**Air-Sea Interactions in Tropical Cyclones Workshop**

**Camp Springs, DC 24-25 May 2005**

**Preface:**

This workshop was convened to address the near- and far-term
theoretical, observing, and modeling challenges in developing the
next-generation coupled ocean-hurricane prediction system to become
operational at the National Weather Service/National Centers for
Environmental Prediction (NWS/NCEP) during 2007. A broad cross-section
of researchers, numerical modelers, operational forecasters, and
managers of governmental and university research programs gathered at
NCEP in May 2005 to identify the scientific challenges associated with
coupled models and to discuss potential avenues for addressing those
challenges.

The context for this workshop, in both the NWS and US Weather Research
Program (USWRP) frameworks was provided by Steve Lord
(NCEP/Environmental Modeling Center) and Naomi Surgi (NCEP/EMC). Nick
Shay (Rosenstiel School of Marine and Atmospheric Science/University of
Miami) provided the overall charge of the workshop, which is to assess
progress in the Air-Sea Interaction Community based on field programs
and modeling studies sponsored by National Science Foundation, Office of
Naval Research and National Oceanic and Atmospheric Administration
through the USWRP Hurricane Landfall program, and to identify pressing
scientific issues related to improving the physics of the air-sea
interaction problem under strong winds in a hurricane and forecast
models. Central to this theme is how the forecasting community can use
these data sets to improve predictions from coupled ocean-atmosphere
models. A clear objective of the workshop was to open the dialogue
between the forecasting and research communities, and understand each
group's needs. Breakout groups were designed to maximize discussions
between forecasters and researchers in addressing these cross-cutting
issues.

To set the scene for the challenges that lie ahead, the workshop began
with a series of overview presentations from NCEP-related activities:
Operational Modeling (Surgi), Wave Modeling (Tolman), Ocean Modeling
(Lozano), Data Assimilation (Derber), and Coupled Modeling
(Ginis-University of Rhode Island). A recurrent theme was that any
potential improvements for intensity forecasts must not degrade track
forecasts. The two breakout groups in the afternoon focused on model
forecasting and required observations. The second day focused on
research issues and their importance for forecasting issues: Oceanic
Observations (Shay-UM), Atmospheric Boundary Layer Observations
(Barnes-University of Hawaii), Ocean Modeling (Jacob-University of
Maryland-Baltimore County), and Sea Spray Parameterization Schemes
(Fairall-Environmental Technology Laboratory). In addition, two brief
talks were given by Girton (University of Washington-Applied Physics
Laboratory) and Terrill (Scripps Institution of Oceanography) on
profiling floats that were deployed in the ONR-Coupled Boundary Layer
Air-Sea Transfer (CBLAST) program. This session emphasized the need for
continued observations to improve our understanding of physical
processes and model parameterizations prior to implementation in
forecast models. The afternoon breakout sessions focused on setting
priorities and refining focused recommendations discussed in Plenary on
the first day.

A summary of the workshop presentations and findings is given in the
following report: the key recommendations of the two working groups are
presented first and this is followed by summaries of the individual
presentations. The Appendices contain the workshop agenda, lists of
workshop participants and working group members and discussions of
individual break-out groups. We thank all of the contributors to this
report, including all of the speakers and workshop attendees. Thanks to
Steve Lord and colleagues at EMC/NCEP for providing the support for the
workshop.

Nick Shay, Naomi Surgi, Joe Cione

Workshop Conveners June 2005

##### Table of Contents

Introduction

Workshop Report and Overview

> Executive Summary 3
>
> Key Recommendations 4
>
> A. Air-Sea
> Parameterizations.....................................................................\...5
>
> B. Data Archive 5
>
> C. Sampling Approach 6
>
> D. Ocean Model Initializations and Mixing Parameterizations 7
>
> 1.0 Welcome, Introduction and Purpose of the Workshop (Stephen
> Lord/Naomi Surgi,
>
> NWS Environmental Modeling Center) 9

2.0 Summary of April 05 CBLAST Workshop 10

3.0 Summary of Presentations 10

> A. NCEP Forecaster Overviews 11
>
> A.1 Operational Modeling at NCEP (Naomi Surgi, NCEP) 11
>
> A.2 Surface Wave Modeling at NCEP (Hendrik Tolman, NCEP) 11
>
> A.3 Operational Ocean Modeling at NCEP (Carlos Lozano, NCEP) 12
>
> A.4 Data Assimilation Efforts at NCEP (John Derber, NCEP) 12
>
> A.5 Coupled Modeling at URI/ NCEP (Issac Ginis, URI) 13
>
> B. Researcher Overviews 14
>
> B.1 Upper Ocean Observations (Lynn K. (Nick) Shay, RSMAS) 14
>
> B.2 Atmospheric Boundary Layer (Gary Barnes, UH) 16
>
> B.3 Ocean Modeling (S. Daniel Jacob, UMBC) 16
>
> B.4 Sea Spray Parameterizations (Chris Fairall, ETL) 17
>
> B.5 EM APEX Floats (James Girton, UW/APL) 18
>
> B.6 ARGO Profiling Floats (Eric Terrill, SIO) 18

Appendix A: Agenda for Air-Sea Interactions in Tropical Cyclones
Workshop 24-25 May 2005 20

Appendix B: Questions 21

Appendix C: Participants / Break Out Group Assignments 22

Appendix D: Workshop Organizers 23

Appendix E: Data needs for the Coupled HWRF/HYCOM 24

Appendix F: Instrumentation for Coupled HWRF/HYCOM 25

Appendix G: Break Out Group 1 Notes 26

Appendix H: Break Out Group 2 Notes 27

**Air-Sea Interactions in Tropical Cyclones Workshop**

**Camp Springs, DC 24-25 May 2005**

**Workshop Report and Overview**

**Executive Summary**

The Weather and Research forecast system (WRF) is currently under
development by the U.S. research and operational modeling communities
and will replace current mesoscale modeling capabilities for various
mesoscale The Weather Research and Forecast (WRF) system is currently
under development by the U.S. weather research and operational modeling
communities. The WRF will replace current mesoscale modeling
capabilities for various mesoscale forecast applications at operational
Numerical Weather Prediction centers including NCEP and AFWA beginning
in 2004. The WRF for hurricane forecasts (HWRF) will replace the
Geophysical Fluid Dynamics Laboratory hurricane prediction system at
NWS/NCEP and will be coupled to the Hybrid Community Ocean Model (HYCOM)
in 2007. This coupled system will serve as the nation's next-generation
operational hurricane prediction system, as well as serve as the primary
research hurricane model.

Although significant progress has been made over the past several
decades in advancing our Nations hurricane track forecasting capability,
many forecast challenges remain that need to be addressed by the next
generation Although significant progress has been made over the past
several decades in advancing our nation's hurricane track forecasting
capability, scientific and forecast challenges remain that need to be
addressed by the next-generation coupled ocean-wave-atmosphere hurricane
prediction system, which includes understanding the role of the upper
ocean on hurricane intensity through the air-sea interface and the
atmospheric boundary layer. Given a spectrum of differing track
scenarios such as erratically moving storms, storms that accelerate, and
storms that stall, any improvements to the hurricane intensity forecast
must not degrade track forecasting. In the case of a tropical cyclone
interacting with the upper ocean, any subsequent intensity change is
sensitive to the track forecasts. Notwithstanding, when the forecast
track is fairly certain within 36 hours of landfall, understanding the
ocean's role on the intensity change through air-sea interactions
becomes of paramount importance as deep ribbons of high oceanic heat
content water surround the US coastline. By providing better initial
conditions ocean conditions, and improving air-sea parameterization
schemes in the coupled models, we may expect improved forecast of the
tropical cyclone surface wind field, the ensuing storm surges and the
inland flooding, which accounts for a majority of the Nation's
hurricane-related fatalities.

To meet the above forecast challenges significant advances must
concurrently occur in advanced observations, data assimilation
techniques and model development for both the hurricane environment and
the hurricane core To meet these forecast challenges, significant
advances must concurrently occur in observations, data assimilation
techniques; and model development for both the hurricane environment and
the hurricane core to properly simulate the complex interactions between
the physical and dynamical processes on different scales of motion that
determine the hurricane motion, and to forecast intensity changes over
the open and coastal ocean during hurricane landfall. The HWRF will be a
high-resolution, coupled air/sea/land hurricane prediction model with
advanced physics. Other planned advancements in the HWRF system include
a local advanced atmospheric data assimilation capability to address the
next generation initialization of the hurricane-core circulation. It is
envisioned a similar process must occur for oceanic data assimilation on
the basin scale, such as from the ongoing Global Ocean Data Assimilation
Experiments (GODAE).

The U.S. Weather Research Program \[USWRP\] was designed to bring
together researchers and the operational community to meet such
challenges as these. It is under the auspices of USWRP that this
workshop was The the The U.S. Weather Research Program (USWRP) was
designed to bring together researchers and the operational community to
meet such challenges as these. It is under the auspices of the USWRP
that this workshop was convened to begin discussing: (1) the
state-of-the-art in tropical cyclone models and observations; (2)
maximizing the usefulness of various data sets that have been acquired
by various groups in hurricane environments over the past five years
(ONR CBLAST in multiple hurricanes; NSF/NOAA Experiments in Isidore and
Lili; NRL in Ivan; MMS in Georges, etc); and (3) upper-ocean
observational strategies to acquire more complete data sets that must
now include ocean current and salinity profiles as well as thermal
profiles to evaluate the oceanic and coupled forecast models.

One of the key impediments that must be addressed by the community is to
provide a comprehensive data archive to support the operational
implementation of the HWRF in the 2007 time horizon. Specific attention
must be directed toward improving air-sea parameterizations (such as
drag and enthalpy coefficients), and to assess the relative importance
of sea spray under fetch-limited wave fields. The development and
testing of air-sea parameterizations at high wind speeds are required
for the tropical cyclone forecast problem for both the large-scale
environment and on the tropical cyclone scale. These were the
overarching objectives presented to the broad cross-section of
researchers, modelers, operational forecasters, and physicists, and
managers of governmental and university research programs who gathered
at the NCEP in May 2005.

Break-out groups purposely included both forecasters and researchers to
deal with cross-cutting ocean-atmosphere issues. Each group focused on
the same sets of questions with the intent to recommend a set of
priorities to deal with the coupled ocean-wave-atmosphere part of the
forecast models. Within the broad framework of ocean-atmosphere
coupling, the central questions posed to each breakout group were:

1.  What is the current *state-of-the-art* in observations and models
    for the tropical cyclone problem, and how can this community
    maximize recently acquired data sets?

2.  What relevant time-space scales need to be resolved to improve
    intensity predictions in the models and what observations are needed
    to evaluate them with regard to vertical mixing, wave coupling, and
    air-sea parameterizations?

3.  What metrics need to be in place for assessment of model-generated
    fields, and how do we implement them in near-real time for
    forecasting needs?

4.  What is the design of an optimal field program for the evaluation of
    these models fields for *in situ* and satellite-based support? How
    can the community maximize the Global Ocean Observing System data to
    steadily improve ocean models?

A benefit of this approach was a similar set of recommendations were
determined from both break-out groups. That is, a consensus was reached
from the more than 30 participants. In addition, the informal exchanges
between forecasters and researchers will inevitably foster
collaborations. Such collaborative ties between academia, government,
and private sectors are central to advancing our understanding of the
tropical cyclone intensity forecast problem and achieving the NCEP goal
of having a fully coupled HWRF/HYCOM model for operations.

**Breakout Group Recommendations:**

Both working groups agreed that infrastructure and resources need to be
developed over the next three years. Specific recommendations are:

1.  Given the range of uncertainty in the surface drag (e.g., wave
    effects), heat fluxes (e.g., sea spray), and initial conditions
    (e.g., wind field) beyond 30 m s^-1^ using CBLAST data, assess how
    these uncertainties propagate through the coupled GFDL/HWRF model;

> 2\. Develop an archive of data sets and model outputs and make these
> archives publicly available for research and operational purposes.
> Investigate the potential use of these data sets in assimilation,
> evaluation, and verification of models and parameterization schemes
> (e.g., HYCOM);
>
> 3\. Create an in-situ tropical cyclone ocean-atmosphere observing
> program for pre-storm, storm, and post-storm environments. Develop
> optimal observing strategies and observational mix for spatial
> evolution of upper ocean, interface, and atmospheric fields (including
> secondary circulations such as roll vortices in the hurricane boundary
> layer); and;
>
> 4\. Develop improved ocean model initialization schemes through data
> assimilation of satellite and *in situ* measurements, and test mixing
> parameterizations for a spectrum of ocean, wave and atmospheric
> conditions including the impact of waves on the surface heat, moisture
> and momentum fluxes and thus on the evolving ocean mixed layer.

A recurrent theme in all of the discussions from both breakout groups
was that this program needs to build on recent field programs such as
ONR-CBLAST experiments in multiple years and NSF/NOAA in Isidore and
Lili. In this broader context the background and justification for each
of these four recommendations is provided in the following four
subsections.

**1. Air-Sea Parameterizations**

A central issue in the air-sea interaction parameterizations is the
appropriate value for the surface drag coefficients during high winds.
It is clear from the recent experimental data that the drag coefficient
does not continue to increase *ad-infinitum* with winds. Several
investigations have shown that the coefficient seems to have a maximum
between 28 to 32 m s^-1^ with values of 2.5 to 3.5 x 10^-3^. These
investigations range from using Global Positioning Sondes (GPS) sonde
wind profiles extrapolated to the surface, wind-wave tank results,
turbulent flux measurements, numerical modeling results with coupled
wave-atmospheric models and using forced upper ocean currents as a
tracer of momentum flux. While the air-sea community agrees on the
leveling off of surface drag values, what remains unclear is whether the
drag decreases with higher winds or remains relatively constant.
Measurements must be acquired on the right side of the storm where the
wind and waves are presumably interacting with the ocean current field
to impact the momentum flux and the surface drag, which then feeds back
to hurricane intensity.

Another critical issue is the role of sea spray in high winds, and
especially thermodynamic effects of the evaporation of spray in the
tropical cyclone boundary layers. Three important parts in understanding
the impact of sea spray are: 1) size spectrum characterization as a
function of forcing (stress, wave breaking, etc); 2) exchanges of heat
and moisture with an initial state at rest; and 3) sub-grid scale
distortion of the surface layer temperature and moisture structure by
droplets. Of particular interest is the feedback mechanism that
characterizes the manner in which the various sizes of evaporating
droplets modify the stratification near the oceanic surface layer, which
reduces further droplet evaporation, but enhances the sensible heat
fluxes. This approach introduces tuning coefficients based on the ratio
of the enthalpy flux and surface drag coefficient that are a function of
tropical cyclone intensity. For a high-droplet source function, this
ratio decreases in the current version of the model. To get the impact
of sea spray correct, measurements in the surface layer (\~50 m) are
required that include turbulent fluxes, mean profile structures, wave
spectra, wave breaking and accurate estimates of rain rates.
Measurements at 50-m levels may not be attainable from the NOAA WP-3D
aircraft, but perhaps a sensor package could be potentially developed
for a Unmanned Aerial Vehicle (UAV) to address this scientific question
(see
ftp://ftp.etl.noaa.gov/user/cfairall/onr_droplet/parameterization/).

In a broader context, the ONR-CBLAST data must be used to examine the
sensitivity of the model simulations to these parameterizations. This
modeling-based approach would provide insights into the parameter space
of these important air-sea processes where data in the atmospheric and
oceanic boundary layers can be used to constrain model solutions. This
would lead to an understanding of uncertainties in observations and
provide a motivation for the next series of field experiments discussed
below.

**2. Data Archive**

The breakout working groups agreed that coupled ocean-atmosphere data
sets must be archived and maintained for the community for use in model
evaluation studies (the evaluation step is considered to come before the
validation step). Such data sets must include:

1.  Josephine (1984) and Gloria (1985) current and temperature profiles
    from the Ocean Response to a Hurricane (ORTAH ) project;

2.  Gilbert (1988) current and temperature profiles prior, during, and
    subsequent to the storm from the ONR/NOAA project;

3.  Dennis (1999) ocean mixed layer float data acquired prior, during,
    and subsequent to the storm for an NSF project;

4.  Georges (1999) current and temperature profile data acquired prior,
    during, and subsequent to the storm for an Minerals Management
    Service (MMS) project;

5.  Isidore and Lili (2002) current, temperature, and salinity profiles
    acquired prior, during, and subsequent to the storm for an NSF/NOAA
    project;

6.  Frances (2004) current, temperature and salinity profiles acquired
    prior, during and subsequent to the storm for the ONR CBLAST
    project; and

7.  Ivan (2004) current, temperature, and salinity data acquired prior,
    during and subsequent to the storm for an NRL project in the
    northern Gulf of Mexico.

*In summary, only in a few storms have ocean current and shear
structures been observed over the past 21 years from aircraft
campaigns.* Moored measurements during Georges and Ivan were fortuitous
encounters, as opposed to focused aircraft-based experiments in CBLAST
and NSF/NOAA programs. Given its importance for shear-induced mixing
processes (Richardson number instabilities), this relatively poor data
base needs to be improved to advance coupled modeling during hurricane
conditions.

These data sets, along with surface forcing from remote sensors (both
satellite- and aircraft-based), GPS sondes and available wave data
should have a permanent archive site where the community can access
these valuable data sets. The NDBC surface buoy data and thermal
profiles from Airborne eXpendable Bathythermographs (AXBT) from decades
of measurements must be included in such an archive. The archive should
also include model-generated fields from GFDL that could be used by
graduate students for their thesis/dissertation research. As noted in
both breakout groups, this will require resources to establish the
archive, locate the data and establish quality controls, and maintain it
perhaps on a password basis for investigators working with NCEP. This
effort will require a full-time position for a couple of years to
establish it.

**3. Sampling Approach**

In support of these recommendations, and the recent successes of the ONR
CBLAST and the NSF/NOAA program, the minimum sampling approach must
include pre-storm, during and post-storm measurements to understand the
impacts of the ocean forcing on the atmosphere, and the oceanic response
to the tropical cyclone forcing. Specifically, the required types of
observations and platforms to address this problem are:

1.  Pre-storm survey (oceanic temperature (T), velocity (u,v) including
    shear, salinity (S), pressure (p)) using a combination of Lagrangian
    floats and drifters, and aircraft expendables. These ocean
    measurements should be at least through the main thermocline (upper
    250 m or deeper in warm ocean features) and preferably to as deep as
    1000 m to resolve the background flows through the dynamic height
    field. Boundary layer structure must also be observed with GPS
    sondes and remote sensors such as the Stepped Frequency Microwave
    Radiometer (SFMR);

2.  Storm survey (T, u, v, S, p) from floats and drifters, and
    expendables profiling through at least 250 m; wave measurements from
    floats and aircraft remote sensors; boundary layer structure from
    GPS sondes; surface winds from Lagrangian drifters and aircraft
    remote sensing; sea-spray down to 50 m; and turbulence flux profiles
    from aircraft-based (or UAV) measurements; and,

3.  Post-storm (T,u,v, S, p) from floats and drifters, and expendables
    over the domain of the storm survey; surface wave and wind
    measurements from floats and remote sensors; and GPS sondes for the
    atmospheric boundary layer structure.

This approach emphasizes observations over both space and time using
floats, drifters, and expendables that are capable of measuring current,
temperature, and salinity. What is lost in time from the spatial
snapshots from the aircraft is gained by high time resolution in floats
and drifters. Thus, the measurement approach emphasizes flexibility to
optimize the data acquisition efforts since no single approach will
resolve the coupling issues.

Upper-ocean measurements of T, u, v, and S should have a vertical
resolution of less than 4-m to accurately estimate current shears and
Richardson numbers and the floats should measure these profiles at least
at hourly intervals. In terms of horizontal resolution during the storm,
the oceanic and atmospheric profiles should be spaced no more than 0.5
radii of maximum winds (Rmax). Remote sensing and flux measurements must
be as rapidly as possible.

For non-events and more routine measurements for model evaluation and
validation of the basic state of the ocean, both groups recommended
enhancements to the NDBC buoy program to measure temperature and current
profile time series, surface wind stress and directional surface waves;
continued enhancements of the ARGO/Electro-Magnetic Autonomous Profiling
EXplorer (APEX) floats (including mixed layer floats) and drifters as
part of Integrated Ocean Observing System (IOOS); utilization of the
growing network of High Frequency (HF) Coastal Radars deployed as part
of the Coastal Ocean Observing System (COOS) to measure currents, waves
and winds; and NWS WSR-88D radar networks.

**4. Ocean Model Initialization and Mixing Parameterizations:**

Based on recent findings, particularly in the Loop Current and warm core
ring complex in the Gulf of Mexico, initializing ocean models with the
correct background states represents a challenge for the modeling
community. To improve the understanding of the role of the upper ocean
on tropical cyclone intensity, the background state must be specified
with the correct thermal and density structure that will then give rise
to ocean features where energetic currents occur along frontal
boundaries. Such features include the Loop Current, Florida Current and
Gulf Stream which lead to the transport warm, high oceanic heat content
from the tropics to the mid-latitudes as part of the climate cycle. One
method is adjusting the model is through data assimilation of the
sea-surface height from satellite radar altimetry and sea-surface
temperature fields and projecting the surface height field vertically as
is currently done in the HYCOM model. In many instances, this approach
has worked reasonably well. However, assimilating T/S profiles from
float data (or other routine measurements) is an opportunity that must
be fully explored to get the correct basic state in terms of the
thermal, haline, density and velocity structures. Time-dependent
behavior of these warmer oceanic features (significantly reduced
negative feedback to the hurricane) must also be evaluated with these
data sets to ensure that the initial model fields are correct prior to
the passage of a tropical cyclone.

A second important issue deals with the oceanic mixing parameterizations
in ocean models. Given the number of mixing schemes available at the
present time, choosing the most appropriate scheme for an oceanic or
coupled system requires careful examination of simulated fields with
observed profiles to understand the sensitivity of the oceanic response
to these mixing schemes. With the exception of the bulk schemes, the
turbulent kinetic energy schemes depend primarily on shear at the base
of the oceanic mixed layer to parameterize entrainment heat flux. This
shear term has been shown to contribute between 60 to 80% to the
observed oceanic mixed layer cooling in predominately negative feedback
regimes (away from frontal boundaries). Vertical shear effects in the
ocean are similar to those of atmospheric shear, although the shear must
be calculated over much smaller vertical scales. Large values of ocean
shear, will lower the Richardson numbers to below criticality, and force
the upper ocean to mix and cool. Recent simulations from each of these
schemes has shown that for the same initial ocean conditions and same
forcing, the amount of cooling in the ocean mixed layer differs
considerably in terms of magnitude and structure. The amount of ocean
cooling impacts the available air-sea fluxes that provide heat and
moisture for the storm. The amount of uncertainties in surface fluxes
from these various mixing parameterizations is unacceptable for an ocean
model or fully coupled system because they will lead to larger
uncertainties in intensity and structure of a tropical cyclone. In
addition, the oceanic mixed layer heat, mass, and momentum budgets are
affected by advection of the gradients in frontal regimes due to the
background and wind-forced currents. In these cases, the oceanic mixed
layer budgets are not 1-D, rather they are 3-D. Thus, careful attention
must be devoted to mixing schemes and considerably more current and
shear data are required to represent parameter space for oceanic models.

Little attention has been given to the impact of the surface wave
interactions with the surface current field, and the impact of the wave
coupling on the oceanic mixed layer processes through breaking waves.
For example, in strong oceanic current regimes, the vorticity field
associated with background and wind-forced currents will impact the
surface waves through wave-current interactions. This may have a
positive or a negative impact on air-sea fluxes depending on whether the
wave heights are increased (caustics) or decreased (shadow region). To
investigate such interactions numerically and their possible impact on
air-sea fluxes will require much higher resolution Large Eddy Simulation
(LES) oceanic models similar to those developed in the CBLAST program.

**Air-Sea Interactions in Tropical Cyclones Workshop**

**Camp Springs, DC 24-25 May 2005**

**Final Report**

1.  .0 **Welcome, Introduction and Purpose of the Workshop (Stephen
    Lord/Naomi Surgi, NWS Environmental Modeling Center)**

This workshop was convened to address the near- and far-term
theoretical, observing, and modeling challenges in developing the
next-generation coupled ocean-hurricane prediction system to become
operational at the National Weather Service/National Centers for
Environmental Prediction (NWS/NCEP) during 2007. A broad cross-section
of researchers, numerical modelers, operational forecasters, and
managers of governmental and university research programs gathered at
NCEP in May 2005 to identify the scientific challenges associated with
coupled models and to discuss potential avenues for addressing those
challenges.

The context for this workshop, in both the NWS and US Weather Research
Program (USWRP) frameworks was provided by Steve Lord
(NCEP/Environmental Modeling Center) and Naomi Surgi (NCEP/EMC). Nick
Shay (Rosenstiel School of Marine and Atmospheric Science/University of
Miami) provided the overall charge of the workshop, which is to assess
progress in the Air-Sea Interaction Community based on field programs
and modeling studies sponsored by National Science Foundation, Office of
Naval Research and National Oceanic and Atmospheric Administration
through the USWRP Hurricane Landfall program, and to identify pressing
scientific issues related to improving the physics of the air-sea
interaction problem under strong winds in a hurricane and forecast
models. Central to this theme is how the forecasting community can use
these data sets to improve predictions from coupled ocean-atmosphere
models. A clear objective of the workshop was to open the dialogue
between the forecasting and research communities, and understand each
group's needs. Breakout groups were designed to maximize discussions
between forecasters and researchers in addressing cross-cutting issues.

To set the scene for the challenges that lie ahead, the workshop began
with a series of overview presentations from NCEP-related activities:
Operational Modeling (Surgi), Wave Modeling (Tolman), Ocean Modeling
(Lozano), Data Assimilation (Derber), and Coupled Modeling
(Ginis-University of Rhode Island). A recurrent theme was that any
potential improvements for intensity forecasts must not degrade track
forecasts. The two breakout groups in the afternoon focused on model
forecasting and required observations. The second day focused on
research issues and their importance for forecasting issues: Oceanic
Observations (Shay-UM), Atmospheric Boundary Layer Observations
(Barnes-University of Hawaii), Ocean Modeling (Jacob-University of
Maryland-Baltimore County), and Sea Spray Parameterization Schemes
(Fairall-Environmental Technology Laboratory). In addition, two brief
talks were given by Girton (University of Washington-Applied Physics
Laboratory) and Terrill (Scripps Institution of Oceanography) on
profiling floats that were deployed in the ONR-Coupled Boundary Layer
Air-Sea Transfer (CBLAST) program. This session emphasized the need for
continued observations to improve our understanding of physical
processes and model parameterizations prior to implementation in
forecast models. The afternoon breakout sessions focused on setting
priorities and refining focused recommendations discussed in Plenary on
the first day.

Steve Lord and Naomi Surgi welcomed the participants scientific meeting
on the HWRF modeling system. The overall WRF program is to provide the
community with a full-range of Numerical Weather Prediction (NWP) model
capabilities that include such things as model software architecture and
physics, data assimilation, input/output applications interfaces,
testing and verification, documentation, standards, as well as a
framework within which to develop and test new theories, models, and
capabilities. The WRF is a community effort that provides a modeling
infrastructure to run on a number of platforms such as the IBM at the
National Center for Atmospheric Research (NCAR), Alpha-Linux system at
the Forecast Systems Laboratory (FSL) , and Linux PC systems. The
WRF-community based models will be available to both university and
governmental organizations.

Within the overall WRF activities, the hurricane modeling system is a
particular subset with unique characteristics and issues. The HWRF will
be a coupled land/sea/atmosphere model. The HWRF will have a nested wave
model coupled to the ocean model, and the land surface model will be
coupled to hydrology to address the inland flooding problem. Development
of this advanced hurricane modeling system will provide a unique
opportunity for collaboration between the research and operational
communities to take advantage of a variety of expertise that is
necessary for the successful modeling system development.

Lord and Surgi challenged the workshop participants to consider the data
needs for such a hurricane prediction system -- including assimilation
issues, as well as considering the configuration of the optimal coupled
land/sea/atmosphere model for the hurricane forecast problem, and any
roadblocks to achieving either the data or modeling goals. They charged
the workshop participants with beginning to design, through working
group sessions, a pathway to implementation of the next-generation
hurricane forecast model.

2.  **.0 Summary of ONR CBLAST April 2005 Workshop (P. Black)**

    The ONR CBLAST workshop was held 4-6 April 2005 in Miami and brought
    together scientists involved in the CBLAST field and modeling
    studies under the sponsorship of ONR and NOAA. The goal was to
    discuss the progress from the field campaigns and ongoing model
    studies largely focused on the Isabel (2003) and Frances (2004)
    cases. Presentations and summaries from the breakout groups can be
    found at: <http://www.aoml.noaa.gov/hrd/CBLAST/CBLAST4.html>. Two
    important findings from that workshop are:

    1\. Upper ocean floats such as ARGO-Solo and the electromagnetic
    APEX floats developed by SIO and WEBB and UW/APL, respectively,
    worked well in the hurricane environment by providing measurements
    of T, S, u, v (current) profiles, waves and acoustical properties
    for the first time; and

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2.  Model studies are suggesting a new wind-wave coupling
    parameterization in which the behavior of the drag coefficient
    levels off between 28 to 32 m s^-1^ with a range of values ranging
    from 2.8 to 3.5 x 10^-3^ at 40 m s^-1^.

Direct measurements of the air-sea fluxes during the CBLAST storms were
valid for winds to 30 m s^-1^ measured in the left-front quadrant of a
tropical cyclone. It is encouraging that several studies are showing
this leveling off, and not a continued increase of the drag coefficient
with surface winds as suggested by earlier drag coefficient
parameterizations. In a broader context, the ONR-CBLAST data in must be
used to examine the sensitivity of the model simulations to these
parameterizations. This modeling-based approach would provide insights
into the parameter space of these important air-sea processes where data
in the atmospheric and ocean boundary layers can be used to constrain
model solutions. This would lead to an understanding of uncertainties in
observations and provide a motivation for the next series of focused
field experiments.

**3.0 Summary of Presentations**

**A. Forecaster Overviews:**

**A.1 Operational Modeling at NCEP (Naomi Surgi, EMC/NCEP)**

Naomi Surgi gave an overview of the progress on the Weather and Research
Forecast system for hurricane prediction, e.g., the HWRF scheduled for
operational implementation at NCEP in 2007 when it will replace the
current GFDL model. This advanced hurricane prediction system is being
developed at the NWS/NCEP's EMC to address the nation's next-generation
hurricane forecast problems. The HWRF will have the capability to fully
address the intensity, structure, and rainfall forecast problem in
addition to advancing wave and storm surge forecasts. As continued
advancements in track prediction will remain an important focus of this
prediction system, any new enhancements for physical processes to
improve the intensity and structure forecasts cannot be implemented if
they degrade track forecasting.

The HWRF will be a high resolution coupled air-sea-land prediction model
with a movable nested grid and advanced physics. To address the totality
of the hurricane forecast problems noted above, the HWRF will also
include coupling to an ocean surface wave model that will eventually be
coupled to a dynamic storm surge model. To facilitate these
requirements, the HWRF will incorporate advanced air-sea physics of the
atmospheric and oceanic boundary layers. Additionally, the land-surface
component will also serve as input to hydrology and inundation models to
address to hurricane-related inland flooding problem. For initialization
of the hurricane core circulation, an advanced data assimilation
technique is under development at EMC that will make use of real-time
airborne Doppler radar data from NOAA's high altitude G-IV jet to
initialize the 3-D storm-scale structure.

**A.2 Surface Wave Modeling at NCEP (Hendrik Tolman, NCEP)**

This presentation consisted of four parts. First, a general review of
common wind-wave modeling practices was given. Second, a brief overview
of WAVEWATCH III was given that covered its history, and its main
features (numerics, physics, island blocking). Third, operational models
at NCEP were discussed where special attention was focused on hurricane
wave models, and on the quality of the hindcasts and forecasts. Finally,
future plans were discussed that focused on hurricane wave prediction,
e.g., the development of a multi-scale wave model, new approaches to
nonlinearities in the wave model, and physics of wind-wave interaction
at high wind speeds.

Since 1994, NCEP has been running a third-generation ocean wave model.
The decision was made to

build a new model termed WAVEWATCH based on the WAM, but with
significant differences.

WAVEWATCH became the operational ocean wave model in 2000. WAVEWATCH is
initialized by

global model winds and has versions customized for the western North
Atlantic and the eastern North

Pacific Ocean. All of the models use 24 directions and 25 frequencies
for wave forecasts. Some aspects

of the models must be parameterized due to the lack of both computing
power and physics limitations.

For example, capillary waves are critically important, but are not
included in the dynamic model and

must be parameterized.

Hourly wind fields are essential to forecast the wave field development,
especially for rapidly moving, intense, small-scale hurricanes. Hourly
wind field analyses were implemented in 2002 for the Atlantic hurricane
season. Such hourly analyses are necessary to ensure continuity of the
wave model and for swell forecasts. The ocean and atmosphere are coupled
through various fluxes that are also a function of surface waves. Some
examples of the coupling are:

1\. Momentum is transferred from the atmosphere to the ocean by surface
stress and subsequent wave actions.

2\. The wave breaking and spray influence the fluxes of mass and heat.

3\. Wave breaking also is a large source of turbulent energy in the
upper ocean and the momentum in the waves is released during the
breaking action.

One of the scientific issues that needs serious attention is that the
momentum transfer and drag coefficients included in the models are
extrapolated from moderate wind conditions. Information is not available
at the low and high ends of the wind velocities. The errors introduced
by this extrapolation have a first-order impact on wave growth rates.

**A.3 Operational Ocean Modeling at NCEP (Carlos Lozano, NCEP)**

High-resolution ocean forecast systems for nowcast and short term (5
days) forecast in the Atlantic and the Pacific Ocean basin will form the
backbone for the regional ocean model components of the coupled
hurricane models. The ocean forecast system for the Atlantic Ocean basin
(25^o^S-76^o^N) is being prepared for daily oceanic operations with
resolution of \~5 to 7 km along the path of most hurricanes. Hindcast
ocean simulations (uncoupled) during Isabel and Frances hurricanes
illustrate the advantages of a high-resolution ocean model to capture
sea surface temperature cooling due to turbulent mixing and
near-inertial pumping on the thermocline. Initial ocean conditions will
be provided by operational nowcasts that will include the assimilation
of SST (remotely sensed and in situ), sea surface height anomalies from
altimeters (Jason, GFO, etc), and *in situ* temperature and salinity
observations (CTD, AXBT, buoys and drifters). There is a clear
requirement for comprehensive ocean and atmosphere observations in a
storm-coordinate system to evaluate coupled hurricane models, and for
the development of efficient deployment strategies that provided these
gridded observations.

**A.4 Data Assimilation Efforts at NCEP (John Derber, NCEP)**

The basic objective of the NWP data assimilation is to combine all
relevant information from any source to produce an estimate of the most
likely state of the atmosphere at the beginning of the forecast cycle.
Generically, the "cost" or "fit" function optimizes the fit of the
background field with the observations and other constraints. In some
data-sparse areas of the world, the background field is as good as the
observations.

1\. The first step is to convert the analysis (background field) to
observation-like information and compare that information to
observations. Forward models to make the conversions can be such things
as a simple interpolation scheme, a complex radiative transfer function,
or a precipitation algorithm.

2\. The weights given to the various terms in the equations are related
to the estimates of the error covariances.

3\. The final terms are lumped under "other constraints", for example,
to force the moisture values to be non-negative, and keep a balance
between the mass and momentum in mid-latitudes. Significant differences
exist in the data assimilation issues for large-scale processes in the
tropics and for hurricanes. For the most part, the issues are mesoscale
or smaller in nature. Clearly, data assimilation for hurricanes is much
more difficult than for the larger-scale tropical circulations.

Some of the data assimilation challenges for the tropics and hurricanes
include:

1\. **Balance equations**: In the tropics (and for mesoscale in
general), balance is dominated by moist processes and is much more
complex than for the larger scales. Failure to properly treat the
balance issues will result in a rapid loss of useful information at the
beginning of the forecast. The increase in non-linearity due to moist
processes make the tropical/hurricane problem more difficult to solve.

2\. **Analysis variables:** To accurately analyze variables in the
tropics such as cloud liquid water and cloud ice, a balance has to be
achieved and all the fields involved need to be initialized, which also
means the surface and ocean fields must be correctly specified. The
ability to achieve a realistic balance is not as straightforward as for
the larger scales.

3\. **Background error covariance:** For the tropics, it is essential to
have circulation-dependent error covariances, but they are difficult to
determine. For example, the structure of the background error
covariances for cloud and surface fields are almost certainly to be
dependent on small-scale dynamics that are not well known. Further, it
is critical to include in the background error covariances the
relationships between the variables (e.g., water vapor and clouds).

Significant progress has been made over the past 18 months in the
development of the operational WRF 3DVAR data assimilation system. . The
research state-of-the-art version of the WRF 3DVAR is scheduled for
2006. The advanced four-dimensional data assimilation (A4DDA) scheme is
likely to be implemented by 2010. The coupled ocean model data
assimilation will focus on:

1\. Upper ocean and mixed layer as being of primary importance,

2\. Skin temperature, which is a primary measurement from satellites,

3\. Bulk water temperatures obtained from ship observations. The
satellite retrievals are calibrated to the bulk temperature, and

4\. Profiles of the thermal (and salinity) structure and mixed layer
depth which are provided by floats and expendable conductivity
temperature and depth probes.

In summary, the improved specification of the background error
covariance has top priority and not all of the observations are useful.
Significant progress over the last few years has been made in how to
assimilate data from a wide range of sources. However, recent
observations are still not being used to the maximum extent possible,
and some new observations have not yet been incorporated into the data
assimilation system. The task of achieving an effective data
assimilation scheme for a new observational data set may be on the order
of 1-2 years from the time the data are reliably available. Data
assimilation systems can and should be as transportable to different
platforms as are the models.

**A.5 Coupled Modeling at URI/NCEP (Isaac Ginis, URI)**

In 2001 the GFDL/URI coupled hurricane-model model was implemented at
NCEP/EMC for operational forecasting in the Atlantic basin. Since then
joint research efforts of the URI, GFDL, and NCEP scientists have been
focusing on further improvements of the GFDL/URI model. In this
presentation, the latest research and development efforts are
highlighted.

1\. New ocean model initialization method:

A new ocean data assimilation and initialization package has been
developed to improve simulations of the Loop Current (LC) in the
GFDL/URI operational coupled hurricane prediction system. This procedure
is based on feature modeling and involves cross-frontal "sharpening" of
background temperature and salinity fields according to data obtained in
specialized field experiments. It allows specifying the position of the
LC in the Gulf of Mexico using available observations. The new
initialization procedure will be tested during the 2005 hurricane season
in the Atlantic basin. It is planned for operational implementation in
2006.

2\. Improving air-sea momentum flux parameterization:

In the GFDL hurricane model, the air-sea momentum flux is parameterized
with a constant non-dimensional surface roughness (or Charnock
coefficient, $z_{\text{ch}} = z_{0}\frac{g}{u_{}^{2}},$where $z_{0}$ is
the roughness length, $u_{}$ is the friction velocity and *g* is the
gravitational acceleration) and the stability correction based on the
Monin-Obukhov similarity theory, regardless of wind speeds or sea
states. This parameterization assumes an increase in C~d~ with wind
speed. However, a number of studies have suggested that the value of the
Charnock coefficient depends on the sea state represented by the wave
age. Lively debate is ongoing in the research community over this
relationship. The major reason leading to the discrepancies among
different studies is the paucity of in situ observations, especially in
high wind speeds and young seas.

We investigated the Charnock coefficient under hurricane conditions
using a coupled wind-wave (CWW) model that includes the spectral peak in
the surface wave directional frequency from WAVEWATCH III and a
parameterized high frequency part of the spectrum using a recently
developed model. The wave spectrum was then introduced to the wave
boundary layer model to estimate the Charnock coefficient at different
wave evolution stages. We found that the drag coefficient levels off at
very high wind speeds, which is consistent with recent field
observations. The most important finding of this study is that the
relationship between the Charnock coefficient and the input wave age
(wave age determined by the peak frequency of wind energy input) is not
unique, but strongly depends on wind speed. The regression lines between
the input wave age and the Charnock coefficient show a negative slope at
low wind speeds but a positive slope at high wind speeds. This behavior
of the Charnock coefficient in high winds provides a plausible
explanation why the drag coefficient under tropical cyclones, where seas
tend to be extremely young, may be significantly reduced in high wind
speeds.

3\. Improving air-sea heat and humidity flux parameterization:

Heat and humidity flux parameterizations are a crucial factor in the
hurricane-ocean coupling. In high wind conditions, heat and humidity
exchange coefficients c~h~ and c~e~ can be directly related to the
roughness lengths of temperature and water vapor (Z~T~ and Z~q)~. We
have tested various parameterizations Z~T~ and Z~q~ in the GFDL
hurricane model and found that for simulations of very intense
hurricanes with maximum wind speeds exceeding 50 m s^-1^, large values
of C~H~ are necessary, with c~h~/c~d~ \>1. For example, testing the
parameterization of Z~T~ and Z~q~ used in the GFS global model for
Isabel (2003) indicates that the storm fails to intensify beyond 50 m
s^-1^, while the observed maximum winds reached about 70 m s^-1^. It is
possible that sea spray, which is neglected in these experiments, may
provide an additional heat and moisture source.

4\. Development of a coupled hurricane-wave-ocean model:

We have coupled the GFDL hurricane model, the Princeton Ocean Model
(POM), and the WAVEWATCH III model with the URI wind-wave boundary layer
model. The highest resolution of the model in the movable inner-most
mesh is 1/12 degree. We have developed a movable nested grid
configuration of the wave model. The inner mesh of higher resolution
follows the storm center, as it is done in the GFDL hurricane model. It
is a necessary step to reduce significant computational requirements of
the WW3 model. Although the testing and evaluation of the new coupled
system has just begun, the first numerical experiments show encouraging
results.

**B. Researcher Overviews:**

**B.1 Upper Ocean Observations (L. K. (Nick) Shay, UM)**

Over the past two decades, it has been fairly well documented that ocean
current and the shear field play an important role in cooling and
deepening of the oceanic mixed layer (negative feedback regimes). By
contrast where the ocean mixed layer (and depth of the 26^o^C isotherm)
is deeper, the ocean current shears may not be large enough to
significantly cool the upper ocean. Such positive (or less negative)
feedback regimes, which provide more of a sustained heat flux to the
atmosphere during hurricane passage, are usually associated with deep
warm fronts and eddies that are often characterized as deep ribbons of
high oceanic heat content water. That is, advection of thermal gradients
by the strong currents may counterbalance upwelling and mixing effects
and provide more heat to the atmosphere.

1\. Thin Mixed Layers : (Negative Feedback):

In negative feedback regimes, wind-driven vertical current shear induces
mixing of the oceanic mixed layer and top of the thermocline (i.e.,
entrainment heat flux). Strong shear events lower the Richardson number
to below criticality and thereby cause the ocean mixed layer to deepen
and cool as cooler water from the thermocline is mixed with the warmer
ocean mixed layer water. In this case, the sea-surface temperature
represents a proxy for the ocean mixed layer temperature even using
crude bulk ocean mixed layer models. Thus, the available ocean heat
content, which is defined as the amount of heat from the surface to the
depth of the 26^o^C isotherm, decreases and then negatively impacts
storm intensity.

Despite the importance on the physics of the air-sea interactions
(available heat and moisture), only seven aircraft-based experiments
have specifically focused on measuring current and current shear for
this important aspect of the tropical cyclone-ocean interaction problem.
Airborne eXpendable Current Profilers were first launched in 1984 and
1985 as part of an oil company-consortium initiative [Ocean Response To
A Hurricane Program (ORTAH)]{.underline} in Norbert (eastern Pacific
Ocean), and Josephine and Gloria (western Atlantic Ocean). Since that
experimental effort, AXCPs have only been deployed in Hurricanes Gilbert
(1988), Isidore and Lili (2002). As described below, profiling floats
with electromagnetic current and shear measuring capability were
recently deployed in Frances, and measured strong near-inertial currents
and vertical shears over several days in the cold wake region.

2\. Deep Warm Mixed Layers: Positive Feedback

Coupled ocean-atmosphere measurements were acquired during an
NSF/NOAA-sponsored Hurricane Air-Sea Interaction Experiment.
Dual-aircraft experiments mapped 3-dimensional fields using expendable
profilers (AXCPs, AXCTDs, AXBTs, GPS) deployed from NOAA research
aircraft as Isidore and Lili moved into the Gulf of Mexico in September
and October 2002. As the storms encountered the Loop Current, Isidore
intensified to a category 3 and Lili rapidly intensified to a category 4
storm. Even at these levels of intensity, the upper ocean response was
minimal SST decreases of less than 1^o^C and ocean heat content (OHC)
losses less than 10 KJ cm^-2^. That is, advection of thermal gradients
may have counterbalanced shear-induced mixing processes associated with
forced near-inertial motions. In this positive (less negative) feedback
regime, advection of the thermal structure by the strong currents has
time scales of less than a day with large geostrophically balanced
currents transporting high OHC water (150 KJ cm^-2^) from the Caribbean
Sea into the Gulf of Mexico to form the Loop Current core. As Lili moved
northwest of the Loop Current, the upper ocean cooled by more than 2^o^C
with a net OHC loss of about 30 KJ cm^-2^ due primarily to shear-induced
mixing across the base of a thin ocean mixed layer in the Gulf Common
water. The storm subsequently weakened prior to landfall to a category 1
storm due in part to the entrainment of drier air as well as interacting
with an ocean previously cooled by earlier tropical storms Hanna and
Isidore.

Since PDT-5 report (Marks and Shay, 1998), only two focused oceanic and
atmospheric experiments in hurricanes have measured current and shear
along with temperature and salinity. While there have been fortuitous
encounters where tropical cyclones have passed over mooring deployed in
support of other experiments such as Frederic (1979), Allen (1983),
Gloria (1985), Georges (1999) and Ivan (2004). Developing, evaluating,
validating, and implementing accurate ocean/coupled models will require
**a more systematic measurement approach** to accurately represent the
response to the atmospheric forcing and understand the levels of
negative (and positive) feedback to the atmosphere over the life cycles
of several storms. Measurements of T,S and velocity (u,v) acquired in
grids are needed for the models to adequately represent parameter space,
assess the ocean mixing schemes, and evaluate performance. Without the
current and shear measurements, models will not necessarily improve
(i.e., thermal structure is not enough).

**B.2 Atmospheric Boundary Layer Observations (Gary Barnes, UH)**

Observations collected over the last decade with the NOAA-AOC aircraft
(directed by members of the NOAA/AOML/ Hurricane Research Division and
university investigators) and recent specific experiments such as
CBLAST, supported by NOAA, NSF, and ONR are revealing fresh details of
the hurricane boundary layer. The observations are the result of new
aircraft deployment strategies and the interpretation of new
instrumentation that includes the SFMR, Doppler, fast response wind,
temperature, and humidity sensors, and especially the Global Positioning
System (GPS) sondes. At this early stage, the GPS sondes have been
exploited more than the other sensors. Over 300 hundred vertical
profiles of wind speed in numerous hurricanes reveal that roughness
length (and therefore the drag coefficient) does not continue to
increase with increasing wind speed as previously believed. Above 35 m
s^-1^ the drag coefficient remains constant. The profiles also identify
that 10-m winds are typically 0.8 -0.9 of the wind maximum that is
typically located 500 to 700 m altitude.

GPS sondes deployed in Hurricane Bonnie (1998) provided the first views
of vortex-scale horizontal maps of temperature, specific humidity,
equivalent potential energy, and radial and tangential wind components
from 10 m to 2 km altitude. These maps have a variety of structures that
include non-isothermal inflow to the eyewall, rapid moistening of
offshore flow, and the depth and energy content of the inflow layer to
the eyewall. An energy budget of the inflow reveals that the increase of
energy occurs within 50 km of the radius of maximum winds, demonstrating
the importance of understanding the air-sea fluxes in the inner core of
the hurricane.

Profiles of potential and equivalent potential temperature have
structures in the inner core of the hurricane that depart from the
typical undisturbed tropical conditions. Positive lapse rates of
equivalent potential temperature well below the mid-tropospheric
minimum, moist absolutely unstable layers, very shallow mixed layers,
and nearly saturated and super-adiabatic surface layers have been
observed. The GPS sonde results have the potential to serve as a test
field for the GFDL and HWRF hurricane models used for operational and
research tasks. Comparisons between the model fields and the
observations may ultimately lead to improvements in key
parameterizations, and thus result in improved intensity forecasts.

**B.3 Ocean Modeling (S. Daniel Jacob, UMBC)**

Modeling and evaluation of the ocean response to tropical cyclones are
crucial to coupled hurricane intensity prediction. Since the ocean
component in the prediction system provides the lower boundary
conditions that affect the fluxes for rapid intensification or
weakening. This overview focused on uncertainties in the
[state-of-the-art]{.underline} ocean response models from a physical and
numerical perspective and their applications to coupled prediction
system. Due to the availability of observations prior, during, and after
the passage of the storms, simulations were conducted for Gilbert
(1988), Isidore and Lili (2002) using the Hybrid Coordinate Ocean Model
(HYCOM) to quantify the range of uncertainties relevant to coupled
modeling.

1\. Model and Simulations:

Two configurations of HYCOM were used to simulate the upper ocean
response to hurricanes Gilbert, Isidore and Lili for different vertical
resolution. Since Isidore and Lili occurred closely spaced in time,
these two were combined into a 20-day simulation in contrast to a 6-day
simulation in the Gilbert case. Momentum forcing in this study was
derived by combining environmental winds from an atmospheric general
circulation model with aircraft-reduced and buoy-observed winds using
the Hurricane Research Division wind analysis program. While realistic
initial conditions for the Gilbert case were derived from in situ data,
background fields from a data assimilative basin-scale HYCOM run provide
the conditions in the Isidore and Lili cases. Numerical simulations were
conducted to quantify uncertainties for realistic and quiescent initial
conditions and differing entrainment mixing schemes that parameterize
sub-grid scale processes. Initial conditions were evaluated with data
acquired one day prior to the storm passage.

2\. Results:

Realistic initial conditions for the three cases considered here
included the deep warm layers of the western Caribbean Sea, Loop
Current, and the Warm Core Rings that separate from it in the Gulf of
Mexico. Evaluation of initial conditions in the Gilbert case indicates
that they are reproduced accurately for ocean response modeling. While
the location of oceanic features are reproduced by the assimilative
basin-scale model and the vertical thermal structure is comparable to
Levitus and GDEM climatologies, pre-Isidore expendable probe data
indicate a much warmer upper layer in the ocean. Consequently, simulated
cooling is more than the observed cooling by about 0.5° C. This result
highlights the need for routine pre-storm observations for evaluation of
initial conditions used in the ocean component of the coupled model.

While the magnitude of upper-ocean cooling simulated for quiescent
initial conditions compares reasonably well with observations, the
pattern and extent of simulated cooling are modulated by pre-storm
mesoscale variability. While attempts were made in the current ocean
component of the operational coupled model to prescribe a condition that
resolves the Gulf Stream system, the Loop Current eddies are not
initialized in the present system. Results from Gilbert simulations
suggest eddies are a necessity for more accurate prediction of the
upper-ocean heat content evolution in the Gulf of Mexico. An additional
effect of the pre-storm velocity structure is to reduce the frequency of
the near-inertial internal waves generated by the storm and therefore
the phasing of strong shears contributing to significant mixing will be
delayed and make larger more fluxes available to the atmosphere.

One of the significant effects on the upper-ocean heat budget and the
fluxes to the atmosphere is the choice of entrainment mixing
parameterization. For quiescent initial conditions, the range of fluxes
in the directly forced region of the storm exceeded 500 Wm^-2^ for
different schemes. Comparative statistics suggest that the three
higher-order mixing schemes considered will lead to a more accurate
ocean response simulation. These comparisons are limited by data
availability, and therefore routine measurements are necessary to
evaluate the ocean component of the coupled system. Similar to the
post-season track and intensity verification analysis, more ocean
observations must be acquired to evaluate the different schemes on a
post-season basis to build a statistical base of comparisons. Given the
large range in the simulated surface fluxes for different schemes, this
is a crucial step toward reducing this uncertainty. The approach of
stand-alone ocean simulations using derived realistic atmospheric
forcing used here allowed us to focus on and evaluate the ocean model
and associated parameterizations. Since the boundary layer structure
forcing from the atmospheric component of the coupled model is subject
to additional uncertainties, this approach based on observations will
lead to reduction in uncertainties of the ocean component in the coupled
system.

**B.4 Sea Spray Parameterization Schemes (Chris Fairall, NOAA ETL)**

For the last decade, the NOAA Environmental Technology Laboratory (ETL)
has been developing a hierarchy of models of the production of sea spray
at high winds and the subsequent thermodynamic effects of the
evaporation of spray on hurricane boundary layers. The three steps in
this process are: 1) characterization of the size spectrum of droplets
produced by the ocean as a function of the forcing (wind speed, stress,
wave breaking, etc); 2) computation of the exchanges of heat and
moisture between the droplets and an unperturbed near-surface layer
structure; and, 3) accounting for the 'subgrid-scale' distortion of the
standard surface layer T/RH structure by the droplets (a process
referred to as 'feedback'). Our present sea spray source strength
parameterization is derived from the Fairall-Banner physical sea spray
model (which predicts the size spectrum of sea spray produced by the
ocean in terms of wind speed, surface stress, and wave properties). The
Fairall-Banner spectrum has been parameterized into a simple mass flux
representation in terms of friction velocity. The unperturbed
thermodynamic effects are based on integrals of the ratios of
thermodynamic and suspension time constants following Andreas. Finally,
the diagnostic feedback parameterization has been developed to
characterize the way evaporating droplets of various sizes modify the
stratification of the air near the surface, which in turn reduces
further droplet evaporation but enhances sensible heat flux carried by
the droplets. The present form of the parameterization has two tuning
coefficients: one that scales the magnitude of the source strength and
the other that affects the partitioning of enthalpy flux between
sensible and latent heat.

Recently the parameterization was coded in F90 and implemented in the
GFDL hurricane model and a version of Weather Research Forecast (WRF)
model that runs at ETL. Preliminary tests on hurricanes Ivan and Isabel
showed sensitivity to sea spray, but there are interdependencies with
the non-droplet (direct) transfer specifications in the models. More
testing is needed to understand these interdependencies (see:
ftp://ftp.etl.noaa.gov/user/cfairall/onr_droplet/parameterization/ )

**B.5 EM-APEX Floats (James Girton, UW/APL)**

A collaborative, ONR SBIR effort between the UW/APL and Webb Research
Corporation (WRC) has developed an autonomous ocean profiling float that
provides exceptional vertical and temporal resolution of velocity,
temperature and salinity to depths of 2000 m for deployments of many
years. Electrodes were added to the exterior of standard WRC APEX
floats, and electronics were added inside. The electrode voltages result
from the motion of seawater and the instrument through the Earth\'s
magnetic field. Other systems included magnetic compass, tilt, CTD, GPS,
and Iridium (that allow for sampling/mission changes).

Three EM-APEX (Electromagnetic Autonomous Profiling Explorer) floats
were deployed from a C-130 aircraft ahead of Hurricane Frances as part
of the ONR-sponsored CBLAST experiment. The floats profiled for 10 h
from the surface to 200 m, then continued profiling and then between 35
m and 200 m at hourly intervals with excursions to 500 m every half
inertial period (16 hr). The velocity computations were performed
onboard and saved for later transmission. After five days, the floats
surfaced and then transmitted the accumulated processed observations,
then the floats profiled to 500 m every half inertial period until
recovery early in October that was facilitated by GPS and Iridium
positioning The resulting view of the evolution of upper-ocean momentum,
shear, and stratification provides an important set of constraints for
testing parameterizations of wind stress and ocean mixing in coupled
ocean-atmosphere hurricane models. In addition, information on the
direction and amplitude of the dominant surface waves can be extracted
from high-frequency velocity measurements in the upper part of the
profile.

**B.6 ARGO Profiling Floats (Eric Terrill, SIO)**

An autonomous profiling float now exists for observations of the upper
ocean and air-sea interface during hurricanes. This observational tool
was developed, tested, and, deployed as part of the ONR CBLAST
experiments. The air-deployable profiler measures surface waves, wave
breaking, wind-speed, and rainfall (via acoustic ambient noise
inversions), Lagrangian currents, and the temperature and salinity
structure of the upper ocean through rapid profiling of the upper 200 m
of the ocean. The platform which hosts this unique set of underwater
sensors is based upon a heavily modified SOLO float, which is similar to
those now deployed in large numbers for the ARGO global climate
monitoring system. The air deployment package is certified for usage
from WC-130 aircraft.

During the 2004 season, we deployed nine units in the path of Hurricane
Frances in collaboration with the AFRC 53^rd^ WRS using NHC model track
guidance for the airdrop locations and tasking from NHC. All nine units
operated reliably through the course of the storm, with some units
performing beyond expectation in their ability to transmit data during
the winds exceeding 50 m s^-1^ using the ORBCOMM telemetry system. In
addition to providing reliable data telemetry, the bidirectional
communication system allows commands to be sent to the profiler to alter
its mission after deployment. Unique to the platform is the development
of a 'hover' mode that keeps the instrument at a nominal 30-50 m depth
so that the air-sea interface can be probed with compact sonar for the
direct measurement of surface waves.

Additional sensors onboard the instrument package include an acoustic
system for processing ambient noise spectra in real time, a CTD package,
a sonar altimeter for computing wave spectra, and a three- axis
accelerometer. Two floats were equipped with a Aanderaa Optode for
measuring dissolved oxygen. All sampling, power and communication with
peripherals are done using a microcontroller that is independent of the
vehicle control and telemetry system. The hurricane float missions
included:

-   Profile temperature and salinity to 200 m, which we anticipate is
    below the mixed layer

-   Rise to a neutrally buoyant depth of O(30-50)m and enter a
    'hovering' routine. While at this depth, the acoustic ambient noise
    field and surface wave field are sampled using the sonar altimeter,
    pressure sensor, and accelerometer.

-   Profile to surface to obtain GPS position and transmit data using
    the ORBCOMM telemetry system.

-   Repeat cycle every 4 hours for 180 dives.

For more information see http://
[www.sdcoos.ucsd.edu/hurricanefloats](http://www.sdcoos.ucsd.edu/hurricanefloats).

**Appendix A: Agenda for Air-Sea Interactions in Tropical Cyclones
Workshop**

**Tuesday, May 24^th^**

08:00 -- 08:10 Stephen Lord and Naomi Surgi: Welcome, introduction and
purpose of workshop

08:10 -- 08:20 Nick Shay Motivation/Writing Charges

#  {#section .unnumbered}

# A. Forecaster Overviews:  {#a.-forecaster-overviews .unnumbered}

08:20 -- 08:50 Naomi Surgi: Operational Modeling at NCEP

08:50 -- 09:20 Hendrik Tolman: Wave Modeling at NCEP

09:20 -- 09:50 Carlos Lozano: Ocean Modeling at NCEP

09:50 -- 10:20 BREAK

# 10:20 -- 10:50 John Derber: Data Assimilation at NCEP {#john-derber-data-assimilation-at-ncep .unnumbered}

# 10:50 -- 11:20 Isaac Ginis: Coupled Modeling at URI/NCEP  {#isaac-ginis-coupled-modeling-at-urincep .unnumbered}

11:20 -- 12:00 Discussion/Assignment of Break Out Groups

12:00 -- 01:30 LUNCH/Informal Discussion

01:30 -- 03:30 Break Out Groups 1/2

03:30 -- 04:00 BREAK

04:00 -- 05:30 Plenary Discussion/Chair Reports

05:30 Adjourn

**Wednesday, May 25^th^**

# B. Research Overviews:  {#b.-research-overviews .unnumbered}

08:30 -- 09:00 Nick Shay: Upper Ocean Observations

09:00 -- 09:30 Gary Barnes: Atmospheric Boundary Layer Observations

09:30 -- 10:00 Daniel Jacob: Ocean Modeling

10:00 -- 10:30 BREAK

# 10:30 -- 11:00 Chris Fairall: Sea Spray Parameterization Schemes {#chris-fairall-sea-spray-parameterization-schemes .unnumbered}

# 11:00 -- 11:45 Discussion/Charge of the Break Out Groups  {#discussioncharge-of-the-break-out-groups .unnumbered}

11:40 -- 12:00 James Girton: EM-APEX Floats

12:00 -- 01:30 LUNCH/Informal Discussion

01:30 -- 01:50 Eric Terrill: ARGO Floats

01:50 -- 03:30 Break Out Groups 1/2

03:30 -- 03:45 BREAK

03:45 -- 04:30 Plenary Discussion/Chair Reports

04:45 Adjourn

# Appendix B: Breakout Group Questions: {#appendix-b-breakout-group-questions .unnumbered}

#  {#section-1 .unnumbered}

*Session 1:*

Where is the air-sea community on observing and modeling the oceanic and
coupled response to tropical cyclones? What is state of the art in areas
of air-sea interaction/boundary layer processes and upper ocean physics?
What promising technologies are on the horizon? Will they be available
over the next 2 to 5 years?

How can we maximize recently acquired data sets such as ONR-CBLAST, NSF/
NOAA Isidore/Lili, HFP, MMS Georges data sets?

What are relevant time/space scales that models need to be resolved
relative to intensity change?

What is the impact of oceanic coupling on forecasting the atmospheric
structure and intensity?

How do we improve initialization schemes? How important are positive
feedback regimes such as the Gulf Stream, Loop Current on storm
intensity and structure?

Can we use some of the work from GODAE for assimilation of satellite,
drifter and float data?

What observations are needed to improve mixing parameterizations? What
about wave coupling to the OML and ABL?

*Session 2:*

What is the appropriate mix of observations needed to improve the ocean
and air-sea boundary layer

processes in oceanic or coupled models?

What metric(s) are needed to be implemented for consistent assessment of
model(s) performance?

For example showing intensity changes from models is enough for a
validation? How do we implement data and metrics in near-real time for
forecasting needs?

What new real-time experimental plans need to be developed to support
model forecasts? For example, sampling scenarios may differ over the
Loop Current than the subtropical front in the North Atlantic.

Do we follow the life-cycle of one storm, or observe two storms under
differing oceanic conditions each year? Will this be enough statistics
to really improve the models?

How do we maximize use of GOOS float and ship-of-opportunity data? Will
NDBC upgrades be useful? What about Coastal Ocean Observing Systems?

Do we rely on moored instrumentation? Or do we integrate time series
from floats/drifters with snapshots from expendable sensors from
aircraft?

Where do we see satellite remote sensing support going? What type of
data will be useful in supporting experimental plans and data
assimilation in models?

###  {#section-2 .unnumbered}

### Appendix C: List of Participants/Breakout Groups (1/2, C:Chair)  {#appendix-c-list-of-participantsbreakout-groups-12-cchair .unnumbered}

[Visitor (Break Out Group)]{.underline} [Affiliation]{.underline}
[E-Mail]{.underline}

Bao, Jian-Wen (1) NOAA/ETL jian-wen.bao@noaa.gov

Barnes, Gary (1) University of Hawaii gbarnes@hawaii.edu

Bender, Morris (1) NOAA/GFDL morris.bender@noaa.gov

Black, Peter (1) NOAA/AOML peter.black@noaa.gov

Chang, Paul (1) NOAA/NESDIS paul.s.chang@noaa.gov

Cione, Joe (1) NOAA/AOML joe.cione@noaa.gov

Conteras, Bob (1) University of Massachusetts robb@mirsl.ecs.umass.edu

Drennan, Will (1-C) University of Miami wdrennan@rsmas.miami.edu

Fairall, Chris (1) NOAA/ETL chris.fairall@noaa.gov

Falkovich, Alexandr (1) NCEP/EMC alexandr.falkovich@noaa.gov

Fernandez, Dan (1) NOAA/NESDIS daniel.fernandez@noaa.gov

Foster, Ralph (1) Applied Physics Laboratory ralph@apl.washington.edu

French, Jeffrey (1) NOAA/OAR/ARL jeff.french@noaa.gov

Gaynor, John (1) NOAA/OAR john.gaynor@noaa.gov

Ginis, Isaac (1) University of Rhode Island iginis@gso.uri.edu

Girton, James (1) University of Washington/APL girton@apl.washington.edu

Halliwell, George (2) University of Miami ghalliwell@rsmas.miami.edu

Hara, Tetsu (2) University of Rhode Island thara@uri.edu

Howard, Armando (2) NASA/Goddard ahoward@giss.nasa.gov

Jacob, S. Daniel (2) NASA/GSFC jacob@nemo.gsfc.nasa.gov

Liou, Chi-Sann (2) NRL/MRY liou@nrlmry.navy.mil

Liu, Qingfu (2) NCEP/EMC qingfu.liu@noaa.gov

Lord, Steve (2) NCEP/EMC stephen.lord@noaa.gov

Lozano, Carlos (2) NCEP/EMC carlos.lozano@noaa.gov

Lumpkin, Rick (2) NOAA/AOML rick.lumpkin@noaa.gov

Shay, Lynn (Nick ) (2) University of Miami nshay@rsmas.miami.edu

Surgi, Naomi (2) NCEP/EMC naomi.surgi@noaa.gov

Terrill, Eric (2) Scripps Institution of Oceanography eterrill@ucsd.edu

Tolman, Hendrik (2) NCEP/EMC hendrik.tolman@noaa.gov

Tracton, Steve (2) Office of Naval Research tractos@ONR.NAVY.MIL

Tuleya, Bob (2) NCEP/EMC robert.tuleya@noaa.gov

Uhlhorn, Eric (2) NOAA/AOML eric.uhlhorn@noaa.gov

Vincent, Linwood (2) Office of Naval Research vincenc@ ONR.NAVY.MIL

Waldrop, John (2) NCEP/EMC john.waldrop.noaa.gov

Walsh, Ed (2) NOAA/ETL edward.walsh@noaa.gov

Wilczak, James (2-C) NOAA/ETL james.m.wilczak@noaa.gov

Yablonsky, Richard (2) University of Rhode Island ryablonsky@gso.uri.edu

####  {#section-3 .unnumbered}

####  {#section-4 .unnumbered}

**Appendix D: Workshop Organizers**

Naomi Surgi

EMC/NCEP

National Weather Service

Camp Springs, DC

Email: [naomi.surgi@noaa.gov]{.underline}

Phone: 301-763-8000 (Ext 7285)

Cell: 240-676-5016

Fax: 301-763-8545

Lynn K. (Nick) Shay

Division of Meteorology and Physical Oceanography

Rosenstiel School of Marine and Atmospheric Science

University of Miami

Miami, FL. 33149

Email: <nshay@rsmas.miami.edu>

Phone: 305-421-4075

Cell: 305-205-0305

Fax: 305-421-4696

Joseph J. Cione

NOAA Hurricane Research Division

Atlantic Oceanographic and Meteorological Laboratory

Miami, FL. 33149

Email: <joe.j.cione@noaa.gov>

Phone: 305-361-4406

Fax:305-361-4402

**Appendix E: Data needs for the Air-Sea Component of Coupled Hurricane
WRF**

Necessary types and resolution of observations to define the coupled
ocean-atmosphere problem for modeling:

1\) Ocean structure and heat content

-   Essential for verification (T, u, v, S)

-   Radial and azimuthal resolution - critical between center and
    200-250 km (24 h) ahead of storm

-   Vertical resolution -- mean values in the mixed layer critical --
    need to resolve mixed layer (2-4 m resolution)

    2\) Wind

-   radial resolution most important -- 0.5-1.0 km

-   height resolution next most important -- high resolution (100 m) in
    ABL, outflow, and to resolve eyewall

    3\) Moisture

-   Vertical structure and latent heat fluxes

-   Height resolution critical -- high resolution (100 m) in ABL.

-   Azimuthal resolution next most important

-   Radial resolution -- a function of Rmax.

    4\) Temperature profile

-   Vertical structure and sensible heat fluxes

-   Mean vertical profile, plus variation in radius

-   Height resolution critical -- high resolution (100 m) in ABL and
    near tropopause.

-   Resolution a function of Rmax.

    5\) Ocean waves

-   Essential for verification

-   Azimuthal structure critical -- resolve asymmetry in wave height and
    length -- wave# 2

-   Radial structure next critical -- resolve radius of 8' and 12'
    seas - 20-50 km

    **Appendix E: Instrumentation needs for the Air-Sea Component of
    Coupled Hurricane WRF**

1)  Oceanic Structure

-   Aircraft Expendables (AXCPs, AXCTDs, AXBTs): Weakness: limited time
    resolution

-   Profiling Floats: Weakness: deployment into fronts

-   Satellite IR. Weakness: no data in cloudy regions

-   Satellite altimetery. Weakness: vertical projection in models

-   Interferometric SAR: Weakness surface currents only

-   HF radar networks: Weakness large gaps along the coastline

-   Fixed/drifting buoys. Weakness limited spatial resolution (Cannot
    deploy in Loop Current, Gulf Stream)

    2\) Wind

-   Airborne and ground based Doppler radars (limitation is winds only
    where it is raining, and poor vertical coverage near the surface
    because of ground clutter)

-   Satellite Scatterometers/SAR and cloud drift winds (Weakness of
    scatterometer/SAR: only at the surface level. Weakness of cloud
    drift winds: coarse and uncertain vertical resolution

-   Surface drifters: Weakness: one level

-   Aircraft in-situ. Weakness: one level.

-   Dropsondes. Weakness: limited spatial resolution

-   Doppler LIDAR. Weakness: limitation to winds in non cloudy regions.

-   SFMR. Weakness: only at surface.

-   IWRAP?

    3\) Waves

-   Radar altimetery (SRA):Weakness only Sweel Components

-   Laser altimetery. Weakness limited to no cloud or precipitation

-   Fixed/drifting buoys. Weakness limited spatial resolution

-   Solo Floats

-   SAR imaging

    4\) Moisture

-   Dropsondes/Rawinsondes. Weakness: limited spatial resolution

-   Microwave radiometric/interferometry. Weakness: limited vertical
    resolution

-   Aircraft in-situ. Weakness: one level

-   DIAL LIDAR (NASA LASE)

    5\) Temperature

-   Dropsondes/Rawinsondes. Weakness: limited spatial resolution

-   Radiometric/interferometry. Weakness: limited vertical resolution

-   Aircraft in-situ. Weakness: one level

    6\) Rainfall

-   Buoys/ground stations. Weakness one level and limited spatial
    coverage

-   Radar/polarization diversity. Weakness limited vertical resolution,
    limited view near coastline, and calibration between radars

-   SFMR rain. Weakness one level surface

-   Satellite. Weakness: limited to cloud/no cloud

-   Profilers and sub-millimeter radars

    **Appendix F: Breakout Group 1 Notes**

> Data Base for Observation-Model Comparisons: CBLAST and other data
> constitute a good basis for joint investigations by
> operational/OAR/University researchers: Need to create data base
>
> What Ocean data are available?

-   1988 - Hurricane Gilbert (Shay)

-   2002 -- AXCP, AXCTD, AXBT; Isidore and Lili (Shay and Uhlhorn)

-   2003 -- CBLAST 10 drifters/profilers Fabian

-   2004 -- CBLAST 40 drifter/profilers Francis and Jean

-   Collections of current profilers before/after storms -- Steve Riser

```{=html}
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-   What Atm data are available?

    -   HRD data base

    -   Various NSF/CBLAST field programs

    -   Coastal Radars

-   What model outputs (initializations, NWP fields, HWIND)

-   What satellite data

-   Other data -- waves, buoys,

-   Metadata -- descriptions, reports, papers, movies

Recommend allocating resources to set up infrastructure to create data
base for existing data and facilitating rapid production of usable,
quality controlled, standard products, integrated data for future
hurricane program (HRD, FSU, NCAR-JOSS, NCDC?)

Maximize Usefulness of the data base

-   Already discussed the need for model-usable data archive

-   Questions about what data in which form

-   Streamline future observation analysis

-   Analysis of model outputs with data

-   Comprehensive, easy to use

Observational Technologies Research and/or Transition to Operational

-   Walsh's scanning radar wave measurement -- 2D spectra available in
    realtime

-   UAV -- near surface fluxes/BL

-   Airborne remote sensors for look-down near surface measurements (sea
    spray, wind profiles, breaking wave characteristics, )

-   ARL batprobe for buoys (research)

-   Ocean profilers

Our Big Three (four):

-   Public data base for model studies to promote joint studies (see
    slides 1&2)

-   Basic structure of near-surface BL in both ocean and atmosphere

    -   Secondary Circulations

    -   Mean profiles (u,T,q)

    -   Upper boundary (fluxes, definition,..)

-   Sea spray and enthalpy transfer coefficient U\>30 m/s still a big
    question

-   Ocean problems

    -   Initialization

    -   Mixing parameterizations

What observations to test coupled ocean-atmosphere models

-   Before -- snapshot synoptic field of ocean structure to 200 m
    ...1000 m(u,v,T,S)

-   During

    -   Float array (u,v,T, S, P, waves, acoustics)

    -   Airdrop profiler snapshots in storm

    -   2-D wave spectra surveys

    -   Standard a/c everything package

-   After -- another snapshot along track

-   Routine

    -   NDBC enhancements (thermistors, stress,...)

    -   ARGO, APEX floats; drifters

    -   Coast Radar (HF, WSR-88D)

    -   Gliders

What observations to advance coupled ocean-atmosphere physics and
develop parameterizations: atmospheric

-   Sea spray profiles below 50 m

-   Direct turbulent flux profiles

-   Mean profile structures (radius, quadrant, etc)

-   Complete 2-D wave spectra and wave breaking statistics

-   Accurate fields of rain rate

-   Near surface bulk variables

    **Appendix G: Breakout Group 2 Notes**

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-   We are still a long way away from many aspects of the project (bulk
    transfer coefficient)

-   Advancement of physics is a long term project.

-   Just because we haven't made vast improvements, we are working
    toward a long-term goal

    -   It may look like the GFDL model, but there are long term goals

-   There is improved skill in the operational model

-   Incremental upgrades =\> bigger impact on some things like track
    forecasting

-   We can't degrade the track forecast in the HWRF or the project will
    not be accepted

-   Same model is used for the East Pacific

    -   Must also make sure that the East Pac forecast isn't degraded

-   Started talking about what the actual weak points are of the project

    -   Is it model components or the coupling?

        -   Getting models to run together

        -   Deciding what we are going to transfer between models

        -   Physics problem & the coupling problem

-   Increasing the levels from 42 to 64

    -   This vertical upgrade should vastly improve the forecast

-   Navy doesn't seem interested in the intensity of the storms

    -   Intensity isn't correlated to the structure of the storm

-   There is a need for scale dependent background

-   Observational programs are very expensive

    -   Must fully-utilize programs that we currently have

-   There is difficulty in getting flux in high winds

-   Hurricane Center needs buoy data

    -   Wave part doesn't use data assimilation because of how quickly
        it moves away

-   Is the ocean data coming in real-time? No- but it will be coming in
    soon

-   Overcooling the upper ocean causing the air-sea interaction to die
    and the storm doesn't develop

-   How should we deal with compensating errors?

    -   We should try and put in the best science

-   Need multiple parallel tracks

    -   One for the best physics

    -   Another one for research purposes and have the best science

    -   Finally, one that does best in reality

-   Until we have the observations of intensity, it's useless putting a
    forecast out.

***Recommendations***

-   Series of sensitivity tests on coupled system when it becomes
    available

-   Researchers need access to model output and vice-versa

-   Maximize use of data sets

-   Determine which data has value to assimilation, evaluation,
    validation

[Where should we go in the next 5-10 years as far as
modeling?]{.underline}

*Modeling:*

(1) Uncertainty in air-sea parameterizations, and depending on what you
    do, one can obtain any intensity that can be tuned to fit the best
    track data. From an observational perspective, we have to place
    error bounds on what are realistic values, but we still must address
    these parameterizations (e.g. c~h~, c~d~, sea spray).

(2) Timeline for HWRF is 2007 which sets the physics timeline. By this
    time next year, GFDL physics will be frozen, so advancements in
    physics will occur after this GFDL freezing. In other words, the
    physics of HWRF will be similar to GFDL.

(3) What observations will be useful for data assimilation? and for
    model evaluation (vice

verification)?

*Understanding:*

(1) Constrained by resolution (i.e. computer resources) in terms of what
    we can explicitly resolve vs. what is parameterized.

(2) Can the intensity problem be addressed given the current resolution
    of the models? To some extent, but we must work within our
    computational constraints, so we should ask, "what can we address
    given a 9-km grid spacing?"

*Timeline:*

(1) If nothing else is done between now and 07 other than build the HWRF
    infrastructure and migrate the physics, it must be at least as
    skillful as GFDL to become operational.

(2) That is one of the issues. In HWRF development, comparing against
    the heavily tuned GFDL model so we might require a scientific side
    path to get the HWRF as good as GFDL.

(3) Purpose of everyone being here is that if all goes as planned with
    an operational HWRF in 07, then as long as we have been working on
    improvements all along, it will be possible to implement these
    improvements much faster (soon after initial operations).

(4) There should be opportunities for statistics and data to become
    available to researchers immediately so researchers can advise the
    forecasters in a timely manner

*Weaknesses:*

(1) Where are the biggest weaknesses? In the atmospheric, wave, or
    oceanic components? The first issue is getting all of the three
    components to work together correctly (technical issue). This is the
    current problem. Second issue: what parameters do you transfer
    between the different model components?

(2) For the atmospheric side, the parameterizations are the key issue.
    The other problem is the coupling problem between the various
    models.

*Physics and Assimilation Issues:*

(1) For ocean and wave model, are there similar parameterization
    problems such as incorporating Stokes drift, Langmuir Cells,
    wind-driven currents, and small-scale turbulence in wave model.

(2) Increase in vertical resolution from 45 to 64 levels, will affect
    physical parameterizations and in some cases not necessarily
    cost-effective for the gain in resolution (i.e. diminishing returns)

(3) From Navy's perspective, intensity problem should be separate from
    structure problem and may not be well correlated. That is, structure
    problem may be more amenable to advances in prediction than just
    intensity (max winds). This contrasts the NCEP view in that storm
    structure is well correlated to intensity.

(4) Underestimating the work required for good data assimilation into
    the models. What other than satellites would be helpful for
    modelers? AXBT's, altimeter data, floats, aerosondes (UAV) for
    boundary measurements. These data should be able to be assimilated
    if it improves background states and intensity/structure
    predictability.

(5) Coastal Ocean Observing Systems are including high frequency Doppler
    current radars along the US coastline. Surface current measurements
    can help constrain the coastal ocean models (nudge towards reality)
    or Coastal Ocean Data Assimilation Experiments.

(6) Big issue: is the evaluation of model simulations in that it
    requires enough data coverage in space and time to account for model
    bias and uncertainty This is especially true when resolution
    decreases from submesoscale (\<10 km) to the mesoscale (50 to 100
    km). Observations must also capture this variability for a true
    comparison. We do not have enough of basic ocean data (T, S, u, v).

(7) Need differing types of observations (Eulerian and Lagrangian) to
    assess model performance in the global and coastal oceans. Most of
    these data used to be for local purposes, but now they are becoming
    widely available at various websites. Evaluation of model output
    must be done with data not assimilated into the model-parallel
    numerical experiments.

(8) Impact studies for each type of satellite data assimilated into
    models at NCEP-which satellite(s) are providing more bang for the
    buck.

(9) In only a few storms, we have model simulations with in situ data.
    Need to quantitatively assess cooling patterns (magnitude and
    spatial extent). However, cooling is sensitive to shear and
    stress-induced mixing parameterizations. Will we get better
    parameterizations or better assimilations from new observations?

> *Air-Sea Parameterizations:*

(1) Observations suggest a leveling off of c~h~ and c~d~ some of which
    were based on similarity theory in the surface layer. Is this valid
    under high wind conditions? How do we parameterize the fluxes that
    can differ by factor of 2 depending on assumptions and surface layer
    thickness? Challenge is acquiring concurrent measurements in both
    fluids to address the problem.

(2) z~0~ has wind speed and wave age dependency, but what about enthalpy
    flux above 30 m s^-1^ which may be constant. One possibility is to
    use ocean velocity measurements of mixed layer as evidence of
    momentum flux. Gridded ocean observations to help close the ocean
    mixed layer heat and salt budgets to estimate heat fluxes. Difficult
    to close the oceanic heat budget in high wind conditions, diagnostic
    model fields are beginning to converge to observed fields, but these
    simulations are sensitive to the imposed mixing scheme, initial
    ocean conditions and wind field. Still cannot get turbulent flux
    measurements down to 10-20 m... Note the same PBL and surface
    physics are in HWRF and GFDL. Current state is that GFDL is coupled
    to POM that will be coupled to HYCOM.

(3) There may be PBL issues related to resolution and at
    high-resolution, can get double-counting of eddies because of PBL
    parameterization being based on large eddy statistics. GFDL ocean
    and atmospheric data are archived, so these data can be validated w/
    observations. Oceanographers can start looking at HYCOM output where
    observations show warmer mixed layers than predicted. This bias may
    be due to the fact that NRL initializes from biased climatology.

> *Model Initialization:*

(1) Is there a sense in the model community of how much error there is
    in the initial ocean state prior to the storm? When you incorporate
    upper ocean observations that is much warmer than climo, it can make
    significant improvements in model simulations.

(2) What other kinds of observations are on the horizon? Drifters that
    can take temp (have thermistor chains) deployed by aircraft with an
    expected lifetime of months-year. Difficult to make good current and
    shear measurements from drifters.

(3) What spatial scale is required for moorings to make a significant
    improvement in models?. Assimilating data in wave models is
    pointless because there is no way of evaluating (eventually
    validating) the results. Need wave buoy data or SAR data from
    satellites etc. For the modeling effort, wave observations are not
    important, but it is vital for forecasters... it would be great to
    have the wave data from aircraft available in real time. SRA will
    eventually be transferred to NOAA with data link to NHC to acquire
    wave spctra from the time the aircraft leaves the coast until it
    gets back.

(4) Two issues with waves: if a sensor is deployed on a buoy/float in
    front of a hurricane, you will at best get a 1-D spectra because
    array is too small to get 2-D. Compact Doppler sonars can give you
    2d, but it is difficult and you will need several buoys and floats
    to get the 2-D wave field. From data collection standpoint, it is
    much more feasible to collect wave data from aircraft ahead of storm
    (continuous measurements) than dropping buoys a few days in advance
    (risky because storm may avoid buoys).

(5) Oceanic mixing parameterizations: 6 diff mixing schemes yields 6
    diff answers... can overcool upper ocean, etc..."coupled" model
    system is really just 3 models running together. It is important to
    test one or two at a time and conduct sensitivity studies to
    evaluate the output, rather than couple three differing models
    together with a detailed set of agreed upon metrics for rigorous
    evaluation.

(6) How should oceanic and atmospheric turbulence interact w/ the wave
    model where a vertical resolution of 1-2 m in the vertical is
    necessary in the surface mixed layer. SHOULD get down to this res.
    and do sensitivity experiments. In atmosphere, have sharp changes
    near surface, which is why surface layer fluxes are needed to rather
    resolve this. On the ocean side, when energy is transferred from
    atmos to ocean, see large diff when using 1 m resolution than when
    using 10 m resolution.

*Coupling and Compensating Errors:*

(1) What is the correct philosophical approach to dealing w/
    compensating errors, esp. when dealing with coupled models. By
    including, e.g. wave model results in atmosphere model, could be
    including more realism.

(2) Need to put the best science first and foremost, but this may
    degrade the forecast, and forecasters won't deal with a degradation
    in track forecast. Have two parallel model experiments with a
    control data set with one model tuned by best forecasts and one with
    the "best" physics as we understand it. NCEP is always making
    tradeoffs...

(3) Parameterizations are not perfect... meant to work in specific
    ranges... the "compensating errors" are what keep everything
    running. You run into all kinds of problems when you do "plug and
    play" physics because everything interacts nonlinearly. Sensitivity
    testing of different parameterization for numerical models require
    data (moored ADCPs from Ivan, airborne profiles from Isidore and
    Lili, float measurements in Frances, Georges mooring data) with
    concurrent atmospheric measurements. Thus we need to maximize use of
    the sparse (available data sets).

(4) Should feel comfortable enough with bulk transfer coefficients and
    sea spray to implement into model over the next two years. Still
    working on the vertical mixing scheme -- only a few good data sets
    with current and shear to test schemes.

(5) Evaluating coupled models on storm "intensity" is not enough rather
    should also include size or storm structure in addition to max wind.
    Waves would be much worse in bigger storm... perhaps maximum wave
    height? At the present time it doesn't make sense to have wave
    metric because of lack of observations. Till 4 years ago, ATCF files
    just contained max winds, radius to max winds, pressure, and track
    location. Now includes max winds and location in each quadrant as
    well. If there is a strong signal, it should be model independent.

**Recommendations:**

-   Series of sensitivity tests on coupled system when it becomes
    available

-   Researchers need access to model output and vice-versa

-   Maximize use of data sets

-   Determine which data has value to assimilation, evaluation,
    validation

Experimentalists and theorists need to be aware of why or how model
parameterizations perform under differing conditions. Forecasters have a
responsibility to provide good forecasts, whereas experimentalists and
theorists have a responsibility to acquiring high quality measurements
and understanding them within the context of good science.

Note that we don't want duplication of effort... so communication
between NCEP and other researchers are vital. Funding must be allocated
for standardizing the observational and numerical data in a format that
is easily and publicly accessible.