Modeling of regional atmospheric circulation using high-resolution - - PowerPoint PPT Presentation

Modeling of regional atmospheric circulation using high-resolution hydrodynamical model

Mikhail A. Tolstykh, Institute of Numerical Mathematics, RAS, and Hydrometcentre of Russia

Outline

• SLAV model – what it is?
• Recent developments and results, in

particular for Asia and Western Siberia

• Towards high-resolution global model:

necessary developments

SLAV model

• Global finite-difference semi-Lagrangian semi-implicit

dynamical core of own development + parameterizations of subgrid-scale processes from French model ARPEGE/ALADIN.

• Distinct features of dynamical core – vorticity-divergence

formulation on the unstaggered grid, wide use of 4th order finite differences, usual and compact. High accuracy of dynamical core ( Tolstykh, J. Comput. Phys. 2002).

• Computational efficiency due to semi-Lagrangian

advection and good parallel implementation.

Параллельная реализация перспективной версии на IBM 575 (OpenMP + MPI, только динамический блок)

Perform ance and scalability of testSLM

• n p575 DC 16 CPUs@

1.5G Hz

1.00 15.58 53.33 92.63 146.67 29.83 352.0 22.6 11.8 6.6 3.8 2.4 9732 741 450 306 238 189 1.0 10.0 100.0 1000.0 10000.0

1 mpi * 1

• mp on

1 6CPUs w ith SMT=NO 8mpi * 4omp on 1 6CPUs w ith SMT=YES 1 6mpi * 4omp on 32CPUs w ith SMT=YES 32mpi * 4omp on 64CPUs w ith SMT=YES 64mpi * 4omp on 1 28CPUs w ith SMT=YES 64mpi * 8omp on 256CPUs w ith SMT=YES

tim e (s ec)

0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00

Speed-up C

• de tim

e (sec/step) T im e com m and (sec)

Current state of the constant resolution global semi-Lagrangian model SL-AV

• Horizontal resolution 0,9˚ x0,72˚ lon-lat, 28 vertical

levels.

• Implemented operationally.
• In particular, forecasts for Tomsk area are

available via ftp for TSU

• Initial data – RHMC operational analyses + T2m

and RH2m own OI analysis, surface pressure field from RHMC DAS

• Improved annual mean scores in 2006 vs 2005,

especially in NH and Asia.

• One-year operational tests for precipitation

forecasts finished 30th of June.

• Operational tests for T2m forecasts started on 1st
• f July 2007.

Averaged RMS error for MSLP forecasts. Start time: 12 UTC. 27/10-23/12 2006 . Region: Northern extratropical hemishpere

0,00 1,00 2,00 3,00 4,00 5,00 6,00 7,00 8,00 24 48 72 96 120 Forecast range (hours) RMSE, mb

SLMop SLMex

Innovation vectors (dots), analysis increments (color field) for T2m RHMC DAS analysis

Variable resolution version of SLAV model

• Horizontal resolution 0,5625˚ in longitude,

26-70 in latitude, 28 vertical levels.

• Initial data – interpolated initial data for constant

resolution version

Resolution in latitude as a function of latitude

(in degrees)

Recent developments

• Implementation of finite-element scheme for

integration of hydrostatics equation (see poster by A.V.Shlyaeva, M.A.Tolstykh)

• Development of a nonhydrostatic dynamical

core (see poster by R.Yu. Fadeev, M.A.Tolstykh)

• Assimilation of soil variables; T2m and RH2m

OI analysis, development and first results for 3D-Var assimilation for T2m field (see poster by N.N.Bogoslovskii, A.V.Shlyaeva, M.A.Tolstykh)

Forecast quality of upper air fields over Asia in 2006

Models compared:

• ECMWF – European centre for medium range weather forecasts
• UKMO – UK Meteorological office
• NCEP – USA MRF model
• SMA – Russian T85L31 Eulerian model
• SLAV – Russian semi-Lagrangian model, constant resolution

version

• SLAV-VR – variable resolution version of SLAV model

RMS error of H500 forecast for Asia. Start time 12 UTC. Period: 2006. Verification against analyses

0,0 2,0 4,0 6,0 8,0 10,0 12,0 14,0 24 48 72 96 120 144 168 192 216 240 Forecast range (hours) RMSE, dam

SMA ECMWF UKMO NCEP SLAV SLAV VR

RMS error of MSLP forecast for Asia. Start time: 12 UTC. Period: 2006. Verification against analyses

0,0 2,0 4,0 6,0 8,0 10,0 12,0 14,0 16,0 24 48 72 96 120 144 168 192 216 240 Forecast range (hours) RMSE, hPa

SMA ECMWF UKMO SLAV SLAV VR

RMS error of T850 forecast for Asia. Start time: 12 UTC. Period: 2006. Verification against analyses

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 24 48 72 96 120 144 168 192 216 240 Forecast range RMSE,оС

SMA ECMWF UKMO NCEP SLAV SLAV VR

RMS error of V250 for Asia. Start time 12 UTC. Period: 2006 Verification against analyses

0,0 5,0 10,0 15,0 20,0 25,0 24 48 72 96 120 144 168 192 216 240 Forecast range (hours) RMSE, m/s

SMA UKMO SLAV SLAV VR

Verification of precipitation forecasts

• Region – 50-61˚ N, 60-85˚ E.
• Occurrence of precipitation: proportion correct,

Heidke skill score, Pearcy criteria.

• Quantiative precipitation forecast - absolute

error for following grades of forecast: rain (0,3- 1,0; 1,1-10,5; 10,6-19,5 mm/12 h) ; snow (0,2-1,0; 1,1-4,5; 4,6-9,5 mm/12 h).

• Separately for summer period (July-September

2006, May-June 2007) and winter period (October 2006 – April 2007)

Models compared:

• EXE – UK MO global model
• NCEP – USA MRF model
• T85 – Russian Eulerian T85L31 model
• Reg – “regional” model with 75 km

resolution

• SLAV – constant resolution semi-

Lagrangian model

• SLAV-VR – variable-resolution version of

SLAV

Proportion correct for precipitation forecasts

• ver Siberia (%). October 2006 - April 2007.

0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0 80,0 90,0 12 24 36 48 60 72 Forecast range (hours)

EXE NCEP T85 Reg SLM SLMVar

Heidke skill score (HSS) x 100. October 2006 - April 2007.

0,0 10,0 20,0 30,0 40,0 50,0 60,0 12 24 36 48 60 72 Forecast range (hours)

EXE NCEP T85 Reg SLM SLMVar

Pearcy criteria х 100. October 2006 - April 2007

0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0 12 24 36 48 60 72 Forecast range (hours)

EXE NCEP T85 Reg SLM SLMVar

Abs error (mm) of snow forecast for range 0,2-1,0 mm/12 h. Ocotber 2006 - March 2007.

0,0 0,5 1,0 1,5 2,0 2,5 12 24 36 48 60 72 Forecast range (hours)

EXE NCEP T85 Reg SLM SLMVar

Abs error (mm) of snow forecast for range 1,1-4,5 mm/12 h. Ocotber 2006 - March 2007.

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0 12 24 36 48 60 72 Forecast range (hours)

EXE NCEP T85 Reg SLM SLMVar

Abs error (mm) of snow forecast for range 4,6 - 9,5 mm/12 h. October 2006 - March 2007

0,0 1,0 2,0 3,0 4,0 5,0 6,0 12 24 36 48 60 72 Forecast range (hours)

EXE NCEP T85 Reg SLM SLMVar

Precipitation forecast - proportion correct (%) July-September 2006.

0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0 80,0 90,0 12 24 36 48 60 72 Forecast range (hours)

EXE NCEP T85 Reg SLM SLMVar

Heidke skil score (HSS) x 100 July-September 2006.

0,0 10,0 20,0 30,0 40,0 50,0 60,0 12 24 36 48 60 72 Forecast range (hours)

EXE NCEP T85 Reg SLM SLMVar

Pearcy criteria x 100 July-September 2006 .

0,0 10,0 20,0 30,0 40,0 50,0 60,0 12 24 36 48 60 72 Forecast range (hours)

EXE NCEP T85 Reg SLM SLMVar

0,00 0,50 1,00 1,50 2,00 2,50 3,00 12 24 36 48 60 72 Forecast range (hours)

EXE NCEP T85 Reg SLM SLMVar

• Abs. Error of precipitation forecast for

grade 0,3-1,0 mm/12h. July -September 2006.

0,00 1,00 2,00 3,00 4,00 5,00 6,00 12 24 36 48 60 72

EXE NCEP T85 Reg SLM SLMVar Forecast range (hours) Abs error of precipitation forecast for grade 1.1-10.5 mm/12 h. July - September 2006.

0,00 2,00 4,00 6,00 8,00 10,00 12,00 14,00 12 24 36 48 60 72

EXE NCEP T85 Reg SLM SLMVar

Forecast range

• Abs. Error of precipitation forecasts

for grade 10.6-19.5 mm/12 h. July-September 2006.

Precipitation forecast (accumulated 6hr sum) around

• Tomsk. Start time 21.07, 00UTC. Valid for 22.07, 07-

13hr local time (left), 13-19 hr (right)

Precipitation forecast (accumulated 6hr sum) around

• Tomsk. Start time 22.07 00UTC. Valid for 23.07,

07-13hr local time (left), 13-19 local time (right)

Conclusions on precipitation forecasts (1)

• In winter, the quality of precipitation

forecasts over Western Siberia using SLAV and SLAV-VR models are close to the quality of UKMO and NCEP forecasts up to 48 hr range. Later ranges are somewhat less successful for SLAV models.

• The same conclusions are valid for summer,

but for 36 hr instead of 48 hrs. Summer conclusions are however preliminary – the period is too short

Conclusions on precipitation forecasts (2)

• Quantitatively, the grades more than 10.5

mm/12hr are predicted with larger (negative) mean error as compared with UKMO and NCEP models. For smaller grades , the error is approximately the same.

Plans for further development of the SL-AV model

• Increase of the horizontal resolution first to

0.5, then to 0.25 degrees, 31 then 45 levels in vertical on a new 10 TFlops supercomputer at RHMC.

• Implementation of ALARO

parameterizations (includes prognostic microphysics, TKE scheme in PBL). + 5 prognostic variables.

• Implementation of the reduced grid.
• Implementation of the nonhydrostatic

dynamical core.

Impact of the horizontal resolution

Analysis (color), forecast (isolines). Left - SLAV (70km), right -SLAV-VR (30 km)

Prognostic variables in ALARO parameterizations

Problems of the regular latitude- longitude grid

• Due to convergence of meridians towards poles,

the grid step in longitude is much smaller than the grid step in latitude near the poles.

• This is bad for parameterizations, for calculating

the horizontal derivatives.

• Redundant computations.
• Solution – reduced grid: number of points in

longitude at each latitude circle can be different

Implementation of reduced grid in the SLAV model

• A part of calculations is carried out in space of

Fourier coefficients in longitude.

• The semi-Lagrangian advection is used (no

nonlinear advective terms) => Necessary latitudinal derivatives (i.e. geopotential gradient) can be calculated in Fourier space. How to construct a reduced grid for a finite-difference semi-Lagrangian model? – look R.Fadeev, Russian Meteorology and Hydrology, 2006 Currently, in the debugging phase for 3D model

Thank you for attention!