COSMO-RU ensemble weather forecasting system: first steps

Dmitry Alferov,Elena Astakhova, Gdaly Rivin, Inna

Rozinkina

Hydrometcenter of Russia13-th COSMO General Meeting, Rome, 5-9 September 2011

ContentsGlobal medium-range EPS at the Hydrometcenter of Russia

COSMO-RU EPS descriptionCOSMO-RU EPS productsCase study: freezing rain in Moscow

COSMO-RU EPS verificationProspects

Basic model (horis. resolution) Spectral T169L31 (~75 km)

Levels 31 levels; σ=0.01 –0.9952

Membership14: 12 perturbed T169L31

1 control T169L31 1 control SLAV-2008

Initial data perturbationsBreeding with regional rescaling,

12hr cycling

Model uncertainty perturbations No

Surface boundary perturbations No

Runs per day (times in UTC) 1 (12 UTC)

Forecast length and step interval T+0h -- T+240h at 6 hrs

Input Hydrometcenter of Russia OA data

Global medium-range EPS at the Hydrometcenter of Russia

SLAV-2008 model : Semi-Lagrangian vorticity-divergence dynamical core, ALADIN/LACE parameterizations,0.9x0.72 degrees lon/lat (~70 km), 28 levels

Global EPS productsSpaghetti (T850, pmsl, H500) Ensemble meteograms (T2m, prec, T850, total

clouds, middle clouds, pmsl)Mean+spread (H500, T850)Plumes(T850, T2m, 6h prec)Postage stamps (T2m, prec)Probability maps (24-h prec, 6-h prec, wind 10m,

wind 850 hPa, T850 anom, H500 anom, pmsl anom)

Thresholds from the Guideline of the Lead center on Verification of Ensemble Prediction Systems

Since October 2010: Verification results for precipitation are published on the Web site of the Lead Centre on Verification of Ensemble Prediction

Systemshttp://epsv.kishou.go.jp/EPSv/html/rumseps/probdiagrams.html




COSMO-RU EPS DESCRIPTION: main features 28 members Different variants of model

physics, numerical schemes for model dynamics and boundary conditions schemes

Ensemble members: COSMO-RU model, grid: 350×310×40, Δx=Δy=14 km

Control experiment: COSMO-RU model, Δx=Δy=7 km

Forecast length: 78 hours Computer: SGI Altix 4700

Itanium 2, 1.66 GHz, NUMALink, 1664 PEs, Peak 11 Tflops

Performance: 256 CPUs, forecast ready in 7 hours

1 run / day at 00 UTCThe model integration domain

MoscowOffenbach

Sochi

Rome

Omsk

Murmansk

Athens

COSMO-RU EPS DESCRIPTION: applied perturbations

PERTURBATIONPARAMETER RANGE

DEFAULT

VALUEUSED VALUES

DYNAMICS

Numerical schemeLeapfro

g

Leapfrog, 2nd order Runge-

Kutta, 2nd order Runge-Kutta

TVD schemes

Boundary conditions scheme

Implicit Implicit, explicit

PHYSICS

Deep convection parameterization scheme

TiedtkeTiedtke,

Kain-Fritsch

Length scale of sub-scale surface thermal patterns

over land (pat_len)0–10000 m 500

0, 500, 10000(like used in COSMO-

SREPS [Marsigli, 2009])

Scaling factor for the thickness of the laminar boundary layer for heat

(rlam_heat)

0.1–10.0 1.0

0.1, 1.0, 10.0(tested in COSMO-

SREPS and CSPERT projects [Marsigli,

2009])




COSMO-RU EPS PRODUCTS: probability forecasts(6 h accumulated precipitation)

Probability of precipitation > 0.25 mm / 6 hInitial time: 00 UTC 30.05.2010, forecast valid at 06 UTC 2.06.2010

Moscow

COSMO-RU EPS PRODUCTS: spaghetti plots (T2m)25˚C isotherm spaghetti, 31 July 2010 + 78 hours (blocking case with extreme heat)

• Thick black line – actual data;• Thick red line – nonperturbed control 78-hour forecast;• Thick blue line – ensemble mean;• Thin coloured lines – ensemble members.

COSMO-RU EPS PRODUCTS: spaghetti plots (T2m)25˚C isotherm spaghetti, 31 July 2010 + 78 hours (blocking case with extreme heat)

• Thick black line – actual data;• Thick red line – nonperturbed control 78-hour forecast;• Thick blue line – ensemble mean;• Thin coloured lines – ensemble members.

Large instability in the Urals region

Ensemble mean forecast shows much better skill

(and some members too)




CASE STUDY: freezing rain in Moscow

• Intense freezing rain in Moscow region on 25-26 December 2010 caused damage of trees, electric lines and constructions due to large mass of glazing ice formed during this time.• Transport problems and closing of airports followed.


Wind

Temp, C

PMSL,hPa

mm/3hPrecmm/h

Clouds

Convclouds,m


Wind

Temp, C

PMSL,hPa

mm/3hPrecmm/h

Clouds

Convclouds,m

Combined rain and snow


Wind

Temp, C

PMSL,hPa

mm/3hPrecmm/h

Clouds

Convclouds,m

Temperature inversion near 0˚C

CASE STUDY: freezing rain in MoscowCOSMO-RU 18-hour control forecast (grid size 7 km)

PMSL, clouds, precipitation PMSL, T2m, H500

• Left scale – clouds;• Right scale – precipitation;• Isolines – PMSL;• Initial time: 12 UTC 25.12.2010;• Forecast valid at 06 UTC 26.12.2010

• Color scale – T2m;• Brown isolines – H500;• White isolines – PMSL;• Initial time: 12 UTC 25.12.2010;• Forecast valid at 06 UTC 26.12.2010

CASE STUDY: freezing rain in Moscow Temperature, cross-section along the latitude of Moscow (55.786˚ N)

Analysis for COSMO-RU/14 model

• Initial time: 12 UTC 23.12.2010• Forecast valid at 06 UTC 26.12.2010

Longitude Longitude

-4˚C

-4˚C

0˚C

0˚C

0˚C

Longitude of Moscow(37.557˚ E)

66-hour COSMO-RU ensemble forecast

0˚C isotherm ‘spaghetti’ plot

CASE STUDY: freezing rain in Moscow Temperature, cross-section along the latitude of Moscow (55.786˚ N)

Analysis for COSMO-RU/14 model

• Initial time: 12 UTC 23.12.2010• Forecast valid at 06 UTC 26.12.2010

Longitude Longitude

-4˚C

-4˚C

0˚C

0˚C

0˚C

Longitude of Moscow(37.557˚ E)

66-hour COSMO-RU ensemble forecast

0˚C isotherm ‘spaghetti’ plot

Temperature inversion near 0˚C successfully forecasted with high probability

Ensemble members with pat_len = 10000 m gave the worst forecasts at all lead times




COSMO-RU EPS VERIFICATIONReliability diagrams

T2m > 30˚CJuly-August 2010

T2m < -20˚CDecember 2010 – January 2011

Reliability diagrams show the quality of probability forecast. These diagrams show very good forecasts, almost perfect in summer 2010 and

a bit worse in winter 2010.

Forecast probabilityForecast probability

No resolution (climatology)No resolution (climatology)




ProspectsRegular ensemble runs

A comprehensive study of the effect of different perturbations, better choice of parameter values

Reduction of the number of ensemble members for higher performance

Analysis of EPS skill in probabilistic forecasting of various weather elements (wind, H500, etc.)

High-resolution (2.2 km) ensemble for Sochi region

Thank you!

Documents

COSMO-RU ensemble weather forecasting system: first steps