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Development of Data Assimilation Systems for Short-Term Numerical Weather Prediction at JMA. Tadashi Fujita (NPD JMA) Y. Honda, Y. Ikuta, J. Fukuda, Y. Ishikawa, K. Yoshimoto. Contents 1 . Meso -scale NWP system (MA: Meso -scale Analysis) 1-1. MA operational system 1-2. recent update
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Development of Data Assimilation Systems forShort-Term Numerical Weather Prediction at JMA Tadashi Fujita (NPD JMA) Y. Honda, Y. Ikuta, J. Fukuda, Y. Ishikawa, K. Yoshimoto
Contents 1. Meso-scale NWP system (MA: Meso-scale Analysis) 1-1. MA operational system 1-2. recent update 2. Local NWP system (LA: Local Analysis) 2-1. LA trial operation system 2-2. recent developments 3. Summary
Contents 1. Meso-scale NWP system (MA: Meso-scale Analysis) 1-1. MA operational system 1-2. recent update 2. Local NWP system (LA: Local Analysis) 2-1. LA trial operation system 2-2. recent developments 3. Summary
Meso-scale NWP System • Forecast Model : Meso-Scale Model (MSM) based on JMA Nonhydrostatic Model (JMA-NHM) • Data Assimilation System : Meso-scale Analysis (MA) based on Nonhydrostaticmeso 4DVar-system (JNoVA) Specifications Domain • Horizontal resolution:5km • Domain: 3600*2880km (721*577 grid points) • Forecast term + 00,06,12,18Z => 15hours + 03,09,15,21Z => 33hours • Forecast model • Meso-Scale Model (MSM) • Initial condition (atmosphere) Meso-scale Analysis (MA) • Boundary condition 20km-GSM (Global Spectral Model)
Objectives of Meso-scale NWP System • Disaster Prevention • Prediction of severe weather such as heavy rainfall is one of the main targets for mitigation and reduction of damage to property and loss of life. • Input to short-range precipitation forecast system • Input to storm surge model • Aviation Weather Forecast • Enrichment of the weather information for aviation safety • Terminal Area Forecast (TAF) Guidance and so on.
MA operational system 00UTC 03UTC 03UTC 06UTC FG (5km JMA-NHM) FG (5km JMA-NHM) Obs. - FG Obs. - FG JNoVA 4DVar (inner model 15km JMA-NHM) JNoVA 4DVar(inner model 15km JMA-NHM) Analysis increment Analysis increment MA Outer model 5km JMA-NHM outer model 5km JMA-NHM MSM MSM (5km JMA-NHM) 33h forecast 15h forecast
Coverage Maps of Observation Data Direct assimilation of satellite radiance data
Score of MSM Precipitation Forecast Verification Grid : 20km Square Verified Element: 1mm/3hr Verification Period :From Mar. 2001 to Sep. 2011 Threat Score Radar reflectivity satellite radiance temperature 20km GSM GPS Nonhydro model dx=10km=>5km Nonhydro 4DVar Major revision of physical processes 4DVar Improvement of convective scheme 9 9
Contents 1. Meso-scale NWP system (MA: Meso-scale Analysis) 1-1. MA operational system 1-2. recent update 2. Local NWP system (LA: Local Analysis) 2-1. LA trial operation system 2-2. recent developments 3. Summary
Assimilation of RH data retrieved from3D radar reflectivity => Improvement of humidity and precipitation forecast of MSM Use of 3D radar reflectivity data (started 9 Jun. 2011) Ze from Radar simulator Ze obs. First Guess (MSM) RH retrieval algorithm retrieved RH retrieved RH retrieved RH MA inner model (15km) MSM (5km) Outer model (5km) MSM 3h accumulated precipitation forecast 26 Jul. 2009 03UTC (cf. Meteo France method)
Contents 1. Meso-scale NWP system (MA: Meso-scale Analysis) 1-1. MA operational system 1-2. recent update 2. Local NWP system (LA: Local Analysis) 2-1. LA trial operation system 2-2. recent developments 3. Summary
Local NWP System • Forecast Model : Local Forecast Model (LFM) JMA Nonhydrostatic Model (JMA-NHM) • Data Assimilation System : Local Analysis (LA) JNoVA 3DVar • Trial operation started in Nov. 2010 • operation planned in 2012 Specifications Objectives Producing sophisticated disaster prevention and aviation weather information with high resolution NWP • Horizontal resolution:2km • Forecast term + 9hoursForecast model • Local Forecast Model (LFM) • Initial condition (atmosphere) Local Analysis (LA) • Boundary condition5km-MSM domain used in trial operation LFM(2km 551x801) LA(5km 441x501)
LA trial operation system MSM (in operation) FT=3 Rapid update cycle (RUC) 3DVAR 3DVAR(5km) 3DVAR 3DVAR 3DVAR LF1(5km) LF1 LF1 LFM (2km) LA MSM (in operation) FT=3 FT=-3 FT=-2 FT=-1 FT=0 Boundary Condition First Guess hydrometeors Analysis LF1 JMA-NHM 1h forecast, dx=5km
LA Coverage Maps of Observation Data Wind Profiler (horizontal wind) Doppler radar (radial velocity) Surface stations (temperature and wind) Ground-based GPS (total column water vapor) Aviation(temperature and horizontal wind)
LFM precipitation forecast • precipitation related to heated land in the afternoon (16 Aug. 2010 09UTC 1h precipitation) LFM (FT=3) Observation
Contents 1. Meso-scale NWP system (MA: Meso-scale Analysis) 1-1. MA operational system 1-2. recent update 2. Local NWP system (LA: Local Analysis) 2-1. LA system in trial operation 2-2. recent development 3. Summary
(i) Use of radar reflectivity observation Simulate radar reflectivity from LF1 (JMA-NHM forecast) => estimate RH from reflectivity => assimilate RH in 3DVAR RH - reflectivityDatabase 3DVAR RH retrieval Ze Ze Rain, snow, graupel Radar simulator LF1 LF1 Radar obs.
(i) Use of radar reflectivity observation 3h accumulated precipitation(FT=3) Control Test Observation FT=0 Total column water vapor(Test-Control)
(ii) Vertical Coordinate of Control Variable • Control(=Trial Operation) : z*-coordinate • Influence of topography remains strong up to high altitudes • Test : New coordinate • follow terrain near the surface =>rapidly shift to z-coordinate aloft z*-coordinate CV new coordinate model top z-coordinate z-coordinate Slowly shift to z-coordinate Rapidly shift to z-coordinate ground
(ii) Vertical Coordinate of Control Variable Vertical Cross Section of T increment Control Test Reasonably limits the influence of topography within the lower troposphere.
(iii) Extension of Control Variables • Control: ground potential temperature is fixed ⇒excessive temperature increment in the lower troposphere • Test: extend the control variable to include ground potential temperature Obs • ⇒Analyze ground PT to mitigate excessive increment excessive increment Analyze ground PT 20m 20m the lowest model level surface 1.5m 1.5m 0m 0m PT ground fixed
(iii) Extension of Control Variables Vertical cross section of temperature analysis increment Control Test Mitigate excessive temperature increment in the lower troposphere
(iv) Incremental Analysis Updates Gradually add 3DVar increment in the assimilation window => enhance balance of the analysis MSM Obs. Obs. Obs. Obs. 3DVar 3DVar 3DVar 3DVar 30min. Gradually add increment LFM (cf. Bloom et al. 1996, Clayton 2003, Lee et al. 2006, etc.)
(iv) Incremental Analysis Updates Gradually add 3DVar increment in the assimilation window => enhance balance of the analysis Actual implementation in test experiment MSM Obs. Obs. Obs. Obs. 3DVar 3DVar 3DVar 3DVar 30min. 5km JMA-NHM
(iv) Incremental Analysis Updates (Test with 5km forecast) Domain averaged Ps tendency Qc summed over (limited) domain update of B.C. Control Test Control Test Rapid update cycle FT=6h FT=0 5km forecast 5km forecast FT=6h FT=-3h FT=0
(v) Terrain-AdjustedBackground Error Correlation • Terrain between grid points is used to modify horizontal background error correlation (steep => damp fast) • Implemented using coordinate transformation + recursive filter Test by single surface T observation (T increment on the lowest model level) Control Test
Summary • JMA operates Meso-scale NWP system aimed at disaster prevention and aviation weather information services. • Steady improvement of MSM forecast has been attained from various improvements of the system, including recent introduction of radar reflectivity data (retrieved RH) in MA. • Trial operation of Local NWP system is currently underway, toward the operational run scheduled in 2012. • Various development of LA is underway to improve the system. • introduction of new observation, including radar reflectivity data • new CV vertical coordinate • ground PT analysis • IAU • terrain-adjusted background error correlation