Satellite-based Land-Atmosphere Coupled Data Assimilation Toshio Koike Earth Observation Data Integration & Fusion Research Initiative (EDITORIA) Department Civil Engineering, Engineering School The University of Tokyo

OBS 1998 (2003 unavailable) NCEP JMA UKMO Seasonal variation （ May - September) Sensible （ H ）－ Latent(LE ）－ H RMSE [W/ ㎡ ] LE RMSE [W/ ㎡ ] LDASUT NCEP JMA UKMO LE daily-mean ( June) Observed Modeled GCMs

Land Surface Scheme Snow Physics Model Cloud Physics Model Soil Moisture Soil Moisture Snow Microwave Radiometer Microwave Radiometer Precipitation Surface Emissivity & Temp. Aqua TRMM Land-Atmosphere Data Assimilation Land-Atmosphere Data Assimilation

Land Surface Scheme Satellite Data Minimization Scheme Radiative Transfer Model Cost Function LDAS GCM Forcing

OBS 1998 (2003 unavailable) NCEP JMA UKMO Seasonal variation （ May - September) Sensible （ H ）－ Latent(LE ）－ H RMSE [W/ ㎡ ] LE RMSE [W/ ㎡ ] LDASUT NCEP JMA UKMO LE daily-mean ( June) Observed Modeled LDASUT LDASUT- GCMs

GCM Land Surface Scheme Satellite Data Minimization Scheme Radiative Transfer Model Cost Function GCM Forcing Regional Model Physical Down-scaling

soil moisture (Surface perspective) Assimilation No Assimilation

(Atmospheric perspective) Vertical Wind field GMS IR1-based convective Index No Assimilation caseAssimilation case Vertical Wind field

Radar at BJ With Land Assimilation Without Assimilation

Cloud Physics Scheme Radiative Transfer Model Cost Function Regional Model Satellite Data Minimization Scheme GCM Physical Down-scaling

IF J min No Yes ARPS Model Output (Initial Guess) Observation Operator (RTM) (Tb mod ) Model Operator (Lin Ice Scheme) (Assim. Parameter:ICLWC, IWV) Cost (J)= (Tb mod - Tb obs ) 2 Global Minimization Scheme (Shuffled Complex Evolution) Duan et al, 1992 Optimized Initial Condition Cloud Parameter Update IMDAS Framework Tb obs Precipitation Prediction by ARPS

12z 16z 20z 24z 04z 08z 12z ARPS Model Simulation 16:30z 16:30z 17:10z Assimilation Window: 40 mins TB obs AMSR-E Initial Guess 29 th Jan th Jan :30z 17:00 18:00 19:00 20:00 Assimilation Window: 40 mins Prediction Start of Prediction with Improved Initial Condition

Initial condition with no assimilation 29 th Jan, 17:00z dbz=200R**1.60 (Aonashi, 2004) Precipitation Rate(mm/hr) IMDASIMDAS Initial condition with assimilation

3hour prediction with no assimilation 29 th Jan, 20:00z dbz=200R**1.60 (Aonashi, 2004) Precipitation Rate(mm/hr) IMDASIMDAS 3hour prediction with assimilation

Cloud Physics Scheme Radiative Transfer Model Cost Function Regional Model Land Surface Scheme Satellite Data Minimization Scheme Radiative Transfer Model Cost Function GCM

Coupled Soil Atmosphere RTM By coupling AIEM with atmosphere RTM we get better agreement. For wetter cases AIEM is sufficient.

Atmosphere-Land Coupled Data Assimilation System

Tb Error Atmospheric effect derived from AMSR-E vs. MODIS Cloud Top Temperature LDAS onlyMODIS/IRA-L Coupled DAS

Integrated Cloud Liquid Water Atmospheric effect derived from AMSR-E vs. MODIS Cloud Top Temperature LDAS onlyMODIS/IRA-L Coupled DAS

24 hour Prediction of Rainfall over the Tibetan Plateau Prediction with the A-L Coupled Data Assimilation As an Initial Condition Only NestingGOES IR

Coupler System

Preliminary Design for Multi-scale Land Impact Research by of L-A Coupled DAS Regional-scale approach by L-A DAS without CMDAS Regional-scale approach by L-A DAS without CMDAS Extent: 40ºE - 160ºE and 0ºN - 60ºN Extent: 40ºE - 160ºE and 0ºN - 60ºN Grid size: 25 km → nx = 355, ny = 223, nz = 35 Grid size: 25 km → nx = 355, ny = 223, nz = 35 Meso-scale “mobile” approach by L-A DAS with CMDAS Meso-scale “mobile” approach by L-A DAS with CMDAS Point-scale by the CEOP Reference Sites Network + Point-scale by the CEOP Reference Sites Network +

モデルによる統合化