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NWP and AMMA case studies J.-P. Lafore, F. Beucher, F. Pouponneau, F. Rabier, C. Faccani, N. Fourrié, F. Karbou, P. Moll, M. Nuret, J-L Redelsperger, J.

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Presentation on theme: "NWP and AMMA case studies J.-P. Lafore, F. Beucher, F. Pouponneau, F. Rabier, C. Faccani, N. Fourrié, F. Karbou, P. Moll, M. Nuret, J-L Redelsperger, J."— Presentation transcript:

1 NWP and AMMA case studies J.-P. Lafore, F. Beucher, F. Pouponneau, F. Rabier, C. Faccani, N. Fourrié, F. Karbou, P. Moll, M. Nuret, J-L Redelsperger, J. Stein CNRM-GAME, Météo-France and CNRS, Toulouse, France With thanks to: A. Agusti-Panareda, P. Bauer (ECMWF, Reading), O. Bock, P. Drobinski (IPSL/LMD and LATMOS, France), G. Berry, C. Thorncroft (SUNNY, US), W. Thiaw (NCEP, US), J. Heming (UKMET), R.D. Torn (NCAR, U. New York), J-B Ngamini (ASECNA, Senegal), Z. Mumba (ACMAD, Niger)… WWRP-THORPEX African Regional Committee meeting 8-10 May 2012, Geneva, Switzerland

2 évaluation AERES janvier Some NWP Scores Extra-Tropics (1/3) Always in progress! Reduction of dispersion Europe Atlantic domain Geopotential Z - RMS 500 hPa Range

3 évaluation AERES janvier Scores for Tropics: wind field V (2/3) h Wind intensity is a more pertinent variable in the Tropics Its is large ~5 m/s 850 hPa) and increases with altitude (~8 m/s 250 hPa) Dispersion between models is ~1 to 2 m/s (850 to 250 hPa) Progresses are slow! Tropiques/RS (55) RMS of V h range ( ) range 1 to 10 days V 850 V 250 Wind RMS error against TEMP observations increases fast with the forecast range at the same rate for all models V 250 V h

4 évaluation AERES janvier EUMETSAT (28-30 June 2011) WMO RAI Dissemination Expert Group 2nd Meeting 1. African Eaterly Waves scores for 4 NWPs in 2007 (3/3) Correlation coefficients as fct of the range of 700 hPa curvature vorticity Private communication by Gareth Berry et al Weak forecast skill for AEWs ( 2 days) Large dispersion between models for the Wave-Convection link and the variability at 3 longitudes

5 évaluation AERES janvier AMMA opportunity (1/7) AMMA-1 International project (Redelsperger et al. 2006) AMMA legacy: –Better understanding of the West African Monsoon –Observations of the WAM: improvement of the operational observation network (soundings…), GPS, driftsondes, surface conditions, satellite, research observations (lidar, radar, aircraft…) opportunity to evaluate NWP models and the impact of observations 30th Conference on Hurricanes and Tropical Meteorology (15-20 April 2012)

6 évaluation AERES janvier Impact on quantitative prediction of precipitation over Africa (2/7) Higher scores for AMMABC Lowest scores for NO AMMA CNTR: data from GTS AMMA: from the AMMA database AMMABC: AMMA + bias correction PreAMMA: with a 2005 network NOAMMA: No Radiosonde data Faccani et al, 2009 Positive impact of the assimilation of AMMA dataset Very poor performances of NOAMMA Best performance of AMMABC

7 évaluation AERES janvier Downstream impact (3/7) Impact on geopotential at 500hPa, averaged over 45 days 72hr forecasts: AMMABC vs PREAMMA Faccani et al, 2009

8 évaluation AERES janvier 2008 Impact on TCWV Average over the period 1 Aug-14 Sep06 2. Assimilation of AMSU-B over land (4/7) TCWV (EXP-CTL) More humidity in EXP TCWV diurnal cycle at TOMB Karbou et al, 2009a, b Positive impact of the assimilation of AMSU over land Large impact over Tropics in Monsoon regions especially over Africa and in region with a poor data coverage Improvement of the diurnal cycle

9 évaluation AERES janvier Assimilation of AMSU-B over land (5/7) T (EXP-CTL) Vz (EXP-CTL) Karbou et al. 2009a, b AEJ increase

10 évaluation AERES janvier 2008 EUMETSAT (28-30 June 2011) WMO RAI Dissemination Expert Group 2nd Meeting 2. Assimilation of AMSUB over land (6/7) 24h Karbou et al. 2009a, b Smaller errors in EXP 48h 72h Positive impact of the assimilation of AMSU over land Large impact over all Tropics on the wind field in the upper troposphere Forecast errors versus ECMWF analyses (forecast–analysis) 200hPa Z, 1-31 Aug06 Difference between EXP and CTR

11 évaluation AERES janvier AEW case study in 2006: Pre-Helene TS Torn (2010) (7/7) Ensemble-Based (96 members) Sensitivity Analysis (EnKF) WRF model ( km) Sensitivity to: initial state, convection schemes, resolution Rain, Curvature Vort. (mean, var) 1. Weak skill (<2 days) 2. Initial state Wave: at early stage mid-layer e: later 3. Better for CRM Propagation Growing ratePDF 3.

12 évaluation AERES janvier CRMs: AEWs - Convection (1/2) AMMA well-documented case July 2006 Barthe et al., 2010, Cuesta et al –Monsoon surge + AEW + Convection Observations AROME 5 km)ARPEGE RR (mm/h) + Vm (m/s) NWP at low resolution: Wrong diurnal cycle and AEW-convection coupling High-resolution (CRM): Better representation of the AEW-convection link

13 évaluation AERES janvier CRMs: precipitation distribution (2/2) Precipitation (latitude) ARPEGE 30th Conference on Hurricanes and Tropical Meteorology (15-20 April 2012) Different distributions of precipitation Meridional distribution Rain regimes: ARPEGE: weak events are too frequent intense events are rare CRM: distribution of events in better agreement with TRMM QPF scores improved for CRM positive impact of data assimilation (AMSU-B) Rain regimes contribution to total precipitation

14 évaluation AERES janvier Coupling with Dust AROME (5 km) coupled with a dust module on a large domain Evaluation on the March 2006 dust storm (Kocha et al 2011) –Positive feedback of dust on the cold surge intensity Simulation of the whole June 2006 month –Diurnal cycle, dust lifted by convective wakes –Negetive feedback on the Heat Low Forecast in June 2011 during the FENNEC experiment –Good forecast skill of convective dust storm 00UTC Wind, Dust surface MSG: aerosols - clouds

15 évaluation AERES janvier Conclusion Poor NWP skill over Tropics and especially over Africa is as compared with extra- tropics Due to large Roosby Radius (non-balanced flow, except TC), to the lack of observations and to the key role played by the physics (dry and moist convection, surface, radiation, turbulence, aerosols…) Nevertheless large scale thermodynamical and dynamical structures are rather well depicted and are very useful for forecasters. Major progresses in recent years especially in the assimilation area (microwave data) and the dispersion between models decrease Nevertheless the forecast skill of the water cycle and of precipitation progresses very slowly CRMs (few km) improve drastically some aspects of forecasts relative to convection (life cycle, duration, propagation…), the diurnal cycle, dusts… Need to improve the representation of convection (dry air issue for Africa) and its coupling with AEWs, surface, aerosols… Intra-seasonal variability potential predictability to be exploited

16 évaluation AERES janvier Further work Treatment of the Ougadougou flood case (2009) Comparison of different CRMs: –COSMO (KIT, Germany) –AROME (Météo-France) –New metrics (MCS tracking…) –Ensemble simulations (COSMO) Analysis at different scales (link with the ISV) Predictability –Wave-convection link –Coupling with the surface 30th Conference on Hurricanes and Tropical Meteorology (15-20 April 2012) WWRP-THORPEX African Regional Committee meeting 8-10 May 2012, Geneva, Switzerland

17 évaluation AERES janvier Some References Agustí-Panareda A, Beljaars A, Cardinali C, Genkova I, Thorncroft C. 2010a. Impact of assimilating AMMA soundings on ECMWF analyses and forecasts. Wea.Forecasting 25: 1142–1160. doi: /2010WAF Andreas H. Fink et al., 2011: Operational meteorology: observational networks, weather analysis and forecasting. Atmospheric Science Letters, Volume : 12, Issue : 1, Special Issue : Sp. Iss. SI, Pages : Doi : /asl.324 Faccani C, Rabier F, Fourri´e N, Agust´ı-Panareda A, Karbou F, Moll P, Lafore JP, Nuret M, Hdidou FZ, Bock O The impact of the AMMA radiosonde data on the French global assimilation and forecast system. Weather and Forecasting 24: 1268–1286. Karbou F, Rabier F, Lafore JP, Redelsperger JL, Bock O. 2010b. Global 4D-Var assimilation and forecast experiments using AMSU observations over land. Part II: impact of assimilating surface sensitive channels on the African Monsoon during AMMA. Weather and Forecasting 25: 20–36. Redelsperger J-L, Thorncroft CD, Diedhiou A, Lebel T, Parker DJ, Polcher J African Monsoon Multidisciplinary Analysis: An international research project and field campaign. Bull. Am. Meteorol. Soc. 87: 1739–1746. Torn R. D. 2010: Ensemble-Based Sensitivity Analysis Applied to African Easterly Waves.. Weather and Forecasting 25: 20– doi: /2009WAF th Conference on Hurricanes and Tropical Meteorology (15-20 April 2012) WWRP-THORPEX African Regional Committee meeting 8-10 May 2012, Geneva, Switzerland


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