2013

Contents

Foreword

2

Staff and Organization

4

Research Programme

7

Progress Reports
Projects

10

Division of Regional – Scale Water Cycle Processes

14

Laboratory of Meteorology

14

Laboratory for Cloud and Precipitation Climatology

20

Division of Global – Scale Water Cycle Variations

22

Eco-Climate System Laboratory

22

Laboratory of Satellite Biological Oceanography

28

Laboratory of Bio-Physical Oceanograph32

Endowed Research Division

34

Stakeholder Management Research Laboratory

34

List of Publications

36

Foreword
During summer of year 2013, it was very hot and also it rained heavily breaking records in many
places in Japan. Many people suffered damages caused by typhoon and other water related disasters,such as floods and landslides, possibly related to global warming. Many of members of Hydrospheric
Atmospheric Research Center (HyARC) were very busy for research projects and contributions tosociety during this year. Specifically, members of the laboratory of meteorology doing modeling andobservations of extreme weather faced busy schedules such as TV interviews.
As a Joint Usage/Research Center, 25 collaborations for 5 planned researches and 4 workshops wereconducted. Cloud and rain particles just before becoming typhoon was observed by Multi-parameterradar system and cloud particle sonde in Republic of Palau as a collaborative research with Japan Agency
for Marine-Earth Science and Technology and other organizations. Ka-band radar for observation of
inside of cloud, which was requested several years, was accepted at the end of 2012 and introduced thisyear.
As international activities, MOU with Taiwan Ocean Research Institute for research to use ocean
HF radar was extended, and it is decided to sign a MOU with Korean Ocean Satellite Center of Korea
Institute of Ocean Science and Technology for verification and use of ocean color satellite data.
Associate Professor Tomo’omi Kumagai was honored to be invited by His Royal Highness The Prince ofWhales to the meeting at the Royal Society and at St. James’s Palace for “St. James’ Palace
memorandum on Tropical Forest Science” with other famous scientists.
HyARC stuffs also contributed to the education. 10 master and 3 Ph.D students of Graduate
School of Environmental Studies were finished their degree courses with supervised by stuffs of HyARC.
Mr. Tomonori Tsujino awarded best student presentation award of Hydrospheric and Atmospheric
Science section of Japan Geosciences Union Meeting 2013. Global COE program lead by Prof.
Tetsuzo Yasunari was completed, and two stuffs are now participating “Leadership Development
Program for Space Exploration and Research” conducted mainly by Graduate Schools of Science andEngineering and Solar-Terrestrial Environmental Laboratory (STEL). Beautiful pictures were taken at
the stratosphere with a smart phone on a sonde during an event of “Anomalo goes to Space” conductedby Laboratory of Meteorology, Gamagori Network Research Center Natural History Museum –Sea ofLife- and Nagoya Institute of Technology.
From 2012 to 2013, HyARC is entering a phase of major change. Most of the stuff moved to 6
and 7th floors of a new building with STEL and EcoTopia Science Institute (EcoTopia) from thescattering temporal spaces stayed during latter 2012. This building was name as Research Institutes
Building. The old building built on 1969 during Water Quality Science Research, Faculty of Science
was mostly abandon to the stuff of Hydrospheric-Atmospheric group of Graduate School ofEnvironmental Studies. The new building is very comfortable and can be saved the expenses of utilities.
Construction of the second Research Institutes Building has been started for EcoTopia, STEL, HyARC
as well as Center for Chronological Research (CCR). Administration office of HyARC was alsochanged from the Graduate School of Environmental Studies to the same office of STEL and EcoTopia.
It is further expected that the collaboration of the research will be also enhanced with STEL after the
sharing of the building and administration office together.
Prof. Kenji Nakamura, former director and worked hard for change from the Institute for
Hydrospheric-Atmospheric Sciences to HyARC, was retired. From 2013, Prof. Joji Ishizaka became
the director, and Assistant Prof. Taro Shinoda became Associate Professor. Furthermore, Endowed
Research Division of Stakeholder Management Research Laboratory was established with the limit of2

two years.
For this laboratory, Prof. Kimiaki Yasuda, Assistant Prof. Memi Motosu andspecial-appointment Prof. Eiichi Tanoue was arrived. It was decided that Dr. Tetsuya Hiyama, wholead a project in Research Institute for Humanity and Nature, will come back from 2014. Therefore,
HyARC is now within large changes for personnel affairs too.
During the large changes, the mid-term evaluation by Ministry of Education, Culture, Sports,
Science and Technology (MEXT) in early 2013 was conducted, followed by the evaluation of
department by the university and the external evaluation. Unfortunately, the evaluation of the MEXT
was not as good as we believed. We are now starting the reformation in many ways. One of thepossibilities of the drastic change is the formation of new institution with STEL and CCR are started
discussion.
We are now searching a new direction in order to enhance support of the community, such as Japan
Meteorological Society, Japan Oceanographic Society, and Japan Society of Hydrology and Water
Resources who endorsed the HyARC, and preparing to new certification of the Joint Usage/ResearchCenter. We hope the scientific communities provide us the warm advice and guidance.
d with a theme of “Precipitation measurement from space and its applications”.

Ishizaka Joji
Director
Hydrospheric Atmospheric Research Center3

Staff and Organization

Research
Division

Division of Regional-Scale Water Cycle Processes
Lab. of Meteorology
Prof. UYEDA Hiroshi, Prof. TSUBOKI Kazuhisa, Assoc. Prof. SHINODA TaroLab. for Cloud and Precipitation Climatology
Assoc. Prof. MASUNAGA Hirohiko

Board ofCouncilors

Director

Division of Global-Scale Water Cycle Variations

Advisory
Board

Eco-Climate System Lab.
Assoc. Prof. KUMAGAI Tomo’omi, Assist. Prof. FUJINAMI Hatsuki
Lab. of Satellite Biological Oceanography
Prof. ISHIZAKA Joji, Assist. Prof. MINO Yoshihisa
Lab. of Bio-Physical Oceanography
Assoc. Prof. MORIMOTO Akihiko

Board onResearch
Collaboration

Endowed Research Division
Stakeholder Management Research Lab.
Prof. YASUDA Kimiaki, Special Appointee Prof. TANOUE Eiichiro
Assist. Prof. MOTOSU MemiVL Promotion Unit
Designated Assist. Prof. OHIGASHI Tadayasu
Technical Office (Technical Center)
MINDA Haruya, KYUSHIMA Moeto

Administrative
Office for
Research
Institutes

General Affairs Division
Research Strategy and Promotin Office
Research Strategy and Promotin Section
General Affairs Section / Personnel Affairs Section
Accounting Division
Accounting Section / Supplies Section / Management Section

4Administration
Board of Councilors●Members from Nagoya Universituy
TANAKA Kentaro: Prof., Graduate School of Science
TSUJIMOTO Tetsuro: Prof., Graduate School of Engineering
TAKENAKA Chisato: Prof., Graduate School of Bioagricultural Sciences
KANZAWA Hiroshi: Prof., Graduate School of Environmental Studies
MATSUMI Yutaka: Prof., Solar-Terrestrial Environment Laboratory
ISHIZAKA Joji: Director, Prof., Hydrospheric Atmospheric Research Center
UYEDA Hiroshi: Prof., Hydrospheric Atmospheric Research Center
TSUBOKI Kazuhisa: Prof., Hydrospheric Atmospheric Research Center

Advisory Board●Members from outside of Nagoya University
FUJIYOSHI Yasushi: Prof., Institute of Low Temperature Science, Hokkaido University
HANAWA Kimio: Prof., Graduate School of Science, Tohoku University
TERASHIMA Ichiro: Prof., Graduate School of Science, The University of Tokyo
NAKAMURA Kenji: Prof., Department of Economics on Sustainability, Dokkyo University
SUMI Akimasa: President, National Institute for Environmental Studies
YAMANAKA Manabu: Principal Scientist, Research Institute for Global Change, Japan Agency for
Marine-Earth Science and Technology
TANIGUCHI Makoto: Prof., Research Institute for Humanityand Nature
OKI Riko: Senior Researcher, Earth Observation Research Center, Japan Aerospace Exploration
Agency●Members from HyARC, Nagoya University
UYEDA Hiroshi: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
TSUBOKI Kazuhisa: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
ISHIZAKA Joji: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
MASUNAGA Hirohiko: Assoc. Prof., Hydrospheric Atmospheric Research Center, Nagoya University
KUMAGAI Tomo’omi: Assoc. Prof., Hydrospheric Atmospheric Research Center, Nagoya University
MORIMOTO Akihiko: Assoc. Prof., Hydrospheric Atmospheric Research Center, Nagoya University

5

Board on Research Collaboration●Members from outside of Nagoya University
FUJIYOSHI Yasushi: Prof., Institute of Low Temperature Science, Hokkaido University
YAMANAKA Manabu: Principal Scientist, Research Institute for Global Change, Japan Agency for
Marine-Earth Science and Technology
TANIGUCHI Makoto: Prof., Research Institute for Humanityand Nature
OKI Riko: Senior Researcher, Earth Observation Research Center, Japan Aerospace Exploration
Agency●Members from Nagoya University
UYEDA Hiroshi: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
TSUBOKI Kazuhisa: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
MASUNAGA Hirohiko: Assoc. Prof., Hydrospheric Atmospheric Research Center, Nagoya University

Stakeholder Management on Offshore Wind Endowed Research Division Steering
Committee●Members from outside of Nagoya University
FUJIYOSHI Yasushi: Prof., Institute of Low Temperature Science, Hokkaido University●Members from Nagoya University
KANZAWA Hiroshi: Prof., Graduate School of Environmental Studies, Nagoya University
YASUDA Kimiaki : Prof., Endowed Research Division Professor, Hydrospheric AtmosphericResearch Center, Nagoya University
MATSUMI Yutaka : Prof., Solar-Terrestrial Environment Laboratory, Nagoya University
ISHIZAKA Joji: Director, Prof., Hydrospheric Atmospheric Research Center, Nagoya University
UYEDA Hiroshi: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
TSUBOKI Kazuhisa: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
MORIMOTO Akihiko: Assoc., Prof. Hydrospheric Atmospheric Research Center, Nagoya University

6Research Program
Satellite Data Simulators and their application to numerical model
evaluation
A satellite simulator is a computer program that reproduces satellite-observed radiances or radar
echoes by applying radiative transfer computations to temperature and humidity profiles and cloud andprecipitation fields generated by numerical models such as cloud-resolving modes and generalcirculation models. We develop and distribute the Satellite Data Simulator Unit (SDSU) at HyARC and,as an effort for its applications, conduct an evaluation study of the cloud microphysical schemes for
CReSS. This research program is aimed at strengthening the link between the satellite simulator
developers and existing and new users across the country. In this year, which is the first year of thisprogram, we began new collaborations with the Joint-Simulator developer team lead by Prof. Masaki
Satoh at AORI of University of Tokyo and the JMA Meteorological Satellite Center team in charge of thedata product for the next generation Geostationary Meteorological Satellites.
A joint workshop on GSMaP and satellite simulators was held together with the GSMaP developer groupon February 18th and 19th, 2006. Scientists specializing in broad areas of satellite meteorology
participated in this workshop, leading to further reinforcement of our confidence that HyARC are andwill be playing a pivotal role in the relevant research community in Japan.

Multi-scaled vegetation-climate interaction –from a leaf to continents
In this research project, to clarify resilience and variation characteristics of land-climate interactionsin terms of hydrologic climatic processes, we showed the significance of vegetation (terrestrial
ecosystems) in the climate system. In this year, several groups joined our projects and conducted theirown subprojects. The results are as follows:
Some historical climatic data analyses and numerical modelling researches revealed that impacts ofland-use changes on vegetation-climate interactions should be involved in causes for long-term andlarge-scale changes in Asian monsoon activity.
Some promising methods for high-accurate evaluation of temporal and spatial variation invegetation status were examined using everyday-observations of ecological phenology and cloud coverat a super-site in Asian tropical rainforests. Items of the observations were GRVI (Green-Red ratio Index)
estimated from multi-satellites remote sensing data and phenology images captured by digital cameras,
found to be very effective for accurately detecting forest destruction and degradation caused by bothhuman activity and natural disaster.
To directly detect the impact of climate change on vegetation ecosystems, a group has observed
temporal variations in Fraxinus platypoda flowering at two super-sites for more than 20 years. They
revealed that changes in trends of the flowering patterns were mainly attributed to local or/and global
climate change.

7

Research on Coast Circulation, Biological Production and Material Transportwith Remote Sensing
Coastal area is between land and open ocean, and high biological production, active circulation andmaterial transport are maintained by freshwater input with materials from land, including human origin,and by physical variations affected by topography. Because it is difficult to access to oceanic area, unlike
on land, observation by remote sensing is very important. However, satellite sensors covering andresolving typical time and spatial scales in coastal area are limited, and remote sensing of coastal area is
not fully operational because many technical problems still remain.
Scientists in Hydrospheric-Atmospheric Research Center have conducted research on developmentof remote sensing data and analysis of the data in coastal area, such as development of verification
system of primary production, estimation and behavior of chlorophyll and suspended maters in East
China Sea, red tide in Japanese coastal area, circulation in the East China Sea using sea surface
topography and HF radar data. Japan Aerospace Exploration Agency (JAXA) is proposing new ocean
color and sea surface topography sensors, and it is expecting that activities of remote sensing user
community for coastal environment will be expanded.
Research program, “Research on Coast Circulation, Biological Production and Material Transportwith Remote Sensing”, has been started from 2011, and five collaborative research programs were
accepted and conducted for 2013 as followings.
- 10th Korea-Japan Workshop on Ocean Color Remote Sensing was held as Asian Workshop on Ocean
Color 2013 on Dec 3-5, 2013, in Taiwan, and it was decided to make an agreement of research between
HyARC and Korea Ocean Satellite Center.
- Chlorophyll-a measurements of Ise Bay and Biwa Lake by ocean color remote sensing and current
measurements in Tsushima Strait was established.
- Accurate tidal model was developed with data assimilation of satellite and tidal data on numericalmodel.

8

Development of remote sensing technology for atmosphere and ocean
phenomena
We have set up ocean Radar sites in Tsushima of Nagasaki Prefecture and Aishima of Yamaguchi
Prefecture in FY 2013. The ocean Radar sites consist of 15 or 14 array of 2 elements Yagi as receiving
antenna, 3 elements Yagi as transmitting antenna, and a container which is put up radio and PCs. Electric
power and communication have been supplied, and it is final adjustment stage for continuous operation.
We will observe sea surface current field vicinity of Tsushima Straits for 3 years. In addition, we willdevelop a new type of ocean Radar with NICT, Ryukyu University, National Fisheries University, andKyushu University.
We promote the preparation of ocean Radar observation in Wakasa Bay in order to understandmechanism of sudden strong current in the Bay. The sudden strong current called “Kyucho” occurs
especially in summer in Wakasa Bay, which causes damage to fisheries industry in the Bay. It issuggested that Kyucho is caused by a clockwise circulation in the Wakasa Bay associated with the
Tsushima Warm Current approaching to Wakasa Bay. However, generation mechanism of the Kyucho is
not evident at the moment. We made a research plan to capture the circulation in the Bay using ocean
Radar which measures sea surface current within 70km from the Radar site.

Advanced utilization of the polarimetric radars and the cloud-resolving
model for cloud and precipitation research
The research program is aiming at a research frontier of cloud and precipitation physics byadvanced utilization of various polarimetric radar parameters and the cloud-resolving model. In this year,
12 principal investigators (PIs) performed the following researches in the research program. Some
researches made further development of the CReSS model and related program codes. In these research,an ocean model and wave model were incorporated into CReSS. In particular, the CReSS model wasapplied to the Mars atmosphere. CReSS was used for a regional weather prediction in Aizu University.
Daily weather prediction using CReSS has been performed at HyARC and that in a new region started.
CReSS was also used for a research of transportation of pollution.
The polarimetric radar of Nagoya University was installed in Palau and used for a research oftropical precipitation systems. Some of PIs of the HyARC research program joined the radar observation
program in Palau led by Prof. Uyeda and a collaboration was performed in the tropical region.
A data assimilation research using CReSS and radar was performed in the program. The
assimilation of radar data to the CReSS model increase the accuracy of prediction of thunderstorms. The
data assimilation is a promising technique to combine observation and modeling. We expect that thetechnique will be apply to various research of cloud and precipitation.

9

Progress Reports

Projects

Formation of a virtual laboratory for diagnosing the earthʼs climate system(VL)
To conduct collaborate research and education in addressing a diagnosis of the earth’s climate
system being under great stress such as global warming, “The virtual laboratory (VL) for diagnosing theearth’s climate system” was formed in 2007 by the four university research centers studying climate andenvironment. HyARC sets up “Atmospheric Research Promotion Team (VL Promotion Team)” andmainly studies water budget associated with cloud and precipitation and develops an observation andanalysis system. To be concrete, we analyze two X-band polarimetric Doppler radar data for diagnosing acategory of hydrometeor particles, develop a cloud-resolving model named Cloud Resolving Storm
Simulator (CReSS) and validate its results using a satellite simulator named Satellite Data Simulator Unit
(SDSU), and establish data assimilation method on a mesoscale precipitation system.
In 2013, we conduct a field observation using a polarimetric Doppler radar and hydrometeor
videosondes (HYVISs) in Republic of Palau in June to clarify the formation process of initial vortices oftropical cyclones (TCs) and contribution of cloud microphysical processes on the formation of TCs. The
other radar have installed at Kobe International University to observe thunderstorms over the Osaka
Plain.
Comparison in brightness temperature (TBBs) of infrared and reflectivity obtained from satellite
observations with those calculated by SDSU applied to the daily simulation results using CReSS iscarried out. We focus on the evaluation of number concentration of cloud ice in the upper troposphere.
Simulated area less than 220 K in TBBs of infrared band corresponding to upper anvil clouds is greaterthan the observed one (not shown). Figure shows vertical cross section of observed reflectivity for 94
GHz obtained by CloudSat-CPR and that of simulated one. Simulated weak reflectivity region in theupper troposphere that corresponds upper anvil clouds extends narrower than the observed one. These
results are attributed to greater number concentration of cloud ice in the simulation, thus the simulatedparticle size of cloud ice is smaller than the observed one. This results suggests that the ice nucleation
process in the CReSS model should be improved.
Fig. 1： Vertical cross section of (a)observed reflectivity for 94 GHz
obtained by CloudSat-CPR and (b)simulated one (CReSS-SDSU)
over the Taiwan-Okinawa region at
18 UTC on May 29, 2010.

10

Core Research for Evolutional Science and Technology (CREST)
Development of a method to comprehend and predict wind conditions required foroffshore wind-power generation
Research Project “Development of a method to comprehend and predict wind conditions requiredfor offshore wind-power generation” (Research director: Prof. H. Uyeda, Nagoya University) started
from October 2012 for two and a half years. The research is one of topics in the research area of“Creation of fundamental theory and technology to establish a cooperative distributed energy
management system and integration of technologies across broad disciplines toward social application”
in the Japan Science and Technology Agency/Core Research for Evolutional Science and Technology(JST/CREST). Strategic object of the research area is the creation of theory, mathematical model, andfundamental technology to establish a cooperative distributed energy management system, which enables
the optimization of demand and supply for various energies including renewable energy. Offshorewind-power generation is one of the plausible ways to supply renewable energy.
Understanding of offshore wind conditions are required in order to promote the business of offshore
wind power generation capable. However, from the difficulty of observation, available data is limited.
Under these circumstances, year-round observations of offshore wind conditions off Wajima, west coastof Japan, have been started from November 24, 2010. The data of three wind observation towers (50 mheight) in Hegura-jima and in two other sites along the coast are provided to the research group at
Nagoya University. On the other hand, a very high-resolution simulation is necessary for estimation andprediction of offshore wind power. To perform such a high-resolution simulation with
explicitly-calculating convective clouds, we use a cloud-resolving model named the Cloud Resolving
Storm Simulator (CReSS) developed by Tsuboki and Sakakibara (2002). A detailed cloud microphysics
and an atmospheric turbulence are considered in the model. It has been used for real weather prediction
with high resolution. In the present study, estimation and prediction of offshore wind power were
performed using CReSS. The performance of the CReSS for simulating offshore wind is confirmed incomparison with the tower data in Hegura-jima as shown in Fig. 1. The output data of calculations will
be used for an estimation of offshore electric power to be generated by wind turbines in collaboration
with Prof. Morinishi group, Nagoya Institute of Technology. The developer of CReSS, Prof. Tsuboki,
Nagoya University, is seeking for new studies on estimation, prediction and utilization of offshore wind
for the next five years.
Fig. 1：Comparison of windspeed of anemometer at theheight of 50 m on a wind
tower in Hegura-jima andCReSS simulation of 2 km x
2 km horizontal resolution for
the anemometer point: time
variation of wind speed forJanuary 2013 of anemometer(left top panel) and that ofCReSS simulation (leftbottom panel), and scatterplot of them (right panel).

11

Program for Risk Information on Climate Change (SOUSEI Program)
Development of coupled ocean-atmosphere non-hydrostatic model for typhoon research
A super-typhoon, the most intense tropical cyclone category in the western North Pacific, occurs
infrequently, but its landfall causes catastrophic disaster. The purpose of our research group is moreaccurate estimation of the maximum possible intensity of typhoon in the future climate using a numericalmodel. In 2013, we developed a coupled atmosphere-wave-ocean non-hydrostatic model,
CReSS-NHOSE with a wave model (Figure 1). The exchange of momentum between the atmosphere andthe ocean is performed by the wave model. Consequently, the maximum surface wind region is notnecessary to coincide with the region of maximum wave height and the wind direction is not necessary to
be the same as the direction of wave propagation. We also incorporated the ocean mixing layer model
which was developed by the Hibiya's group in the Kakushin Program. The first step of the coupled model
development was completed. Using the coupled mode, daily simulation experiment is performed for thedomain including the main part of the Kuroshio current in the western North Pacific. We also performed
nine typhoons in 2012 and 2013 to examine the effect of coupling the ocean model for typhoon
simulation. The maximum difference between the coupled model and the atmospheric model was 10 hPa.
The simulation results using the coupled model were compared with an ocean observation to verify themodel performance. The results show that the modification of the ocean mixing layer due to the passage
of a typhoon and the Kuroshio current to the northeast of Taiwan were successfully simulated. The
atmospheric part of typhoon simulation was compared with drop-sonde observations. The
thermodynamic structures such as temperature and moisture around the typhoon center showed a good
agreement with the observations. Besides, simulation experiments of the super-typhoon Haiyan (2013)
and the typhoon Bolaven (2012). Using cloud-resolving models, CReSS and MRI-NHM, we performed
downscale simulation experiments of vary intense typhoons simulated by the MRI-AGCM20km in the
future climate. The horizontal grid spacing was 2 km in the downscale experiments. The life-timeminimum sea level pressure of the simulated typhoons is often lower than that of the AGCM and thetheoretical maximum possible intensity. Both models showed similar results. This increases the reliabilityof the downscale simulations.
Fig. 1：Schematic
representation of the Coupled
Atmosphere-Wave-Ocean
Non-hydrostatic Model(CReSS-NHOSE).

12

Program for Risk Information on Climate Change ( SOUSEI)
Eco-climate system in Northeastern Eurasia and Southeast Asian tropics: impacts of global
climate change
We are conducting predictions and assessments on how climate change alters forest vegetation andthen whether the altered forest vegetation affects the climate. The main research sites are in Asian
rainforests and the eastern boreal Siberia. We are studying the changes in the major forests in the world,such as the tundra forest.
One of this year’s results is as follows: Rubber (Hevea brasiliensis Müll. Arg.) plantations are a
viable resource for the economics of Southeast Asian countries. They are rapidly expanding into bothclimatically optimal and sub-optimal environments throughout mainland Southeast Asia, potentiallychanging the partitioning of water, energy, and carbon at multiple scales, compared with traditional land
covers that are being replaced. To provide a useful tool for a resource management strategy for rubber
plantation agriculture, e.g., balancing rubber plantation productivity with the need to reduce theenvironmental impacts associated with agricultural development, we developed the Spatially Explicit
Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating bothprimary productivity and latex productivity in rubber plantations (R-SEIB: Fig. 1). R-SEIB can take theclimatic impacts on productivity processes into consideration, and thus, allows us to project future rubber
plantation productivity under climate change conditions. In this study, model results were compared withmeasurements collected at a field site in central Cambodia, and after validating the R-SEIB’s
performance, we conducted numerical experiments addressing rubber plantation management issues,
revealing insights, such as the effects of enhanced photosynthetic ability on latex productivity and therelationships between latex tapping interval and tree growth rate and the timing of plateau of theabove-ground biomass and latex production.

Fig. 1： Simulation results of 30 m×30 m rubber plantation dynamics for 50-years at a Cambodian site.

13

Division of Regional – Scale Water Cycle Processes
Laboratory of Meteorology
Vortex structure and development process of parent storm of a tornado occurred in Inabe
City, Japan
A tornado struck Inabe City, central Japan, at about 15 JST on September 18, 2012. This event isreferred to as "Inabe tornado" in this study. The parent storm of the Inabe tornado developed in the humid
environment in which tornadoes occur occasionally in Japan. The purpose of this study is to reveal
characteristics of a tornado and its parent storm in the humid environment, by a case study of the Inabe
tornado. In particular, this study focuses on the vortex structure and development process of the parent
storm using three X-band polarimetric radars that covers Inabe city.
Vertical vortices are detected by a method proposed by Donaldson (1970) and Suzuki et al. (2000)
to apply the plan position indicator (PPI) data of each elevation angle of all radars. Vertical velocity is
estimated by dual-Doppler analysis on a Doppler velocity field obtained by all radars.
Since a mesocyclone whose diameter of approximately 4 km is identified within the parent storm,
the Inabe tornado is recognized to be associated with a supercell type storm. A hook echo, weak-echo
region under an echo overhang, which are typically observed in the supercell storm over the Great Plains
are detected in the parent storm. The updraft velocity in a core of the parent storm is approximately 14 m
s-1 at a height of 2 km (Fig. 1), and is weaker than typical supercells over the Great Plains. Cold outflow
produced by a downdraft in the core with wind speed of 10
m s-1 at a height of 1 km is balanced with the warm andmoist southeasterly inflow. A smaller scale vortex referred toas “misocyclone” is detected within the mesocyclone. A
misocyclone is observed adjacent to the mesocyclone a few
minutes before the occurrence of the Inabe tornado. It isnoteworthy that a pair of positive and negative vortices withthe diameter about 1-3 km is detected in a rear-flank of theparent storm before the appearance of the misocyclone.
Fig. 1：Vertical cross section of reflectivity
Figure 2 shows schematic images of the structure of the (shading), vertical velocity (contour), andparent storm of the Inabe tornado. A vortex pair is formed by storm-relative wind velocity (vectors) on theplane along an inflow through the core of thethe tilting of the horizontally elongated vortex tube that has updraft at 1505 JST. The thick and dashedhorizontal vorticity by an updraft associated with a contours indicate updraft and the downdraft-1-1
rear-flank downdraft and cold outflow. The cyclonic vortex every 2 m s starting from 1 m s ,respectively.
of the vortex pair moves into themesocyclone just before the deep
development of the misocyclone.
As the location of themisocyclone in the parent storm
corresponds to the damage trackof the Inabe tornado, we proposethat the formation of the Inabe
tornado is attributed to theregional intensification of an Fig. 2：Schematic images of the structure of the parent storm of the Inabe tornado
at the stage of (a) the formation of the vortex pair and (b) the development of the
updraft by the misocyclone.
misocyclone. The thick arrows indicate updraft and downdraft. The thin arrows
indicate the storm-relative wind. The circular arrows indicate the vortex detected byradars. The thick line in (b) indicates the damage track of the Inabe tornado.

14

Distribution of solid particles in precipitation systems during the Baiu season in Okinawa
To clarify precipitation mechanisms in mesoscale precipitation systems during the Baiu season,
distributions of solid particles, such as ice crystals, snowflakes, and graupels, above melting level should
be investigated. In this study, we reveal vertical distribution of hydrometeors using data obtained by an
X-band polarimetric radar installed at Aguni Island, Okinawa Prefecture. We use total 1392 data of range
height indicator (RHI) obtained in 36 days from May 23, 2011 and in 41 days from May 7, 2012.
First we exclude the case that echo-top height is lower than the melting level (approximately at aheight of 5 km), and 548 cases still remain. Precipitation systems are divided into 3 types. "A stratiform
precipitation system" is defined by the criteria: Echo-top height of 30 dBZ does not exceed above themelting level and a significant bright band is detected. "An isolated convection" is defined by that:
Echo-top height of 30 dBZ exceeds above the melting level and no significant bright band is detected.
"Convective cells embedded in a stratiform precipitation system" is defined by that: Echo-top height of
30 dBZ exceeds above the melting level and a significant bright band is detected. Figure 3 shows asample of the three types. According to the definition, 465, 23, and 60 cases are classified into a
stratiform precipitation system, an isolated convection, and convective cells embedded in a stratiform
precipitation system, respectively. Thus precipitation during the Baiu season in Okinawa is expected tobe mainly brought about by a staratiform precipitation system.
A hydrometeor classification analysis is applied to all of the RHI data and vertical distribution of
frequency of each solid particle; ice crystal, dry snow, and dry graupel, is analyzed for each type of the
precipitation system (Fig. 4). Frequency of ice crystal and dry snow is dominant through all types of the
precipitation system above the melting level. Dry graupel is detected very few in a stratiform
precipitation system. On the other hand, dry graupel is detected below 11 km and its frequency exceeds
35% at a height of 5.5 km (around the melting level) in an isolated convection. Since frequency of an
isolated convection and convective cells embedded in a stratiform precipitation system is quite few incomparison with that of a stratiform precipitation system, the contribution of graupel to produce a heavy
rainfall event is expected to be small during the Baiu season in Okinawa. As a result, the coalescenceprocess of raindrops should be mainly attributed to produce a heavy rainfall in the precipitation
mechanism.

Fig. 3：A sample of RHI images of reflectivity for 3 types of the precipitation system: (a) a stratiform precipitation
system, (b) an isolated convection, and (c) convective cells embedded in a stratiform precipitation system.

Fig. 4：Vertical distributions of frequency of solid particles; ice crystal (gray broken line), dry snow (solid line), and dry
graupel (dotted line) above a height of 5.5 km (around the melting level) for 3 types of the precipitation system: (a) astratiform precipitation system, (b) an isolated convection, and (c) convective cells embedded in a stratiform
precipitation system.

15

Structure of a mesoscale convective system observed in PALAU2013: A preliminary result
To clarify structure of mecoscale convective systems(MCSs) over the tropical ocean, we conducted an intensive
field experiment in Republic of Palau in June 2013
(PALAU2013). Direct observations of ice particles usinghydrometeor videosondes (HYVISs) were conducted within
the observation ranges of a polarimetric radar and a Doppler
radar. This study shows an overview of the field experimentand preliminary result in PALAU2013.
An X-band polarimetric Doppler radar whose observation
range is 60 km was installed at the northern tip of Palau, theNgarchelong site (Fig. 5). Another X-band Doppler radar
whose observation range is 150 km has already been installed Fig. 5：The location of radar sites and theirat the Aimeliik site since 2004. Both radars made a continuous observation ranges in Republic of Palau
during PALAU2013.
volume scanning observation at every 7.5 min. HYVIS
observations were also conducted at the Aimeliik site. Totally 19 HYVISs were launched in
PALAU2013.
HYVIS observations identify vertical profiles of ice particle's properties (type, size, and number
concentration) as well as the height, air temperature, and humidity.
Passage of MCSs is detected by a large echo area (Fig. 6). Three MCSs that develop to typhoon
T1303, T1304, and T1306 after the passage of the observation region are observed on June 06(DOY=157), 15 (DOY=166), and 26 (DOY=177), respectively. A MCS accompanied leading convective
and trailing stratiform regions with meridional length of 200 km and zonal width of 150 km propagatedwestward over the observation range of the radars on June 15. Four HYVISs were intermittently
launched into the MCS. Figure 7 shows particle images at a height of 6.1 km of the first HYVIS
launched just behind the convective region. Ice particles of column and plate types and a frozen drop as
well as small particles of supercooled liquid water are found in this image.
We will make a dual-Doppler analysis to detect a vortex structure in a convection and a matching
analysis on hydrometeor classification obtained by a polarimetric radar and HYVIS observations in near
future.

Fig. 6：Time series of echo-top height (gray bar graph)and echo area at a height of 2 km (solid line) from May
28 (DOY = 148) to July 1 (DOY = 182), 2013. Bothecho-top height and echo area are defined by 15 dBZ.

16

Fig. 7：A particle image obtained by a HYVIS at aheight of 6.1 km (temperature -5.2 Celsius degree)
launched at 1445 LST from the Aimeliik Site,
Republic of Palau. Horizontal and vertical scales of
the image are 1.2 mm and 0.9 mm, respectively.

Evaluation of environmental modulators influencing the intensity change of a tropical
cyclone using a coupled atmosphere-ocean non-hydrostatic model
Environmental modulators such as ocean heat content (OHC) and vertical wind shear (VWS)
influence on the intensity change of tropical cyclones (TCs). Park et al. (2012; Tropical Cyclone
Research and Review) showed that OHC and VWS influence the intensity change of TCs in terms of a
two-dimensional phase diagram (hereafter PEH diagram) using reanalysis data of the atmosphere andocean. However, they were not able to evaluate the relationship between them in comparison with many
previous studies. In the present study, we try to evaluate the relationship between OHC and VWS for
T1013 (Megi) using a coupled atmosphere-ocean non-hydrostatic model, Cloud Resolving Storm
Simulator (CReSS) and Non-Hydrostatic Ocean model for Earth Simulator (NHOES), CReSS-NHOES
with horizontal grid resolution of 0.02 degree both for latitude and longitude (approximately 2 km). The
simulation is conducted for 7 days from 00 UTC on October 14, 2010, after one day of the formation of
T1013.
The simulation well reproduces its track (not shown) and the tendency of central pressure (Fig. 8).
The simulated minimum central pressure (889 hPa) corresponds to the observed one (885 hPa).
We define the inner core region of the TC as the maximum wind speed in the vertical column
exceeds 25 m s-1, thus the size of the inner core region is flexible. The atmospheric environment in which
VWS between 850 and 200 hPa is estimated, is defined as the outer region in the range of 2 degrees of
the inner core region. The oceanic environment in which OHC is calculated by heat content above thedepth of 26 degree Celsius, is defined as the ocean below the inner core region. Figure 9 shows the PEH
diagram obtained by the CReSS-NHOES simulation. In this diagram, the lower right (upper left) areashows high (low) OHC and low (high) VWS; that is favorite (not favorite) on the development of a TC.
When T1013 intensifies (initial development period between Oct. 14 and 16, and rapid intensification
period between 12 Z on Oct. 17 and 00 Z on Oct. 18), VWS is lesser than 6 m s-1 and OHC is larger than
90 kJ cm-2. These environmental modulators are suitable for the intensification of TCs shown in previous
studies. On the other hand, when T1013 maintains its intensity between 00 Z on Oct. 16 and 12 Z on Oct.
17, VWS increases above 7.5 m s-1 and OHC decreases below 90 kJ cm-2. Using the PEH diagram, we
reproduce well the relationship between these modulators and the intensification of T1013. Incomparison with Park et al. (2012), the impact of the dynamical process around the center of TCs on theenvironment (VHS) should be needed to evaluate the intensity change of TCs. In addition, the interactionof TCs and ocean should be included to evaluate it.

Fig. 8 ： Time series of observed (solid line) andsimulated central pressure of T1013. Gray shadedshows that T1013 landfall on Luzon Island, thePhilippines.

17

Fig. 9：The PEH diagram using the CReSS-NHOES
simulation on T1013. Horizontal and vertical axes
show OHC and VWS, respectively. Intensification rateof the TC is calculated by 3 hours before and after thetime. Dark and light gray marks show theintensification and decaying at the time, respectively.
Crosses show the period when T1013 landfall on
Luzon Island.

A formation mechanism of gust wind around a meso-β-scale vortex developed along theJapan-Sea Polar-airmass Convergence Zone during the cold-air outbreak
When cold-air outbreak occurs over the Sea of Japan during the winter season, meso-β-scalevortical disturbances (meso-β vortices), with horizontal scale of several tens km, are frequently observed
along the Japan-Sea Polar-airmass Convergence Zone (JPCZ) by satellite images. The meso-β vortices
are sometimes accompanied with the spiral and comma shaped radar echoes and bring about gust windafter their landing on the coastal region facing the Sea of Japan. However, a mechanism of its gust wind
has been unclear, because it is difficult to observe the vortices over the sea; that is, their horizontal scaleand lifetime are too small and short to observe. The purpose of the present study is to clarify theformation mechanism of gust wind related to the meso-β vortices using a cloud resolving model: Cloud
Resolving Storm Simulator (CReSS). We performed a simulation with horizontal resolutions of 500 m on
meso-β vortices observed on January 29, 2011.
Figure 10 shows simulated vertical integrated hydrometeor amount corresponding to cloud coverageof meso-β vortices over the Sea of Japan as well as the visible satellite image at 1430 JST on January 29,
2011. The model simulated well the cloud pattern over the Sea of Japan, and the position and scale ofvortices along the JPCZ in comparison with the satellite image. The diameter and thickness of themeso-β vortices shown in "A" in Fig. 10 are approximately 100 km and 1.5 km, respectively.
Time-height section of area averaged kinetic energy including the meso-β vortex "A" shows that thelayer of maximum kinetic energy is found in the low-level and that of minimum appears around a heightof 2 km above the top of the meso-β vortex (not shown). Another maximum layer is found above a heightof 3.5 km, thus the low-level maxima of kinetic energy is clearly separated with the upper-level one. As aresult, the origin of the gust wind around the surface in the meso-β vortex is not expected to be theadvection of the high wind region from the upper-level.
A back trajectory analysis is examined to investigate the origin of the gust wind. Figure 11 showstime series of wind speed, kinetic energy, and pressure gradient force of air parcel intruding the gustwind region of the meso-β vortex along the back trajectory. The air parcel has its origin at a height of
1 km of the north and wind speed issmall at that time. The wind speed
accelerates as the air parcel
approaches the meso-β vortex
corresponding to the increase ofpressure gradient force. Thus weconcludedthattheformingmechanism of gust wind around themeso-β vortex is the acceleration by
Fig. 10：(a) Visible image over the Sea of Japan at 1430 JST on
pressure gradient force, not by theJanuary 29, 2011. (b) Vertical integrated hydrometeor amount (kgvertical advection of the high wind inm-2) simulated by CReSS at the same time. White color shows thethe upper level.
existence of high hydrometeor (dense cloud region).
Fig. 11 ： Time series of the back trajectory analysis
starting at 2100 JST on January 29, 2011 calculatedusing the simulation result. The upper panel shows timeseries of wind speed (gray solid line), height (solid line),and distance from the starting position of the backtrajectory (dotted line) of the air parcel. The lower panel
shows time series of kinetic energy (gray solid line) andpressure gradient force (solid line) of the air parcel.

18

Impacts of GPS and Doppler radar data assimilation on precipitation prediction- A heavy rainfall event in the southern Gifu Prefecture on July 15, 2010 To Improve reproducibility of a numerical weather prediction on local heavy rainfall events,
improving an initial condition should be needed. In particular, a moisture field is one of the lessdescribed variables in initial conditions because of its high spatial and temporal variability. The aim of
the present study is to clarify the sensitivity of data assimilation of the moisture field on the location andamount of precipitation. We conduct a numerical simulation on a heavy rainfall event in the southern
Gifu Prefecture on July 15, 2010 using Cloud Resolving Storm Simulator (CReSS) with horizontal grid
resolution of 1 km. We cannot reproduce the rainfall distribution and maximum rainfall amount aroundthe target region without assimilating Global Positioning System derived precipitable water vapor(GPS-PWV) and horizontal wind (HW) derived from Doppler radar. Three-dimensional variational data
assimilation (3DVAR DA) system is used to investigate the impact of GPS-PWV. HW is also assimilated
by nudging method. This study investigates the impact of three different GPS-PWV data such as "NearReal Time analysis (NRT)," "reanalysis," and "F3" data.
Figure 12 shows the impact of GPS-PWV and HW on the horizontal distribution of total
precipitation amount for 9 hours starting from 18 JST on July 15, 2010. The location and amount ofprecipitation in the southern Gifu Prefecture is improved by assimilating both GPS-PWV and HW in
comparison with no assimilation experiment (Fig. 12b). However, total precipitation amount is less thanhalf of the observation. Application of sequential assimilation of GPS-PWV with nudging technique
improve the reproducibility of total precipitation amount (Fig. 12c, 12d). It suggests that the sequential
assimilation of GPS-PWV is quite useful to quantitative precipitation forecasting (QPF).
Figure 13 shows time series of hourly precipitation of each GPS-PWV assimilation as well as theobserved one at Tajimi. Maximum precipitation and its peak time assimilating the "reanalysis" GPS data
are reproduced better than those assimilating "NRT" and "F3" data. The "reanalysis" GPS data estimates
more accurate PWV using a correct GPS satellite position relative to the Earth surface. However, itcannot release in real time since GPS orbit data before and after 30 days are needed to calculate. Thus the"reanalysis" GPS data cannot apply for the forecasting on heavy rainfall events. However, this result
suggests that providing more accurate GPS-PWV data is expected to improve the forecasting on heavy
rainfall events.
Fig. 12：Sensitivity of GPS-PWV and HW on horizontal distributions of
total precipitation amount for 9 hours starting from 18 JST on July 15,
2010. White contour shows that observed by JMA at every 100 mm.
Result of (a) assimilating only GPS-PWV (NRT) data, (b) assimilating
GPS-PWV (NRT) and HW data, (c) conducting sequential assimilation of
GPS-PWV with nudging technique for all GPS observation points, and (d)same as (c) except for the GPS observation points that observed PWV isgreater than the simulated one are drawn.

Fig. 13：Time series of hourly precipitation ofsequential assimilation of different method on
GPS-PWV at a grid including Tajimi AMeDAS
station. Observed series (solid line), assimilating"NRT" (dotted line), "reanalysis" (chain line), and"F3" (broken line) GPS data are drawn.

19

Division of Regional – Scale Water Cycle Processes
Laboratory for Cloud and Precipitation Climatology
A Mechanism of Tropical Convection Inferred from Observed Variability in the Moist
Static Energy Budget
Temporal variability in the moist static energy (MSE) budget is studied with measurements from acoordination of different satellites including the Tropical Rainfall Measuring Mission (TRMM) and
Afternoon Train (A-Train) platforms. A composite time series before and after the development of moist
convection is obtained from the observations to delineate the evolution of MSE and moisture
convergences and, in their combination, gross moist stability (GMS). A new algorithm is then applied toestimate large-scale vertical motion from energy budget constraints (Fig. 1) through a vertical mode
decomposition into first and second baroclinic modes and a background-shallow mode.
The findings are indicative of a possible mechanism of tropical convection. A gradualdestabilization is brought about by the MSE convergence intrinsic to the positive second baroclinic mode
(congestus mode) that increasingly counteracts a weak MSE divergence in the background state (Fig. 2b).
GMS is driven to nearly zero as the first baroclinic mode begins to intensify, accelerating the growth ofvigorous large-scale updrafts and deep convection (Fig. 2c). As the convective burst peaks, the positive
second mode switches to the negative mode (stratiform mode) and introduces an abrupt rise of MSE
divergence that likely discourages further maintenance of deep convection. The first mode quickly
dissipates and GMS increases away from zero, eventually returning to the background-shallow mode
state. A notable caveat to this scenario is that GMS serves as a more reliable metric when defined withradiative heating rate included to offset MSE convergence.
Fig. 1：Composite timeseries of large-scalemean vertical velocity
anomaly (hPa/h).

Fig. 2：Composite time series of moisture and MSE
budget parameters. (a) Moisture budget, (b) MSE
budget, and (c) gross moist stability (GMS).

Reference: Masunaga, H., 2013: A Mechanism of Tropical Convection Inferred from Observed
Variability in the Moist Static Energy Budget, J. Atmos. Sci., in press.
20

A Satellite Study of Propagation Characteristics of Sea Surface Temperature associatedwith the Intraseasonal Oscillations
This study is aimed at understanding the potential roles of sea surface temperature (SST) variability
associated with the Intraseasonal Oscillation (ISO) using various satellite data. A composite analysis of
the ocean mixed-layer heat budget in term of ISO phases is performed for boreal winter and summer toexamine the seasonal variation of ISO propagation. A warm SST anomaly preceding the propagation ofan enhanced ISO convection from the Indian Ocean to the Maritime Continent (Fig. 3) mainly arises
from the variability of shortwave and latent heat fluxes. An easterly anomaly to the east of convection
diminishes scalar wind, and thus latent heat flux, when superposed onto a background westerly, implyingthat the presence of basic westerly wind is important for the development of a warm SST anomaly aheadof the ISO convection. The seasonal migration of background westerly, confined into a southernequatorial belt in boreal winter while spread across the north Indian Ocean in boreal summer (Fig. 4),
may offer a mechanism that partly accounts for the seasonal characteristics of ISO propagation. The
northward propagation of the SST variability associated with the boreal summer ISO is found to also
involve a similar mechanism with the meridional wind modulation of scalar wind.

Fig. ４：Climatology of surface zonal wind in (a) boreal
winter and (b) boreal summer.

Fig. ３：OLR (contour) and SST (shaded) anomalies foreach MJO phase in (a) boreal winter and (b) boreal
summer.

Reference: Kanemaru, K. and Masunaga, H., 2014: A Satellite Study of Propagation
Characteristics of Sea Surface Temperature associated with the Intraseasonal Oscillations,J. Climate, in press.

21

Division of Global – Scale Water Cycle Variations
Eco-Climate System Laboratory
Dynamics of distinct intraseasonal oscillation in summer monsoon rainfall over the
Meghalaya–Bangladesh–western Myanmar region
This study investigated the detailed rainfall distribution
related to the submonthly (7–25-day)-scale intraseasonal
oscillation (ISO) around the Meghalaya–Bangladesh–western
Myanmar (MBWM) region. The associated three-dimensional
atmospheric circulation and time-evolution features were
investigated for the whole Asian summer monsoon systemfrom the tropics to the mid-latitudes using APHRODITE,
TRMM-PR, and JRA25 reanalysis datasets.
The MBWM region, where a tremendous amount of Fig1. Time series of rainfall averaged overthe domain of 20°–26°N, 88°–93°E in 1988
rainfall is observed in summer, is the most dominant area of (black bars; left axis) and 7–25-day filteredsubmonthly-scale ISO among the Asian summer monsoon rainfall (solid line; right axis).
regions (Fig. 1). A distinct rainfall ISO is caused by the low level zonal wind fluctuations and its
interaction with the regional-scale topographical features around the MBWM, with a remarkable
alternation between westerly and easterly flow. In the active phase of the ISO over the MBWM, alow-level westerly/southwesterly prevails over the MBWM and a center of cyclonic vorticity appears
over Bangladesh. Therefore, the wind components normal to the windward slopes of the Meghalaya
Plateau, the Chittagong Hill Tracts, and the western coast of Myanmar are enhanced high rainfall is thenobserved over these regions due to the orographic lifting of moist air (Figs. 2a and 2c). Relatively highrainfall in the lowland area of the MBWM away from the regional-scale mountains is due to frictional
convergence in the boundary layer under strong low-level cyclonic circulation. In contrast, the directionof moisture flow changes such that easterly/southeasterly flow prevails along the Gangetic Plain in thepeak break phase (Figs. 2b and 2d). The easterly/southeasterly flow can travel along the Gangetic Plain

Fig 2. Composites of (a) rainfall (APHRODITE) andvertically integrated (from surface to 100 hPa) water
vapor flux vectors in the peak active phase of the 7–
25-day ISO over the MBWM. The contours of
925-hPa positive (i.e., cyclonic) vorticity more than
2.5 9 10-5 s-1 are shown by dotted lines. The
topographic contours of 500 and 3,000 m are also
shown as thin solid lines. (b) As in (a), but for peak
break phase. (c) Composite of rainfall obtained from
TRMM-PR in the active phase. (d) As in (c), but forthe break phase.

22

from northwestern Bangladesh without orographic barriers. Thus, precipitation decreases significantly
along the Gangetic Plain on peak break days.
The distinct alternation of the low-level zonal wind around the MBWM is caused by the westward
propagating vortex pair with zonal wavenumber ~6 and westward phase speed of ~6.5 m s-1 in the tropics,
which is consistent with the n = 1 equatorial Rossby (ER) wave. The centers of the vortices propagate
westward along ~15°N and 5°S. Thus, the twin vortex structure of the ER wave shifts northward by 5°,
likely due to the large north–south asymmetric nature of the ambient Asian summer monsoon circulationin the tropics (Fig. 3). The northern vortex can affect the MBWM region. As the anticyclonic vortex
moves into the Bay of Bengal, the westerly/southwesterly becomes strengthened around the MBWM,
which is covered by the northern fringe of the anticyclonic vortex. Additionally, the MBWM region is
located in the easternmost part of the Gangetic Plain, an east–west flat lowland that is surrounded to thenorth and south by high-elevation areas (i.e., the Himalayas/TP and the Chota Nagpur Plateau). The
topographic features of the Gangetic Plain enhance the zonal wind fluctuation, andwesterly/southwesterly flow brings high rainfall on submonthly timescales around the MBWM.
Additionally, robust circulation signals relevant to the ISO appear over the mid-latitudes. In theupper troposphere, a wavetrain structure is evident along the Asian subtropical jet. The waves have a
Rossby wavelike structure with a zonal wavenumber of ~4.5 and a westward phase speed relative to theground of ~2.7 m s-1, consistent with the theory of mid-latitude barotropic Rossby waves in terms of thezonal phase speed relative to the mean background wind. In addition to the slow westward propagation,
the eastward development of the new center of action is observed along the Asian jet, indicative of
Rossby wave energy dispersion along the waveguide of the Asian jet. The waves have barotropic verticalstructure around the TP. In the active phase of the ISO over the MBWM, the cyclonic anomaly dominates
throughout the troposphere around the TP (e.g. Fig. 3). This is associated with the deepening of themonsoon trough just to the south of the TP. Thus, the cyclonic anomaly to the south of the TP enhances
the north–south pressure gradient and in turn enhances the westerly flow in conjunction with theanticyclonic anomaly over the Bay of Bengal. The robust circulation and convection signals relevant to
the ISO extend across the whole Asian summer monsoon system from the tropics to the mid-latitudes
over the MBWM region.

Fig. 3. Composite of the 500-hPa streamfunction (ψ) andwind vector anomalies at the peak active phase (day 0)
with reference to the 7–25-day rainfall anomalies over the
MBWM. Shaded areas correspond to areas of 99 %confidence in the ψ anomalies. Only wind vectors
statistically significant at the 99 % level are plotted. The
contours of topographic contours for 1,500 and 3,000 m
are shown as dashed lines.

Reference：Fujinami, H., T. Yasunari and A. Morimoto, 2014: Dynamics of distinct intraseasonal
oscillation in summer monsoon rainfall over the Meghalaya-Bangladesh-western Myanmar region：
Covariability between the tropics and mid-latitudes, Climate Dynamics, in press.

23

Water and carbon cycling in Cambodian rubber plantations
Rubber (Hevea brasiliensis Müll. Arg.) plantations, which are rapidly expanding into bothclimatically optimal and sub-optimal environments throughout mainland Southeast Asia, potentiallychange the partitioning of water, energy, and carbon at multiple scales, compared with traditional land
covers that are being replaced.
Eddy covariance towers were established within two rubber plantations, one each in Bueng Kan,northeastern Thailand, and Kampong Cham, central Cambodia, to measure ecosystem fluxes. The results
show that evapotranspiration (ET) at both sites is strongly related to variations in available energy andleaf area, and moderately controlled by soil moisture. Measured mean annual ET was 1128 and 1272 mm
yr-1 for the Thailand and Cambodia sites, respectively. After adjustment for energy closure, mean annual
ET was estimated to be 1211 and 1459 mm yr-1 at the Thailand and Cambodia sites, respectively. Basedon these estimates and that of another site in Xishuangbanna, southwestern China, it appears that ET ofrubber is higher than that of other land covers in the region, including forest (Fig. 4).

Fig4. Distribution of studied rubber plantation sites’ annual evapotranspiration (ET) in the Southeast
Asian tropics ET map. From Prof. Thomas W. Giambelluca at University of Hawaii at Manoa.

Sap flow measurements were used to study the intra- and inter-annual variations in transpiration rate(Et) in a rubber stand in the lowlands of central Cambodia. Mean stand sap flux density (JS) indicate
rubber trees actively transpire in the rainy season, but become inactive in the dry season. A sharp, brief
short-time drop in JS synchronization occurred simultaneously with leaf shedding in the middle of the dry
season in January. Although annual maxima of Js were approximately the same in two experimental years,
maximum daily stand Et of ~ 2.0 mm day-1 in 2010 increased to ~ 2.4 mm day-1 in 2011. Stomatal
response was well explained by changes in solar radiation, vapor pressure deficit, soil moistureavailability, leaf area, and tree diameter. Rubber trees had a relatively small potential to transpire,compared with average diffuse-porous species in the beginning of study period. After two years ofgrowth in tree diameter, transpiration potential was comparable to other species. Sensitivity of canopy
conductance (gc) to the atmospheric drought indicates isohydric behavior of rubber trees. Modeling also
predicted relatively small sensitivity of gc to the soil moisture deficit and rapid decrease in gc under
extreme drought conditions (Fig. 5). However, annual observations suggest the possibility of change in24

leaf characteristics with tree maturity and/or initiation of latex tapping. Estimated annual stand Et was
469 mm year-1 in 2010, increasing to 658 mm year-1 in 2011. Diagnostic experiments using the obtained
gc model showed that inter-annual change of stand Et in the rapidly growing young rubber stand wasdetermined mainly by the tree growth rate, not changes of air and soil variables in the surrounding
environment. Future research should focus on the potentially broad applicability of the relationshipbetween Et and tree size as well as environmental factors at stands different in terms of clonal type andage.

Fig5. Soil moisture (black solid line), canopy stomatal conductance estimated from sap flow
measurements (closed circles) and their modeled values (gray line).

We developed a soil-vegetation-atmosphere transfer(SVAT) model applicable to simulating CO2 and H2O fluxes
from the canopies of rubber plantations, which arecharacterized by distinct canopy clumping produced byregular spacing of plantation trees. Describing thebiosphere-atmosphere exchange in rubber plantations via
SVAT modeling is important to understanding the impacts onenvironmental processes. The regular spacing of plantation
trees creates a peculiar canopy structure that is not well
represented in most SVAT models, which generally assume anon-uniform spacing of vegetation. Herein we develop a
SVAT model applicable to a rubber plantation and anevaluation method for its canopy structure, and examine how
the peculiar canopy structure of rubber plantations affects
canopy CO2 and H2O exchanges. Model results are comparedwith measurements collected at a field site in central
Cambodia (Fig. 6). Our findings suggest that it is crucial toaccount for intensive canopy clumping in order to reproduce
observed rubber plantation fluxes. These results suggest apotentially optimal spacing of rubber trees to produce highprimary productivity and water use efficiency.
25

Fig6. Mean diurnal cycles of measured (grayzones) and modeled (solid circles) ecosystem
CO2 exchange (a) and latent heat flux (b) for
5-14 (10 days) August 2011. The gray zone
denotes the range of the middle two quartilesof observations in the study period.

Deforestation-induced reduction in rainfall
A spatial distribution of atmospheric moisture convergence averaged over 1998-2010 in the eastern
Pacific Ocean (built using a reanalyzed and gridded four-dimensional meteorology dataset, Japanese
25-year ReAnalysis (JRA-25) and the Japan Meteorological Agency (JMA) Climate Data Assimilation
System (JCDAS) available via <http://jra.kishou.go.jp/JRA-25/index_en.html>) suggests less moisture
convergence and divergence over Borneo compared with other regions (Fig. 7). On the other hand, theTropical Rainfall Measuring Mission (TRMM) satellite measurements from 1998 to 2010 (NASA
Goddard Earth Sciences (GES) Data and Information Services Center (DISC), available via<http://disc.sci.gsfc.nasa.gov/about-us>) showed a larger amount of precipitation above islands of themaritime continent in the western Pacific Ocean compared with sea areas, suggesting a notably large
amount of precipitation over Borneo (Fig. 7). In short, while little atmospheric moisture horizontallymoves into and out of the atmospheric space over Borneo, this area has plenty of precipitation.

Fig7. Maps of (upper panel) annual mean moisture convergence and (bottom panel) annual mean
precipitation in the western Pacific Ocean, (constructed using JRA-25 and Tropical Rainfall
Measuring Mission (TRMM) satellite measurements 3B42 Ver.7 datasets, respectively withvalues averaged over the period 1998-2010).

Therefore, a question arises: where does water for precipitation come from? According to theatmospheric water budget equation, assuming that the time change of local available precipitable watercontent is negligible, annual evapotranspiration over Borneo was roughly estimated to be ~7 mm day-1
and balanced with the annual precipitation, implying that most of the precipitation was recycled fromterrestrial evapotranspiration over Borneo. However, this evapotranspiration value surpassed the upper
limit of the potential evaporation when taking into consideration basic meteorological variables in thisregion. The computation of the budget equation using the combination of the reanalysis and the satellite
measurement data, which are different in their derivations, might cause such a discrepancy. Nevertheless,in light of comparisons with the other areas, it is certain that there are large amounts of precipitation, andlittle moisture advection into or out of, the Bornean region (Fig. 7). Also, a yearly eddy covariance26

observation conducted at a Bornean tropical rainforest site indicated the high rate of pristine rainforest
evapotranspiration, which can be approximated using the same mechanism as the evaporation from anextensive water surface, to be ~4 mm day-1 as an annual mean. Thus, we concluded that there is a higher
ratio of recycling from terrestrial evapotranspiration into the precipitation over Borneo, and that
deforestation and forest degradation could alter this eco-hydro-climatological cycling.
Therefore, it is plausible that the deforestation and forest degradation has led to a long-term decline
in precipitation in Borneo, showed by the long-term daily grid precipitation datasets (APHRODITE’s
Water Resources, available via http://www.chikyu.ac.jp/precip/) over Borneo (Fig. 8). In addition, it waspointed out that a slowdown of the Walker circulation over the last 60 years suppressed moisture
convergence over the maritime continent including Borneo, resulting in the historical decline in land
precipitation. We argue that deforestation and forest degradation can be still a major factor inducing thedecline in precipitation because such a weakening of moisture convergence would promote recycling of
the terrestrial evapotranspiration into the precipitation.
3200

c 3,000
Precipitation (mm/year)

3000
2800
2600
2400
2200

2000
2,000
1800
1600
1400
1200
1000
1,000
1950
1950

1960
1960

1970
1970

1980
1980

1990
1990

2000
2000

2010
2010

Year
Fig8. The decreasing trend (-12.7 mm yr-1) in annual precipitation integrated over Borneo, in the
period 1951-2007. A significant regression line is also shown (p < 0.0001). Note that even though
precipitation data in 1997 and 1998, when a strong El Niño event occurred and caused an
extreme drought, were excluded, this decreasing trend was unchanged.

27

Laboratory of Satellite Biological Oceanography
Estimation of phytoplankton size fractions from light absorption spectra
Size structure of phytoplankton in aquatic environment is very important for biogeochemical
processes such as food chain and material transport, and it is affected by environmental conditions suchas river discharge. Here, we developed remote sensing algorithm to estimate phytoplankton size structureof marine environment. Most of the previously developed algorithms just focused on the open ocean, andrely on an assumption that small and large cells dominate in low and high chlorophyll a (Chl-a) waters,
respectively (Brewin et al., 2010). However, this assumption is not always valid in river influenced
coastal waters such as in the East China Sea (ECS) (Wang et al., 2014).
Light absorption spectra of phytoplankton should have great potential to retrieve the size structure
because it is strongly depend on packaging effect caused by phytoplankton cell size and on different
pigment composition related to phytoplankton taxonomy (Ciotti et al., 2002). In this study, we developed
an estimation method of phytoplankton size-fractions which is applicable to coastal waters as well as
open ocean using principal component analysis (PCA) of normalized light absorption spectra.
We measured phytoplankton absorption coefficient (aph(λ)) and High Performance Liquid
Chromatograph (HPLC) pigment concentrations in the ECS, Tsushima Strait and Ise-Mikawa Bay.
Remote sensing reflectance, Rrs(λ), were also measured during some stations using an underwater
spectral radiometer (PRR-800/810). Size-fractions of total phytoplankton Chl-a (Tchl-a) were derived
from HPLC pigments by diagnostic pigment analysis (Hirata et al., 2008). aph(λ) was normalized using
four methods to remove total biomass influence; 1) divided by Tchl-a (aph*(λ)), 2) divided by aph(675)(aph675(λ)), 3) divided by average of aph(λ) (aphave(λ)), and 4) subtracted by the wavelength average anddivided by the standard derivation of aph(λ) (aphstd(λ)). PCA was used to capture spectral variations of thenormalized aph(λ) and separate the variance into uncorrelated principal component (PC). Then, empirical
relationships between HPLC-derived size-fractions (f) and PC scores (S) were examined as following;
1
,
f 
n
1  exp(  0 
 i Si )
i 1

where f is the large (micro-) and small (pico-) phytoplankton fractions. Si and n is the i th PC score andthe number of PC which was four in this study, respectively. β0 and βi are the regression coefficients
between f and Si. For middle size (nano-) phytoplankton, the fraction (fnano) was calculated as;
f nano  1  f micro  f pico .

Applicability of the model satellite (MODIS) data was validated using aph(λ) derived from in situ Rrs(λ)
by the version 5 of quasi-analytical algorithm (QAA).
aph*(λ) showed clear differences with changes of the phytoplankton size-fractions (Fig. 1). Samples
with high fractions of micro-phytoplankton displayed low aph*(λ) because of the high packaging effect,
whereas aph*(λ) of samples with high pico-phytoplankton fractions were high due to the low packaging
effect. The packaging effect of nano-phytoplankton dominated samples were medium, and moderate
aph*(λ) were seen for these samples. The micro-phytoplankton dominated samples showed flat spectra
and a shoulder around 450–470 nm. On the contrary, the spectra of samples dominated bypico-phytoplankton were sharp and showed a lifting at about 490 nm.
The PCA clearly separated the variations of aph*(λ) into different PC modes, and the first four modes
contained 94.1%, 3.1%, 1.1% and 0.6% of the variance. Phytoplankton size-fractions estimated from thefirst four PC scores agreed well with those derived from HPLC pigments (Fig. 2). Comparisons of the28

PCA model performance between the four normalized aph(λ) revealed that the PCA model was robust for
the normalization method and that aphstd(λ) was slightly better than other three normalized aph(λ).
Therefore, aphstd(λ) derived from in situ Rrs(λ) at only MODIS bands was used to validate the model
performance, and the results showed that the PCA model could derive an acceptable accuracy with R2 of
0.85, 0.61 and 0.76 and RMSE of 0.130, 0.126 and 0.112 for micro-, nano- and pico-phytoplankton
fractions, respectively. This indicates that if the adequate atmospheric correction can be achieved, the
PCA approach can map phytoplankton size-fractions from satellite observations. Furthermore, weapplied the PCA approach to the NASA bio-Optical Marine Algorithm Dataset (NOMAD) which werecollected from the global ocean. The results showed that the PCA approach was also applicable to theglobal ocean.
In conclusion, the PCA approach proposed in this study could derive an acceptable estimation ofphytoplankton size-fractions from absorption spectra both in coastal waters and global ocean. Next stepof the study should focus on the practicability of the PCA approach for real satellite observations.
Fig.１：Spectra of aph*(λ)
for all samples. Gray levels
indicate size fractions (f) of
micro-, nano- andpico-phytoplankton.

Fig.２：aph*(λ)-modelled
versus HPLC-derived size
fractions. Black lines
indicate the 1:1 line, andgrey dashes indicate the ±0.2 fraction ranges relative
to the 1:1 line.

Transport of giant jellyfish, Nemopilema nomurai, in Yellow Sea and East China Sea
Outbreaks of giant jellyfish, Nemomilema nomurai, have been a serious problem for the fisheries ofnortheast Asian countries, especially Japan, China, and Korea, in 2000s. Abundance of the giant jellyfish
in the Yellow Sea (YS), East China Sea (ECS), and the Sea of Japan was high during the summer.
However, the benthic stage, polyp, of the giant jellyfish was not found in the field. The initial floatingstage separated from the polype, ephyrae, were found only one time offshore of Jiangsu coast in May.
The young jellyfish was found in the ECS and Tsushima Strait in June (Kawahara et al., 2006; Yoon et al.,2008), and relatively large adults (diameter >30 cm) was captured in the Sea of Japan in August. It is
expected that the benthic stage is in the coast of the YS and ECS and that the floating stage is transported
to offshore by current. However, it remains unclear how the ephyrae and young medusae is transported
and distributed in the different water masses. The main objectives of this study were to investigate the
distribution of young medusae with the relationship to water mass expressed as seawater temperature andsalinity, to understand the transport of the jellyfish by current, and furthermore to identify the possible
source area using ship observations, satellite data, and a particle-tracking experiment with model flow
fields.

29Based on the temperature and salinity properties in the surface during the cruises in July 2013, eightmain water masses were identified by the cluster analysis; Changjiang Diluted Water (CDW), South
Yellow Sea Water Mass (SYSW), North Yellow Sea Water Mass (NYSW), Taiwan Warm Current watermass (TWC), Kuroshio Warm Current water mass (KWC), Changjiang mouth Upwelling Water mass
(CUW), mixed water of CDW-TWC, and mixed water of CDW-KWC. The jellyfish were mostly
concentrated in YS and northern ECS water, and hardly observed in the south ECS water.
Results of the backward trajectories of water masses by flow field of JCOPE2 in YS, whichreflected the modeled flow pattern, indicated that the coastal current flow northward, northward or
northeastward, and eastward in May, June and July, respectively (Fig. 3 b, d and f). The this modeled
flow pattern was consistent with wind-driven current. Satellite SST data also indicated that the warm
water (>15 oC) intruded north or northeastward to the offshore of YS from May to July (Fig. 3 a, c and e).
Majority of water masses (particle No. 2, 3, 4 and 7) in the southern YS with high abundance of jellyfish
were back traced to Jiangsu coast in early May (Fig. 3 b, d and f), when the 15oC isotherm was formednear the traced position (Fig. 3 a, c and e). While, water masses without jellyfish were staying in theoffshore of the YS, or traced back Changjiang mouth inlet and Taiwan Strait. The inconsistency of model
salinity to the field data indicates that the backward trajectories of CDW were questionable. However,transport of jellyfish from the Jiangsu coast in early May was verified by the forward tracking
experiments and an independent ferry boat observation data.
The study based on the young medusa available to visual observation in July with coupling ofsatellite data and particle tracking experiment provided a possible source area of the medusa. The highabundance of giant jellyfish observed in YS in July probably transported by wind-driven currentfrom thenorth of the Changjiang mouth to northern Jiangsu coast in May when ephyrae were liberated frompolyps after SST became higher than 15oC.

Fig. ３：MODIS monthly mean SST (a, c, e) and monthly mean SST/flow fields of JCOPE2 model (b, d, f) from July to
May 2013. Numbers in a, c, and e were the final positions of the particle-tracking experiments of water masses ineach month with (△) and without (no mark) jellyfish. Black and grey lines in b, d, and f indicate backward trajectories
of water masses during the month with and without jellyfish, respectively. White line indicates the 15℃ isotherm.

30

Biogeochemical responses associated with the passage of a cyclonic eddy in the western
North Pacific
The primary productivity in the subtropical region was considered to be low due to the low
concentration of nutrients in the surface layer. However, the possibility of nutrient supply into the surface
layer associated with mesoscale perturbations such as eddies are pointed out recently. We conducted a
shipboard high-resolution hydrographic survey in the subtropical region of the western North Pacificfrom October to November 2008 and found part of a cyclonic eddy around 30oN, 145oE (Figure 4). This
eddy had propagated westward with an average transit speed of 7 cm s-1 in the region south of theKuroshio Extension for at least 6 months as a wavelike disturbance (Figure 5). Within this eddy,
isopycnals shallowed between a depth of 600 m and just below the surface mixed layer. In addition,
maximal dissolved oxygen concentrations were observed in the subsurface layer between depths of 50
and 100 m (Figure 6). Nitrate was depleted within this subsurface maximal oxygen layer.
These results suggest that nutrients in the deeper layers were supplied into the euphotic layer as aresult of the uplift of isopycnals in the eddy, fueling the photosynthesis of phytoplankton in thesubsurface and emitting an excess of oxygen due to new production. Compared with the outside of theeddy, the enhancement of oxygen and the decrease of nitrate in the center of the eddy were estimated tobe 2.7 mol O2 m–2 and 0.22 mol N m–2, respectively. The primary productivity calculated using theeddy speed was 650 mg C m–2 d–1 at the center of the eddy. The enhanced primary productivity due tothe passage of the eddy is likely to have an important role in the ecosystem and on material cycling in thesubtropical region.

Fig.4：The altimetric sea surface height map
southeast of Japan on 22 October 2008. Thick blacklines indicate the hydrographic sections of theKH-08-3 cruise leg 2.

Fig.5：Time series of sea surface height anomalies
along the zonal band of 28–30oN. A black dot
indicates the position and time of the shipboard
observation.
Fig.6：Vertical profiles of(a) potential density, (b)dissolved oxygen
concentration, (c) nitrateconcentration. Coloredand gray lines are theprofiles for stations insideand outside the eddy,
respectively.

31

Loboratory of Bio-Physical Oceanography
Interannual variation in the third branch of the Tsushima Warm Current path controlled
by winter surface cooling in the Japan Sea
In order to investigate interannual variation in the third branch of the Tsushima Warm Current(TBTWC) path in the Japan Sea, EOF, correlation, and lag correlation analysis are applied to a monthly
mean absolute sea surface dynamic heights (ASSDH) data with high spatial-temporal resolution. These
analyses suggest as follows. A subarctic circulation is intensified by stronger winter cooling compared tonormal year, and then more amount of cold water mass is transported to off Korean coast by the current.
As a result, the cold water mass off Korean coast expand in wider area. The TBTWC adjusts the density
distribution off Korean coast and separates from the coast at lower latitude. There might be time lag
between intensification of the subarctic circulation current and transport of cold water mass to off Korean
coast.
The relationship between change of separation position of the TBTWC in summer and that of
surface cooling in winter is explained as follows by a reduced gravity model. Stronger surface cooling in
winter makes increase of upper layer thickness along north coast. Hence subarctic circulation in spring is
intensified. Intensified subarctic circulation transports cold water mass to the south along west coast.
Since southward flow along west coast in strong surface cooling year in winter is faster than that innormal sea surface cooling year in winter, deeper upper layer thickness expand to more south in summer
with cold water mass (Fig. 1). Consequently, the northward current (TBTWC) along west coast in strong
sea surface cooling year separates at lower latitude than that in normal sea surface cooling year insummer time.
Fig. 1：Sea surface current and pressure
distribution of model result in summer.
Vectors show current and contour lines
show pressure. Dashed line allows
indicate the third branch of the Tsushima
Warm Current path.

Development of tidal assimilation model for altimetry data
Satellite altimetries have been observed sea surface height continuously since 1992. Assuming
geostrophic balance, sea surface currents are calculated and temporal and spatial variation of the sea
surface currents are revealed from altimetry data. However, accuracy of the altimetry data are notsufficient in the marginal seas where tidal amplitude is large and tidal phenomena is complicated because
of inaccurate tidal model. It is well-known that altimetry data in the Yellow and East China Seas include
large error related with tidal model error. In the present study, we developed tidal assimilation model for
accuracy improvement of altimetry data in the Yellow and East China Seas. We used the Princeton Ocean
32

Model. The model is 2 dimensional and grid size of the model is 1/36 degree. We calculated tidal
amplitude and phase lag of 8 principal tidal constituents by the model. The model is constrained by tidal
variation at open boundaries which is calculated NAO99Jb model, and sea level variation derived fromaltimetry data and tide gauge data in Japan, Korea, and China are assimilated into the model. Table 1
shows errors of the present model and NAO99Jb for each tidal constituent.
Error of the present model for each tidal constituent was less than 2 cm and total error of 8 principal
constituents were 8.7 cm which was fewer than half of the number of NAO99Jb. Total error of thepresent model was approximately 5 cm in the area where water depth is more than 10 m. The error of 5
cm allows us to calculate sea surface current from altimetry data.
Table 1. Errors of the present model and NAO99Jb for 8 principal tidal constituents. Unit in cm.

Tidal constituents

M2

S2

O1

K1

Q1

P1

K2

N2

Total

Present model

1.6

0.8

1.5

1.6

0.8

1.2

0.6

0.7

8.7

NAO99Jb

3.8

2.1

2.9

3.4

0.9

1.1

2.3

1.2

17.7

Investigation of air-sea flux and its variation over the Kuroshio Extension region
Advanced Microwave Scanning Radiometer 2/Global Change Observation Mission 1st for Water:
AMSR2/GCOM-W1 developed by JAXA was launched successfully in May 2012 and its observations
were started from July 2012. Validation of AMSR2 is one of significant missions because the satellite
sensor remotely observes ocean surface and its accuracy is unknown. The first time validation of AMSR2
standard products with in-situ observations was conducted over the ocean, particularly in the Kuroshio
Extension region as a collaborative study with JAXA. Comparison with in-situ observations for a year,
we could confirm that AMSR2 observation is fine and accuracy meets a criteria for standard data release:
SST: 0.8℃, SSW: 1.5m/s (see Figure). AMSR2 ocean standard products promise to provide us good
information for air-sea interaction, climate, and water cycle studies.

Fig. 2：Scatter-diagrams between KEO buoy (x-axis) and AMSR2 (y-axis) for (a) sea surface temperature (SST,deg.C) and (b) sea surface wind speed (SSW, m/s).

33

Endowed Research Division
Stakeholder Management Research Laboratory
Since the Great East Japan Earthquake of 2011, there has been great concern on expanding the useof renewable energy. However, in order for the actual construction of offshore wind farms to be executed,
the nation-level macro perspective of moving away from dependence on fossil fuels and nuclear power
generation is not sufficient and the micro perspective of building consensus among local stakeholders isnecessary. In addition, looking to the coastal areas closely involved with offshore wind farms, additional
problems have become apparent including population decline and the aging of local fishermen, and therevitalization of fishing communities has emerged as an important challenge. If the introduction of
offshore wind farms can be used not only for the purposes of supplying power but also as a mean ofrevitalizing local communities, we believe this will contribute not only to the spread and expansion of
offshore wind power generation itself, but also to the restoration of regional vitality. This study suggests
methods for achieving mutually beneficial relationships between local communities and offshore wind
power.
While some demonstration offshore wind projects have taken place in Japan, no large-scale facilities
have yet been built by the private sector. For this reason, there remains insufficient basic research forbuilding the consensus necessary for moving forward with offshore wind projects. For example, there
is little knowledge of the positive and negative impacts of the wind farm on the fishing industry. It is also
not clear that which stakeholders need to be involved. We are conducting fieldwork in association withprojects in four Japanese communities planning offshore wind power generation projects. In 2013, we
carried out primarily interview-based investigation of local issues through discussions with coastal
fishermen. We found that a resource-management fishery based in part on the use of offshore windturbines constituted one method that might resolve local challenges. However, due to the possibility ofinterference with particular fishing methods (e.g., trawlnets), as well as that the sites of offshore windfarms might serve as shelter areas for ships, we came to the new realization of a future need to coordinate
views with differently positioned stakeholders such as offshore fishermen. In addition, as we have built acollaborative relationship with Statoil ASA, who have developed large-scale offshore wind power
generation projects in Europe, and with DNV GL, a firm that provides risk management services, we arecollecting information on European methods for generating consensus and investigating the possibility ofadapting these to Japan. Furthermore, we have been selected for the project by NEDO in “Research andDevelopment of Wind and Renewable Energy Technology - Research and Development of Offshore
Wind Power Technology - Basic Research For Local Co-Existence with Offshore Wind Farms(FY2013-2014 )”, with future plans to conduct research on coexistence and harmony with coastal
communities on top of local fishing industries.
Our outreach activities have included hosting seminars and symposiums on offshore wind power
generation and participating in workshops held by the Royal Norwegian Embassy in Tokyo in order tointroduce the stakeholder management research and share the knowledge of rules for marine utilization(e.g. fishing rights). In addition, in terms of university educational initiatives, we have been running“Environmental Innovation” as part of the Education for Sustainable Development (ESD) Program
managed by the five graduate schools of environmental studies, and visiting researchers and others in our
endowed research division have been offering lectures on energy-centered initiatives in the private sector.
We also invited Statoil ASA, who is our research collaborator, to take part in our HyARC Seminar, which34

focused on the themes of environmental impact assessment and floating offshore wind turbine
development.

Fig. 1：First symposium “Offshore wind projects and stakeholder management”

Fig. 2：The floating offshore wind project of Statoil “Hywind”

Fig. 3：Sheringham Shoal offshore wind farm35

List of Publications*:Staffs, students and research fellows in the HyARC.
January, 2013～March, 2014
№

1

2

3

4

5

Author

Title

JournalFerraro, R., C. Peters- An evaluation of microwave IEEE Transactions
Lidard , C. Hernandez, land surface emissivities over on Geoscience
F. J. Turk, F. Aires, C.
the continental United States and Remote
Prigent, X. Lin, S.-A.
to benefit GPM-era
SensingBoukabara, F.A.
precipitation algorithms.
Furuzawa, K.
Gopalan, K. Harrison,
F. Karbou, L. Li, C. Li,
H. Masunaga, L. Moy,
S. Ringerud, G.
Skofronik-Jackson, Y.
Tian, and N.-Y. Wang
Ueyama, M., K. Ichii,
Upscaling terrestrial carbon
Journal of
H. Iwata, E.S.
dioxide fluxes in Alaska with
GeophysicalEuskirchen, D. Zona,satellite remote sensing andResearch:
A.V. Rocha, Y.
support vector regression.
Biogeosciences
Harazono, C. Iwama,
T. Nakai, W.C. Oechel
Li, W., T. Hiyama, N.
Seasonal Variations of the
Atmospheric andKobayashiSurface Fluxes and Surface
Climate Sciences
Parameters over the Loess
Plateau in China.
Igarashi,Y., N. Tanaka, Seasonality of water andEcohydrology
T. Yoshifuji, C. Sato, C. carbon dioxide exchanges atTantasirin and M.
a teak plantation in northern
SuzukiThailand.
Siswanto, E., J.
Detection of harmful algal
Remote Sensing ofIshizaka, S.C. Tripathy, blooms of Karenia mikimotoi Environment
K. Miyamura
using MODIS measurements: A
case study of Seto-Inland Sea,
Japan.

Volume

Page
doi

Date

51

378 - 398
doi:10.1109/TGRS.2012.
21991212013/1/1

1081266-1281
doi:
10.1002/jgr
g.20095

2013/1/1

3

111-120

2013/1/30

6(1)125-133

2013/2/1

129(15)185-196

2013/2/15

Volume

Page
doi

Date

48(1)

141-148

2013/4/1

Progress in
Oceanography111

125-139

2013/4/1

Scientific Online
Letters on the
Atmosphere (SOLA)

9

April, 2014～March, 2015№

Author

Title

JournalIchikawa, K., W.C.
Preliminary results of the
Ocean Science
Yang, A. Morimoto, Y. Japan-Taiwan joint survey on Journal
Yoshikawa, S.
combining ocean radar data
Sugitani, W.S. Chiang, in the Kuroshio upstream
1
J.W. Lai, E.Y. Liang,
region.
C.T. Liu, C.W. Lee, K.
Yufu, M. Kyushima, S.
Fujii, T. Senju, Y. Ide
Takahashi, D., A.
Morimoto
2

Imaoka, K. and K.
Nakamura
3

Mean field and annual
variation of surface flow in
the East China Sea asrevealed by combining
satellite altimeter and drifter
data.
Statstical Analysis of Temporal
Variation of Heating Profiles
Associated with Isolated
Tropical Cold Cloud Systems
by Using Satellite
Observations.

36

51-55
2013/4/19
doi:10.2151/sola.2913012

№

Author

JournalVolumeM. Rafiuddin, H.
Uyeda, M. KatoDevelopment of an arcshaped precipitation system
during the pre-monsoon
period in Bangladesh.

Meteorology andAtmosphericPhysics

120,3-4

Yamaguchi, H., J.
Ishizaka, E. Siswanto,
Y.B. Son, S. Yoo, Y.
Kiyomoto

Seasonal and spring
Continental Shelfinterannual variations in
Researchsatellite-observed chlorophylla in the Yellow and East
China Seas: New datasetswith reduced interference
from high concentration ofresuspended sediment.

59

Characteristics of
Polar Scienceevapotranspiration from apermafrost black spruce forest
in interior Alaska.

7

136–148

2013/6/1

7

174-187

2013/6/1

7149-161

2013/6/1

7125-135

2013/6/1

264204-4218

2013/6/1

4(6)

65A

1-17
2013/6/1
doi:org/10.
1890/ES1300125.1
19681
2013/6/28

33(8)1909-1916

2013/6/30

26

4858-4875

2013/7/1

4

5

Page
doi

Title

Nakai, T., Y. Kim, R.C.
Busey, R. Suzuki, S.
6 Nagai, H. Kobayashi,
H. Park, K. Sugiura, A.
Ito
Park, H., J.E. Walsh, Y.
7 Kim, T. Nakai, T.
Ohata
Sugiura, K., S. Nagai,
T. Nakai, R. Suzuki
8

The role of declining Arctic sea Polar Science
ice in recent decreasing
terrestrial Arctic snow depths.
Application of time-lapse
Polar Science
digital imagery for groundtruth verification of satellite
indices in the boreal forests of
Alaska.
Nagai, S., T. Nakai,
Seasonal changes in camera- Polar Science
T.M. Saitoh, R.C.
based indices from an open
Busey, H. Kobayashi,
canopy black spruce forest in
9 R. Suzuki, H. Muraoka, Alaska, and comparison with
Y. Kimindices from a closed canopy
evergreen coniferous forest inJapan.
Kanemaru, K. and H. A satellite study of the
Journal of Climate
Masunaga
relationship between sea
surface temperature and10column water vapor overtropical and subtropicaloceans.
Maeshiro, R., B.
Using tree functional diversity Ecosphere
Kusumoto , S. Fujii, T. to evaluate management
11
Shiono and Y. Kubota impacts in a subtropicalforest.
Sun, W.-Y., O. M. Sun A modified atmospheric non- Tellus
and K. Tsubokihydrostatic model on low
Tellus Series A12
aspect ratio grids: part II.
Dynamic
Meteorology andOceanography
Panicker, A. S., D. I.
Decadal climatologicalInternational
Lee, Y. V. Kumkar, D. trends of aerosol optical
Journal of
13 Kim, M. Maki and H.
parameters over three
Climatology
Uyeda
different environments inSouth Korea.
Kanamori, H., T.
Modulation of the Diurnal
Journal of Climate
Yasunari, and K. Kuraji Cycle of Rainfall Associated14with the MJO Observed by a
Dense Hourly Rain Gauge
Network at Sarawak, Borneo.

37

Date

165-176
2013/5/1
doi:
10.1007/s00
703-0130244-x
1-9
2013/5/15

№

AuthorYamazaki, T., K. Kato,
T. Ito, T. Nakai, K.
15 Matsumoto, N. Miki,
H. Park, T. Ohta

Title
A common stomatalparameter set used tosimulate the energy andwater balance over boreal
and temperate forests.

JournalVolume

Page
doi

Date

Journal of
MeteorologicalSociety of Japan

91273-285

2013/7/1

Tomita, H., S-P. Xie, H. Cloud response to the
Journal of Climate
16 Tokinaga, and Y.
meandering Kuroshio
Kawai
Extension front.
Wang, S., J. Ishizaka, Influence of river discharge on Biogeosciences
H. Yamaguchi, S.C.
phytoplankton absorption
Discuss
Tripathy, M. Hayashi, Y. properties: a
17 Xu, Y. Mino,case study in the East China
T. Matsuno,
Sea and Tsushima Strait.
Y. Watanabe andS. YooMasunaga, H.
A satellite study of tropical
Journal of the
moist convection andAtmosphericenvironmental variability: A
Sciences
18
moisture and thermal budget
analysis.

26(23)

702443-2466
http://dx.doi.org/10.1
175/JAS-D12-0273.1

2013/8/1

Kumagai, T., R.G.
Simulation of canopy
EcologicalMudd, Y. Miyazawa,
CO2/H2O fluxes for a rubber
Modelling
W. Liu, T.W.
(Hevea brasiliensis) plantation
Giambelluca, N.
in central Cambodia: the19 Kobayashi, T.K. Lim, M. effect of the regular spacing
Jomura, K.
of planted trees.
Matsumoto, M.
Huang, Q. Chen, A.
Ziegler and S. Yin
Kataoka, R., Y.
Stereoscopic determination of Annals of
Miyoshi, K.
all-sky altitude map of aurora Geophysics
Shigematsu, D.
using two ground-based
Hampton,Y. Mori, T.
Nikon DSLR cameras.
20
Kubo, A. Yamashita,
M. Tanaka, T. Takahei,
T. Nakai, H. Miyahara,
K. Shiokawa

265

P124-135

2013/9/1

311543-1548

2013/9/1

224:1763

2013/10/1

Chiwa, M., T. Enoki, N. The increased contribution of Water, Air, & Soil
Higashi, T. Kumagai
atmospheric nitrogen
Pollution
21 and K. Otsuki
deposition to nitrogen cycling
in a rural forested area of
Kyushu, Japan.
Xu, Y., J. Ishizaka, H.
Relationships of interannual
Journal of
Yamaguchi, E.
variability in SST and
Oceanography
Siswanto and S. Wang phytoplankton blooms withgiantjellyfish (Nemopilema
22
nomurai ) outbreaks in the
Yellow Sea and East China
Sea.
23

Hamada, S., T.
Tanaka, T. Ohta

Saito, T., H. Matsuda,
M. Komatsu, Y.
24 Xianga, A.
Takahashic, Y.
Shinohara, K. Otsuki

Impacts of land use and
Urban Forestry &topography on the cooling
Urban Greening
effect of green areas on
surroundig urban areas.
Forest canopy interception
Journal ofloss exceeds wet canopy
Hydrology
evaporation in Japanesecypress (Hinoki) and Japanesecedar (Sugi) plantations.

38

10

69(5)

9393-9398 2013/7/19
doi:org/10.
1175/JCLID-1314475-14514
2013/8/1
doi:10.5194/bgd-1014475-2013

511-526
2013/10/1
doi:
10.1007/s10872-0130189-1

12(4)426-434

2013/11/1

507

287-299

2013/12/1

TitleJournalVolume

Page
doi

Date

Li, X., W.-K. Tao, H.
Masunaga, G. Gu,
25
and X. Zeng

Aerosol effects on cumulus
congestus population over
the tropical Pacific: A cloudresolving modeling study.

Journal of the
MeteorologicalSociety of Japan

91

817-833

2013/12/1

Kumagai, T., H.
26 Kanamori and T.
Yasunari
Kumagai, T., M.
Tateishi, Y. Miyazawa,
M. Kobayashi, N.
27
Yoshifuji, H. Komatsu
and T. Shimizu

Deforestation-induced
reduction in rainfall.

Hydrological
Processes

27(25)

3811-3814

2013/12/15

508

66-76

2014/1/1№

AuthorEstimation of annual forest
Journal of
evapotranspiration from a
Hydrology
coniferous plantationwatershed in Japan (1): Water
use components in Japanesecedar stands.
Yoshifuji, N., Y.
Inter-annual variation in theInternational
Igarashi, N. Tanaka, K. response of leaf-out onset to Journal of
28 Tanaka, T. Sato, C.
soil moisture increase in a
Biometeorology
Tantasirin, M. Suzuki
teak plantation in northern
Thailand.
Lee, K.-O., H. Uyeda, Microphysical structures
AtmosphericDong-In Lee
associated with
Research
29
enhancement of convective
cells over Mt. Halla, Jeju
Island, Korea on 6 July.
Fujinami, H., T.
Dynamics of distinct
Climate Dynamics
Yasunari and A.
intraseasonal oscillation in
Morimotosummer monsoon rainfall over30
the Meghalaya-Bangladeshwestern Myanmar region：
Covariability between thetropics and mid-latitudes.
Umezawa, Y., A.
Seasonal shifts in the
Biogeosciences
Yamaguchi, J.
contributions of the
Ishizaka, T.
Changjiang River and the
Hasegawa, C.
Kuroshio Current to nitrate
31 Yoshimizu, I. Tayasu, H. dynamics in the continental
Yoshimura, Y. Morii, T. shelf of the northern East
Aoshima, and N.
China Sea based on a nitrate
Yamawakidual isotopic composition
approach.
Ito, M., A. Morimoto, Tsushima Warm Current paths Progress in
32 T. Watanabe, O.
in the southwestern part of
Oceanography
Katoh, T. Takikawa
the Japan Sea.
Tian, Y., C. PetersQuantifying uncertainties inIEEE Transactions
Lidard , K. W. Harrison, land surface microwave
on Geoscience
C. Prigent, H. Norouzi, emissivity retrievals.
and Remote
Sensing
33 F. Aires, S.-A.
Boukabara, F. A.
Furuzawa and H.
Masunaga
Kobayashi, H., R.
Suzuki, S. Nagai, T.
34 Nakai, Y. Kim

Terauchi, G., R.
Tsujimoto, J. Ishizaka,
35 H. Nakata

Spatial scale and landscapeheterogeneity effects on
FAPAR in an open canopy
black spruce forest in interior
Alaska. IEEE Trans.
Preliminary assessment ofeutrophication by remotelysensed chlorophyll-a inToyama Bay, the Sea ofJapan.

39

Geoscience andRemote Sensing
Letters, IEEE

Journal of
Oceanography

onlinefirst

135-136

2014/1/1

76-90

2014/1/1

doi:
2014/1/25
10.1007/s00
382-0132040-1

11(4)1297-1317
doi:10.5194/bg-111297-2014

2014/2/1

121

83-93

2014/2/1

52829-840

2014/2/1

11564-568

2014/2/1

doi:10.1007 2014/2/18/s10872-0140222-z

№Author

Title

JournalVolume

Page
doi

Date

398-411

2014/3/7

Mino, Y., S.
Matsumura, T.
Lirdwitayaprasit,
36
T. Fujiki, T. Yanagi, T.
Saino

Variations in
Journal of Plankton
phytoplankton photoResearchphysiology and productivity ina dynamic eutrophic
ecosystem: a fast repetition
rate fluorometer-based study.

36 (2)

Ohigashi, T., K.
Tsuboki, Y. Shusse, H.
37 Uyeda

An Intensification Process of a Journal of theWinter Broad Cloud Band on Meteorologicala Flank of the Mountain
Society of Japan
Region along the Japan-Sea
Coast.
Transpiration characteristics of Tree Physiology
a rubber plantation in central
Cambodia.

92

Kobayashi, N.,
Kumagai, T.,
Miyazawa, Y.,
Matsumoto, K.,
38
Tateishi, M., Lim, T. K.,
Mudd, R. G., Ziegler,A., Giambelluca, T. W.
and Yin, S.
Lee, K.-O., H. Uyeda
Effect of an isolated ellipticaland D.-I. Lee
terrain (Jeju Island) on rainfall
enhancement in a moist
39
environment.

40

TellusTELLUS SERIES ADYNAMIC
METEOROLOGYAND
OCEANOGRAPHY

34(3)

66

71-93
2014/3/14
doi:10.2151/jmsj.2014105
285-301

2014/3/18

doi:http:// 2014/3/19
dx.doi.org/
10.3402/tellusa.v66.204
84

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The 2013 Annual Report was published October 2014
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