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

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 2013. 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

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 2013.12.1.00 UTC to 2014.2.28.18 UTC (J/kg) Total impact of each observation sub-type on the operational global NWP for the period from 2013.12.1.00 UTC to 2014.2.28.18 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