development of data assimilation systems for short-term numerical weather prediction at jma tadashi...
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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
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 Nonhydrostatic
meso 4DVar-system (JNoVA)
•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)
Domain Specifications
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 system00UTC 03UTC
JNoVA 4DVar(inner model 15km JMA-NHM)
FG (5km JMA-NHM)
Outer model 5km JMA-NHM
33h forecast
Obs. - FG
Analysis increment
03UTC 06UTC
JNoVA 4DVar(inner model 15km JMA-NHM)
FG (5km JMA-NHM)
outer model 5km JMA-NHM
15h forecast
Obs. - FG
Analysis increment
MA
MSM
MSM (5km JMA-NHM)
MA Coverage Maps of Observation Data
Coverage Maps of Observation Data
Direct assimilation of satellite radiance data
9
9
Score of MSM Precipitation ForecastVerification Grid : 20km SquareVerified Element: 1mm/3hr Verification Period :From Mar. 2001 to Sep. 2011
Threat Score
4DVar
20km GSM GPS
Major revision of physical processes
dx=10km=>5km
Nonhydro 4DVar
Nonhydro model Improvement of
convective scheme
satellite radiance temperature
Radar reflectivity
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
MSM 3h accumulated precipitation forecast26 Jul. 2009 03UTC
Use of 3D radar reflectivity data (started 9 Jun. 2011)
(a) (b) (c)
Control FT=12 Test FT=12 Obs 2009/07/26 03UTC
First Guess (MSM)
Ze from Radar simulator Ze obs.
RH retrieval algorithm
retrieved RH
retrieved RH
retrieved RH
MSM (5km)Outer model (5km)
inner model (15km)
MA
(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
•Horizontal resolution : 2km•Forecast term + 9hours Forecast model Local Forecast Model (LFM)•Initial condition (atmosphere) Local Analysis (LA)•Boundary condition 5km-MSM
SpecificationsObjectivesProducing sophisticated disaster prevention and aviation weather information with high resolution NWP
LA (5km 441x501)
LFM(2km 551x801)
domain used in trial operation
LA trial operation system
3DVAR(5km)
LF1(5km)
3DVAR
LF1 LF1
3DVAR
LFM (2km)
MSM (in operation)
3DVAR
JMA-NHM 1h forecast, dx=5kmBoundary ConditionFirst GuesshydrometeorsAnalysis
LF1
MSM (in operation)
LA
Rapid update cycle (RUC) 3DVAR
FT=0FT=-1FT=-2FT=-3
FT=3
FT=3
LA Coverage Maps of Observation DataSurface stations
(temperature and wind)Doppler radar
(radial velocity)
Aviation(temperatureand horizontal wind)
Ground-based GPS(total column water vapor)
Wind Profiler(horizontal wind)
LFM precipitation forecast• precipitation related to heated land in the afternoon
(16 Aug. 2010 09UTC 1h precipitation)Observation LFM (FT=3)
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
LF1 LF1
3DVAR
Radar simulator
retrieval
Radar obs.
ZeZe Rain, snow, graupel
RH
RH - reflectivity Database
3h accumulated precipitation ( FT=3 )
Control Test Observation
FT=0 Total column water vapor (Test-Control)
(i) Use of radar reflectivity observation
(ii) Vertical Coordinate of Control Variable• Control(=Trial Operation) : z*-coordinateInfluence of topography remains strong up to high altitudes
ground
model top
Slowly shift toz-coordinate
Rapidly shift toz-coordinate
z-coordinate
z-coordinate
z*-coordinate CV new coordinate
• Test : New coordinatefollow terrain near the surface => rapidly shift to z-coordinate aloft
Vertical Cross Section of T increment
Control Test
Reasonably limits the influence of topography within the lower troposphere.
(ii) Vertical Coordinate of Control Variable
• Control: ground potential temperature is fixed⇒excessive temperature increment in the lower troposphere
ground
1.5m
20m
0m
surface
the lowest model level
PT
Obs
excessive increment
• Test : extend the control variable to include ground potential temperature
1.5m
20m
0mAnalyze ground PTfixed
⇒ Analyze ground PT to mitigate excessive increment
(iii) Extension of Control Variables
Control Test
Vertical cross section of temperature analysis increment
Mitigate excessive temperature increment in the lower troposphere
(iii) Extension of Control Variables
(iv) Incremental Analysis Updates
Obs. Obs. Obs. Obs.
MSM
LFM
Gradually add increment
3DVar 3DVar 3DVar 3DVar
Gradually add 3DVar increment in the assimilation window => enhance balance of the analysis
30min.
(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
Obs. Obs. Obs. Obs.
MSM
5km JMA-NHM
Actual implementation in test experiment
3DVar 3DVar 3DVar 3DVar30min.
Domain averaged Ps tendency Qc summed over (limited) domain
ControlTest
(iv) Incremental Analysis Updates(Test with 5km forecast)
Control
Test
FT=0FT=-3h FT=6h
Rapid update cycle 5km forecast FT=0 FT=6h5km forecast
update of B.C.
Test by single surface T observation(T increment on the lowest model level)
ControlTest
•Terrain between grid points is used to modify horizontal background error correlation (steep => damp fast)•Implemented using coordinate transformation + recursive filter
(v) Terrain-Adjusted Background Error Correlation
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