2011

Contents
Foreword

2

Staff and Organization

3

Research Programme

6

Progress Reports
Projects

8

Division of Regional – Scale Water Cycle Processes

9

Laboratory for Climate System Study

9

Laboratory for Cloud and Precipitation Climatology

13

Division of Global – Scale Water Cycle Variations

15

Laboratory of Satellite Meteorology

15

Laboratory of Environmental Biophysics

17

Laboratory of Satellite Biological Oceanography

19

Laboratory of Bio-Physical Oceanography

23

List of Publications

25

Foreword
On March 11, 2012, a catastrophic earthquake occurred off the coast of Japan. The disastrous
earthquake affected us throughout the 2012 fiscal year. Although, the impact of the earthquake on the
Hydrospheric Atmospheric Research Center (HyARC) was limited, the earthquake forced us to think
deeply about the relationship between science and society. The results of scientific research do notalways give us a direct benefit, but a prompt response to direct disasters is strongly expected by oursociety. Scientific research is supported by society, and we cannot ignore its possible contribution tosociety.
The research environment is changing and becoming more competitive. The competition is not only
for the research budget but also for the researchers themselves. Even capable researchers are leaving the
research community, and those working at HyARC are no exception.
As described in this annual report, the research activity at HyARC is maintained at a high level andthe themes of the studies are diverged. Since it is natural that the researche field diverges as theirresearch progresses, this divergence should be acknowledged. However, HyARC has its own research
objective, that is, investigating the mechanism of the global water cycle, and we should always be careful
to coordinate between individual research and HyARC’s objective.
HyARC functions as an inter-university collaborative system, which is in many ways unique in theworld. To ensure its research activity, HyARC was accredited as a Joint Usage/Research Center in April
2010 by the Ministry of Education, Culture, Sports, Science, and Technology, Japan.
The University Project supported a virtual laboratory for diagnosing the earth’s climate system.
HyARC has also collaborated with numerous institutions such as the Research Institute of Humanity
and Nature (RIHN) and the National Institute of Information and Communication Technology (NICT).
HyARC has also taken part in international collaborations. As part of the UNESCO International
Hydrology Program (IHP), HyARC has hosted training courses supported by the Japan Trust Fund. This
year’s course was conducted by the Disaster Prevention Research Institute, Kyoto University. While
selecting projects and activities, HyARC considers the project’s feasibility, its significance, and thecollaboration requirements. Although HyARC has only 10 permanent staff members (four professors,
three associate professors, and three assistant professors), it supports many postdoctoral candidates in
active research. In addition, HyARC has accepted graduate students in the Department of Environmental
Studies.

Nakamura Kenji

Director
Hydrospheric Atmospheric ResearchCenter2

Staff and Organization
Research
Division
Board ofCouncilors
Director

Division of Regional-Scale Water Cycle Processes
0Professor

0UYEDA Hiroshi

0YASUNARI Tetsuzo

0Assoc. Professor

0TSUBOKI Kazuhisa

0MASUNAGA Hirohiko

0Assist. Professor

0SHINODA Taro0FUJINAMI Hatsuki

Advisory
Board
Board onResearch
Collaboration

VL Promotion Unit
0Designated Assist.
0OHIGASHI Tadayasu
0Professor
Division of Global-Scale Water Cycle Variations
0Professor

0NAKAMURA Kenji

0ISHIZAKA Joji

0Assoc. Professor

0KUMAGAI Tomo’omi 0MORIMOTO Akihiko

0Assist. Professor

0MINO Yoshihisa

0Designated Assoc.
0TANAKA Hiroki
0Professor
0Technical Office
0MINDA Haruya0(Technical Center)
0Secretary Office

0HATTORI Ayumi

Administrative Office
0Administrative
0Director

0NAGAO yoshinori

0Administrative
0Vice-Director

0SUGIE Osamu
0General Affairs
0Section
0Accounting Section
0Research Promotion
0Section
0Supplies Section
0Student Affairs
0Section

30KYUSHIMA MoetoAdministration
Board of Councilors
NAKAMURA Kenji: Director, Prof., Hydrospheric Atmospheric Research Center, Nagoya University
UYEDA Hiroshi: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
YASUNARI Tetsuzo: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
ISHIZAKA Joji: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
TANAKA Kentaro: Prof., Graduate School of Science, Nagoya University
TSUJIMOTO Tetsuro: Prof., Graduate School of Engineering, Nagoya University
TAKENAKA Chisato: Prof., Graduate School of Bioagricultural Sciences, Nagoya University
KANZAWA Hiroshi: Prof., Graduate School of Environmental Studies, Nagoya University
MATSUMI Yutaka: Prof., Solar-Terrestrial Environment Laboratory, Nagoya University

Advisory Board●Members from Nagoya University
UYEDA Hiroshi: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
YASUNARI Tetsuzo: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
ISHIZAKA Joji: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
TSUBOKI Kazuhisa: Assoc. 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●Members outside Nagoya University
FUJIYOSHI Yasushi: Prof., Institute of Low Temperature Science, Hokkaido University
HANAWA Kimio: Prof., Graduate School of Science, Tohoku University
SUMI Akimasa: Prof., Integrated Research System for Sustainability Science, The University of Tokyo
FUKUSHIMA Yoshihiro: Designated Prof., Tottori University of Environmental Studies
YAMANAKA Manabu: Principal Scientist, Research Institute for Global Change, Japan Agency for
Marine-Earth Science and Technology
YAMANOUCHI Takashi: Prof., National Institute of Polar Research
TANIGUCHI Makoto: Prof., Research Institute for Humanityand Nature
OKI Riko: Senior Researcher, Earth Observation Research Center, Japan Aerospace Exploration Agency

4

Board on Research Collaboration●Members from Nagoya University
UYEDA Hiroshi: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
ISHIZAKA Joji: Prof., Hydrospheric Atmospheric Research Center, Nagoya University
MORIMOTO Akihiko: Assoc. Prof., Hydrospheric Atmospheric Research Center, Nagoya University●Members outside 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

5Research Program
Development of remote sensing technology for atmosphere and ocean
observations
The Okinawa Subtropical Environment Remote-Sensing Center, an observation facility in Okinawa,
Japan, was established by the National Institute of Information and Communication Technology (NICT).
These facilities offer the use of full polarimetric Doppler radar (COBRA), 400 MHz wind profiler radar,
Doppler sodar, disdrometers, rain gauges, and ocean radars. In 2005, an interuniversity collaboration
was formed between NICT, Okinawa, and the Hydrospheric Atmospheric Research Center at Nagoya
University, Japan (HyARC). Based on the results of collaboration studies, this fiscal year, the project has
re-started with a new title as "Development of remote sensing technology for atmosphere and ocean
observations" recognizing the demand of new techniques for the atmosphere and ocean remote sensing.
The Japan Aerospace Exploration Agency (JAXA) has developed a new dual Ka-band radar system
for ground validation of the Global Precipitation Measuring Mission (GPM). As one of the atmosphereobservations, rain observation experiment with this radar was conducted in NICT Okinawa withcollaboration of JAXA. For the ocean observation, a new idea of flexible ocean radar idea has emerged.
NICT performed basic development and the system seems very feasible. The new radar may be used for
the Tsushima Current observation.

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 coveringand resolving 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.
Thus, a new research program, “Research on Coast Circulation, Biological Production and Material
Transport with Remote Sensing”, has been started from 2011, and four collaborative research programs
were accepted for following research topics.
-Developments of ocean color and sea surface height algorithms and verification around Japan andcoastal areas.
-Application research on circulation of coastal area, biological production and material transport withthose remote sensing data and combinations with other data and models-Enhancement of international collaboration with Asian counties, specifically with Korea
8th Korea-Japan Workshop on Ocean Color Remote Sensing was also held in Korea Ocean Researchand Development Institute as a part of the research program.
6

Advanced utilization of the polarimetric radars and the cloud-resolving
model for cloud and precipitation research
Advanced research of cloud and precipitation with utilizing the polarimetric radars and thecloud-resolving model
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,
three principal investigators (PIs) performed the following researches in the research program.
1. PI: Nakakita, E. (Kyoto University) To study formation and development of heavy rainfall, they
performed the Okinawa Baiu observation in May and June and cumulonimbus cloud observation in Kobe
area from September. These observations were combined with other observations such as the video sonde,
millimeter-wave radar, and GPS to make various studies on cloud-microphysics processes.
2. PI: Wakazuki, Y. (University of Tsukuba) Since he develops a simplified data assimilation technique,he studied kinematic properties of convective clouds to contribute the technique development. In
particular, a scheme to convert radar data to an idealized convective cell was developed. This enables us
to relate the idealized convective cells derived from real rainfall distribution to convective cells producedby the cloud-resolving model CReSS.
3. PI: Sano, T. (Nagoya University) The purpose of the study is to clarify the heavy rainfall formation
process in a basin and surrounding mountains in a warm season. Using the X-band polarimetric radar,precipitation systems in the Kofu basin and the surrounding mountains were studied. On July 28, 2010, a
cumulonimbus cloud which was maintained for 6 hours above Asagiri plateau to the west of Mt. Fuji wasobserved. They revealed the maintaining process of the cloud and the formation process of heavy rainfall
on the basis of the behavior of convective cells within the cloud.

Land-climate interaction through water and material cycles
Study on nonlinear and dynamic equilibrium interaction between land (i.e., vegetation, soil,
topography) and climate through water cycle and material cycle need a new interdisciplinary approach
including hydrology, forest science and ecology, in addition to climatology and meteorology. Based on
results and issues from these different fields, this research plan aims to clarify how the land-climate
interaction maintain and fluctuate and furthermore how the interaction relate the maintenance andvariation of a whole climate system of the earth, focusing on water cycle. The main target area is the
Asian monsoon region that includes the Eurasian Continent and the maritime continent with a complex
topography and biodiversity.
On August 22 – 24, 2011, an international workshop on Asian monsoon and water cycle, co-hosted
by MAHASRI, was held in Nhatrang, Vietnam. In this workshop about 80 participants attended fromJapan, China, Taiwan, Malaysia, Vietnam, Philippines, Thailand and USA. Fifty participants presented
new scientific results and there was a lively discussion. On November 15, a domestic workshop on
climate-land interaction over Eurasia/ Asian monsoon region was held in HyARC, Nagoya University.
Twelve participants gave interesting talks. Future issues on the land-climate interaction were also
discussed.
7

Progress Reports

Projects

The Innovative Program of Climate Change Projection for the 21st Century( KAKUSHIN Program)●Cloud Modeling and Typhoon Research
The cloud modeling team has been developing a cloud-resolving model named the Cloud Resolving
Storm Simulator (CReSS). The cloud microphysics and computation scheme of CReSS are improved for
accurate and high-speed calculation. Convective clouds in the tropical region and typhoons are important
objectives of our team. The CReSS model is also coupled with global models to simulate convective
regions. CReSS is used for typhoon research with aims to help verify typhoon simulations made byglobal models and to produce accurate and quantitative evaluations of typhoon effects on human society
under the current and warming climates. The program is ended in March 2012. Some of important results
are summarized as follows.
●Improvement of the cloud-resolving model and typhoon simulations
Since typhoons are composed of intense convective
clouds as well as associated stratiform clouds, acloud-resoling model is necessary for accurate prediction of
their intensity. In the present study, we have improved theCReSS model to perform simulation in an arbitrary-shaped
computational domain. Using the cloud-resolving model, asimulation experiment with a computation domain along thetyphoon track was performed. Figure 1 compares thesimulation result of the typhoon No. 18 (2004) at 312 hours Fig. 1: (a) Simulation result of typhoon No.18 offrom the initial time (09 JST August 25, 2004) with the radar 2004 using CReSS with the Tiling Domain
observation provided by JMA (the Japan Meteorological Technique at 312 hours from the initial time (09Color levels are rainfall
Agency). The position of the typhoon center, eye wall, JST August 25, 2004).
-1
intensity (mm hr ), contours are sea level
surrounding spiral rainband and orographically enhanced
pressure and arrows are horizontal velocity. (b)heavy rainfall are correctly simulated. The result shows that JMA radar observation at the same time of (a).
the cloud-resolving model enables us to predict Color levels are rainfall intensity (mm hr-1).
quantitatively the intensity of typhoon.
●Projection of super-typhoons in global warming climate using the CReSS model
Observation, theory and numerical studies have been showing that intensity of hurricanes andtyphoons increases with global warming. Since tropical cyclones such as typhoon bring a huge disaster in
East Asia including Japan as well as water resources, future change of typhoon intensity with climatechange will give a large impact on human society. In particular, intensity increase of the most intense
category of typhoon is a big problem for disaster prevention planning and risk managements. Our teamhas studied maximum intensity of typhoons in the future(late-21 century) and near future (about 30 years later)
climates in collaboration with the Extreme Event Projection
team and found that some typhoons will become much more
intense in the future climate that in the present-day climate.
Typhoons with a surface maximum wind speed of 67 m s-1 orlarger are referred to as “super-typhoon”. Number andintensity of super-typhoon will increase in the future climate.
Moreover, super-typhoons will reach higher latitude such as
the main islands of Japan because of higher sea surface
temperature. Figure 2 shows a simulated super-typhoon by Fig. 2: The super-typhoon in the future climate
CReSS with a horizontal resolution of 2km. The (September 2076) simulated by the CReSS
model. The contours are sea level pressure
super-typhoon moved northward over the Pacific and was(hPa) and color levels are rainfall intensity
making landfall over Japan with a central pressure of 880 (mm/hr).
hPa.
8Division of Regional – Scale Water Cycle Processes
Laboratory for Climate System Study
The modulation of the diurnal cycle of rainfall associated with the MJO observed by adense hourly rain gauge network at Sarawak, Borneo
This study investigates temporospatial characteristics of the diurnal cycle (DC) of rainfall over
Sarawak, western Borneo using a dense hourly rain gauge network. Their association with the large-scale
intraseasonal disturbances is represented by the Madden-Julian Oscillation (MJO). The spatial pattern of
the DC is divided between coastal and interior regions over the western part of Borneo, based onremarkable differences in rainfall peak times and amplitudes. The spatial distribution of daily rainfall in
the active and break phases over Sarawak using the rain gauge datasets are shown in Fig. 1. In the active
phase, rainfall over Sarawak increases relative to the break phase, although the spatial pattern of large
rainfall amounts in the interior mountains and southwest coastal areas does not change greatly undereither regime. The largest difference appears over the coastal region and foothills of the interior region.
In particular, enhancement in rainfall is drastic near the coast. The spatial distribution of the rate ofchange in rainfall shows a clear difference. The coastal areas facing northwest show the largest change inrainfall from the break to active phase of MJO, whereas those facing north shows less change, and themountain region in the interior of the island, where large amounts of rainfall occur, shows smallerchanges still. Thus, the daily rainfall data derived from rain gauge increases in the active phase over thewhole region, with coastal areas responding strongly to the MJO. And also, TRMM 3B42 rainfall isoverestimated (underestimated) over the coastal (interior) regions compared with the rain gauge data.
The TRMM shows that the rainfall between land and its surrounding oceans increases in the active phase.
In surrounding ocean regions, the distribution of heavy rainfall areas extends to widely from the coastline
to the open ocean in the active phase, are limited to near coastal areas in the break phase. It is found that
the TRMM underestimates the impact of the MJO on rainfall compared with that estimated from the rain
gauge data. However, the common message from both datasets is that the large-scale MJO influences
rainfall differently over oceanic, coastal land and interior land areas, and does so consistently between
the two datasets.
Although the amplitude of the DC and daily rainfall amount increase in the active MJO phase at allsites as shown in Fig.2, the MJO has a stronger effect in the coastal rather than the interior region. This
modulation of rainfall in the interior region is dependant on an increasing frequency of rainfall. In the
coastal regions, this is caused by the enhanced frequency and intensity of rainfall from the break to active
phases of the MJO. Hence the change of the DC between the break and active phases in the interior
region is explained by the change of the DC of frequency. On the other hand, the change of the DC in the
coastal region is affected not only by the change of frequency but also by the intensity of rainfall. The
DC in the coastal region is strongly affected by the characteristics of the oceanic DC, where the influenceof the large-scale cloud system associated with the MJO is important.

9

Fig. 1：Composites of daily rainfall in (a) the active phase and (b) the break phase over Sarawak based on
50 rainfall stations. (c) Spatial distribution of rate (%) of change in rainfall from active phase to break phase,
which is defined as [(active phase)/(break phase)-1] × 100. (d) to (f) Same as (a) to (c), but based on TRMM
3B42 data over Borneo and the surrounding ocean.

Fig. 2：Composite of the DC of rainfall
based on rain gauge in both the active
phase and the break phase for coastal andinterior categories (upper figures). The
solid (dashed) line indicates the active(break) phase rainfall in the respective
categories. Composite of the DC of
frequency (%) and intensity (mm/hr) ofrainfall for coastal and interior categories(bottom figures). The gray (white) bar
indicates frequency of rainfall in the active(break) phase with right axis and the solid(dashed) line indicates intensity of rainfall
in the active (break) phase with left andright axis, respectively.

10

Dominant modes of Trends and Interannual variations of summer precipitation in East
Siberia
In Eastern Siberia, there exists great reaches of boreal forest, covering about14% of forests on theearth. This boreal forest play a great role in global hydrological and carbon cycles (eg., Zhang et al.,2011). It has been noticed that the growth of these boreal forests depends on interannual variability ofsummer precipitation. However, temporal and spatial variabilities of summer precipitation in Eastern
Siberia has poorly been understood. In this study, we investigated dominant time-space patterns ofinterannual variability of summer precipitation in Eastern Siberia (90°E-140E,50°N-70°N), using theEOF (Empirical Orthogonal Function) analysis based upon daily precipitation grid data (APHRODITE,
Yatagai et al.,,2011) from 1979 to 2007. The association of the EOFs of monthly precipitation withatmospheric circulation water vapor transport (and its divergence) fields are also analyzed, using the
global objective reanalysis data from Japan Meteorological Agency (JMA).
We focused on the analysis of the top-three predominant patterns based on the contribution ratio of the
EOFs. The first pattern (EOF1, contribution ratio: is 22.0%) represents the variation in the large areafrom central n to western region of Eastern Siberia (central Siberian highland) and combined with thesoutheast part of Eastern Siberia (far east Siberia) but with an opposite sign. The second pattern (EOF2,
contribution ratio: is 13.8%) represents a dipole-like pattern (in precipitation variability) between east
and west part of Eastern Siberia. The third pattern (EOF3, contribution ratio: is 9.3%) represents patternof summer precipitation variability in northeast in Eastern Siberia.
These three EOF patterns have been proved to occur as a result of interaction between the westerly
waves along 60 N with slight changes oftrough (or ridge) system and water vapor field controlled byzonally-oriented stationary water vapor sources along 50-60N (possibly related to evapotranspirationfrom the boreal forest there) and by transport from the Arctic sea region.
In wet (dry) year in EOF1, deeper pressure trough (ridge) at around the Central Siberian Plateau(80E-120E) is likely to cause more (less) transport of water vapor from the Arctic sea (particularly fromthe Kara Sea). In wet (dry) year in EOF2, a pressure trough (ridge) at around western Central Siberian
Plateau (80E) and a pressure ridge (trough) at around eastern Central Siberian Plateau (120E) is likely tocause more (less) water vapor transport from Laptev Sea (Arctic Sea) and less (more) transport fromKara Sea ( Arctic sea). In wet (dry) year in EOF3, a pressure trough (ridge), remarkable only in a lower
troposphere, extending from the Arctic Sea to Mongolia is likely to cause more (less) water vapor
transport and convergence over regions of Verkhoyansk mountain Range and Mongolia. The timecoefficients of the EOF1 show a remarkably increasing trend of precipitation in the Central Siberian
Plateau region (Fig. 3a,b).
Finally, geographical pattern (or classification) for these interannual variation modes of precipitation has
been deduced based upon the spatial eigen value patterns of the EOFs patterns as shown in Fig. 4: that is,
the interannual variability of summer precipitation in western region of central Siberian plateau isrelevant to EOF1 mode and that in Verkhoyansk Range on east bank of Lena River is relevant to EOF2
mode, and that in North Verkhoyansk Range is relevant to EOF3 mode.. It has also been found that thesummer precipitation amount in central Siberian plateau has shown increasing trend particularly since
1990s.
11

Fig. 3：Spatial patterns and time scores (coefficients) of the three dominant three EOF modes in Eastern Siberia. (a),(b) for the EOF1, (c), (d) for the EOF2 and (e), (f) for the EOF3mode, respectively.

Fig. 4：Regional patterns based on interannual variations of summer precipitation in Eastern Siberia. Regions I, II and
III represent those for EOF1, EOF2, and EOF3, respectively. + or － represents variations with positive or negative
sign for each time coefficients.

12

Laboratory for Cloud and Precipitation Climatology
On the Relationship between Tropical Precipitation and Tropospheric Humidity
The tropics, receiving significant rainfall more than a half as much as the global precipitation, is a
key of global water cycle offering critical clues for understanding the mechanism driving the large-scaleatmospheric circulation. Tropical atmospheres, however, are not tightly controlled by synoptic-scale
dynamics such as baroclinic instability at work in mid latitudes, making it difficult to construct acomprehensive theory that explains the initiation and development of precipitation in the context oflarge-scale dynamics and thermodynamics. Controversies still remain despite of a long history of
research to date on the environmental conditions governing the activation and suppression of tropicalmoist convection.
Observational evidence of the close relationship between mid-tropospheric humidity and precipitation
has been found relatively recently and raised new research questions to address. Precipitation is known toincrease exponentially with column relative humidity (CRH), but the rate of the increase disagrees
among existing studies: compared to a satellite based daily climatology (Bretherton et al., 2004), thenon-linearity of CRH as a function of precipitation turns out to be much stronger when constructed within-situ measurements (Raymond et al., 2007). The current goal is to reconcile this apparent discrepancy.
The present work is, while based in either case on satellite data only, constituted of two different sets ofanalyses. The first utilizes daily mean climatology as done by (Bretherton et al., 2004), and the otherapplies the analysis method devised by Masunaga et al. (2012) to extract the variability on a time scalecomparable to convective life cycles. This composite scheme is aimed at capturing the atmosphericvariability over hourly to daily time scales in association with the development of convective systems as
depicted in Figure 1.

Fig. 1：CloudSat cloud profiles composited against the TRMM detected convection. Time series (top) and verticallysliced snapshots at 6 hours before convection (upper-middle), at the time of convection (lower-middle), and 6 hours
after convection (bottom). Composited separately for 4 types of convective systems from shallow cumulus (left) tovery organized systems (right).

13

Figure 2 shows the observed relation between CRH and precipitation. It is evident that the
non-linearity is much stronger when composited over a time scale of the convective life time (marked
lines) compared to the daily climatology (solid line). The result implies that the known discrepancy arises
from a difference in time scale of interest. The weak non-linearity in the daily climatology may beinterpreted as a superposition of different types of convective systems combined together (Figure 3).

Fig. 2：CRH-precipitation relationship from daily climatology (solid) and composite over a time scale of convective life
cycles (marked) . Numbers in the legend refer to the CRH at the convective peak. Left) Organized convective
systems (i.e., right half of Figure 1), Right) shallow convection (left half of Figure 1).

Fig. 3：Schematic of the CRH-precipitation relation based on Figure 2.

14

Division of Global – Scale Water Cycle Variations
Laboratory of Satellite Meteorology
Study on precipitation characteristics around Bangladesh using satellite data
It is well known that a rain activity is high not only during monsoon season but also during
pre-monsoon season around Bangladesh, and the rain intensity is different between pre-monsoon season
and monsoon season. In this study, the difference of precipitation systems with different rain intensities
during pre-monsoon season and monsoon season are investigated using the long-term (13 yrs.) TropicalRainfall Measuring Mission (TRMM) / Precipitation Radar (PR) data. It is clarified that there are alsosignificant differences in these precipitation systems. The fraction of convective rainfall and rain top
height are higher in pre-monsoon season than in monsoon season. The horizontal size of precipitation
systems during pre-monsoon season is larger than monsoon season. The vertical structure of precipitation
systems in pre-monsoon season are characterized by strong intensity up to high altitude and peakintensity at altitude of 3–3.5 km. On the other hand, the conditional rain-rate profile in monsoon season
has no maximum and continues to increase from top to the lower part of the profile. Vertical variations ofconditional rain-rate in monsoon season is smaller than in pre-monsoon season. Such differences ofvertical structure of precipitation systems appear to be common in convective rainfall. Deep precipitation
systems with intense rain dominate over the slope and foothills on the windward side of the Megalaya
plateau, Chittagong hill tracts, and Himalaya mountains. Atmospheric fields associated with thedifference of precipitaion systems around Bangladesh during two rainy periods are investigated using
Japanese Re-Analysis 25 years (JRA25) data by classifying into rain cactive and break phases. As aresult, the stability of the atmosphere seems to affect vertical profiles of the precipitation system. In the
pre-monsoon season, mid-level air is very dry because of westerly wind from inland of India. During theactive phase, air-layer has convective instability when warm and moist flow enters into the low-level
over Bangladesh. Moreover, the air-layer with convective instability is raised by the orographic liftingover the Megalaya plateau, and convections are initiated. Then a deep system with intense rain is likely
to be formed. On the other hand, during the break phase, atmospheric condition is unfavorable forrainfall development due to the incoming southwesterly moisture flow from the Bay of Bengal which is
weaker than during the active phase. In the monsoon season, convective instability during the active
phase is smaller than pre-monsoon season because the humidity at mid-level is high. Thus, moderate
rainfall with low rain top height is dominant in monsoon season. During break phase, moisture amountfrom the Bay of Bengal seems similar during the active phase, but the incoming southeasterly moistureflow can easily escape from the flat lowland of northwestern Bangladesh into the Ganges Plain, and cancause a decrease in rainfall over Bangladesh.

Dual Ka-band Radar Experiment for GPM DPR Algorithm Development
A dual Ka-band radar system is developed by the Japan Aerospace Exploration Agency (JAXA) for
the GPM DPR algorithm development. The dual Ka-radar system which consists of two identicalKa-band radars can measure both the specific attenuation and the equivalent radar reflectivity at Ka-band.
Those parameters are important particularly for snow measurement. Using the dual Ka-radar systemalong with other instruments, such as a polarimetric precipitation radar, a windprofiler radar,ground-based rain measurement systems, the uncertainties of the parameters in the DPR algorithm can be
reduced. The verification of improvement of rain retrieval with the DPR algorithm is also included as an
objective.
Observations using the dual Ka-radar system were performed in Okinawa Island, in Tsukuba, overthe slope of Mt. Fuji, and in Nagaoka, Japan. In Okinawa Island, the performance of the measurement
has been confirmed by rain observation. In Tsukuba, one radar was directed in vertical and the other wasin slant direction. By this configuration, total attenuation in the melting layer was estimated. The
objective of the Mt. Fuji experiment was to observe the melting layer. An X band polarimetric radar was
15simultaneously operated. Unfortunately, the melting layer did not come in between the two radars due towarm weather. In Nagaoka, a lot of wet snow fell, and much data on the snow have been obtained.
The main results are the k-Ze relationships.
For the rain, reasonable k-Ze relationship has
been obtained. The feasibility of total
attenuation in melting layer has been studied.
Different k-Ze relationships have been obtainedin snow observations. Compared with rain, wetsnow shows large specific attenuation. Figure 1
shows the concept of the vertical-slant pathexperiment and the radar echo examples. Using
the difference in radar echoes due to the path
length difference between vertical and slant
paths, total attenuation in the melting layer canbe estimated. Estimated attenuation in themelting layer was twice or three times larger ofthe ground-measured rain rates. The total
Fig. 1：Concept of the vertical-slant path observation (left),attenuation seems to correspond to the estimatesand example of radar echoes (right).
from the ground-based measurements

Comparison of X-band multi-parameter radar network data
Operational test of X-band Multi-Parameter (MP) radar network installed by the River Bureau of
the Ministry of Land, Infrastructure, Transport and Tourism, Japan (MLIT) has started from July 2010.
By these radars, more detailed precipitation observation than the C-band radars of the Japan
Meteorological Agency (JMA) is attained. On the other hand, TRMM (Tropical Rainfall Measuring
Mission) is performing rain observation with precipitation radar (PR). In this study, comparison of the
MP radar data installed in the Tokai area for nine cases from August 2010 to May 2011 is performed, andtheir rain rates are compared with TRMM PR and a disdrometer to clarify the characteristics ofprecipitation estimation of these three MP radars.
At first, each parameter (reflectivity (Zh), differential reflectivity (ZDR), specific differential phase(KDP) and rain rate (Rr)) is compared among three MP radars.
It turns out that all parameters except for KDP tend to underestimate depending on the distance fromthe radar. Vertical variation of rain seems to cause the underestimation.
KDP seems to be the most helpful to precipitation intensity estimation. However, when the rain rate(Rr) is compared with PR, the Rr derived from KDP isoverestimated.
This overestimated value is about 1.3 times aslarge as Rr computed from a theoretical formula of the
KDP-Rr relationship. Based on this result, Rr of MP
radar is recalculated from KDP using the theoreticalformula. And when comparing with PR, The obtained
result becomes comparatively in agreement with PR(Fig.2). However, the differences appear in the casewith local strong rains.
Finally, comparison of Rr computed from thetheoretical formula with the disdrometer isperformed.Rr computed from the KDP-R theoreticalFig. 2 ： Comparison of retrieved rain rate fromformula of MP radar is overestimated, while Rr
TRMM precipitation radar and that of ground-based
computed from the Zh-R theoretical formula is
MP radar for the rain on 31 October, 2010.
underestimated.
16

Laboratory of Environmental Biophysics
Water use strategy of a Bornean tropical rainforest as a function of annual rainfall
Although Bornean tropical rainforests are among the moistest biomes in the world, theysporadically experience periods of water stress. The observations indicate that these ecosystems tend tohave little regulation of water use, despite episodes of relatively severe drought (Fig. 1). This water-use
behavior is often referred to as anisohydric behavior, as opposed to isohydric plants that regulate
stomatal movement to prevent hydraulic failure. Although it is generally thought that anisohydric
behavior is an adaptation to more drought-prone habitats, we show that anisohydric plants may also be
more favored than isohydric plants under very moist environments where there is little risk of hydraulicfailure.
To explore this subject, we examined the advantages of isohydric and anisohydric species as a functionof the hydroclimatic environment using a stochastic model of soil moisture and carbon assimilation
dynamics parameterized by field observations. The results showed that under very moist conditions,anisohydric species tend to have higher productivity than isohydric plants, despite the fact that the twoplant types show almost the same drought-induced mortality. As precipitation decreases, the mortality ofanisohydric plants drastically increases while that of isohydric plants remains relatively constant andlow; in these conditions, isohydric plants surpass anisohydric plants in their productivity (Fig. 2).

A

0.3

0.5
0

3.0

‹An›a–‹An›is (m3/m3)

1.0

Nov-2008

Dec-2008

B(mol/m2day)

0.7

A

11/01/2008 11/02/2008 11/03/2008 11/04/2008 11/05/2008 11/06/2008

C

2.0

-0.1

B

0.6
0.6

0.2
0.2
00
500

12/03/2008 12/04/2008 12/05/2008 12/06/2008 12/07/2008 12/08/2008

1

0.4
0.4

1.0
0

0.9

1.0

0

0.8
0.8

ηa–ηi

Sap flow (g/s)

1.0

3.0

0.8

0.1

-0.2
11

2.0

0

0.2

10
3

1000

1500
1500

2000
2000

2500

3000

Θ (mm)
Fig. 1：(A) Nomalized soil moisture content under thethroughfall exclusion experiment (thick line) and normal(thin line) conditions., and sap flow rate of a
Dipterocarpaceae tree (B) before and (C) after theexperiment. Arrow means start of the experiment. There
was little change in sap flow between normal and severe
drought conditions.

17Fig. 2：Differences in mean assimilation rate 

i : B)( An a  An i : A) and tree death index ( abetween anisohydric and isohydric plants as functions ofannual total rainfall (Θ) for a given frequency of rainfall
events (λ = 0.54 day-1). Lines represent different valuesof parameters for gas exchange characteristics (A) andtolerance against drought (B), as indicated by numbers
alongside.

Drought-induced mortality of a Bornean tropical rainforest amplified by climate change
Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling inSoutheast Asian tropical rainforests, where severe droughts are projected to occur more frequently,
especially under El Niño conditions. We examine how the mortality of a Bornean tropical rainforest isaltered by projected shifts in rainfall, using field measurements, global climate model (GCM) simulation
outputs, and an index developed for drought-induced tree mortality (Tree Death Index η) associated witha stochastic ecohydrological model. All model parameters have clear physical meanings and wereobtained by field observations.
Rainfall statistics as primary model forcing terms are constructed from long-term rainfall records for thelate 20th century, and 14 GCM rainfall projections for the late 21st century. These statistics indicate that
there were sporadic severe droughts corresponding with El Niño events, generally occurring inJanuary–March, and that seasonality in rainfall will become more pronounced, e.g., dry (January–March)seasons becoming drier and wet (October–December) seasons becoming wetter. The computed η wellreflects high tree mortality under severe drought during the 1997–1998 El Niño event. For the present,
model results demonstrate high and low probabilities of mortality in January–March andOctober–December, respectively, and they predict that the difference in such probabilities will increase in
the future. Such high probability of mortality in the dry season is still significantly high, evenconsidering the beneficial effect of increased soil water storage in the wet season (which is projected toincrease in the late 21st century) (Fig. 3).

Observation
14 GCMs average
HADCM3

1968-2001
2080-2099

Observation in 1998

η’JFM

0.6

0.4

0.2

0
0

100

200

300

400

500

600

ΘJFM (mm)Fig. 3 ： Mean total Tree Death Index in January–March (  ' JFM ), considering effect of water storage in preceding
October–December (s0) as a function of total seasonal rainfall in January–March (ΘJFM). Also shown is  ' JFM , calculatedusing rainfall parameters obtained from observations under El Niño conditions in 1998. Upper part of the figure shows
mean ΘJFM and standard deviations in late 20th century (observations from 1968–2001) and late 21st century (projectionsfor 2080–2099 by the 14 GCM average and HADCM3).

18

Laboratory of Satellite Biological Oceanography
The susceptibility to photoinhibition of natural phytoplankton assemblages in thesubarctic and subtropical gyres in the western north PacificPhytoplankton undergo a large change in irradiance dueto the vertical transport by mixing (and turbulence) as well as
the diurnal insolation cycle. Therefore, cells have evolved avariety of functions to acclimate oneself to the changing lightfields, which resulted in taxonomic or inter-specificdifferences in the strategy for acquiring light energy. Such
differences affect the competitive dominance among species
under a given light condition. Species succession in nature is
the key for ocean biogeochemical cycling because it cancontrol a behavior of photosynthetically_produced materials
via their morphological and chemical properties. Here we
determined the physiological parameters on
Fig. 1：Sampling sites.
photoinhibition of natural assemblages in thesubarctic and subtropical gyres in the western northPacific to assess a regional difference in thelight-acquiring strategy of dominant cells.
Photoinhibition experiments were conducted
for phytoplankton in the surface waters of the station
K2 (47°N, 160°E) and the waters from the surface
and subsurface Chl maximal (SCM) layers of thestation S1 (30°N, 145°E) during Feb. to Mar.
(winter) and Jun. to Jul. (summer) in 2011 (Fig. 1).
In the experiments, cells were exposed to high-light
Fig. 2：Maximum photochemical quantum yields ofand the following low-light conditions, in which the
PSII (Fv/Fm) during the photoinhibition experiments
maximum photochemical quantum yields of PSII
for control (□) and lincomycin (absence of PSII repair:■) treatments. Gray shaded areas depict low-light(Fv/Fm) were monitored by using the fast repetition
conditions of ~20 umol photons m-2 s-1 for 210 min,rate fluorometer (FRRF). Each sample was split into
and white areas depict high-light exposure at 750
two bottles: one was supplemented with lincomycinumol photons m-2 s-1 for 90 min. The difference
to block chloroplast protein synthesis, thereby
between control and lincomycin treatments reflects
PSII repair rate constants.
inhibiting PSII repair. Measurements of both
treatments (with and without lincomycin) enable to estimate the susceptibility of PSII tophotoinactivation (σi, Å2 photon-1) and the PSII repair rate constants (RPSII, s-1).
Regardless of season both parameters (σi and RPSII) for cells in the surface waters exhibited higher
values in S1 relative to K2 (Fig. 3a). This means that the subtropical phytoplankton were more
susceptible to PSII photoinactivation while they recovered from high-light stress with more rapid PSII
repair. Conversely, cells with less susceptibility to pthotodamage of PSII but less restorative capacity
dominated in the subarctic conditions. This means that in K2 a lower-risk for pthotodamage would afford
a competitive advantage since cells were exposed to wide (or rapid) changes in irradiance by deep (oractive) mixing. Under ill-lit condition (~1% of the sea surface PAR) of the SCM layer of S1, dominant
cells showed a remarkably lower ability of PSII repair relative to cells in the surface waters. Such lessrestorative capacity of cells found in the surface waters of K2 and the SCM layer of S1 may be attributed
19

to a lower light availability. In actual,
after 2-days incubation under 25% or
3% of the surface PAR, cells in the
SCM layer enhanced PSII restorative
capacity in proportion to the light level(Fig. 3b). This implies that cells canacclimate to a light level by altering
PSII repair rate within 2 days after thegrowth irradiance changes. In otherwords, it is essential for cells to growthat their risk of PSII photoinactivation
is low enough to be compensated by thelight-depended PSII repair rate. Thenfurther understanding the mechanisms
controlling σi of cells is needed in order
to simulate the algal succession in theoceanic condition.

Fig. 3：(a) Effective target size for photoinactivation of PSII (σi: upper
panel) and PSII repair rate constants (RPSII: lower panel) for cells
collected in the stations K2 and S1.
(b) σi and RPSII for cells in the SCM layer of S1 after 2-days
incubations under two light levels (25% and 3% of the surface PAR).

Sinking processes of particulate matters in the center of the East China Sea
Large area of the East China Sea (ECS) occupied by a broad and shallow continental shelfsurrounded by Japan, China and Korea. The spatial distribution of water mass of the ECS, especiallyduring summer, is influenced by the discharge from the Changjiang. Accordingly, chemical andbiological properties in the upper waters show heterogeneous distributions, mainly due to inputs ofland-source and anthropogenic materials. The relatively high concentrations of satellite-derived
chlorophyll (Chl) have been found to coincide with the distributions of less-saline, Changjiang Diluted
Water (CDW; salinity <30 psu), which spreads eastward over the ECS during summer when the
discharge increases. And east-west gradients of surface Chl (decreases with distance from the estuary)
implies that nutrients derived by Changjiang are utilized by phytoplankton and gradually deplete. The
decrease needs the processes that remove nitrogen and phosphorus from the CDW, but these remain
unclear. Here, focusing on the sinking of particles as a removal process, we aim to assess the nitrogenbudget in the water-column of the ECS and its relation to the CDW by using data of sediment trap
experiments.
Two drifting sediment trap experiments were conducted in the ECS (around 31-32ºN, 125-126ºE)
during the cruises of the T/V Nagasaki Maru in July 2010 and 2011. The sinking particles were captured
at 10, 20, 30, 40m depths, and their mass and N contents were measured. During the experiments (3-5days), both physical (temperature and salinity) and biogeochemical (Chl and nutrients) parameters weremonitored in the study area by intensive CTD/water sampling casts. Concurrently, measurements of the
primary productivity (from 13C tracer bottle incubation), and sampling of suspended and sedimentary PN
were also conducted. Vertical diffusion coefficients were estimated from observations using Turbulence
Ocean Microstructures Acquisition Profiler (TurboMAP).
Figure 4a shows the nitrogen budget of the water column in the experimental area in 2010. The
CDW was found covering the upper layer of 10 m depth, in which the concentration of dissolved
inorganic nitrogen (DIN) was almost under the detection limit. Therefore, the productivity in the CDW
was mainly supported by regenerated nitrogen. While, the amount of suspended PN in this layer was
46.6mmol_N, and 5% (2.1 mmol_N) of the PN sank below the depth of 10 m. In the layer of 10 to 20 m,
there are pycnocline, nitracline, and subsurface Chl maximum (SCM; averaged Chl. conc.: 15 mg m-3).
20

The upward flux of DIN by vertical diffusion at 20 m depth was estimated to be ~0.7 mmol_N m-2 d-1,
which corresponded to the magnitude of the sinking flux of PN from this layer (0.7 mmol_N m-2 d-1).
These results suggest that the diffusive DIN supply from below explained 15 % of nitrogen sources
needed for productivity within the SCM layer (i.e. 85 % was supported by regenerated nitrogen). The
ratio of PN flux at the 40 m (4.2 mmol_N m-2 d-1) to the euphotic zone-integrated productivity (15.6mmol_N m-2 d-1) was 0.27, and a half was derived from the CDW.
In 2011, salinity of the upper water was relatively high, indicating less impact of Changjiang riverwater (figure 4b). Pycnocline, nitracline and SCM (averaged Chl. conc.: 2 mg m-3) appeared at therelatively deeper layer (20 to 30 m). Correspondingly, magnitudes of productivity and sinking flux were
one-third of those in the previous year. Through the base of nitracline around 30 m depth, both fluxes of
DIN diffusion and PN sinking seemed to be balanced (= ~0.5 mmol_N m-2 d-1), and this DIN diffusion
supported 33% of the SCM productivity. Those results implied that a relative importance of new andregenerated nutrients for productivity of SCM layers would vary depending on the presence or absenceof CDW.

Fig. 4：Nitrogen budget in the water column per unit area, and per day in trap experimental region in the East China
Sea. Black, white and gray arrows show PN fluxes （mmolN m-2 d-1 ）, DIN fluxes （mmolN m-2 d-1 ） and
depth-integrated primary productivity in each layer （mmolN d-1）, respectively. Boxes with solid line and break line
mean the suspended PN and dissolved organic nitrogen (DON) pools and the DIN pools. (a) 2010 and (b) 2011.

Inter-annual variation of giant jellyfish abundance and satellite observed phytoplankton
bloom in the Yellow and East China Seas
Since 2002, massive appearances of Nemopilema nomurai were reported in northern East China Sea,
Yellow Sea and the Sea of Japan almost every year, except 2008, 2010 and 2011. Source area of thelarvae of jellyfish (ephyrae) was still unknown because the attached stages (polyp) of the jellyfish were
never discovered in the field. Causes of jellyfish bloom were also not intensively explored, and it isrequired to study with environmental factors. Recently, new satellite datasets suring 1997 and 2010 withless influence of turbidity in the Yellow and East China Seas (Fig. 5, YECS) were produced from satellite
ocean color sensors, SeaWiFS and MODIS/Aqua. Satellite derived time series of sea surface
chlorophyll-a concentration (SSC), can be used as a proxy for phytoplankton biomass, and the data canbe used to study the inter-annual variability. Phytoplankton blooms should stimulate the production of21

zooplankton which, in turn, provides forage for larval jellyfish. Inter-annual variations of jellyfish
abundance with the relation of these environmental variables were analyzed here based on thematch/mismatch hypothesis.
Timing of phytoplankton bloom was derived fitting by Gaussian function;.
Chl(t) was SSC concentration, Bs was baseline slope, Bi was baseline intercept, a was peakconcentration, tp is peak time, tp -2 and tp +2 were defined as initiation and termination times of thebloom. Timing of phytoplankton blooms were compared with time of sea surface temperature (SST)
become 15oC which is the temperature expected for separation of ephyrae from polyp.
At the mouth of Changjiang River (CRM), high SSC was observed during summer when SST became
15oC (Fig. 6). This is expected the influence of Changjiang River discharge. At the middle of Yellow
Sea (YSM), spring bloom was observed March 20 - May 16, and it was before SST became 15oC. At
Korean side of Yellow Sea (YSK), spring bloom was observed mostly March 20 - June 9, and SST
became 15oC when bloom ended. At offshore of Changjiang River (CRO), spring bloom was observed
mostly March 20 - June 1, and SST became 15oC during the bloom. Sporadic high SSC was observed
after the spring bloom, and it was expected to be the influence of Changjiang Diluted Water. At China
side of Yellow Sea (YSC), high (>1.5 mg m-3) and low (< 1 mg m-3) SSC occurred in winter and summer,
respectively. SST became 15oC when the SSC became the minimum.
If SSC concentration can be used as an indicator of food for giant jellyfish ephyrae, CRM was mostfavorable condition for both timing and abundance.
YSC and CRO may have been also goodcondition because of the sporadic higher SSC concentration but not as high as CRM. YSM and YSKshould not be good condition because of the mis-match of spring bloom resulted low SSC concentration.
In all the areas, gradual increase of SSC was observed and indicating possible eutrophication of the areas,
and, in this sense, food conditions for jellyfish may be becoming better. This may be one of reasons
jellyfish bloom often occurred from 2002. SST was colder, timing to be 15oC was late in 2008, 2010
and 2011 than other years, and it may result no jellyfish bloom. However, the time difference of SST to
be 15oC was not as large as variation of phytoplankton bloom timing. Thus, the hypothesis ofmatch/mis-match of the phytoplankton bloom and ephylae may not explain the condition of recent
non-jelly fish years.

Fig.5：Observation areas in the Yellow and East China Seas.
Fig.6：SSC variations of weekly satellite data (left) and derived
spring bloom timing (shaded area of right) in 1998-2010. Thickolines indicate time when SST became 15 C.

22

Loboratory of Bio-Physical Oceanography
Trajectory of giant jellyfish by satellite altimetry data.
Giant jellyfish blooming in the Japan Sea has damaged tofishery industry in recent years. The giant jellyfishes appear in(
the East China Sea and are transported to the Japan Sea by thecurrent such as the Tsushima Warm Current. In the present study,
we examined the possibility of trajectory of the giant jellyfish
using satellite altimetry data. The particles regarded as giant
jellyfish were tracked by Euler-Lagrange method. Initialcondition of the calculation is applied from the distribution ofvisual observation result. Sea surface currents were derived every
7 days from sea surface current anomaly evaluated from satellite
altimetry, climatological sea surface current calculated from anumerical model, and wind driven current estimated from sea
surface wind data. The trajectory experiment was carried out thecase in 2009, giant jellyfish blooming occurred and visualobservations were conducted many times.
40 passive traces were set around Changjiang River mouth
where giant jellyfish were observed on 10 June 2009 (Fig 1a) andwere added every 72 minutes for 12 hours, and then 400 traces
were tracked. The tracers deployed on 10 June were transported
to the northeastward, and almost tracers distributed east of Cheju
Island on 23 June (Fig. 1b). Since enormous giant jellyfishes
were observed by visual observation, the result of tracer
experiment was consistent with observation. Many of the tracers
went through the Cheju Strait and then arrived in the western
channel of the Tsushima Strait on 4 July. Giant jellyfishes wereobserved in the western channel of the Tsushima Strait on thesame day by visual observation. It is suggested that giant
jellyfishes observed in the Tsushima Strait on 4 July come from
Changjiang River mouth taking about 1 month.
According to visual observation on 20 June, enormous giant
jellyfishes distributed in the central part of the Yellow Sea. In
order to investigate where the giant jellyfish were transported,
tracer experiment was conducted. Almost tracers weretransported to the northeastward and reach the west coast of Fig.1：Tracers distribution on (a) 10
June 2009 (b) 23 June 2009 (c) 4 July
Korea. This result suggests that giant jellyfish in the central part2009.
of the Yellow Sea were not transported to the Japan Sea.
Since visual observations were conducted only along ferryboat tracks, we carried out tracer experimentassuming the giant jellyfish distributed south of the ferry boat tracks. As a result, the tracers located southof 33°N were only transported to the Tsushima Strait.
23

Fig. 2：Tracer experiment result for the case, which giant jellyfish distribute in the central part of the Yellow Sea.

Interannual variation of the Tsushima Warm Current paths in the southwestern part of
the Japan Sea
In order to examine the Tsushima Warm Current(TWC) paths, we created sea surface dynamical height(SSDH) and current field information data using Argos
buoy trajectory and satellite altimetry data from May 1995
to October 2010. This data set has higher spatial-temporal
resolution than that of ship observed data. We recognizedthat the TWC paths have not only seasonal variation but
also interannual variation in the southwestern Japan Sea(SWJS).
To investigate the interannual variation in the TWC
paths, the SSDH data were applied 13 months runningmean filter. Empirical orthogonal function (EOF) analysis
was applied to the low-pass filtered SSDH data to extract
predominant mode. The first EOF mode indicated variationof the TWC paths along the east coast of Korea (Fig.1).
Since previous study suggested that the interannual
variation in the TWC paths is synchronized with that ofwinter weather around Japan (Naganuma, 1985), we
focused on the east Asian winter Monsoon Index (MOI)
which indicates blowing of cold air into the Japan Sea. Theinterannual variation of MOI was created by applying threeyear running mean to remove shorter temporal variation(Fig. 2).
A cold-water upwelling occurs near the east coast of Korea
in summer. Yun et al.(2004) reported that this cold-wateroriginates from a water imposed cooling at thenorthwestern Japan Sea. Thus, we compared between
latent/sensible heat flux in the northwestern Japan Sea and
MOI, and correlation was significant. The correlation
coefficient between temporal variation of the EOF firstmode in summertime (June to August) and MOI was 0.66
which was more than 99% significant level (Fig.2). When
MOI was low (1998) or high (2005), the TWC paths along
the east coast of Korea taken different path. The results
suggested that the TWC path along the east coast of Korea
was varied with intensity of winter cooling.
24

Fig. 1：First EOF mode of the SSDH variability
over the SWJS:(a) spatial structure of first EOF,(b) temporal variation of first EOF.
(Unit: m)

Fig. 2：Normalized time series of summer timemean of temporal variation of first EOF (solidline) and MOI (broken line)List of Publications*:Staffs, students and research fellows in the HyARC.
1.

Fujinami, H.*, D. Hatsuzuka, T. Yasunari*, T. Hayashi, T. Terao, F. Murata, M. Kiguchi, Y. Yamane, J.
Matsumoto, M. N. Islam and A. Habib
Characteristic intraseasonal oscillation of rainfall and its effect on interannual variability overBangladesh during boreal summer. International Journal of Climatology, 31(8), 1192-1204,
doi:10.1002/joc.2146, 2011.

2.

Kim, H.-J., K. Takata, B. Wang, M. Watanabe, M. Kimoto, T. Yokohata and T. Yasunari*Global monsoon, El Niño, and their interannual linkage simulated by MIROC5 and the CMIP3 CGCMs.
Journal of Climate, 24(21), 5604-5618, doi:10.1175/2011JCLI4132.1, 2011.

3.

Kobayashi, N.* and T. Hiyama
Stability Dependence of Canopy Flows over a Flat Larch Forest. Boundary-Layer Meteorology, 139(1),97-120, doi:10.1007/s10546-010-9572-2, 2011.

4.

Kume, T., N. Tanaka, K. Kuraji, H. Komatsu, N. Yoshifuji, T. M. Saitoh, M. Suzuki and T. Kumagai*
Ten-year evapotranspiration estimates in a Bornean tropical rainforest. Agricultural and Forest
Meteorology, 151(9), 1183-1192, doi:10.1016/j.agrformet.2011.04.005, 2011.

5.

Masunaga, H.* and T. S. L' Ecuyer
Equatorial asymmetry of the east Pacific ITCZ : observational constraints on the underlying processes.
Journal of Climate, 24(6), 1784-1800, doi:10.1175/ 2010JCLI3854.1, 2011.

6.

Miyazawa, Y., M. Tateishi, H. Komatsu, T. Kumagai* and K. Otsuki
Are measurements from excised leaves suitable for modeling diurnal patterns of gas exchange of intact
leaves? Hydrological Processes, 25(18), 2924-2930, doi:10.1002/hyp.8107, 2011.

7.

Oka, E., T. Suga, C. Sukigara*, K. Toyama, K. Shimada and J. Yoshida“Eddy Resolving” observation of the North Pacific Subtropical Mode Water. Journal of Physical
Oceanography, 41(4), 666-681, doi:10.1175/2011JPO4501.1, 2011.

8.

Oue, M.*, H. Uyeda* and D.-I. Lee
Raindrop size distribution parameters estimated from polarimetric radar variables in convective cells
around Okinawa Island during the Baiu period. Asia-Pacific Journal of Atmospheric Sciences, 47(1),33-44, doi:10.1007/s13143-011-1003-x, 2011.

9.

Saba, V. S., M. A. M. Friedrichs, D. Antoine, R. A. Armstrong, I. Asanuma, M. J. Behrenfeld, A. M.
Ciotti, M. Dowell, N. Hoepffner, K. J. W. Hyde, J. Ishizaka*, T. Kameda, J. Marra, F. Mélin, A. Morel, J.
O'Reilly, M. Scardi, W. O. Smith Jr., T. J. Smyth, S. Tang, J. Uitz, K. Waters and T. K. Westberry
An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic
regions across the globe. Biogeosciences, 8(2), 489-503, doi:10.5194/ bg-8-489-2011, 2011.

10. Shiozaki, T., K. Furuya, H. Kurotori, T. Kodama, S. Takeda, T. Endoh, Y. Yoshikawa, J. Ishizaka* and T.
MatsunoImbalance between vertical nitrate flux and nitrate assimilation on a continental shelf : Implications of
nitrification. Journal of Geophysical Research, 116, C10031, doi:10.1029/2010JC006934, 2011.
11. Siswanto, E., J. Tang, H. Yamaguchi, Y.-H. Ahn, J. Ishizaka*, S. Yoo, S.-W. Kim, Y. Kiyomoto, K.
Yamada, C. Chiang and H. Kawamura
Empirical ocean-color algorithms to retrieve chlorophyll-a, total suspended matter, and colored dissolved
organic matter absorption coefficient in the Yellow and East China
Seas. Journal of Oceanography, 67(5), 627-650, doi:10.1007/s10872-011-0062-z, 2011.

25

12. Son, Y. B., J. Ishizaka*, J.-C. Jeong, H.-C. Kim and T. Lee
Cochlodinium polykrikoides red tide detection in the South Sea of Korea using spectral classification of
MODIS data. Ocean Science Journal, 46(4), 239-263, doi:10.1007/ s12601-011-0019-6, 2011.
13. Takikawa, T., G. Onitsuka, K. Fukudome, J.-H. Yoon, A. Morimoto*, M. Moku and A. Watanabe
Spatial and temporal variation of a cyclonic eddy detected downstream of the Tsushima Islands inNovember 2007. Estuaries and Coasts, 34(4), 775-784, doi:10.1007/s12237-011-9395-5, 2011.
14. Venkatraman, P.* and T. Yasunari*
Simulated changes in the atmospheric water balance over South Asia in the eight IPCC AR4 coupledclimate models. Theoretical and Applied Climatology, 104(1-2), 139-158, doi:10.1007/s00704-010-0331-6,
2011.
15. Xu, J., K. Masuda, Y. Ishigooka, T. Kuwagata, S. Haginoya, T. Hayasaka and T. Yasunari*
Estimation and verification of daily surface shortwave flux over China. Journal of the MeteorologicalSociety of Japan, 89A, 225-238, doi:10.2151/jmsj.2011-A14, 2011.
16. Xue, B.-L., T. Kumagai*, S. Iida, T. Nakai, K. Matsumoto, H. Komatsu, K. Otsuki and T. Ohta
Influences of canopy structure and physiological traits on flux partitioning between understory andoverstory in an eastern Siberian boreal larch forest. Ecological Modelling, 222(8), 1479-1490,
doi:10.1016/j.ecolmodel.2011.01.021, 2011.
17. Yamamoto, M., T. Ohigashi*, K. Tsuboki* and N. Hirose
Cloud-resolving simulation of heavy snowfalls in Japan for late December 2005 : application of ocean
data assimilation to a snow disaster. Natural Hazards and Earth System Sciences, 11, 2555-2565,
doi:10.5194/nhess-11-2555-2011, 2011.
18. Yamamoto, M. K. and K. Nakamura*
Typical patterns of microwave signatures and vertical profiles of precipitation in the midlatitudes from
TRMM data. Journal of Applied Meteorology and Climatology, 50(6), 1236-1254, doi:10.1175/2010
JAMC2539.1, 2011.
19. Yamamoto, M. K., K. Ueno and K. Nakamura*Comparison of satellite precipitation products with rain gauge data for the Khumb region, Nepal
Himalayas. Journal of the Meteorological Society of Japan, 89(6), 597-610, doi:10.2151/jmsj.2011-601,
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20. Yamashima, R., K. Takata, J. Matsumoto and T. Yasunari*
Numerical study of the impacts of land use/cover changes between 1700 and 1850 on the seasonalhydroclimate in monsoon Asia. Journal of the Meteorological Society of Japan, 89A, 291-298,
doi:10.2151/jmsj.2011-A19, 2011.
21. Yasunari, T. J., A. Stohl, R. S. Hayano, J. F. Burkhart, S. Eckhardt and T. Yasunari*Cesium-137 deposition and contamination of Japanese soils due to the Fukushima nuclear accident.
Proceedings of the National Academy of Sciences, 108(49), 19530-19534, doi:10.1073/pnas.1112058108,
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22. Zhang, N., T. Yasunari* and T. Ohta
Dynamics of the larch taiga-permafrost coupled system in Siberia under climate change. Environmental
Research Letters, 6(2), doi:10.1088/1748-9326/6/2/024003, 2011.

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Hydrospheric Atmospheric Research Center (HyARC)
Nagoya University

Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan

Office:Telephone: +81-52-789-3466
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The 2011 Annual Report was published July 2012 by
the Hydrospheric Atmospheric Research Center (HyARC)
Nagoya University.