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Data assimilation for sea fog over the Yellow Sea

Shanhong Gao. Data assimilation for sea fog over the Yellow Sea. 中国海洋大学 海洋气象学系. MODIS, MTSAT, FY images. Three aspects are important. model. ● initial conditions ● micro-physics ● PBL scheme. Obs. fog area. inversion. Observations. sound. synop. ships. QuikSCAT. airs. gps.

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Data assimilation for sea fog over the Yellow Sea

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  1. Shanhong Gao Data assimilation for sea fog over the Yellow Sea 中国海洋大学 海洋气象学系 MODIS, MTSAT, FY images

  2. Three aspects are important model ● initial conditions● micro-physics●PBL scheme Obs fog area inversion

  3. Observations sound synop ships QuikSCAT airs gps others

  4. Obs DA result model analysis first guess (bg) Data assimilation methods DA methods：OA, 3DVAR, 4DVAR, Kalman Filters

  5. (a) 3DVAR (3 dimensional varational ) analysis first guess obs Observation error Background error

  6. EnKF yo time 3DVAR xb xa xb 3DVAR + ETKF (b) Hybrid-3DVAR ( ETKF + 3DVAR ) xb xb xa xa xb xb Xb: bgyo: obsXa: analysis 3DVAR: 3-dimensional variational Advantages: • based on the existed frame of 3DVAR • flow –dependent background error EnKF: Ensemble Kalman Filter ETKF: Ensemble Transform Kalman Filter

  7. (c) flow-dependent background error (BE) 3DVAR uses static BE. In fact, flow-independent is better. Temporal mean Non-flow dependent flow dependent (Hamillet al., 2006)

  8. Data assimilation Tools • Based on the WRF model, we have developed • Cycling-3DVAR DA module • Hybrid-3DVAR Da module

  9. create_my_case 子系统主要目录结构

  10. 2. Two study cases Case1: Observed fact(Year 2006) 20 LST 06 Mar 02 LST 07 Mar 08 LST 07 Mar 20 LST 07 Mar 12 LST 07 Mar 14 LST 07 Mar 02 LST 08 Mar 05 LST 08 Mar MTSAT IR(Gaoet al., 2009) TBB of IR1

  11. Model configuration Specifications of WRF run Domains

  12. Obs Comparison of simulated results Exp-A FNL only Single 3DVAR Exp-B Cycling 3DVAR Exp-C Hybrid Ens=12 Exp-D Hybrid Ens=24 Exp-E

  13. Case2: Observed facts (Year 2007)

  14. Model configuration Specifications of WRF run Domains

  15. Assimilating MTSAT-derived humidity MTSAT-IR Dual-channel detection Step1 Step2 Step3 DA

  16. Result Single 3DVAR Cycling 3DVAR Cycling 3DVAR + MTSAT

  17. Assimilating MTSAT-derived humidity Wang et al. (2014)

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