| Ill    | 2 in pair         | \-           | 49    | No             |
| eginni |                   |              |       |                |
+--------+-------------------+--------------+-------+----------------+
| Gagan  | 2 in pair         | \-           | 66    | No             |
+--------+-------------------+--------------+-------+----------------+
| Roi    | 7 gauges in 5     | 1 within     | 80    | No             |
| -Namur | positions within  | hedge        |       |                |
|        | 500m scale array  | shelter      |       |                |
+--------+-------------------+--------------+-------+----------------+

![](media/image29.wmf)

**Figure 26:** Republic of Marshall Islands (RMI) (1989). Kwajalein
Atoll lies at 8.5N and 167.5E \-- it is the world's largest atoll.
Reagan Test Site encompasses several islands within atoll, including
Kwajalein Island itself, located at southern tip of atoll. \[University
of Texas at Austin Library\]

![](media/image30.wmf)

**Figure 27:** Rainfall for Kwajalein Island, RMI. \[National Climatic
Data Center, NOAA\]

![](media/image31.wmf)

**Figure 28:** Average frequency of rainfall for Kwajalein, RMI.
\[NCDC\]

2.  ***West Africa***

**GPM GV Activities in West African Nations (Benin, Niger, Senegal)
*(Everett Joseph, Greg Jenkins and Jose Fuentes)***

There are several existing and planned measurement programs that provide
significant opportunity for a West Africa GV site. One effort is the
Howard University West Africa Rainfall Analysis project which is a
participant in the NASA precipitation program. The Howard project is
working to establish physical as well as support infrastructure for a GV
site in Dakar Senegal through development of a partnership among Howard
University, NASA, Ecole Superieure Polytechnique of Cheikh Anta Diop
University, and Direction De La Meteorologie Nationale (DMN; the Nation
Meteorological Service) and other institutions in Senegal.

Initial measurements will be conducted as part of the African Monsoon
Multidisciplinary Analysis (AMMA) \[AMMA, 2003; and US-AMMA SSG, 2003\]
experiment that is planned for the rainy season of 2006. A brief
description of AMMA is given below. The focus of the Howard measurement
effort in Senegal in 2006 will be to characterize the precipitation
structure and antecedent conditions of the regime that is unique to
coastal West Africa. For this purpose a dense gauge network (40) with
disdrometers will be deployed to capture the small scale (dense network
on a pixel scale) and large scale rainfall variability; this network
will remain in place long-term. Thermodynamic and dynamic measurements
will also be conducted using flux towers, profiles, and balloons. The
gauge network will also provide error bounds for ground-based radar
rainfall estimates. The NASA precipitation program will most likely
support deployment of the NASA Polarmetric Radar (NPOL) to provide the
ground-based radar rain measurements. The Laboratory for Atmospheric
Physics-Simeon Fongong (LAPSF) in Ecole Superieure Polytechnique of
Cheikh Anta Diop University has existing rain gauges and disdrometers
that will enhance the planned network. More significantly, DMN will
purchase at least one S-Band radar to expand coverage across Senegal
(possibility for dual-Doppler coverage during SOP2-3), a number of
automated weather stations, an aircraft with cloud physics measurement
capabilities, and will enhance its communication and internet capacity.
These investments stem from a mandate given to DMN by the President of
Senegal, Abdoulaye Wade, to examine the possibility of rain enhancement
by cloud seeding including the monitoring of cloud and precipitation
processes. The Howard team is working with university and government
officials to integrate the objectives of AMMA and a GPM GV site into the
national plan of Senegal for precipitation measurement.

The CATCH regional surface network (illustrated in Figure 29), which
covers Benin, Niger, Togo, Ghana, Burkina, and Mali provides opportunity
for an interior GV site. The three mesosites in CATCH will play a
central role in AMMA over the LOP: Oueme, Niamey, and Gourma. Each has
45, 34, and 11 raingauges, respectively. The French will locate an
X-band Radar in the Oueme catchment during the AMMA EOP. Operation
weather radars are shown in Figure 29. The US AMMA science team has
proposed intensive observation during SOP1-2 in the meridianal transect
of the CATCH domain that will include dual-Doppler capabilities and
airborne radars.

**AMMA:** AMMA is a multi-year, international project aimed at improving
understanding of the West African Monsoon (WAM) and its influence on the
physical, chemical and biological processes on a global and regional
scale, and relating climate variability to societal issues and
monitoring strategies. AMMA will utilize existing monitoring
infrastructure (national services and ongoing measurement programs), but
will directly and indirectly make enhancements to the quality and
frequency of surface observations across West Africa: gauge networks,
radars, radiosoundings, and soil properties. AMMA will be conducted
across multiple spatial and temporal observing scales. The long and
enhanced observing periods (LOP and EOP), which will extend to 2007, and
2010+, respectively, may directly overlap with GPM; however, the special
observing period in 2006 (designed to span one WAM cycle) will have the
most comprehensive measurement activities, and will yield significant
understanding of the characteristics of the West African precipitation
regime, which will be invaluable to GPM. The regional coverage of AMMA
is illustrated in Figure 29. The key AMMA sites include: coastal
(Senegal), Benin, and Niamey. These locations may represent the best
opportunity for GPM GV in West Africa because they have the most
accurate and reliable -- which will be enhanced in AMMA -- observational
infrastructure that is support through local and international
collaboration.

![](media/image32.jpeg){width="6.559722222222222in"
height="4.919444444444444in"}

**Figure 29:** Existing and planned surface observation networks in West
Africa that will operate during AMMA SOP and EOP/LOP. \[Source: US-AMMA
SSG, 2003\]

**4.2 Nation/Region-by-Nation/Region GV Site Readiness Summary**

1.  ***Australia (Provided by Elizabeth Ebert)***

  -------------- ------------ -------------------- ------------- ------------------
  **Facility**   **Agency**   **Equipment**        **Status**    **Additional
                                                                 Info**

  Darwin         BMRC                                            

                              C-band Doppler Radar operational   

                              C-band Polarimetric  operational   
                              Radar                              

                              Rain Gauges          operational   

                              Dense Rain Gauge     operational   
                              Network                            

                              50/920 MHz Profiler  operational   

                              Radiosonde           operational   

                              Automated Weather    operational   
                              Stations                           

                 US DOE       ARM Atmospheric      operational   
                              Radiation and Cloud                
                              Station                            

  Brisbane (CP2)                                   planned       

                              [S- and X-band       planned       
                              Polarimetric         (2004)        
                              Radar]{.underline}                 

                              220 Rain Gauges      operational   

  National       BoM          Radar-Rain Gauge     operational   Primarily costal;
                              Network                            500 synoptic, 1500
                                                                 telemetric, 4000
                                                                 cooperative rain
                                                                 gauges
  -------------- ------------ -------------------- ------------- ------------------

2.  ***Austria (Provided by Michael Schoenhuber)***

  -------------- ------------ ------------------- ------------ ------------------
  **Facility**   **Agency**   **Equipment**       **Status**   **Additional
                                                               Info**

  Graz                        Polarimetric Radar               
  -------------- ------------ ------------------- ------------ ------------------

3.  ***Brazil (Provided by Roberto Calheiros)***

  ----------------- -------------- --------------------- ------------- ------------------
  **Facility**      **Agency**     **Equipment**         **Status**    **Additional
                                                                       Info**

  National                                                             

                    Ministry of    \>2300 Rain Gauges                  agroclimatology
                    Agriculture,   (not all networked)                 
                    National                                           
                    Institute of                                       
                    Meterology                                         

                    UNESP          M55 Geophysica                      
                    (University)   aircraft                            

                    UNESP          Falcon 20 E-5                       
                    (University)   aircraft                            

                                   Sugar Cane Growers                  

                                   Hydrological                        
                                   Operators                           

  Parana            State Govt                                         

                                   S-Band Doppler Radar  Operational   

                                   Rain Gauge Network    Operational   

  Sao Paulo         State Govt                                         

                                   S-Band Radar          Operating (to 
                                                         be moved)     

                                   X-band Dual           planned       
                                   Polarization Doppler  (early 2004)  
                                   (Metro area of Sao                  
                                   Paulo)                              

                                   X-Band for coastline  planned       
                                                         (2004)        

                                   S-Band Dual Doppler   planned       
                                   1deg class antenna                  

  Sugar Cane                       2-Dedicated                         
                                   micro-meterological                 
                                   research stations                   

  Cerrado                          Dedicated                           
                                   micro-meterological                 
                                   research station                    

  Santarem/Amazon                  Dedicated                           
                                   micro-meterological                 
                                   research station                    

  Bananal Island                   Dedicated                           
                                   micro-meterological                 
                                   research station                    

  Sivam             Federal Govt                                       

                                   10 Networked Radars   6 operating   covers legal
                                                                       Amazonia

                                   200 Meterological     part          covers legal
                                   stations              operational   Amazonia

                                   60 AWS                part          covers legal
                                                         operational   Amazonia
  ----------------- -------------- --------------------- ------------- ------------------

4.  ***Canada (Provided by David Hudak)***

+-------------+-------+-------------------+---------+-----------------+
| *           | # A   | **Equipment**     | **S     | **Additional    |
| *Facility** | gency |                   | tatus** | Info**          |
+-------------+-------+-------------------+---------+-----------------+
| National    |       |                   |         | large emphasis  |
|             |       |                   |         | on snow,        |
|             |       |                   |         | low-level snow  |
|             |       |                   |         | in valleys      |
+-------------+-------+-------------------+---------+-----------------+
|             |       | C-band Radar      | oper    |                 |
|             |       | Network along     | ational |                 |
|             |       | southern border   |         |                 |
|             |       | (31)              |         |                 |
+-------------+-------+-------------------+---------+-----------------+
|             |       | Precipitation     | oper    | small X-band    |
|             |       | Occurrence        | ational | bistatic radar  |
|             |       | Sensing System    |         | for detecting   |
|             |       | (POSS) (95)       |         | precip type,    |
|             |       |                   |         | occurence, &    |
|             |       |                   |         | accum           |
+-------------+-------+-------------------+---------+-----------------+
|             |       | Ground Stations   | oper    | with the POSS   |
|             |       | (95)              | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             |       | 2 aircraft        | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
| C-MOST      |       |                   |         | Canadian        |
|             |       |                   |         | Mesoscale S T   |
+-------------+-------+-------------------+---------+-----------------+
|             |       | 45 ground         | oper    |                 |
|             |       | stations          | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             |       | 2 bi-static links | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             |       | X-band Radar      | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             |       | S-band Dual Pol   | oper    |                 |
|             |       | Radar             | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             |       | 2 Wind Profilers  | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             |       | GPS Rcvr          | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
| CARE        |       |                   |         | Centre for      |
|             |       |                   |         | Atmospheric     |
|             |       |                   |         | Research        |
|             |       |                   |         | Experiment      |
+-------------+-------+-------------------+---------+-----------------+
|             |       | C-band            | planned | set up for      |
|             |       | Dual-polarization | (2004)  | low-level       |
|             |       | Radar             |         | precipitation   |
|             |       |                   |         | off of Great    |
|             |       |                   |         | Lakes           |
+-------------+-------+-------------------+---------+-----------------+
|             |       | X-band Radar      | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             |       | 915 MHz Wind      | oper    |                 |
|             |       | Profiler          | ational |                 |
+-------------+-------+-------------------+---------+-----------------+

5.  ***China (Provided by Lu Naimeng)***

  -------------- ---------------- ------------------ ------------- ----------------
  **Facility**   **Agency**       **Equipment**      **Status**    **Additional
                                                                   Info**

  National       China            S-band Dual-Pol    operational   
                 Meteorological   Radar                            
                 Administration                                    

                                  C-band Dual-Pol    operational   
                                  Radar                            

                                  X-band Radar       operational   

                                  2300 Rain Gauges   operational   
  -------------- ---------------- ------------------ ------------- ----------------

6.  ***European Union {Provided by Ralf Bennartz)***

+-----------+---------+-------------------+---------+-----------------+
| **F       | #       | **Equipment**     | **S     | **Additional    |
| acility** |  Agency |                   | tatus** | Info**          |
+-----------+---------+-------------------+---------+-----------------+
| BALTRAD   |         | 30 radars from 11 |         |                 |
|           |         | countries         |         |                 |
+-----------+---------+-------------------+---------+-----------------+
|           |         | Rain Gauges       |         |                 |
+-----------+---------+-------------------+---------+-----------------+

7.  ***Finland (Provided by Jarmo Koistinen)***

+-------------+-------+-------------------+---------+-----------------+
| *           | **Age | **Equipment**     | **S     | **Additional    |
| *Facility** | ncy** |                   | tatus** | Info**          |
+-------------+-------+-------------------+---------+-----------------+
| Sodankyla   | FMI   | C-band Doppler    | oper    | 3D polar data   |
|             |       | weather radar     | ational | continuously    |
| (latitude   |       |                   |         | archived        |
| 67 N) CEOP  |       |                   |         |                 |
| reference   |       |                   |         |                 |
| site        |       |                   |         |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | 48-metre          | oper    | Temperature,    |
|             |       | instrumented mast | ational | wind, CO2, O3   |
|             |       |                   |         | eddy-covariance |
|             |       |                   |         | fluxes, solar   |
|             |       |                   |         | and terrestrial |
|             |       |                   |         | radiation       |
|             |       |                   |         | components etc. |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | Radiosonde        | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | UV-radiation      |         |                 |
|             |       | spectrophotometer |         |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | AWS stations      | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | Rain & snow       | oper    |                 |
|             |       | gauges            | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | Snow depth poles  | oper    | 200 snow days a |
|             |       | and devices       | ational | year            |
+-------------+-------+-------------------+---------+-----------------+
|             | FEI   | Snow courses      |         |                 |
+-------------+-------+-------------------+---------+-----------------+
| Helsinki -- | FMI   | C-band Doppler    | oper    | 3D polar data   |
| Jokioinen   |       | weather radar     | ational | continuously    |
|             |       | network           |         | archived        |
| (latitude   |       |                   |         |                 |
| 60-61 N)    |       |                   |         |                 |
| WMO Nowcast |       |                   |         |                 |
| and         |       |                   |         |                 |
| M           |       |                   |         |                 |
| esoanalysis |       |                   |         |                 |
| Testbed     |       |                   |         |                 |
| (p          |       |                   |         |                 |
| rovisional) |       |                   |         |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | Vaisa | C-band            | Under   |                 |
|             | la/HU | polarimetric      | const   |                 |
|             |       | radar             | ruction |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | F     | AWS stations      | Under   | Meso-network    |
|             | MI/Va | (100)             | con.    |                 |
|             | isala |                   |         |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | Rain & snow       | oper    |                 |
|             |       | gauges            | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | Weighing gauges   | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | Rain&snow gauge   | oper    | Manual          |
|             |       | field             | ational | observations    |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | Snow depth poles  | oper    | 150 snow days a |
|             |       | and               | ational | year            |
|             |       |                   |         |                 |
|             |       | ultrasound        |         |                 |
|             |       | sensors           |         |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | Instrumented      | oper    | T,V, RH         |
|             |       | mast, 300m        | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | Radiosonde        | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | FMI   | Ceilometers       | oper    |                 |
|             |       |                   | ational |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | Va    | Wind profiler(s)  | test    |                 |
|             | isala |                   | use     |                 |
+-------------+-------+-------------------+---------+-----------------+
|             | Va    | Radiosonde        | test    |                 |
|             | isala |                   | use     |                 |
+-------------+-------+-------------------+---------+-----------------+

8.  ***France (Provided by Guy Delrieu)***

+--------------+---------+-----------------+--------+----------------+
| **Facility** | **A     | **Equipment**   | **St   | **Additional   |
|              | gency** |                 | atus** | Info**         |
+--------------+---------+-----------------+--------+----------------+
| Palaiseau    |         |                 |        |                |
+--------------+---------+-----------------+--------+----------------+
|              |         | Radars          |        | CETP           |
+--------------+---------+-----------------+--------+----------------+
| OHM-CV       | Envi    |                 |        |                |
| (            | ronment |                 |        |                |
| Observatoire | R       |                 |        |                |
| Hydromé      | esearch |                 |        |                |
| téorologique | Obse    |                 |        |                |
| M            | rvatory |                 |        |                |
| éditerranéen |         |                 |        |                |
| Cévenn       | (ORE)   |                 |        |                |
| es-Vivarais) | of      |                 |        |                |
|              | French  |                 |        |                |
| The OHM-CV   | M       |                 |        |                |
| observation  | inistry |                 |        |                |
| window       | of      |                 |        |                |
| (200x160     | R       |                 |        |                |
| km2) is      | esearch |                 |        |                |
| located in   |         |                 |        |                |
| southeastern |         |                 |        |                |
| France.      |         |                 |        |                |
|              |         |                 |        |                |
| The region   |         |                 |        |                |
| is           |         |                 |        |                |
|              |         |                 |        |                |
| subject to   |         |                 |        |                |
| intense and  |         |                 |        |                |
| long lasting |         |                 |        |                |
| rain events  |         |                 |        |                |
| and          |         |                 |        |                |
| subsequent   |         |                 |        |                |
| flash-floods |         |                 |        |                |
+--------------+---------+-----------------+--------+----------------+
|              |         | 2 S-band radar  | opera  | ARAMIS         |
|              |         | systems         | tional | network, Météo |
|              |         |                 |        | France         |
|              |         | 1 C-band radar  |        |                |
|              |         | system          |        |                |
+--------------+---------+-----------------+--------+----------------+
|              |         | 400 daily       | opera  | Météo France,  |
|              |         | raingauges      | tional | DDE30, DDE07   |
|              |         |                 |        |                |
|              |         | 160 hourly rain |        |                |
|              |         | gauges          |        |                |
+--------------+---------+-----------------+--------+----------------+
|              |         | 45 stream gauge | opera  | DDE30, DDE07,  |
|              |         | stations        | tional | DIREN RA,      |
|              |         |                 |        | DIREN LR, EDF  |
+--------------+---------+-----------------+--------+----------------+
|              |         | GPS + weather   | Re     | LGIT, LDL,     |
|              |         | stations        | search | CNRM           |
|              |         |                 |        |                |
|              |         |                 |        | (in operation  |
|              |         |                 |        | each autumn    |
|              |         |                 |        | since 2002)    |
+--------------+---------+-----------------+--------+----------------+
|              |         | Doppl           | Re     | LTHE, (not     |
|              |         | er-polarimetric | search | before 2008)   |
|              |         | X-band radar    |        |                |
+--------------+---------+-----------------+--------+----------------+
|              |         | Disdrometer     | Re     | LTHE           |
|              |         |                 | search | (permanent     |
|              |         |                 |        | operation      |
|              |         |                 |        | since 2004)    |
+--------------+---------+-----------------+--------+----------------+
|              |         | Scintillometer  | Re     | LTHE (not      |
|              |         |                 | search | before 2007)   |
+--------------+---------+-----------------+--------+----------------+
|              |         | Innovative      | Re     | LTHE (not      |
|              |         | stream gauge    | search | before 2005)   |
|              |         | stations        |        |                |
|              |         | (video, radar)  |        |                |
+--------------+---------+-----------------+--------+----------------+
|              |         | Hillslope       | Re     | HSM, EMA, LTHE |
|              |         | hydrological    | search |                |
|              |         | instrumentation |        | (partly        |
|              |         | for several     |        | existing, to   |
|              |         | representative  |        | be developed   |
|              |         | basins          |        | in next 3      |
|              |         |                 |        | years)         |
+--------------+---------+-----------------+--------+----------------+

9.  ***Germany (Provided by Martin Hagen)***

  ------------------ ------------ ------------------- ------------- ------------------
  **Facility**       **Agency**   **Equipment**       **Status**    **Additional
                                                                    Info**

  Oberpfaffenhofen                                                  

                     DLR          C-band Polarimetric operational   
                                  Doppler Radar                     

                     DLR          Celiometer          operational   

                     DLR          Lidars              operational   

                     DLR          Ka-band Cloud Radar planned       
                                                      (2006)        

                     DLR          Aircraft            operational   

                     German       100 Rain Gauges     operational   2 owned by DLR
                     Weather                                        
                     Service                                        

                     DLR          Disdrometers        operational   

                     German       2 Weather Radars    operational   
                     Weather                                        
                     Service                                        

  Bonn               U of Bonn                                      

                                  X-band Doppler      operational   
                                  Radar                             

                                  Multi-Frequency     operational   
                                  Radiometer                        

                                  Rain Gauges         operational   

  Lindenberg         German                                         
                     Weather                                        
                     Service                                        

                                  484 MHz Wind        operational   
                                  Profiler                          

                                  1250 MHz Wind       operational   
                                  Profiler                          
  ------------------ ------------ ------------------- ------------- ------------------

10. ***Greece***

  -------------- ------------ ------------------- ------------ ------------------
  **Facility**   **Agency**   **Equipment**       **Status**   **Additional
                                                               Info**

  TBD                                                          
  -------------- ------------ ------------------- ------------ ------------------

11. ***India***

  -------------- ------------ ------------------- ------------ ------------------
  **Facility**   **Agency**   **Equipment**       **Status**   **Additional
                                                               Info**

  TBD                                                          
  -------------- ------------ ------------------- ------------ ------------------

12. ***Israel (Provided by Eyal Amitai & Daniel Rosenfeld)***

+-------------+-------+-------------------+---------+-----------------+
| *           | **Age | **Equipment**     | **S     | **Additional    |
| *Facility** | ncy** |                   | tatus** | Info**          |
+-------------+-------+-------------------+---------+-----------------+
|             | The   | Cloud physics     | Use of  | Work with       |
|             | H     | Aircraft          |         | RAINCLOUDS and  |
|             | ebrew |                   | Own     | Hebrew          |
|             | Unive | Explicit          | model   | University      |
|             | rsity | microphysics      |         | Cloud Model     |
|             | of    | modeL             | Own     |                 |
|             | Jeru  |                   | meth    |                 |
|             | salem | Microphyisical    | odology |                 |
|             |       | retrievals from   |         |                 |
|             |       | MSG               |         |                 |
+-------------+-------+-------------------+---------+-----------------+

13. ***Italy (Provided by Eugenio Gorgucci)***

  -------------- ------------- ------------------- ------------- ------------------
  **Facility**   **Agency**    **Equipment**       **Status**    **Additional
                                                                 Info**

  National                                                       

                               16 C-band Radars    operational   not networked,
                                                                 various
                                                                 capabilities

                 Civil         6 C-Band Doppler    planned       continuous
                 Protection    Dual-Pol            (2004)        operational data
                 Department,                                     collection
                 CIMA                                            

                               8 C-Band Doppler    proposed      continuous
                               Dual-Pol            (2006)        operational data
                                                                 collection

                               Rain Gauges         operational   

  Rome           CNR-ISAC                                        Info from ppt
                                                                 slide

                               C-band Doppler      operational   
                               Dual-Pol                          

                               VHF Wind Profiler   operational   24 hour operation

                               SODAR               operational   acoustic sounder,
                                                                 3 receivers

                               Multiple Receiver   operational   aerosol, temp,
                               Lidar                             water vapor

                               Vehicle-Mounted     operational   
                               Lidar (532 nm)                    

                               Microlidar (µLID    operational   
                               elastic backscatter               
                               lidar)                            

                               Meterorological     operational   temp, humidity,
                               Measurements                      etc

                               Sun Photometer      operational   aerosol optical
                               (440-1020 nm)                     depth,
                                                                 precipitable
                                                                 water, aerosol
                                                                 size distribution,
                                                                 refractive index
                                                                 and single
                                                                 scattering albedo.
                                                                 It is part of NASA
                                                                 GSFC AERONET

                               NET Radiometer      operational   incoming SW and
                                                                 outgoing LW
  -------------- ------------- ------------------- ------------- ------------------

14. ***Japan (Provided by Toshio Iguchi)***

  -------------- ------------ ------------------- ------------- ------------------
  **Facility**   **Agency**   **Equipment**       **Status**    **Additional
                                                                Info**

  Okinawa        JAXA, CRL                                      sub-tropical

                              C-band Polarimetric operational   6-minute scan
                              Radar                             
                              (COBRA/COBRA+)                    

                              C-Band Polarimetric operational   zenith-looking
                              Radar (COBRA Jr.)                 

                              Rain Gauges         operational   

                              Disdrometers        operational   

                              24 GHz Micro Rain   operational   MRR-2
                              Radar                             

                              400 MHz Wind        operational   
                              Profiler                          

                              1300 MHz Wind       operational   
                              Profiler                          

  Wakkanai       JAXA, CRL                                      snow validation
                                                                for DPR; 45.38 deg
                                                                N, 141.68 deg E

                              Wind Profiler       planned       

                              Video Disdrometer   planned       

                              Microwave           planned       
                              Precipiation Radar                
                              (MPR)                             

                              Ku-band Radar       planned       

                              W-band Radar        planned       
  -------------- ------------ ------------------- ------------- ------------------

15. ***Korea (Provided by Jae-Cheol Nam)***

  -------------- ------------ ------------------- ------------- ------------------
  **Facility**   **Agency**   **Equipment**       **Status**    **Additional
                                                                Info**

  National       KMA                                            

                              536 Rain Gauges, 13 operational   .1 and .5 mm
                              x 13 km 1 minute                  tipping bucket
                              readout                           

                              10 Radars           operational   
                              (c-,s-band)                       

                              10 Wind Profilers   planned (2004 
                                                  (2), 2005)    

                                                                

  Hae Nam (KEOP  METRI/KMA                                      operating as CEOP
  supersite)                                                    supersite

                              S-band Doppler      Operational   
                              Radar                             

                              C-band Doppler      Operational   
                              Radar                             

                              X-band Doppler      Operational   
                              Radar                             

                              Autosonde           Operational   

                              Boundary Layer Wind Operational   
                              Profiler                          

                              Micro Rain Radar    Operational   

                              Flux Tower (10 m)   Operational   

                              Optical Rain Gauge  Operational   

                              Radiometer          Operational   

                                                                
  -------------- ------------ ------------------- ------------- ------------------

16. ***Netherlands (Provided by Remko Uijlenhoet)***

  -------------- -------------- ------------------- -------------- ----------------------------
  **Facility**   **Agency**     **Equipment**       **Status**     **Additional Info**

  Cabauw         Consortium of                                     Cabauw Experimental Site for
                 Universities                                      Atmospheric Research
                 and Research                                      (CESAR);
                 Centers                                           Clouds/aerosols/radiation,
                                                                   atmospheric composition,
                                                                   precipitation, land
                                                                   surface/atmosphere

                                1 GHz Wind Profiler operational    

                                3 GHz Rain-Cloud    operational    3-beam Doppler Polarimetric
                                Profiler                           

                                35 GHz Cloud Radar  operational    

                                X-band Radar        planned (2004) high resolution scanning
                                                                   radar, 30 m resolution, 30
                                                                   km range

                                94 GHz Cloud Radar  uncertain      GKSS contribution

                                Non-scattering      operational    
                                Lidar                              

                                Raman Lidar         operational    

                                Scanning Lidar      operational    

                                30 Rain Gauges      12             1 per square km
                                                    operational,   
                                                    others by end  
                                                    of 2003        

                                Microwave           operational    U of Bonn contribution
                                Radiometer                         

                                2 Optical           operational    
                                Disdrometers                       

                                2-D Video           operational    ESA/ESTEC contribution
                                Disdrometer                        

                                Substantial other   operational    IR Radiometer, UV
                                meterological                      Radiometer, pyranometer, 213
                                equipment                          m flux/radiation tower,
                                                                   Ceilometer, ARM-type
                                                                   measurements, ...

                                27 GHz Link         proposed       

  National       KNMI                                              

                                2 C-Band Doppler    operational    De Bilt, Den Helder
                                Radars                             

                                350 Daily Rain      operational    1/100 sq km
                                Gauges                             

                                35 Auto Rain Gauges operational    1/1000 sq km
                                (10 min)                           

                                10\'s of gauges     operational    
                                from water                         
                                authority                          
  -------------- -------------- ------------------- -------------- ----------------------------

17. ***South Africa***

  -------------- ------------ ------------------- ------------ ------------------
  **Facility**   **Agency**   **Equipment**       **Status**   **Additional
                                                               Info**

  TBD                                                          
  -------------- ------------ ------------------- ------------ ------------------

18. ***Spain (Provided by Daniel Sempere-Torres)***

  -------------- ------------ ------------------- ------------- ------------------
  **Facility**   **Agency**   **Equipment**       **Status**    **Additional
                                                                Info**

  Catalunya      UPC                                            interesting events
                                                                of heavy rain: 2
                                                                events per year \>
                                                                100 mm/day; 1
                                                                event per 2 yr \>
                                                                200 mm/day; 15,000
                                                                sq km total area
                                                                seen by 3 radars

                              3 C-Band Doppler    operational   
                              Radars                            

                              2 C-Band Doppler    planned       
                              Radars              (2003, 2004)  

                              Rain Gauges, 1/100  operational   
                              sq km                             

                              Rain Gauges, 1/64   planned       
                              sq km                             

                              Radiosondes                       

                              hydrological                      hydrological
                              monitoring                        validation using
                                                                runoff model
  -------------- ------------ ------------------- ------------- ------------------

19. ***Taiwan (Provided by Chung-Hsiung Sui)***

  -------------- ------------ ------------------- ------------- ------------------
  **Facility**   **Agency**   **Equipment**       **Status**    **Additional
                                                                Info**

  National                                                      working on TRMM
                                                                GV, plan to use
                                                                multiple sensors
                                                                for micro-physical
                                                                determination

                              360 Automatic Rain  operational   hourly data
                              Gauges                            routinely
                                                                available, can
                                                                output at 1 minute
                                                                resolution

                              30 to 40 Rain       planned       
                              Gauges                            

                              5 Weather Radars    operational   

                              S-band Dual         planned       
                              Polarization        (2004)        
                              Doppler Radar                     

                              VHF Radar           operational   

                              Integrated Sounding operational   includes wind
                              System                            profiler

                              2 2-D Disdrometers  operational   

                              3 J-W Disdrometers  operational   
  -------------- ------------ ------------------- ------------- ------------------

20. ***United Kingdom (Provided by John Goddard)***

  -------------- ------------ ------------------- ------------- ------------------
  **Facility**   **Agency**   **Equipment**       **Status**    **Additional
                                                                Info**

  National       MET OFFICE   Radar Network       operational   5-minute scans,
                                                                1-2 km resolution

                              19 MET Office rain  operational   
                              gauges                            

                 NERC / MET   MET Office FAAM     operational   
                 OFFICE       BAe146 Aircraft                   

  Chilbolton     CCLRC        3 GHz Polarisation  operational   25 m antenna, 0.25
                              Doppler Radar                     ^o^ beam width

                 CCLRC        1275 MHz clear-air  operational   25 m antenna
                              radar                             

                 CCLRC        94 GHz Doppler      operational   
                              Cloud Radar                       

                 CCLRC        35 GHz Doppler      operational   
                              Cloud Radar                       

                 CCLRC        UV Raman Lidar      operational   

                 CCLRC        IR Lidar Ceilometer operational   

                 CCLRC        22.2, 28.8, 37.5    operational   
                              GHz Millimetre wave               
                              Radiometers                       

                 CCLRC        2-frequency links   planned       
                              for path                          
                              attenuation                       
                              measurements                      

                 CCLRC        Radid response      operational   
                              drop-counting rain                
                              gauges                            

                 CCLRC        Joss disdrometers   operational   

                 CCLRC        Optical Rain Gauge  operational   

                 CCLRC        Tipping bucket      operational   
                              gauges                            

                 CCLRC        Self-syphoning      operational   
                              capacitance gauge                 

                 CCLRC        Cloud camera        operational   

                 CCLRC        Met station         operational   

                 CCLRC        Visible and IR      operational   
                              Broadband                         
                              Radiometers                       
  -------------- ------------ ------------------- ------------- ------------------

21. ***United States (Provided by*** ***Mark Miller and Sandra E.
    Yuter)***

  -------------- ------------ --------------------- -------------- -----------------------------
  **Facility**   **Agency**   **Equipment**         **Status**     **Additional Info**

  National       NOAA                                              Operational data collection

                              NEXRAD Radar                         

                              Rain Gauges                          

                              Other Extensive                      
                              Meterological                        
                              Monitoring                           

                              Hydro-Meterological   operating and  Substantial set of
                              Testbeds              planned        precipitation instruments

                                                                   

  Continental                                       developing     considering DOE ARM site in
  Site                                              concept and    OK
                                                    requirements   

                 NASA         S-band Polarimetric   planned        
                              Radar                                

                              X-band Polarimetric   planned        
                              Radar                                

                              Rain Gauges           planned        

                              Disdrometers          planned        

                              Dense Rain Gauge      planned        
                              Network                              

                 DOE          Aerosols              operational    ARM

                              Radiosondes           operational    ARM

                              915 MHz Wind Profiler operational    ARM

                              35 GHz cloud radar    planned (2004) ARM

                              94 GHz cloud radar    operational    ARM

                              lidar                 operational    ARM

                              S-band vertical point proposed       ARM
                              radar                                

                              NEXRAD Radar          operational    ARM

  Ocean Site                                        developing     considering Kwajalein Atoll
                                                    concept and    
                                                    requirements   

                 NASA         S-Band Doppler Dual   operational    
                              Polarization Radar                   

                              Qualimetrics tipping  operational    
                              buckets                              

                              Joss-Waldvogel        operational    
                              disdrometers                         

  Central                                                          around Kennedy Space Center
  Florida                                                          

                 NOAA         NEXRAD Radar          operational    Melbourne

                              Rain Gauge Network    operational    

                 NASA         Dense Rain Gauge      operating, tlm 20 pairs on 2 km grid
                              Network               system planned 

                              Very High Density     proposed       20 pairs in 2 km x 2 km
                              Rain Gauge Network                   region

                              222 meteorological    operational    1200 sq km area
                              sensors on 44 towers                 

                              50 MHz Doppler wind   operational    
                              profiler                             

                              915 MHz Wind Profiler operational    

                              Lightning detection   operational    
                              and ranging (66 MHz                  
                              rcvrs)                               

                              Disdrometer network   proposed       3 disdrometers +
                                                                   interpolation/extrapolation
                                                                   algorithm

                 NASA/NOAA    S-band Polarimetric   operational    
                              Doppler Radar                        

                              C-band Doppler Radar  operational    

                 USGS         X-band Polarimetric   planned        
                              Radar                                

                              Vertically-Pointed    operational    
                              Radar                                

                              Rain Gauges           operational    

                              Microwave Links       operational    

                              2-D Video Disdrometer operational    

                              Impact Disdrometers   operational    

  Florida Keys   NASA                                              

                              10 Rain Gauges        operational    

                              1 Disdrometer         operational    
  -------------- ------------ --------------------- -------------- -----------------------------

22. ***West Africa Consortium (Provided by Everette Joseph)***

  -------------- -------------------- ------------------- ------------- ------------------
  **Facility**   **Agency**           **Equipment**       **Status**    **Additional
                                                                        Info**

  Dakar          Howard U, U of VA, U                                   
                 of ND, Cheikh Anta                                     
                 Diop (U of Dakar)                                      
                 LPA, Senegal, NASA                                     

                                      S-Band NPOL         proposed      
                                      Polarimetric Radar  (2006)        

                                      Rain Gauges         proposed      
                                                          (2006)        

                                      Disdrometers        proposed      
                                                          (2006)        

                 Dakar                C-Band Radar        operational   calibration
                                                                        problems

                 Dakar                S-Band Radar        planned       

  Benin          African                                                substantial
                 Multi-Disciplinary                                     equipment planned
                 Monsoon Analysis                                       for 2004

                 France               X-Band Radar        planned       
                                                          (2004)        

                                      Catch Basin Network planned       
                                                          (2004)        

                                      Aircraft            planned       
                                                          (2004)        
  -------------- -------------------- ------------------- ------------- ------------------

**5.0 High-level Recommendations for Successful International GPM GV
Programme**

-   GPM's GV Research Programme should be designed both to validate and
    improve GPM's standard precipitation retrieval algorithms and to
    better understand physical and dynamical nature of precipitating
    storms.

-   Global network of GPM GV sites should be established by
    international partners to enable comprehensive ground-based
    observations of precipitation system's 3-dimensional structure
    (dynamic, thermodynamic, macrophysical, and microphysical processes
    and properties), along with capability for continuous observational
    monitoring of storm life cycles.

-   International GV working group should be established within GPM
    Mission's international framework to ensure and manage data /
    information exchange between GV sites and other
    precipitation-centric data gathering operations (i.e., operational
    data collection programs, specialized national / international
    research-oriented data acquisition projects, and national /
    international field experiments focused on cloud and precipitation
    processes) \-- all of this designed for strong interactions with
    algorithm developers.

-   Subset of GV sites should operate as GV Supersites to enable
    near-realtime error characterization for data assimilation
    applications and to enable continuous algorithm improvement through
    near-realtime detection of significant errors in GPM's standard
    precipitation algorithms.

-   One or more Virtual GV Sites should be established to enable diverse
    sensor observations of regional area(s).

-   At least one GV Supersite for land-based snowfall validation should
    be implemented.

-   Dependable instruments and methods for measurement of rainfall and
    snowfall over ocean should be developed.

-   All GPM GV scientific data, i.e., all GV data and GV data products
    offered for release to GPM Mission by GV site operators (and thus
    designated as GPM GV scientific data) should be provided on free and
    open exchange basis with GPM science and engineering community. Free
    and open GV data policy should be written into GPM Mission's
    "charter".

-   Data transmission delays of GPM GV scientific data should be
    minimized.

    **6.0 GPM GV Point Of Contact for Nation/Region**

1\. Australia Elizabeth Ebert \<e.ebert@bom.gov.au\>

2\. Austria Michael Schoenhuber \<michael.schoenhuber@joanneum.at\>

3\. Brazil (2) Roberto Calheiros \<calheiros@www.radar.ipmet.unesp.br\>

Carlos Morales \<morales@model.iag.usp.br\>

4\. Canada (2) Paul Joe \[Ontario\] \<<paul.joe@ec.gc.ca>\>

David Hudak \[Ontario\] \<David.Hudak@ec.gc.ca\>

5\. China Lu Naimeng \< lunaimeng@nsmc.cma.gov.cn\>

6\. European Union (BALTRAD) Ralf Bennartz \<bennartz@aos.wisc.edu\>

7\. Finland Jarmo Koistinen \<jarmo.koistinen@fmi.fi\>

8\. France Nicolas Viltard \<viltard@cetp.ipsl.fr\>

9\. Germany Martin Hagen \<martin.hagen@dlr.de\>

10\. Greece (2) Emmanouil Anagnostou \<manos@engr.uconn.edu\>

Vasso Kotroni \<kotroni@meteo.noa.gr\>

11\. India Raju Garudachar \<raju_garudachar@hotmail.com\>

12\. Israel (2) Daniel Rosenfeld \<<daniel@vms.huji.ac.il>\>

Eyal Amitai \<eyal@radar.gsfc.nasa.gov\>

13\. Italy Eugenio Gorgucci \<e.gorgucci@isac.cnr.it\>

14\. Japan Shuji Shimizu\<shuji.shimizu@jaxa.jp\>

15\. Korea Byung-Ju Sohn \<sohn@snu.ac.kr\>

16\. Netherlands Remko Uijlenhoet \< Remko.Uijlenhoet@wur.nl\>

17\. South Africa Deon Terblanche \<deon@metsys.weathersa.co.za\>

18\. Spain Daniel Sempere-Torres \<sempere@grahi.upc.es\>

19\. Taiwan Ming-Dah Chou \<mdchou@atmos1.as.ntu.edu.tw\>

20\. United Kingdom John Goddard \<j.w.f.goddard@rl.ac.uk\>

21\. United States Matt Schwaller \<mathew.r.schwaller@nasa.gov\>

22\. West Africa Consortium Everette Joseph \<ejoseph@howard.edu\>

**7.0 References**

AMMA, 2003: An international research project and field campaign.
http://medias.obs-mip.fr/amma/.

Awaka, J., T. Iguchi, and K. Okamoto, 1998: Early results on rain type
classification by the Tropical Rainfall Measuring Mission (TRMM)
precipitation radar. Proc. URSI-F Symp. on Wave Propagation and Remote
Sensing \[Aveiro, Portugal\], 143-146.

Bringi, V.N., and C.V. Chandrasekar, , 2001: *Polarimetric Doppler
Weather Radar*. Cambridge University Press, Cambridge, 636 pp.

Browning, K.A., and R. Wexler, 1968: The determination of kinematic
properties of a wind field using Doppler radar. *J. Appl. Meteor.*,
**7**, 105-113.

Koistinen, J., and D.B. Michelson, 2002: BALTEX weather radar-based
precipitation products and their accuracies. *Boreal Env. Res*., **7**,
253-263.

Koistinen, J., D.B. Michelson, H. Hohti, and M. Peura, 2003: Operational
measurement of precipitation in cold climates. *Weather Radar:
Principles and Advanced Applications* (P. Meischner, ed., 337 pp),
Springer, Berlin, 78-114. \[ISSN 1610-1677; ISBN 3-540-000328-2\]

Koscielny, A.J., R.J. Doviak, and R. Rabin, 1982: Statistical
considerations in the estimation of divergence from single Doppler radar
and application to prestorm boundary layer observations. *J. Appl.
Meteorol*., **21**, 197-210.

Lhermitte, R.M., and D.A. Atlas, 1961: Precipitation motion by pulse
Doppler radar. Proc. 9th Weather Radar Conf. \[Boston\], Amer. Meteorol.
Soc., Boston, MA, 218-223.

Mahfouf, J.-F., V. Marécal, and P. Bauer, 2003: The assimilation of
SSM/I and TMI rainfall rates in the ECMWF 4D-Var system. *Quart. J. Roy.
Met. Soc*., submitted.

Marécal V., and J.-F. Mahfouf, 2002: Four-dimensional variational
assimilation of total column water vapour in rainy areas. *Mon. Wea.
Rev*., **130**, 43-58.

Michelson, D.B., T. Anderson, C.G. Collier, Z. Dziewit, J. Koistinen, S.
Overgaard, J. Riedl, and V. Zhukov, 1999: The international radar
network for the Baltic Sea Experiment. Preprints, 29^th^ Radar
Meteorology Conference \[12-16 July 1999; Montreal, Canada\], Amer.
Meteorol. Soc., Boston, MA, 317-320.

Moreau, E., P. Lopez, P. Bauer, A.M. Tompkins, M. Janiskovà, and F.
Chevallier, 2003: Variational retrieval of temperature and humidity
profiles using rain-rates versus microwave brightness temperatures.
*Quart. J. Roy. Met. Soc.*, submitted.

Pylkkö, P., B. Bizzarri, G. Blöschl, S. Metsämäki, and J. Pulliainen,
2003: Status of snow monitoring. EUMETSAT H-SAF internal document (15
Dec 2003), 10 pp.

Raschke E., J. Meywerk, K. Warrach, U. Andrae, S. Bergström, F. Beyrich,
F. Bosveld, K. Bumke, C. Fortelius, L.P. Graham, S.--E. Gryning, S.
Halldin, L . Hasse, M. Heikinheimo, H.--J. Isemer, D. Jacob, I. Jauja,
K.--G. Karlsson, S. Keevallik, J. Koistinen, A. van Lammeren, U. Laas,
J. Launiainen, A. Lehmann, B. Liljebladh, M. Lobmeyer, W. Matthäus, T.
Mengelkamp, D.B. Michelson, J. Napiorkowski, A. Omstedt, J. Piechura, B.
Rockel, F. Rubel, E. Ruprecht, A.--S. Smedman, and A. Stigebrandt, 2001:
The Baltic Sea Experiment (BALTEX): A European contribution to the
investigation of the energy and water cycle over a large drainage basin.
*Bull. Amer. Meteor. Soc*., **82**, 2389-2413.

Rosenfeld D., and C.W. Ulbrich, 2003: Cloud microphysical properties,
processes, and rainfall estimation opportunities. Chapter 10 of *Radar
and Atmospheric Scienc*e: Chapter 10 \-- A Collection of Essays in Honor
of David Atlas (R.M. Wakimoto and R. Srivastava, eds.). *AMS
Meteorological Monographs*, **52**, 237-258.

Schumacher, C., and R.A. Houze, Jr., 2000: Comparison of radar data from
the TRMM satellite and Kwajalein oceanic validation site. *J. Appl.
Meteor*., **39**, 2151-2164.

Simmons, A., and A. Hollingsworth, 2001: Some aspects on the improvement
in skill of numerical weather prediction. ECMWF Technical Memorandum No.
342, European Center for Medium Range Weather Forecasting, Reading,
England.

Sobel, A.H., S.E. Yuter, C.S. Bretherton, and G.N. Kiladis, 2003:
Large-scale meteorology and deep convection during TRMM KWAJEX. *Mon.
Wea. Rev.*, in press.

Steiner, M., R.A. Houze, Jr., and S.E. Yuter, 1995: Climatological
characterization of three-dimensional storm structure from operational
radar and rain gauge data. *J. Appl. Meteor*., **34**, 1978-2007.

Trapp, R.J., and C.A. Doswell III, 2000: Radar data objective analysis.
*J. Atmos. Oceanic Technol*., **17**, 105-120.

US-AMMA SSG, 2003: A proposal for US participation in the African
Monsoon Multidisciplinary Analysis (AMMA) project.
http://www.joss.ucar.edu/amma.

Waldteufel, P., and H. Corbin, 1979: On the analysis of single Doppler
radar data. *J. Appl. Meteor.*, **18**, 532 - 542.

Yuter S.E., and R.A. Houze, Jr., 1995: Three-dimensional kinematic and
microphysical evolution of Florida cumulonimbus. Part II: Frequency
distributions of vertical velocity, reflectivity, and differential
reflectivity. *Mon. Wea. Rev.*, **123**, 1941-1963.

Yuter, S.E., and R.A. Houze, Jr., 1997: Measurements of raindrop size
distributions over the Pacific warm pool and implications for Z-R
relations. *J. Appl. Meteor.*, **36**, 847-867.

Yuter, S., R. Houze, V. Chandrasekar, E. Foufoula-Georgiou, M. Hagen, R.
Johnson, D. Kingsmill, R. Lawrence, F. Marks, S. Rutledge, and J.
Weinman, 2002: GPM Draft Science Implementation Plan Ground Validation
Chapter. Accessible at: [www.arxiv.org](http://www.arxiv.org/),
arXiv:physics/0211095, 22 pp.

Yuter, S.E., R.A. Houze, Jr., E.A. Smith, T.T. Wilheit, and E. Zipser,
2005: Physical characterization of tropical oceanic convection observed
in KWAJEX. *J. Appl. Meteor*., in press.

**8.0 Appendices**

**8.1 Attendees of Abingdon Meeting**

  -------------- ----------- ------------------------- ------------- -------------------------------------------------------------------------------------------
  **Surname**    **First     **Company / University /  **Country**   **E-mail Address**
                 Name**      Agency**                                

  Amitai         Eyal        NASA - GSFC               USA           [[eyal@radar.gsfc.nasa.gov]{.underline}](mailto:eyal@radar.gsfc.nasa.gov)

  Bauer          Peter       ECMWF                     UK            [[peter.bauer@ecmwf.int]{.underline}](mailto:peter.bauer@ecmwf.int)

  Bibyk          Irene       NASA - GSFC               USA           [[Irene.Bibyk@nasa.gov]{.underline}](mailto:Irene.Bibyk@nasa.gov)

  Bidwell        Steven      NASA - GSFC               USA           [[Steven.W.Bidwell@nasa.gov]{.underline}](mailto:Steven.W.Bidwell@nasa.gov)

  Calheiros      Roberto     IPMET                     Brazil        [[calbeiros@ipmet.unesp.br]{.underline}](mailto:calbeiros@ipmet.unesp.br)

  Chandrasekar   V           Colorado State University USA           [[chandra@engr.colostate.edu]{.underline}](mailto:chandra@engr.colostate.edu)

  Chen           Wann-Jin    Chung Cheng Inst. of      Taiwan        [[Wannjin@ccit.edu.tw]{.underline}](mailto:Wannjin@ccit.edu.tw)
                             Technology                              

  Cifelli        Robert      Colorado State University USA           [[rob@radarmet.atmos.colostate.edu]{.underline}](mailto:rob@radarmet.atmos.colostate.edu)

  Di Michelle    Sabatino    Institute of Atmopsheric  Italy         [[S.DiMichele@isac.cnr.it]{.underline}](mailto:S.DiMichele@isac.cnr.it)
                             Sciences and Climate                    
                             (ISAC)                                  

  Ebert          Elizabeth   Bureau of Meteorology     Australia     [[e.ebert@bom.au]{.underline}](mailto:e.ebert@bom.au)
                             Research Centre                         

  Everett        David       NASA - GSFC               USA           [[David.F.Everett@nasa.gov]{.underline}](mailto:David.F.Everett@nasa.gov)

  Facheris       Luca        Dipart.di Elettronica E   Italy         [[facheris@ingfi1.ing.unifi.it]{.underline}](mailto:facheris@ingfi1.ing.unifi.it)
                             Telecomm.                               

  Ferraro        Ralph       NOAA/NESDIS/Cooperative   USA           [[Ralfph.R.Ferraro@noaa.gov]{.underline}](mailto:Ralfph.R.Ferraro@noaa.gov)
                             Institute for Climate                   
                             Studies                                 

  Fuentes        Jose        University of Virginia    USA           [[jf6s@virginia.edu]{.underline}](mailto:jf6s@virginia.edu)

  Goddard        John        Rutherford Appleton       UK            [[J.W.F.Goddard@rl.ac.uk]{.underline}](mailto:J.W.F.Goddard@rl.ac.uk)
                             Laboratory                              

  Goodison       Barry       Meteorological Service of Canada        [[Barry.Goodison@ec.gc.ca]{.underline}](mailto:Barry.Goodison@ec.gc.ca)
                             Canada                                  

  Gorgucci       Eugenio     Istituto di Scienze       Italy         [[gorgucci@radar.ifa.rm.cnr.it]{.underline}](mailto:gorgucci@radar.ifa.rm.cnr.it)
                             dell\'Atmosfera e del                   
                             Clima                                   

  Haddad         Ziad        Jet Propulsion Laboratory USA           [[zsh@albertovo5.jpl.nasa.gov]{.underline}](mailto:zsh@albertovo5.jpl.nasa.gov)

  Hagen          Martin      Institut fur Physik der   Germany       [[martin.hagen@dir.de]{.underline}](mailto:martin.hagen@dir.de)
                             Atmosphare                              

  Hanado         Hiroshi     CRL, Appl.Sci & Standards Japan         [[hanado@crl.go.jp]{.underline}](mailto:hanado@crl.go.jp)
                             Div.                                    

  Hudak          David       Meteorological Service of Canada        [[David.Hudak@ec.gc.ca]{.underline}](mailto:David.Hudak@ec.gc.ca)
                             Canada                                  

  Hwang          Paul        NASA - GSFC               USA           [[paul.h.hwang@nasa.gov]{.underline}](mailto:paul.h.hwang@nasa.gov)

  Illingworth    Anthony     University of Reading     UK            [[a.j.illingworth@reading.ac.uk]{.underline}](mailto:a.j.illingworth@reading.ac.uk)

  Jones          Linwood     CFL                       USA           [[LJONES5@CFL.RR.COM]{.underline}](mailto:LJONES5@CFL.RR.COM)

  Joseph         Everette    Howard Uni., Dept. of     USA           [[ejoseph@howard.edu]{.underline}](mailto:ejoseph@howard.edu)
                             Physics                                 

  Kakar          Ramesh      NASA                      USA           [[rkakar@hq.nasa.gov]{.underline}](mailto:rkakar@hq.nasa.gov)

  Kidd           Chris       University of Birmingham  UK            [[C.Kidd@bham.ac.uk]{.underline}](mailto:C.Kidd@bham.ac.uk)

  Kitchen        Malcolm     Met Office                UK            [[malcolm.kitchen@metoffice.com]{.underline}](mailto:malcolm.kitchen@metoffice.com)

  Klein          Ulf         European Space Agency     Netherlands   [Ulf.Klein@esa.int]{.underline}
  -------------- ----------- ------------------------- ------------- -------------------------------------------------------------------------------------------

  --------------- ------------ ------------------ ------------- ---------------------------------------------------------------------------------------------------
  **Surname**     **First      **Company /        **Country**   **E-mail Address**
                  Name**       University /                     
                               Agency**                         

  Koistinen       Jarmo        Finnish            Finland       [[Jarmo.Koistinen@fmi.fi]{.underline}](mailto:Jarmo.Koistinen@fmi.fi)
                               Meteorological                   

  Kuo             Kwo-Sen      NASA -GSFC         USA           [[Kwo-Sen.Kuo@gsfc.nasa.gov]{.underline}](mailto:Kwo-Sen.Kuo@gsfc.nasa.gov)

  Lawrence        Richard      NASA - GSFC        USA           [[Richard.J.Lawrence@nasa.gov]{.underline}](mailto:Richard.J.Lawrence@nasa.gov)

  Laws            Kevin        NOAA               USA           [[kevin.laws@noaa.gov]{.underline}](mailto:kevin.laws@noaa.gov)

  L\'Ecuyer       Tristan      Colorado State     USA           [[tristan@kangaroo.atmos.colostate.edu]{.underline}](mailto:tristan@kangaroo.atmos.colostate.edu)
                               University                       

  Levizzani       Vincenzo     ISAC-CNR           Italy         [[v.levizzani@cnr.it]{.underline}](mailto:v.levizzani@cnr.it)

  Matzler         Christian    Universitat Bern   Switzerland   [[matzler@iap.unibe.ch]{.underline}](mailto:matzler@iap.unibe.ch)

  Miller          Mark         Brookhaven         USA           [[miller@bnl.gov]{.underline}](mailto:miller@bnl.gov)
                               National                         
                               Laboratory                       

  Mugnai          Alberto      CNR/ISAC           Italy         [[a.mugnai@isac.cnr.it]{.underline}](mailto:a.mugnai@isac.cnr.it)

  Nakamura        Kenji        Nagoya University, Japan         [[nakamura@ihas.nagoya-u.ac.jp]{.underline}](mailto:nakamura@ihas.nagoya-u.ac.jp)
                               Hydrosheric                      
                               Atmospheric                      
                               Research Center                  

  Nam             Jae-Cheol    Korea              Repub.of      [[jcnam@metri.re.kr]{.underline}](mailto:jcnam@metri.re.kr)
                               Meteorological     Korea         
                               Admin.                           

  Okamoto         Ken\'ichi    AERO               Japan         [[okamoto@aero.osakafu-u.ac.jp]{.underline}](mailto:okamoto@aero.osakafu-u.ac.jp)

  Perez-Fontan    Fernando     ETS Ingenieros de  Spain         [[fpfontan@tsc.uvigo.es]{.underline}](mailto:fpfontan@tsc.uvigo.es)
                               Telecomunicacion                 

  Pollard         David        Met Office         UK            [[david.pollard@metoffice.com]{.underline}](mailto:david.pollard@metoffice.com)

  Ralph           Martin       NOAA/ETL           USA           [[marty.ralph@noaa.gov]{.underline}](mailto:marty.ralph@noaa.gov)

  Roth            Giorgio      CIMA, University   Italy         [[giorgio@cima.unige.it]{.underline}](mailto:giorgio@cima.unige.it)
                               of Genoa                         

  Russchenberg    Herman       Delft University   Netherlands   [[h.w.j.russchenberg@irctr.tudelft.nl]{.underline}](mailto:h.w.j.russchenberg@irctr.tudelft.nl)
                               of Technology,                   
                               IRCTR                            

  Schoenhuber     Michael      Joanneum Research, Austria       [[Michael.Schoenhuber@joanneum.at]{.underline}](mailto:Michael.Schoenhuber@joanneum.at)
                               Appl. Syst. Tech.                

  Schulz          Joerg        University of      Germany       [[joerg.schulz@uni-bonn.de]{.underline}](mailto:joerg.schulz@uni-bonn.de)
                               Bonn, Met.                       
                               Institute                        

  Sempre-Torres   Daniel       UPC                Spain         [[sempere@graphi.upc.es]{.underline}](mailto:sempere@graphi.upc.es)

  Shimizu         Shuji        Earth Observation  Japan         [[shimizu@eorc.nasda.go.jp]{.underline}](mailto:shimizu@eorc.nasda.go.jp)
                               Research Center                  

  Smith           Eric         NASA - GSFC        USA           [[eric.ac.smith@nasa.gov]{.underline}](mailto:eric.ac.smith@nasa.gov)

  Sui             Chung-Hasn   National Central   Taiwan        [[sui@cc.ncu.edu.tw]{.underline}](mailto:sui@cc.ncu.edu.tw)
                               Uni., Hydrol.Sci.                

  Tokay           Ali          NASA - GFSC        USA           [[tokay@radar.gsfc.nasa.gov]{.underline}](mailto:tokay@radar.gsfc.nasa.gov)

  Uijlenhoet      Remko        Wageningen Uni.,   Netherlands   [[Remko.Uijlenhoet@wur.nl]{.underline}](mailto:Remko.Uijlenhoet@wur.nl)
                               Dep. Environ.Sci.                

  Wilson          Carron       Rutherford         UK            [[C.L.Wilson@rl.ac.uk]{.underline}](mailto:C.L.Wilson@rl.ac.uk)
                               Appleton                         
                               Laboratory                       

  Wolff           David        NASA - GSFC        USA           [[wolff@radar.gsfc.nasa.gov]{.underline}](mailto:wolff@radar.gsfc.nasa.gov)

  Wood            Robert       University of      USA           [[robwood@atmos.washington.edu]{.underline}](mailto:robwood@atmos.washington.edu)
                               Washington,                      
                               Atmos.Sci.                       

  Yang            Daqing       University of      USA           [[ffdy@uaf.edu]{.underline}](mailto:ffdy@uaf.edu)
                               Alaska Fairbanks                 

  Yuter           Sandra       University of      USA           [[yuter@atmos.washington.edu]{.underline}](mailto:yuter@atmos.washington.edu)
                               Washington,                      
                               Atmos.Sci.                       
  --------------- ------------ ------------------ ------------- ---------------------------------------------------------------------------------------------------

**8.2 Agenda of Abingdon Meeting**

**Day 1: Tuesday, 4 November**

**09:00 Registration**

**10:00 Preliminaries** *(J. Goddard \-- Session Chair)*

10:00 Welcome *(K.Craig)*

10:15 Definition of International GPM GV Research Program & Workshop
Objectives (*E. Smith)*

**10:30 Session 1a: Status of GPM/EGPM Programs *(J. Goddard \-- Session
Chair)***

10:30 NASA's GPM Mission Program *(R. Kakar)*

10:45 JAXA's GPM Mission Program *(K. Nakamura)*

11:00 ESA's EGPM Mission Program *(P. Baptista)*

**11:15 Tea Break**

**11:35 Session 1b: GV Science Requirements for GPM/EGPM Projects**
***(K. Okamoto \-- Session Chair)***

11.35 JAXA GPM/DPR Calibration & Validation Plan *(S. Shimizu & K.
Nakamura)*

12:00 NASA GPM GV Science Requirements *(E. Smith)*

12:20 ESA/EC EGPM GV Science Requirements *(A. Mugnai)*

12:40 Coordinated Activities for GPM GV European Science Community *(V.
Levizzani)*

**13:00 Lunch at Coseners House**

**14:00 Session 2a: Distributed International GPM GV Program #1 *(G.
Roth \-- Session Chair)***

14:00 GV Research in UK for GPM/EGPM Missions *(J. Goddard, A.
Illingworth & M. Kitchen)*

14:20 NASA GPM Continental Supersite Template *(S. Rutledge)*

14:40 NASA GPM Oceanic Supersite Template *(S. Yuter)*

15:00 European GPM Virtual GV Site Template *(M. Hagen)*

15:20  Japan's Supersite *(H. Hanado & K. Okamoto)*

15:40 Schedule & Technical Requirements for GPM Supersite *(I. Bibyk &
S. Bidwell)*

**16:00 Tea Break**

**16:20 Session 2b: Distributed International GPM GV Program #2 *(R.
Hood \-- Session Chair)***

16:20 Current Implementation of Voltaire Project's Precipitation GV
Research Program *(D. Sempere-Torres & E. Amitai)*

16:40 KMA's Operational Precipitation GV Capabilities in Korea *(J-C.
Nam)*

17:00 Emerging Opportunies for GPM GV in Canada *(D. Hudak)*

17:20 Ongoing Precipitation GV Research Program at BOM in Australia *(E.
Ebert)*

17:40 Scientific & Technical Progress Towards Precipitation GV in Brazil
*(R. Calheiros & H.da Rocha)*

18:00 TRMM & GPM GV Research Projects in Taiwan *(C-H. Sui)*

**18:20 Logistics Update *(C. Wilson)***

**18:30 End of Day's Activities**

**Day 2: Wednesday, 5 November**

**08:30 Pre-Plenary for Splinter Session I *(E. Smith -- Chair)***

08:30 Discussion of & Guidance for Working Groups

**08:50 2-Hour Breakout into Four (4) Working Groups**

WG#1a: Retrieval Error Characterization

*(Chair \-- E. Ebert; Raporteur \-- T. L'Cuyer)*

WG#2a: Regional Mapping of GV Error using Supersite Network

*(Chair \-- M. Hagen; Raporteur \-- R. Cifelli)*

WG#3a: New Challenges and Ideas for GV Research

*(Chair \-- V. Chandrasekar; Raporteur \-- E. Gorgucci)*

WG#4a: GV Opportunities for Operational Raingauge/Radar Networks

*(Chair \-- R. Ferraro; Raporteur \-- C. Kidd)*

**10:50 Tea Break *(Session Chairs & Raporteurs Prepare Summaries)***

**11:20 Post-Plenary for Splinter Session I *(A. Mugnai \-- Chair)***

11:20 Summary Report from WG#1a *(E. Ebert)*

11:30 Summary Report from WG#2a *(M. Hagen)*

11:40 Summary Report from WG#3a *(V. Chandrasekar)*

11:50 Summary Report from WG#4a *(R. Ferraro)*

**12:00 Lunch at Coseners House**

**13:00 5-Hour Field Trip to Chilbolton Observatory *(J. Goddard & C.
Wilson -- Hosts)***

**19:30 *\"Remember Remember the 5th of November\",* Dinner at Coseners
House**

**Day 3: Thursday, 6 November**

**09:00 Session 2c: Distributed International GPM GV Program #3 *(A.
Illingworth \-- Session Chair)***

09:00 New Opportunities for GV Measurement Program in West Africa *(E.
Joseph)*

09:20 Unique Aspects of Rain Measuring Network for GV Research at KSC,
Florida *(L. Jones)*

09:40 Transitioning GV Research from TRMM to GPM in Israel *(D.
Rosenfeld & V. Levizzani)*

10:00 PrecipitationResearch at the Cabauw Experimental Site for
Atmospheric Research *(R. Uijlenhoet, H.W.J. Russchenberg, and I.
Holleman)*

**10:20 Tea Break**

**10:40 Session 3: Synergy with Ongoing GV Research Projects *(R.
Uijlenhoet \-- Session Chair)***

10:40 Scientific Significance of Precipitation GV at DOE's Southern
Great Plains ARM Site *(M. Miller)*

11:00 Recent Developments in Precipitation GV within NOAA *(M. Ralph)*

11:20 TRMM's Ground Validation Research Program *(R. Adler & D. Wolff)*

11:40 Utility for Realtime Rain Retrieval Error Characterization at
ECMWF *(P. Bauer)*

12:00 Evaluating Precipitation GV Measurements in Context of Boundary
Layer Processes (*J. Fuentes & M. Garstang)*

12:20 Progress Towards Physical Error Modeling in Precipitation
Retrieval *(K-S. Kuo)*

12:40 Current GV Research Program at Wallops Island, Virginia *(A.
Toka*y)

**13:00 Lunch at Coseners House**

**14:00 Pre-Plenary for Splinter Session II** ***(E. Smith -- Chair)***

14:00 Discussion of & Guidance for Working Groups

**14:20 2-Hour Breakout into Four (4) Working Groups**

WG#1b: International GPM GV Organizational Requirements

*(Chair \-- V. Levizzani; Raporteur \-- R. Lawrence)*

WG#2b: Scientific Goals of International GPM GV Research Program

*(Chair \-- K. Okamoto; Raporteur \-- P. Hwang)*

WG#3b: Accuracy Requirements

*(Chair \-- P. Baptista; Raporteur \-- J. Schulz)*

WG#4b: Precision and Error Covariance Requirements

*(Chair \-- S. Yuter; Raporteur \-- J. Koistinen)*

**16:20 Tea Break** 

(Session Chairs & Raporteurs Prepare Summaries)

**16:50 Post-Plenary for Splinter Session II *(K. Nakamura \-- Chair)***

16:50 Summary Report from WG#1b *(V. Levizzani)*

17:00 Summary Report from WG#2b *(K. Okamoto)*

17:20 Summary Report from WG#4b *(S. Yuter)*

**17:30 End of Day's Activities**

**Day 4: Friday, 7 November**

**09:00 Session 4: Summary *(B. Goodison \-- Session Chair)***

09:00 Country, Region, and Agency Site Readiness *(D. Everett & J-C.
Nam)*

09:30 Potential GV-Site Concept *(V. Levizzani & J. Goddard)*

10:00 Organizational & Science Objectives *(A. Mugnai and K. Nakamura)*

10:30 Measurement Objectives & New Research Avenues *(S. Yuter and V.
Chandrasekar)*

**11:00 Tea Break**

**11:30 Session 5: Wrap-up *(E. Smith \-- Session Chair)***

**11:30 Pending Action Items (open discussion)**

**11:45 Workshop Document (open discussion)**

**12:00 Goals, Possible Sites, and Time Frame for 2nd Meeting (open
discussion)**

**12:15 Parting Words by Hosts**

**12:30 End of Workshop**

**13:00 Steering Group Meeting**

13:00 Lunch (Election of 2 Co-Chairs)

14:00 Planning for International GPM GV Document

15:30 Tea Break

17:00 Meeting Ends

**8.3 Web Access to Abingdon Meeting Presentation Materials**

All of the presentation materials from the Abingdon Workshop are
available at <http://www.rcru.rl.ac.uk/GPMGV/>. An additional website
has been established at GSFC which contains all of the Abingdon Workshop
materials and will contain all future GV Workshop materials.