LETKF Data Assimilation System for KIAPS AGCM: Progress and Plan

Transcription

1 UMD Weather-Chaos Group Meeting June 17, 2013 LETKF Data Assimilation System for KIAPS AGCM: Progress and Plan Ji-Sun Kang, Jong-Im Park, Hyo-Jong Song, Ji-Hye Kwun, Seoleun Shin, and In-Sun Song Korea Institute of Atmospheric Prediction Systems (KIAPS) ( 재 ) 한국형수치예보모델개발사업단

2 Korea Institute of Atmospheric Prediction Systems Goal To develop a global NWP system optimized to the topographic & meteorological features of Korean peninsula Period 2011~2019 (total 9 years) Total fund About $ 100 million

3 Korea Institute of Atmospheric Prediction Systems (1) (31) (22) (12) There are 14 researchers in a group for data assimilation (DA) 7 for observation pre-processing (QC, bias correction for observation data) 7 for DA system development

4 Computing Facilities Haenam (Cray XE6, AMD 2.1G, 16.9Tflops) One of KMA s supercomputers 2016 cores Gaon1 (Dell, AMD Opteron 2.3G*4cpu, 2.9 Tflops) Belongs to KIAPS 5 nodes with 320 cores (64 cores per node) Gaon2 (IBM, Intel Xeon 2.9G 2cpu, 11.5 Tflops) Belongs to KIAPS 36 nodes with 576 cores (16 cores per node) Gaon3 Will be purchased this year or early next year Expected a similar one with Gaon2 (576 cores) Total 3,488 cores (5325 cores normalized by the performance of Haenam) Backup & Archiving system 210 TB for backup & 330 TB for archiving

5 KIAPS Data Assimilation Systems Plans for KIAPS Data Assimilation System Ensemble Data Assimilation LETKF would be the first system to be constructed as an operational system Hybrid(3D-Var/LETKF) 3D hybrid assimilation systems of which components consist of the ensemble assimilation system, descent algorithm for minimization of 3D- Var cost function Variational data assimilation (3D/4D-Var) KIAPS also plan to develop a 4-d variational data assimilation system

6 Framework of EnKF data assimilation system LETKF CAM_SE (Kang) We are implementing LETKF to NCAR CAM_SE (Community Atmospheric Model-Spectral Element) model, because it has the same horizontal/vertical coordinates as HOMME/KIAPS that will be released as the first version at the end of this year. LETKF implemented to NCAR CAM-SE model can be immediately used for the HOMME/KIAPS when released LETKF SPEEDY (Park) While developing LETKF-CAM_SE(HOMME/KIAPS), we would develop or/and test many essential methods to advance the current LETKF DA system, using the simplified model as a testbed.

7 Model HOMME/KIAPS & NCAR CAM-SE Spectral Element dynamic core The SE dycore uses accurate, high-order numerical methods on rectangular elements in a cubed-sphere geometry (six faces) Each face has Ne*Ne elements (Ne: # of elements in one side of a face) Each element has Np*Np grid points (Np: # of points in one side of a element) Horizontal resolution can be addressed by nexnpy (e.g. ne16np4~2 resolution, ne120np4~0.25, ne240np4~0.125 ) 5

8 LETKF implemented to NCAR CAM-SE Model NCAR CAM 5.2 with Spectral Element dynamic core Horizontal resolution: ne16np4 (~ 2 ) 30 vertical levels with hybrid sigma-pressure coordinate Major modifications of LETKF I/O of the model Data search process The original LETKF codes (from Dr. Miyoshi) compute (ri, rj) for a location of each observation which is a relative position to the model grid (i, j). Since (ri, rj) requires too much consideration near the boundary for cubed-sphere domain when LETKF searches for data within local area, I modified this part so that just (lon, lat) is used instead of (ri, rj). vs.

9 Test of LETKF-CAM_SE Observing System Simulation Experiments Simulated observations for U, V, T, q Radiosonde distribution Simulated observations for Ps Surface stations Observation distribution has been determined by real observation data (NCEP bufr) Observation errors: 1m/s for (U, V), 1K for T, 1g/kg for q, 1hPa for Ps 64 ensembles (cam, clm2, and cice) Random initial condition States at 64 arbitrary timesteps from a nature run + perturbations

10 Preliminary Result RMS difference of background (red) and analysis (blue) to observations in the observation space Reduced RMS difference after the first analysis step It seems working well. I ll make an analysis cycle with ensemble forecast right after getting back to Korea

11 Progress Understanding the model with special horizontal grid of Spectral Element dynamic core on rectangular elements in a cubed-sphere geometry Installing and running CAM-SE (coupled with CLM2 & CICE components) with every 6-hour restart Modifying standard LETKF codes for the model HOMME/KIAPS (NCAR CAM-SE) Analysis system of LETKF-CAM_SE assimilating radiosonde and surface station data has been developed. Preliminary result looks good

12 Plans We plan to include satellite data of AMSU-A & IASI, and GPS radio occultation data into LETKF data assimilation system. Takemasa (radiance DA) & Shu-Chih (GPS RO DA) will visit KIAPS in August for giving us an advice. AIRS retrieval data can be also assimilated and compared. Target resolution of HOMME/KIAPS is ne240np4 (~0.125, very high) with 70 vertical layers Ensemble forecast may have coarser resolution than ne240np4. If the resolution for ensemble forecast is too coarse, we may not be able to get comparable results with others. It would be good to incorporate a mixed resolution of background (Rainwater and Hunt, 2013)? I can test it using CAM! We plan to test many useful techniques in EnKF, especially forecast sensitivity to observations (Kalnay et al. 2012) which KMA is very interested in. Carbon cycle data assimilation (LETKF-C) will be also tested using CAM5.2 with SE, or CAM3.5 with FV Thank you very much for your attention!