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Global

Brief Description and Validation Report March 9, 2020 (ver. 2.3)

Today’s Earth Developing Group

TABLE OF CONTENTS

1. What is “Today’s Earth - Global”? .................................................................................... 1

2. Target of TE-Global ........................................................................................................... 1

3. Outline of TE-Global system ............................................................................................. 1

4. Variable list of TE-Global .................................................................................................. 4

5. Validation results ............................................................................................................... 6

i. Snow Depth ....................................................................................................................... 6

ii. Soil Moisture...................................................................................................................... 7

iii. River Discharge ................................................................................................................. 9

6. Summary of the validation .............................................................................................. 13

7. Terms of use .................................................................................................................... 14

i. Site Policy ....................................................................................................................... 14

ii. User Registration ............................................................................................................. 14

iii. Deletion of User Registration ........................................................................................... 14

iv. Protection of Personal Information & Handling of Personal Information ........................... 14

v. Management of account and password ........................................................................... 14

vi. Ownership of Data etc. .................................................................................................... 14

vii. Deletion of user registration ............................................................................................. 15

viii. Change of the Service ..................................................................................................... 15

ix. Termination of the Service ............................................................................................... 15

x. How to cite ...................................................................................................................... 15

xi. Disclaimer ....................................................................................................................... 15

xii. Contact Information ......................................................................................................... 15

8. Member list of TE developing group .............................................................................. 16

9. References ....................................................................................................................... 17

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1. What is “Today’s Earth - Global”?

“Today’s Earth” (hereafter called “TE”) is JAXA's simulation system of land surface, river

discharge and flood area fraction etc. Various products relating to the conditions of land

surface and river are obtained as the results of numerical land surface model and river model.

“Today’s Earth - Global” (hereafter called “TE-Global”) enables us to access those products

globally. The meteorological forcing data to drive these models are based on the reanalysis

dataset, JRA-55. To provide the products with better accuracy, the TE developer group is now

utilizing satellite derived data; rainfall from the Global Satellite Mapping of Precipitation

(GSMaP) is used for TE-Global GSMaP version, and solar radiation from Aqua and Terra

MODIS provided by the JASMES system is used for TE-Global MODIS version.

The TE developer group consists of the researchers in Japan Aerospace Exploration

Agency (JAXA) Earth Observation Research Center (EORC), The University of Tokyo (UT),

and Remote Sensing Technology Center of Japan (RESTEC). Detailed member list is attached

at the end of this document.

2. Target of TE-Global

TE-Global system aims to produce and evaluate global long-term land water cycle dataset

that is helpful for calculating risk indices of water hazards, particularly floods. This activity is

designed to broadly contribute the society as a part of the climate services.

3. Outline of TE-Global system

The TE system consists of land surface model MATSIRO[1] (Minimal Advanced Treatments

of Surface Interaction and Runoff) version5[2] and river routing model CaMa-Flood[3]

(Catchment-based Macro-scale Floodplain).

By giving forcing of surface meteorological parameters, MATSIRO simulates the water and

energy interactions between a land surface with a vegetation canopy and atmosphere. The

surface runoff and baseflow were calculated independently using Horton flow and the

advanced application in TOPMODEL[4], respectively. Based on the calculated runoff amount,

CaMa-Flood enables hydrodynamic simulation with floodplain on a global scale. The model

solves the local inertial equation[5], considering a rectangular river channel and trapezium flood

plain storage, and represents flood plain dynamics assuming that the elevation profile of the

floodplain monotonically increases in each pixel. Severity index of each variables in the form of

return period or Mahalanobis distance are also visualized.

Table 1 and 2 describe the basic information of TE-Global 3 versions. Figure 1 shows the

schematic procedure of TE-Global system.

2

Table 1. TE-Global components

Land Surface Model

MATSIRO[1][2] (Minimal Advanced Treatments of Surface Interaction and Runoff)

Horizontal resolution

1/2° south west lat. = -90° south west lon. = 0° [Nx, Ny]=[720, 360]

Temporal resolution

output every 3 hours starting from UTC+0 each day.

River Routing Model

CaMa-Flood[3] (Catchment-based Macro-scale Floodplain)

Horizontal resolution

1/4° south west lat. = -90° south west lon. = 0° [Nx, Ny]=[1440, 720]

Temporal resolution

output every 3 hours starting from UTC+0 each day.

Table 2. Version information of TE-Global

Name JRA-55 ver. GSMaP ver. MODIS ver.

Period 1958-present 2001-present 2003-present

Forcing

Data*1

rainfall J G(J)*3 J

snowfall J J J

eastward wind J J J

northward wind J J J

surface air temperature J J J

specific humidity J J J

surface shortwave radiation

(downward)

J J M

surface longwave radiation

(downward)

J J J

surface air pressure J J J

Data distribution Latency*2 About 3.5 days About 5 days About 20 days

1. J: JRA-55 reanalysis[6], G: GSMaP MVK V03[7], M: MODIS V811 2. These are determined by the timing of data availability of JRA-55, GSMaP, and MODIS,

respectively. 3. Since GSMaP provides rainfall rate of 60N-60S region, JRA-55 rainfall is utilized in higher

latitude area. For spatial continuity with GSMaP, JRA-55 rainfall less than 0.01mm/h are eliminated for this experiment.

3

Figure 1. Schematic figure of TE-Global system.

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4. Variable list of TE-Global

All variables distributed from TE-Global are summarized in Table 3. The column of Fig describes whether figures are available or not through the monitor page.

Table 3. Hydrological variables distributed in the TE-Global

Model/Category Variable Name Item Name Unit

(netCDF) Fig

Forcing

Rainfall GPRCT kg/m2/s ○

Snowfall GSNWL kg/m2/s ○

eastward wind GDU m/s -

northward wind GDV m/s -

surface air temperature GDT K ○

specific humidity GDQ kg/kg 〇

surface shortwave radiation (downward) SSRD W/m2 ○

surface longwave radiation (downward) SLRD W/m2 -

surface air pressure GDPS hPa -

MATSIRO

Water balance (State)

soil moisture (at each level) [Z1-Z6]*1 GLW m/m ○

soil moisture (total volume) GLWtot kg/m2 ○

canopy water GLWC m -

snow amount GLSNW kg/m2 ○

Water balance (Flux)

snow melt SNMLT kg/m2/s -

snow freeze SNFRZ kg/m2/s -

snow sublimation SNSUB kg/m2/s -

ice melt ICEMLT kg/m2/s -

ice sublimation ICESUB kg/m2/s -

snow & ice sublimation SSUB kg/m2/s -

transpiration ETFLX kg/m2/s ○

canopy evaporation EIFLX kg/m2/s ○

canopy sublimation EISUB kg/m2/s -

soil evaporation EBFLX kg/m2/s ○

soil sublimation EBSUB kg/m2/s -

total runoff (total) [W1-W2]*4 RUNOFF kg/m2/s ○

base runoff RUNOFFB kg/m2/s ○

surface runoff SRUNOF kg/m2/s ○

runoff (lake & land) [W1-W2]*4 RUNOFFA kg/m2/s -

Heat balance (State)

soil temperature [Z1-Z6]*1 GLG K ○

snow temperature [L1-L3]*2 GLTSN K ○

land skin temperature [C1-C2]*3 GLTS K ○

canopy temperature [C1-C2]*3 GLTC K ○

Heat balance (Flux)

soil heat flux GFLUXS W/m2 ○

snow surface heat flux SNFLXS W/m2 ○

ground heat flux in total GFLXTL W/m2 -

surface shortwave radiation (upward) SSRU W/m2 -

surface longwave radiation (upward) SLRU W/m2 -

sensible heat flux SENS W/m2 ○

latent heat flux LTNT W/m2 ○

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latent heat flux (evaporation) EVAP W/m2 -

River

river flow [W1-W2]*4 RFLOW m3/s -

river water [W1-W2]*4 GDRIV kg/m2 -

river storage [W1-W2]*4 GDRIVL kg/m2 -

Others

snow covered fraction SNRAT - ○

albedo ALB - - snow albedo [A1-A3]*5 GLASN - -

soil potential [Z1-Z6]*1 GPSI Pa -

dust density in snow [L1-L3]*2 CDSTM ppmw -

water flux atmosphere to land WA2L m/s -

water flux land to river WL2R m/s -

soil ice (at each level) [Z1-Z6]*1 GLFRS m/m ○

soil ice (total volume) GLFRStot kg/m2 ○

land water WLND m -

inland water sinkbudget BUDIND kg/m2/s -

distributed water sinkbudget RBUDIND kg/m2/s -

ground water input WINPT kg/m2/s -

lake sh SHLK cm -

lake surface temperature TSIL °C -

CaMa-Flood

river discharge RIVOUT m3/s -

river water storage RIVSTO m3 -

river water depth RIVDPH m ○

river flow velocity RIVVEL m/s -

floodplain flow (discharge) FLDOUT m3/s -

floodplain water storage FLDSTO m3 -

floodplain water depth FLDDPH m ○

flood area FLDARE m2 -

flood fraction FLDFRC - ○

water surface elevation SFCELV m -

total discharge (RIVOUT + FLDOUT) OUTFLW m3/s ○

total storage (RIVSTO + FLDSTO) STORGE m3 - 1. Z1-Z6 represents the soil layers, the depth (m) of which is Z1: 0 - 0.05, Z2: 0.05 - 0.25, Z3: 0.25 -

1, Z4: 1 - 2, Z5: 2 - 4, and Z6: 4 - 14. 2. L1-L3 represents the snow layers. The number of the effective layers and their depth are variable.

See Takata et al. (2003) for more details. 3. C1 and C2 represent the outputs for snow-free canopy and snow-covered canopy, respectively. 4. W1 and W2 represent the values regarding water and ice, respectively. 5. A1, A2 and A3 represent the snow albedo of visible, near-infrared and infrared area, respectively.

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5. Validation results

In order to verify the performance of the TE-Global products, we had validations for 3 variables: snow depth and soil moisture from MATSIRO, and river discharge from CaMa-Flood. For each variable, we compared the results of TE-Global and observation data and made some statistical comparison between them.

i. Snow Depth

First, we investigated the general characteristics of the results of snow depth. Figure 2 is a scatter density diagram showing the relation between TE-Global results (y-axis) and in-situ observation data from WMO Global Summary of Day (x-axis). The validation period is 2012/7/23 – 2016/10/31.

Although every 3 versions of TE-Global shows positive correlation with the observation, usage of satellite data (GSMaP and MODIS) does not necessarily improve the accuracy of snow depth results. Note that GSMaP precipitation is not used for high latitude area (higher

than 60°S and 60°N) where most of the validation points are located.

Figure 2. Scatter diagram for the relation between snow depth of TE-Global results and in-situ observation. Colors in each point show the number of samples included. The results from (a) JRA-55 version, (b) MODIS version, and (c) GSMaP version are shown. The information of accuracy of the TE-Global products are written in the bottom of each sub-figure with abbreviations: Num for the number of samples, R for correlation coefficient, RMSE for root mean square error, and MAE for mean absolute error.

Next, we show time series of snow depth in the location (69.58N, 23.53E) in winter of 2012-2013 (Fig. 3). The values of snow depth of the TE-Global JRA-55 version (black line) agree well with those for in-situ observation (black dots).

(a) (b) (c)

TE-Global JRA-55 ver. snow depth [cm]

TE-Global MODIS ver. snow depth [cm]

TE-Global GSMaP ver. snow depth [cm]

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Figure 3. Time series of snow depth at (69.58N 23.53E). The red (JRA-55), blue (GSMaP), and green (MODIS) lines represent the TE-Global results of snow depth, and black dots show in-situ observation. Precipitation data from the JRA-55 are shown by the light blue bars for daily snowfall and the blue bars for daily rainfall (accumulated to snowfall).

ii. Soil Moisture The validation of soil moisture is performed using four sites in-situ observation data. The observation site information is shown in Table 4.

Table 4. Information of observation sites for soil moisture validation.

Name Evaluation period The number of observation site and each code-name

Thailand 2012/7/2 - 2012/10/31 3 sites KKS1, KKS2, KKS3

Mongolia 2012/7/2 - 2015/8/31 6 sites ASSH811, 813, 815, 818, 820, 821

Australia 2012/7/2 - 2016/1/31 2 sites T1, Y10

Little River 2012/7/2 - 2016/10/31 1 site 2027

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Similarly as the results of snow depth, scatter density diagram to show the correlation between TE-Global results and in-situ observation for soil moisture at all observation sites in Table 4 is shown in Fig. 4. For the reference of the TE-Global performance, comparison of AMSR-2 retrieval results are shown in Fig. 4(a). The correlation coefficient of TE-Global results with in-situ observation are smaller than that of the AMSR-2 results, and the soil moisture in the TE-Global tends to be higher than the observation. The improvement of the positive bias is a challenge for the future.

Figure 4. The scatter density between (a) AMSR-2 retrieval results, (b) TE-Global GSMaP ver., (c) JRA-55 ver., and (d) MODIS ver. (x-axis) and in-situ observation (x-axis). The abbreviation in the figure is the same as the Figure 2.

The results of soil moisture in one observation site is investigated. Figure 5 represents the time series of soil moisture in Australia (34.5S 146.5E – T1 site), where black dots are In-situ observation, red, blue and green lines are TE-Global JRA-55 ver., GSMaP ver. and MODIS ver. results respectively, and blue bar shows daily rainfall of JRA-55. The first peak at the beginning of Nov. 2012, which is thought to be caused by heavy precipitation, is well reproduced, but the second and third ones around Nov. 15th and 27th, respectively do not appear clearly in the observation. This may be due to the spurious occurrence of precipitation and/or the overestimation of actual precipitation in the TE-Global system partly due to spatial coarseness of the model.

(a)

(d) (c)

(b)

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Figure 5. The time series of soil moisture at Australia observation site T1 (34.5S 146.5E). The TE-Global result is shown by red (JRA-55 ver.), blue (GSMaP ver.), and green (MODIS ver.) lines, while the observation is by black dots. The rainfall data used in the TE-Global JRA-55 ver. is represented by blue bars from upside down.

iii. River Discharge Hereafter, we show validation results of CaMa-Flood. Figure 6 shows the correlation coefficient of time series of daily river discharge in each observation point. The value of correlation coefficient is calculated between the observational discharge and the TE-Global discharge results at the nearest grid-point of the observation site. The observation data is obtained from The Global Runoff Data Centre (GRDC), and the validation period is selected to be the common period among the JRA-55, GSMaP, and MODIS versions, i.e., from 2003 to 2016. Although the observation sites with high and low performances are distributed in all regions, we can see the deviation of the distribution such as, high correlation (performance) results in the high-latitude regions (Russian and Canadian regions) and Amazon River area and low correlation

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results in the central area of North America and in Australia. Comparing the 3 versions of the TE-Global, the MODIS results show better performance than the JRA-55 version, while the GSMaP results deteriorate.

Figure 6. The results of validation for daily river discharge. The circles show the site of Global Runoff Data Centre (GRDC) observation data obtained from 2003 to 2016, the color of which represents correlation coefficient between the observation and the results of (a) JRA-55, (b) MODIS, and (c) GSMaP versions of the TE-Global. Mean correlation coefficients are 0.519 for JRA-55, 0.536 for MODIS, and 0494 for GSMaP.

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Inter-annually (2003-2016) and monthly-mean river discharge is investigated for 4 river sites: Amazon, Lena, Amur, and Mackenzie, of which results are relatively accurate. Figure 7 shows comparison results of the three versions of TE-Global and the GRDC observation data. Although there is still room for improvement in terms of the absolute value of river discharge, main characteristics of the seasonal variability are reproduced well by all 3 versions of TE-Global. The GSMaP version tends to yield larger discharge comparing to the other 2 versions. Next, the reproducibility of inter-annual variability is examined. As an example, the discharge at ChaoPhraya River is shown in detail. Figure 8 is the long-term time series of monthly-mean river discharge at 3 observation sites of Chao Phraya River: (a) Bhumibol Dam (17.24N 98.97E), (b) Sirikit Dam (17.76N 100.56E), and (c) Nakhon Sawan (15.67N 100.12E). Temporal variation of river discharge at the 3 sites are well reproduced though the absolute values from JRA-55 and MODIS versions tend to overestimate the observation. The usage of satellite-derived precipitation i.e., GSMaP version improve the overestimation at these sites.

Figure 7. The time series of Inter-annually (2003-2016) and monthly-mean river discharge at each observation site of (a) Amazon River, (b) Lena River, (c) Amur River, and (d) Mackenzie River. Black dashed lines represent the results of observation from GRDC, and blue, red, and green lines are the results of TE-Global products of JRA-55, GSMaP, and MODIS versions, respectively.

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Figure 8. Time series of monthly-mean river discharge at (a) Bhumibol Dam (17.24N 98.97E), (b) Sirikit Dam (17.76N 100.56E), and (c) Nakhon Sawan (15.67N 100.12E) of Chao Phraya River. The blue, green, and red lines show the discharge results of MODIS, GSMaP, and JRA-55 versions of TE-Global. The observation data are shown by black solid lines; black dotted line is the corrected river discharge from which the effect of the upstream dam is eliminated. The results of spatially-averaged precipitation over the whole Chao Phraya river basin are shown by cyan (JRA-55) and blue (GSMaP) lines from upside down.

(a)

(b)

(c)

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6. Summary of the validation

We showed the validation results of the TE-Global system, which simulates the global hydrological cycle on land areas using a reanalysis meteorological data and some satellite-derived observation data. Three variables: snow depth, soil moisture, and river discharge, were investigated to verify the performance of the system. Although the outputs of the TE-Global system are not perfect as well as the meteorological prediction used as the forcing data of our models, we continue to improve the TE-Global system by refining the models and boundary conditions, enhancing the resolution of the models, and using satellite-derived observation data effectively. Table 5 shows a summary regarding the performance of TE-Global system in terms of three validation variables: snow depth, soil moisture, and river discharge.

Table 5. Summary of the validation of TE-Global

Variable Ground

observation data

Correlation coefficient

Root mean square error

Bias Mean absolute error

Daily average of snow depth (m)

WMO Global Summary of Day (2012/7/23 – 2016/10/31)

0.658 (JRA-55) 0.658 (MODIS) 0.644 (GSMaP)

25.9 (JRA-55) 25.8 (MODIS) 27.2 (GSMaP)

9.93 (JRA-55) 10.0 (MODIS) 11.1 (GSMaP)

16.3 (JRA-55) 16.2 (MODIS) 17.2 (GSMaP)

Daily average of soil moisture (%)

In-situ observation data collected by JAXA

0.471 (JRA-55) 0.426 (MODIS) 0.494 (GSMaP)

14.9 (JRA-55) 15.9 (MODIS) 13.7 (GSMaP)

12.9 (JRA-55) 13.8 (MODIS) 12.1 (GSMaP)

13.0 (JRA-55) 14.0 (MODIS) 12.2 (GSMaP)

Daily average of river discharge*1 (m3/s)

The Global Runoff Data Centre (2003-2016)

0.519 (JRA-55) 0.536 (MODIS) 0.494 (GSMaP)

3780 (JRA-55) 3730 (MODIS) 6330 (GSMaP)

-589 (JRA-55) -200 (MODIS) 1570 (GSMaP)

3060 (JRA-55) 3000 (MODIS) 5160 (GSMaP)

1. For daily river discharge, correlation coefficient, root mean square error, bias, and mean absolute error are calculated for each observation site and averaged over the whole sites.

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7. Terms of use

This terms of use is the same as that shown in the TE-Global website https://www.eorc.jaxa.jp/water/term.html?1

Today's Earth - Global (hereinafter referred to as "the Service") provides the simulation data of MATSIRO and CaMa-Flood by the Japan Aerospace Exploration Agency (JAXA) Earth Observation Research Center (EORC) and Institute of Industrial Science, The University of Tokyo, in free of charge (only for research, education and public purposes).

Terms of Use of the Service are terms and conditions that users are expected to follow in the use of the Service. Please read the terms and conditions carefully and agree on them before the use of the Service.

i. Site Policy The site policy (http://global.jaxa.jp/policy.html) of the Japan Aerospace Exploration

Agency (hereinafter referred to as "JAXA") is applicable to the Service.

ii. User Registration User registration is required before the use of the Service because the Service adopts a

user authentication system based on a set of user account and password. The information for the registration is your name, e-mail address, organization, department, country/region, and purpose of data usage.

iii. Deletion of User Registration If you want to delete your user registration, please notify the Water Cycle & Water

Resource Management Research Group described in the follow links.

iv. Protection of Personal Information & Handling of Personal Information JAXA handles the personal information such as names and e-mail addresses in

accordance with JAXA's rules on protection of personal information. For details, please refer to "Privacy Policy" in the JAXA's site (http://global.jaxa.jp/policy.html).

JAXA doesn't use registered personal information except for the following purposes:

➢ Statistic and analysis of data use ➢ Questionnaire surveys to users for improvement of the Service ➢ Response to inquiries from users

In addition, JAXA employs other companies to perform functions on our behalf. The functions include the system management, user management, and the >Water Cycle & Water Resource Management Research Group operation. They may access to personal information to perform the functions, but may not use it for other purposes.

v. Management of account and password User account and password are managed and used under the responsibility of user. JAXA

is not responsible to you for any loss or damage or due to any other cause beyond the control of JAXA that may be caused by misuse of user account and password by another person.

vi. Ownership of Data etc. The copyrights of the standard products and other materials provided in the Service are the

property of JAXA. Please use them in compliance with the conditions stipulated in "Scope and Conditions for Use of the Contents of the Site" in the JAXA's site (http://global.jaxa.jp/policy.html).

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vii. Deletion of user registration JAXA reserves the right to delete your user registration if you have not complied with the

Terms of Use or are an inappropriate user of the Service.

viii. Change of the Service JAXA may change the Term of Use, service contents and conditions of the Service. JAXA

shall notify users of the change on "Information" of the Service. Please confirm the change when you use this service for the first time after the change.

ix. Termination of the Service JAXA reserves the right to terminate the Service by JAXA's own reasons. In that case,

JAXA shall notify users of the termination beforehand by proper means.

x. How to cite Please specify the following sentence when you publish a thesis, a report, and so on by

using the research products and images supplied by the Service.

"'Research product of Yesterday's Earth at EORC that was used in this paper was supplied by Japan Aerospace Exploration Agency and Institute of Industrial Science, The University of Tokyo."

The Water Cycle & Water Resource Management Research Group is collecting the related literature. It would be very appreciated if you could send a reprint or a copy of your research outcome to the Water Cycle & Water Resource Management Research Group.

xi. Disclaimer Please be aware in advance that: Although JAXA has taken every care to manage the Service, JAXA assumes no

responsibility regarding the safety of the contents of the Service or the reliability of information provided on the Service. JAXA is not responsible to you for any damage that may be caused by the use of the Service and/or the information on the Service.

JAXA may change or delete the information on the Service, or may suspend or terminate the operation of the Service. JAXA is not responsible to you for any inconvenience that may be caused by such changes or deletion of the information, or by such suspension or termination of the operation of the Service.

xii. Contact Information If there are any concerns or questions about the Service, please contact us at the following

links, https://www.eorc.jaxa.jp/water/contact_us.html or send an email to

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8. Member list of TE developing group

Latest member list is at https://www.eorc.jaxa.jp/water/contact_us.html

NAME ORGANIZATION ROLE DESCRIPTION

Current Members

R. Oki JAXA*1 ➢ Overall (management, collaboration with other “Water

Cycle and Water Resource Management” topics)

M. Kachi JAXA ➢ Operation of the TE systems ➢ Validation of land variables (snow depth, soil moisture) ➢ Collaboration with other EORC research groups

H. Fujii JAXA ➢ Operation of the TE systems

K. Yamamoto JAXA ➢ Operation of the TE systems ➢ Validation of river variables (runoff, flooding area)

T. Oki UT*2, JAXA ➢ Advisory (science & outcomes)

K. Yoshimura UT ➢ Overall (Principal investigator at UT)

H. Kim UT ➢ Advisory (science & outcomes)

D. Yamazaki UT ➢ Improvement of CaMa-Flood model

K. Hibino UT ➢ Development of Japan 1km-resolution TE ➢ Further improvement of TE ➢ Collaboration with other EORC research groups

W. Ma UT ➢ Development of Japan 1km-resolution TE ➢ Further improvement of TE ➢ Collaboration with other EORC research groups

Y. Ishitsuka UMass Amherst*3 ➢ Further improvement of TE

A. Takeshima UT ➢ Further improvement of TE

T. Higashiuwatoko RESTEC*4 ➢ Operation of the TE systems

T. Andoh RESTEC ➢ Operation of the TE systems

R. Kakuda RESTEC ➢ Operation of the TE systems

Previous Members

T. Nomaki RESTEC ➢ Operation of the TE systems ➢ Validation of land variables (snow depth, soil moisture)

N. Kawamoto RESTEC ➢ Operation of the TE systems ➢ Validation of land variables (snow depth, soil moisture)

T. Itaya UT ➢ Development of downscaling method

S. Urita RESTEC ➢ Operation of the TE systems ➢ Validation of land variables (snow depth, soil moisture)

M. Hatono UT ➢ Validation of river variables (discharge, flooding area)

Y. Yabu UT ➢ Development of Japan 1km-resolution TE

1. JAXA: Japan Aerospace Exploration Agency 2. UT: University of Tokyo 3. UMass Amherst: University of Massachusetts (Amherst) 4. RESTEC: Remote Sensing Technology Center of Japan

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9. References

1. Takata, K., S. Emori, and T. Watanabe, 2003: Development of the Minimal Advanced Treatments of Surface Interaction and RunOff (MATSIRO), Global and Planetary Change, 38, 209-222.

2. Nitta, T, K. Yoshimura, K. Takata, R. O’ishi, T. Sueyoshi, S. Kanae, T. Oki, A. Abe-Ouchi, and G. E. Liston, 2014: Representing variability in subgrid snow cover and snow depth in a global land model: Offline validation, J.Clim., 27, 3318–3330.

3. Yamazaki, D., S. Kanae, H. Kim, and T. Oki (2011), A physically based description of floodplain inundation dynamics in a global river routing model, Water Resour. Res., 47, W04501, doi:10.1029/2010WR009726.

4. Beven, K.J., M.J. Kirkby, N. Schofield, A.F. Tagg, 1984: Testing a physically-based flood forecasting model (TOPMODEL) for three U.K. catchments, J. Hydrol, Volume 69, Issues 1–4, Pages 119-143, ISSN 0022-1694, https://doi.org/10.1016/0022-1694(84)90159-8.

5. Bates, P.D., M.S. Horritt, and T.J. Fewtrell, 2010: A simple inertial formulation of the shallow

water equations for efficient two‐dimensional flood inundation modelling, J. Hydrol., 387, 33–

45, doi:10.1016/j.jhydrol.2010.03.027. 6. Kobayashi S, Ota Y, Harada Y, Ebita A, Moriya M, Onoda H, Onogi K, Kamahori H, Kobayashi

C, Endo H, Miyaoka K, Takahashi K. 2015. The JRA-55 reanalysis: general specifications and basic characteristics. Journal of the Meteorological Society of Japan 93: 5–48. DOI: 10.2151/jmsj.2015-001.

7. T. Kubota, S. Shige, H. Hashizume, K. Aonashi, N. Takahashi, S. Seto, M. Hirose, Y. N. Takayabu, K. Nakagawa, K. Iwanami, T. Ushio, M. Kachi, and K. Okamoto, 2007: Global Precipitation Map using Satelliteborne Microwave Radiometers by the GSMaP Project : Production and Validation, IEEE Trans. Geosci. Remote Sens., Vol. 45, No. 7, pp.2259-2275.