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Presentation on theme: "ATMOSPHERIC PROCESSES in SPACE-ATMOSPHERE-SEA/LAND system."— Presentation transcript:



3 Submodels

4 WMO WEATHER FORECASTING RANGES Nowcasting A description of current weather parameters and 0 -2 hours description of forecasted weather parameters Very short-range Up to 12 hours description of weather parameters Short-rangeBeyond 12 hours and up to 72 hours description of weather parameters Medium-rangeBeyond 72 hours and up to 240 hours description of weather parameters Extended-rangeBeyond 10 days and up to 30 days description of weather parameters, usually averaged and expressed as a departure from climate values for that period. Long-range Monthly outlook Three month or 90 day outlook Seasonal outlook From 30 days up to two years Description of averaged weather parameters expressed as a departure (deviation, variation, anomaly) from climate values for that month (not necessarily the coming month). Description of averaged weather parameters expressed as a departure from climate values for that 90 day period (not necessarily the coming 90 day period). Description of averaged weather parameters expressed as a departure from climate values for that season. Climate forecasting Climate variability prediction Climate prediction Beyond two years Description of the expected climate parameters associated with the variation of inter-annual, decadal and multi-decadal climate anomalies. Description of expected future climate including the effects of both natural and human influences.





9 The system of equations (conservation laws applied to individual parcels of air) (from E.Kalnay) conservation of the 3-dimensional momentum (equations of motion), conservation of dry air mass (continuity equation), the equation of state for perfect gases, conservation of energy (first law of thermodynamics), equations for the conservation of moisture in all its phases. They include in their solution fast gravity and sound waves, and therefore in their space and time discretization they require the use of smaller time steps, or alternative techniques that slow them down. For models with a horizontal grid size larger than 10 km, it is customary to replace the vertical component of the equation of motion with its hydrostatic approximation, in which the vertical acceleration is neglected compared with gravitational acceleration (buoyancy). With this approximation, it is convenient to use atmospheric pressure, instead of height, as a vertical coordinate. V. Bjerknes (1904) pointed out for the first time that there is a complete set of 7 equations with 7 unknowns that governs the evolution of the atmosphere:


11 ECMWF: T511L60 – 40 km; EPS: T255L60 – 80 km; DWD: GME (L41) – 40 km; LM (L35 50 ) – (2.8) 7 km; France: ARPEGE(L41)-23-133km; ALADIN (L41)– 9 km; HIRLAM: -------------- (L16-31) – 5-55 km; UK: UM(L30) – 60 km; (L38) – 12 km; USA: AVP (T254L64) – 60 km; ETA (L60) – 12 km; Japan: GSM(L40) – 60 km; MSM(L40) – 10 km. RusFed.: T85L31 – 150 km; (L31) – 75 km. Moscow region (300kmx300km) - 10 km. 2003, December


13 Modern and Possible further development computational technologies ensemble simulation


15 ECMWF: FORECASTING SYSTEM - DECEMBER 2003 Data Assimilation: Analysis : Mass & wind (four-dimensional variational multi- variate analysis on 60 model levels) Humidity (four-dimensional variational analysis on model levels up to 250 hPa) Surface parameters (sea surface temperature from NCEP Washington analysis, sea ice from SSM/I sat­ellite data), soil water content, snow depth, and screen level temperature and humidity Data used: Global satellite data (SATOB/AMV, (A)TOVS, Quikscat, SSM/I, SBUV, GOME, Meteosat7 WV radiance), Global free-atmosphere data (AIREP, AMDAR, TEMP, PILOT, TEMP/DROP, PROFILERS), Oceanic data (SYNOP/SHIP, PILOT/SHIP, TEMP/SHIP, DRIBU), Land data (SYNOP). Data checking and validation is applied to each parameter used. Thinning procedures are applied when observations are redundant at the model scale.

16 the Penn State/NCAR Mesoscale Model (e.g., Dudhia, 1993), the CAPS Advanced Regional prediction System (Xue et al, 1995), NCEP's Regional Spectral Model (Juang et al, 1997), the Mesoscale Compressible Community (MCC) model (Laprise et al, 1997), the CSU RAMS Tripoli and Cotton (1980), the US Navy COAMPS (Hodur, 1997).


18 WRF Development Teams Courtesy NCAR WG1 WG2 WG3 WG4 WG10 WG7 WG6 WG13 WG5 WG8 WG11 WG14 WG12 WG9 WG15 WG16

19 1 10 100 km Cumulus Parameterization Resolved Convection LES PBL Parameterization Two Stream Radiation 3-D Radiation Model Physics in High Resolution NWP Physics No Mans Land From Joe Klemp, NCAR (Bad Orb, 23-27.10.03 2003)

20 Weather Research and Forecasting Model Goals: Develop an advanced mesoscale forecast and assimilation system, and accelerate research advances into operations 36h WRF Precip Forecast Analyzed Precip 27 Sept. 2002 Collaborative partnership, principally among NCAR, NOAA, DoD, OU/CAPS, FAA, and university community Multi-agency WRF governance; development conducted by 15 WRF Working Groups Software framework provides portable, scalable code with plug-compatible modules Ongoing active testing and rapidly growing community use – Over 1,400 registered community users, annual workshops and tutorials for research community – Daily experimental real-time forecasting at NCAR, NCEP, NSSL, FSL, AFWA, U. of Illinois Operational implementation at NCEP and AFWA in FY04 From Joe Klemp, NCAR (Bad Orb, 23-27.10.03 2003)

21 Hurricane Isabel NOAA –17 AVHRR 13 Sep 03 14:48 GMT From Joe Klemp, NCAR (Bad Orb, 23-27.10.03 2003)

22 Hurricane Isabel Track 18/1700Z 10 km WRF Initialized 15/1200Z 4 km WRF Initialized 17/0000Z From Joe Klemp, NCAR (Bad Orb, 23-27.10.03 2003)

23 Hurricane Isabel 3 h Precip Forecast Initialized: 12 UTC 15 Sep 03 WRF Model 10 km grid 5 day forecast From Joe Klemp, NCAR (Bad Orb, 23-27.10.03 2003)

24 48 h Hurricane Isabel Reflectivity Forecast 4 km WRF forecastRadar Composite Initialized 00 UTC 17 Sep 03 From Joe Klemp, NCAR (Bad Orb, 23-27.10.03 2003)

25 Hurricane Isabel Reflectivity at Landfall Radar Composite 18 Sep 2003 1700 Z 41 h forecast from 4 km WRF From Joe Klemp, NCAR (Bad Orb, 23-27.10.03 2003)

26 Hurricane Isabel Surface-Wind Forecast Initialized: 00 UTC 17 Sep 03 WRF Model 4 km grid 2 day forecast From Joe Klemp, NCAR (Bad Orb, 23-27.10.03 2003)

27 Terrain-following hydrostatic pressure vertical coordinate Arakawa C-grid, two-way interacting nested grids (soon) 3 rd order Runge-Kutta split-explicit time differencing Conserves mass, momentum, dry entropy, and scalars using flux form prognostic equations 5 th order upwind or 6 th order centered differencing for advection Physics for CR applications: Lin microphysics, YSU PBL, OSU/MM5 LSM, Dudhia shortwave/RRTM longwave radiation, no cumulus parameterization WRF Mass Coordinate Core From Joe Klemp, NCAR (Bad Orb, 23-27.10.03 2003)

28 Model Configuration for 4 km Grid Domain – 2000 x 2000 km, 501 x 501 grid – 50 mb top, 35 levels – 24 s time step Initialization – Interpolated from gridded analyses – BAMEX: 40 km Eta CONUS analysis – Isabel: 1 o GFS global analysis (~110 km) Computing requirements – 128 Processors on IBM SP Power 4 Regatta – Run time: 106 min/24h of forecast From Joe Klemp, NCAR (Bad Orb, 23-27.10.03 2003)

29 North American Early Guidance System 5/31/2009 6 km aerosols in radiative transfer & reflectivity 6 km WRF aerosols 5/31/2008 7 km absorption scattering in radiative transfer 7 km WRF improved physics 5/31/20059 km AIRS, GOES imagery & move top to 2mb 9 km NMM top @ 2mb hourly output 5/31/2006 8 km WRF 4DDA8 km WRF 5/31/2010 5 km NPP, advanced 4DDA, NPOESS, IASI & air quality 5 km WRF L100 2/28/200410 km hourly update & improved background error cov. 10 km Meso Eta improved physics 9/30/2002 12 km 3DVAR radial velocity12 km Meso Eta DateData Assimilation Prediction Model

30 Global Forecast System (GFS) 5/31/2009 NPP, integrated SST analysis 40 km / L80 5/31/2008Aerosols in radiative transfer, GIFTS 40 km / L80 5/31/20053-D Background error covariance, cloud analysis, minimization 45 km / L64 5/31/2006 Absorption / scattering in radiative transfer 45 km / L64 + improved microphysics 5/31/2010 Advanced 4DDA, NPOESS, IASI + air quality 35 km / L100 2/28/2004 Grid point version, AIRS, GOES imagery T-254 / L64 add 2 passive tracers 9/30/2002 3D-VAR, AMSU-B, Quikscat T-254 / L64 Date Data Assimilation Prediction Model

31 Timeline for WRF at NCEP North American WRF: Operational in FY05 Hurricane WRF: Operational in FY06 Rapid Refresh (RUC) WRF (hourly): Operational in FY07 WRF SREF : Operational in FY07 Others? (Fire Wx, Homeland Security, etc.) using best WRF deterministic model

32 The Unified Model The Unified Model is the name given to the suite of atmospheric and oceanic numerical modelling software developed and used at the Met Office. The formulation of the model supports global and regional domains and is applicable to a wide range of temporal and spatial scales that allow it to be used for both numerical weather prediction and climate modelling as well as a variety of related research activities. The Unified Model was introduced into operational service in 1992. Since then, both its formulation and capabilities have been substantially enhanced. New Dynamics A major upgrade to the Met Office Global Numerical Weather Prediction model was implemented on 7th August 2002. Submodels The Unified Model is made up of a number of numerical submodels representing different aspects of the earth's environment that influence the weather and climate. Like all coupled models the Unified Model can be split up in a number of different ways, with various submodel components switched on or off for a specific modelling application. The Portable Unified Model (PUM) A portable version of the Unified Model has also been developed suitable for running on workstations and other computer systems.

33 The Met Office Global Numerical Weather Prediction model was implemented on 7th August 2002. The package of changes was under trial for over a year and is known as "New Dynamics". This document details some of the key changes that are part of the New Dynamics package. Non-hydrostatic model with height as the vertical co-ordinate. Charney-Philips grid-staggering in the vertical, Arakawa C-grid staggering in the horizontal, Two time-level, semi-Lagrangian advection and semi-implicit time stepping. Edwards-Slingo radiation scheme with non-spherical ice spectral files Large-scale precipitation includes prognostic ice microphysics. Vertical gradient area large-scale cloud scheme. Convection with convective available potential energy (CAPE) closure, momentum transports and convective anvils. A boundary-layer scheme which is non-local in unstable regimes. Gravity-wave drag scheme which includes flow blocking. GLOBE orography dataset. The MOSES (Met Office Surface Exchange Scheme) surface hydrology and soil model scheme. Predictor-corrector technique with no extraction of basic state profile. Three-dimensional Helmholtz-type equation solved using GCR technique.


35 40(35)






41 Further Development of the Local Systems LME and LMK 2003 to 2006 LME: Local model LM for whole of Europe; mesh size 7 km and 40 layers; 78-h forecasts from 00, 12 and 18 UTC. LMK: LM-Kürzestfrist; mesh size < 3 km and 50 layers; 18-h forecasts from 00, 03, 06, 09, 12, 15, 18, 21 UTC for Germany with explicit prediction of deep convection. 1.Data assimilation 2 Q 2005 Use satellite (GPS) and radar data (reflectivity, VAD winds) 1 Q 2006 Use European wind profiler and satellite data

42 Further Development of the Local Systems LME and LMK 2003 to 2006 2.Local modelling 2 Q 2004 Increase model domain (7 km mesh) from 325x325 up to 753x641 gridpoints (covering whole of Europe), 40 layers 3 Q 2005 New convection scheme (Kain-Fritsch ?)

43 Europa

44 LMK: LM-Kürzestfrist Model-based system for nowcasting and very short range forecasting Goals: Prediction of severe weather on the mesoscale. Explicit simulation of deep convection. Method: 18-h predictions of LM initialised every three hours, mesh size < 3 km Usage of new observations: SYNOP:Every 60 min,METAR:Every 30 min, GPS:Every 30 min,VAD winds:Every 15 min, Reflectivity:Every 15 min,Wind profiler:Every 10 min, Aircraft data.

45 0003(UTC)00211815120906 +3h +6h +9h +12h +18h +15h LMK: A new 18-h forecast every three hours

46 High-resolution Regional Model HRM Operational NWP Model at 13 services worldwide Hydrostatic, (rotated) latitude/longitude grid Operators of second order accuracy 7 to 28 km mesh size, various domain sizes 20 to 35 layers (hybrid, sigma/pressure) Prognostic variables: p s, u, v, T, q v, q c, q i Same physics package as GME Programming: Fortran90, OpenMP/MPI for parallelization From 00 and 12 UTC: Forecasts up to 78 hours Lat. bound. cond. from GME at 3-hourly intervals

47 General structure of a regional NWP system Topographical data Initial data (analysis) Lateral boundary data Regional NWP Model Direct model output (DMO) Graphics Visualization MOS Kalman Applications Wave model, Trajectories Verification Diagnostics

48 Short Description of the High-Resolution Regional Model (HRM) Hydrostatic limited-area meso- and meso- scale numerical weather prediction model Prognostic variables Surface pressure p s TemperatureT Water vapourq v Cloud waterq c Cloud iceq i Horizontal windu, v Several surface/soil parameters Diagnostic variables Vertical velocity Geopotential Cloud coverclc Diffusion coefficientstkvm/h

49 Current operational users of the HRM Brazil, Directorate of Hydrography & Navigation Brazil, Instituto Nacional de Meteorologia Bulgaria, National Meteoro-logical & Hydrological Service China, Guangzhou Regional Meteorological Centre India, Space Physics Lab. Israel, Israel Meteorological Service Italy, Italian Meteorological Service Kenya, National Meteorological Service Oman, National Meteoro- logical Service (DGCAM) Romania, National Meteoro-logical & Hydrological Service Spain, National Met. Institute United Arab Emirates, National Met. Institute Vietnam, National Meteoro- logical & Hydrological Service; Hanoi University

50 Numerics of the HRM Regular or rotated latitude/longitude grid Mesh sizes between 0.25° and 0.05° (~ 28 to 6 km) Arakawa C-grid, second order centered differencing Hybrid vertical coordinate, 20 to 35 layers Split semi-implicit time stepping; t = 150s at = 0.25° Lateral boundary formulation due to Davies Radiative upper boundary condition as an option Fourth-order horizontal diffusion, slope correction Adiabatic implicit nonlinear normal mode initialization

51 Physical parameterizations of the HRM -two stream radiation scheme (Ritter and Geleyn, 1992) including long- and shortwave fluxes in the atmosphere and at the surface; full cloud - radiation feedback; diagnostic derivation of partial cloud cover (rel. hum. and convection) Grid-scale precipitation scheme including parameterized cloud microphysics (Doms and Schättler, 1997) Mass flux convection scheme (Tiedtke, 1989) differentiating between deep, shallow and mid-level convection Level-2 scheme of vertical diffusion in the atmosphere, similarity theory (Louis, 1979) at the surface Two-layer soil model including snow and interception storage; three-layer version for soil moisture as an option

52 Computational aspects of the HRM Fortran 90 and C (only for Input/Output: GRIB code) Multi-tasking for shared memory computers based on standard Open-MP Efficient dynamic memory allocation NAMELIST variables for control of model Computational cost: ~ 3100 Flop per grid point, layer and time step Interface to data of the global model GME available providing initial and/or lateral boundary data Build-in diagnostics of physical processes Detailed print-out of meteographs



55 Further Development of the HRM 2003 to 2006 An MPI version of HRM for Linux PC Clusters, developed by Vietnam, is available to all HRM users since July 2003. A 3D-Var data assimilation scheme developed by Italy will be available to experienced HRM users early 2004. The physics packages in GME and HRM will remain exactly the same. The interaction between the different HRM groups should be intensified. A first HRM Users Meeting will take place in Rio de Janeiro (Brazil) in October 2004.



58 Univ Lancaster Univ. Bristol ECMWF WL|Delft, RIZA SMHI JRC Ispra Univ. Bologna DWD DMI GRDC

59 1) Run the complete assimilation-forecast system for GME and LM for the three historical flood events for a period of roughly 2 weeks for each flood event. 2) Perform for the three flood events high resolution analyses of 24h precipitation heights on the basis of surface observations. 3) Develop a prototype-scheme for near real-time 24h precipitation analysis on the basis of Radar-data and synoptic precipitation observations. In addition to these tasks the operational model results according to task 1) for the period of the Central European flood were retrieved from the archives and supplied to the project ftp-server.


61 Maps of the constant fields for GME and LM.


63 Austria 263 Czech Republic 800 Germany 4238 Poland 1356 Switzerland 435 Alltogether 7092

64 20022003200420052006 ECMWF 0.96 Tf TL511 (40km) L60 10 Tf20 Tf TL511(40km) L60 TL799(25km) L91 DWD 1.92 Tf 60km L31 7 km L35 2.88 Tf 40km L40 7 / 2 km L35 18-28 Tf 30km L45 NCEP 7.3 Tf T170(80km) L42 12km L60 T254(50km) L64 15.6 Tf TL611(40km) L42 8 km 28 Tf 2007: G 30km L 5 km JMA Japan 0.768 Tf T106(120km) L40 20 / 10 km L40 TL319(60km) L42 6 Tf 5 km L50 20 Tf 2007: TL959(20km) L60 CMA China 0.384 Tf T213(60km) L31 25 km L20 3.84 Tf ? 15 km2008: 5 km HMC Russia 35 Gf T85(150km) L31 75 km L30 T Tf ? T169(80km) L31

65 Computer equipment being readied for operational use ECMWF: EQUIPMENT IN USE (end of 2003)

66 Central Computer System (CCS) 2500 TB84 TB2752 MB 2752 1.8+1.3GHz Phase II 6/2004 1250 TB42 TB1408 MB 1408 1.3GHz Phase I 9/2002 200 TB30 TB1216 MB 2432 375MHz Current 2001 Tape Storage Disk Space Memory Processors Clock Speed Phase / Date But what are we going to do if we have not CCS?

67 LINUX (Red Hat 7.3) PGI Workstation 4.0 (Portland Group Fortran and C++) HRM DWD (hydrostatic High Resolution Model) 93 x 73, 31 Layers, 0.125 0 grid spacing (14 km), forecast for 48 hours AMD Duron 1300MHz 384 Mb PC 133 SDRAM 96 min AMD Athlon XP 1800+ MHz 256 Mb DDR266 RAM 81 min Pentium 4 2.4 GHz 512 Mb DDR333 SDRAM 70 min Intel Xeon Workstation 1 processor 2.4 GHz 2048 Mb RDRAM PC 800 60 min 2 processors 2.4 GHz 2048 Mb RDRAM PC 800 33 min Result of V.Galabov (Bulgaria) experiments with different PC

68 program TestOMP integer k, n, tid, nthreads, max_threads, procs logical dynamic, dynamic double precision d (5000) ===== call gettim (hrs1,mins1,secs1,hsecs1) call getdat (year,month,day) max_threads = OMP_GET_MAX_THREADS() procs = OMP_GET_NUM_PROCS() dynamic = OMP_GET_DYNAMIC() nested = OMP_GET_NESTED() !$OMP PARALLEL PRIVATE (NTHREADS, tid, n, k) tid = OMP_GET_THREAD_NUM() nthreads = OMP_GET_NUM_THREADS() !$OMP DO SCHEDULE (STATIC, 5000) do n = 1, 10000 do k = 1, 5000 d(k) = sin (dble(k+n))**2 + cos (dble(k+n))**2 end do !OMP END DO !$OMP END PARALLEL ===== call gettim (hrs2,mins2,secs2,hsecs2) call getdat (year,month,day) end program TestOMP

69 OSBIOSCompilerOpenMPTime Windows XP Threads DISABLE Visual Fortan 6.5 - 3.59 s Windows XP Hyper Threadings Visual Fortan 6.5 - 3.63 s Linux (Mandrake9.2) Threads DISABLE Intel Fortran 8.0 + & - 3.59 s Linux (Mandrake9.2) Hyper Threadings Intel Fortran 8.0 + 2.38 s

70 The future (from E.Kalnay) An amazing improvement in the quality of the forecasts based on NWP guidance. From the active research currently taking place, one can envision that the next decade will continue to bring improvements, especially in the following areas: Detailed short-range forecasts, using storm-scale models able to provide skillful predictions of severe weather. More sophisticated methods of data assimilation able to extract the maximum possible information from observing systems, especially remote sensors such as satellites and radars. Development of adaptive observing systems, where additional observations are placed where ensembles indicate that there is rapid error growth (low predictability). Improvement in the usefulness of medium-range forecasts, especially through the use of ensemble forecasting. Fully coupled atmospheric-hydrological systems, where the atmospheric model precipitation is appropriately downscaled and used to extend the length of river flow prediction. More use of detailed atmosphere-ocean-land coupled models, where the effect of long lasting coupled anomalies such as SST and soil moisture anomalies leads to more skillful predictions of anomalies in weather patterns beyond the limit of weather predictability (about two weeks). More guidance to government and the public on areas such as air pollution, UV radiation and transport of contaminants, which affect health. An explosive growth of systems with emphasis on commercial applications of NWP, from guidance on the state of highways to air pollution, flood prediction, guidance to agriculture, construction, etc.


72 1.Observing system 2.Telecommunication system 3.Computer system 4.Data assimilation 5.Model 6.Postprocessing


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