1. National Meteorological Satellite Center
CURRENT STATUS OF SATELLITE DATA
ASSIMILATION IN KMA
National Meteorological Satellite Center
CGMS-42 Guangzhou, May 19 to 23, 2014

2. Highlights of KMA DA (Data Assimilation)
Overview of KMA DA (UM model)
(2) COMS AMV & CSR data  KMA DA
(3) COMS CSR
- impact from update of the bias correction
 more humid throughout most of the upper levels
Analysis resolution
~ 25km
DA resolution
~ 60km
Analysis domain top
80km (70 levels)
Analysis method
4D-VAR (Hybrid Ensemble)
Used Observation
Synop, Ship, Buoy, ASCAT, Sonde, Pilot, Windprofiler, Airep, ACARS(AMDAR), AMV (Meteosat-7, MSG-3, GOES-W/E, MTSAT-2, COMS, MODIS, AVHRR), ATOVS(global, EARS, AP-RARS, SA-RARS), IASI(MetOp-A/B), AIRS, GPS-RO (COSMIC, GRACE-A, GRAS-A/B), COMS(CSR)
Data Base
ODB(Observation Data Base)
Difference in forecast errors (root mean square of forecast minus verifying analyses) between control (with T24) and experiments (with T16) for 5 day forecasts of 500 hPa geo-potential height from 1 to 30 December Blue colors mean that positive impact of experiments
western Pacific region
Mean difference in analyzed relative humidity (in %) at 300 hPa between the experiment using new coefficients and the control. Average in from 1 to 30 December 2013 for 00 UTC analyses
CGMS-42 Guangzhou, May 19 to 23, 2014

3. Highlights of KMA DA (Data Assimilation)
(4) Forecast Sensitivity to Observations (FSO)
(5) Soil moisture impact on NWP (ongoing work)
-SMOS, GCOM-W1, ASCAT
Total impact of each satellite (a) and total impact of each sensor in MetOp (A/B) satellite (b) from UTC to UTC (J/kg)
Total impact of each observation sub-type on the operational global NWP for the period from UTC to UTC
AMSU-A sensor gives the largest impact (~42%), followed by IASI (19%) and IR of AMV (12%)
CGMS-42 Guangzhou, May 19 to 23, 2014