Challenges for numerical weather prediction in the tropics: AMMA legacy Aida Diongue NIANG ANACIM METEOROLOGY Senegal

Challenges for numerical weather prediction in the

tropics: AMMA legacy

Aida Diongue NIANGANACIM

METEOROLOGYSenegal

évaluation AERES 15-17 janvier 2008 2

Outline

1.Performance of NWP in the tropics and in Africa

2.Rainfall variability and impacts

3. AMMA programme and legacy

4. Implications for operational forecasting

5.Conclusion - Recommendations

Poor NWP model performance in Tropical Africa

ECMWF

ECMWF

Rodwell et al, 2010

Stable Equitable Error in Probability Space To monitor Precipitation forecastthe score measures the error in ‘probability space’ through use of the climatological cumulative distribution function

Rainfall errros in NWP and climate models

4

From Met Office

Similar errors in NWP and climate models: Misrepresentation of key processes (NWP & Climate models ): dry and moist convection, surface, radiation, turbulence,

aerosols…

NB: improvement of the model since

évaluation AERES 15-17 janvier 2008 From Jean-Philippe lafore, Meteo-France and CNRS

Scores Evolution for Tropics: wind field

•Wind RMS @72h 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!


Tropics: RMS errors against TEMP observations through forecast range

• RMS error against TEMP observations increases fast with the forecast range at the same rate for all models

Model performance to predict AEWs in the WAM System

évaluation AERES 15-17 janvier 2008 7Private communication by Gareth Berry et al. 2008

at 3 longitudes

• Very low score beyond 2 days•More skill for western Sahel •Impact on rainfall forecast

-10%

-20%

Niger à Malanville: 106 km²\

20%10%

0

Rainfall Variability Over Sahel:

Anomalies departures from the mean (1905-2005)

17/07/1997Water Vapor Channel

Monsoon onset

[10E-10W] Sultan et al., 2003

Jump of max rainfall

AEJ

Cold Tongue

SAL

ITCZ

Heat Low

Key features of the West African Monsoon Climate System during Boreal summer

Chris Thorncroft

Complexity of the West African Monsoon System

Global SSTTeleconnectionsRemote effects of MJO

Mesoscale Convective Systems

Deep ConvCells

Monsoon Systems

Global

Mesoscale

Regional

Local

YearSeasonDayHour

104 km

103km

102km

101km

Diurnal Diurnal CycleCycle

Seasonal Seasonal CycleCycle

Interannual Interannual VariabilityVariability

Shallow Cells

Major River Basins

Catchments

Vegetation Soil

Pools VegetationSoil

Scale interactionsScale interactions

Intraseasonal Intraseasonal scale is a central scale is a central scale for the scale for the understanding of understanding of Monsoon Monsoon variability and its variability and its impacts: impacts: S2SS2S

Scale interactionsScale interactions Figure adapted from Redelsperger et al , BAMS 2006

AEWs


Outline







Outline





Aerosols

Chemestry

West African Monsoon

IMPACTSIMPACTS

Water Ressources

Health

Agriculture

Multidisciplinary approach

WEATHERFORECASTING & CLIMAT PREDICTION

Days Weeks Seaseson Interannual Climate Change

Decision makers

Early warning systems, advices … Early warning systems, advices …

Seamless Vision Redelperger et al.

Multi-échelles dans le temps et dans l’espace

NiameNiame

yy

DakarDakarOuagaOuaga

GourmGourmaa

OuéOuémémé

SalSal

Sites de Méso-Sites de Méso-EchelleEchelle

6 Avions de Recherche

Déploiement SOP

Sites auxiliaires SOP

Bouées PIRATABouées PIRATA

Réseau Radio-Réseau Radio-sondagessondages

Atalante

Meteor

Ocean-Atmosphere-Continental surface measuremens

impacts data (surveys, …)

Multi-scale measurements (temporal & spatial)

3 bateaux

Observing strategy (original)


AMMA LEGACY

– Better understanding of the West African Monsoon

Publications: ~ 600 reffered / 10 special issues : J. of Geophysical Research (2)/J. of Atmospheric Physics & Chemistry/J. of Hydrology/Quarterly Journal & ASL (RMS)/Weather & Forecast & J. of Atmospheric Sciences (AMS) /Climate

Dynamics

– Capacity Building– PHD; ~ 160, 80 Aricans

– ~ 40 research units for 20 different countries

– Masters, Summer schools, workshop

– 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

AMMA: Impact of using the AMMA radiosonde dataset

• New radiosonde stations

• Enhanced time sampling

• Bias correction for RH developed at ECMWF (Agusti-Panareda et al)

• Data impact studies With various datasets,With and without RH bias correction

Number of soundings provided on GTS in 2006 and 2005

Period: 15 July- 15 September, 0 and 12 UTC

Similar results obtained at ECMWF

Monthly averaged RR better with bias

correction

Faccani et al, 2009

AMMABC: AMMA + RH bias correctionPreAMMA: with a 2005 networkNOAMMA: No Radiosonde data CPC: Observations

• Positive impact of the assimilation of AMMA dataset• Very poor performances of NOAMMA• Best performance of AMMABC

AMMA: Impact of using the AMMA radiosonde dataset (2)

évaluation AERES 15-17 janvier 2008

Assimilation of AMSUB over land

Karbou et al, 2009a, b

TCWV diurnal cycle at TOMB

• Developments @ Météo-France • to assimilate surface sensitive satellite humidity

channels over land

(Karbou et al., 2006)• To improve the hydrological cycle over the

Tropics, in particular over the AMMA region

(Karbou et al., 2009a/b,

Impact on TCWV Average over the period 1 Aug-14 Sep’06

• 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

TCWV (EXP-CTL)


Outline






20

Forecast during the AMMA-SOP 2006 • An unique experiment at ACMAD (Support WM0, AMMA, Europe (FP6), MF, Médias-France)

– Operational forecast during 4 months (JJAS) in 2006 – 2 briefings/day to guide the field experiment– 15 forecasters from 12 West African countries

• Tools and methods– Synergie Forecasting System (MF)

• 4 Stations at ACMAD fed with NWP products + Observations with the RETIM link– AOC-Web site (Medias, MF) http://aoc.amma-international.org/

• VSAT internet link at ACMAD• Reports, quicklooks, NWP products (ECMWF, UKMET, MF, NCEP, Morocco), diagnostics,

research models…• MCS tracking: RDT from SAF-Nowcasting

– Development of a forecasting method WASA/F – 2 weeks training for forecasters

• Major learning– NWP skill is poor especially for convection– But NWP is very useful for the large scale mass and circulation– Need of observations, adequate NWP products and diagnostics– Need to combine several NWPs– Diversity of methods across West African Forecasters Need to have a forecasters handbook

Forecasters’ Handbook projectLeaded by Parker (University of Leeds) and colleagues

• Collaborative programme with the aims of documenting existing good practice in forecasting, and accelerating the translation of new research results into operational forecasting practice.

• The document is close to completion and is expected to be published in 2015.

• The main challenge: to bridge the scientific gap between the theoretical and operational side

• Various new tools for forecasters, including new conventions for plotting of synthetic charts (the West African Synthetic Analysis/Forecast, or WASA/WASF system) and new diagnostics with various case studies.

• THORPEX support , specifically by supporting two workshops, at the International Centre for Theoretical Physics (ICTP) in 2009, and in Dakar in March 2013

WASA- WASF (West African Synthetic Analysis /Forecast) WASA du 06/08/06 06TU

Project

• Collaboration between Senegal Weather Service and CNRM/MOANA: researchers and forecasters

• A real-time website, simple but easily and rapidly evolving, according to the encountered needs and ideas

• Use of websites providing complementary information (broader context)

– e.g. MJO: Wheeler’s website + NCEP

• Regular reports (~2/week) and discussions between Toulouse and Dakar.

• Use of the products in operation al forecasting

Paper in preparation for BAMS

http://isv.sedoo.fr


Summary and Recommendations• NWP skill over Tropics and especially over Africa is still poor as compared with extra-tropics• Due to the lack of observations and to the importance of the role played by the physics (dry

and moist convection, surface, radiation, turbulence, aerosols…) • Nevertheless large scale thermodynamical and dynamical structures that force convection

are better depicted and are very useful for forecasting weather• AMMA allowed to demonstrate the positive impact and the key importance of improving the

operational observation networks• Major progresses have been performed in recent years especially in the assimilation area

(microwave data) • Efforts to be made by countries to maintain orenhance observing systems• Nevertheless the forecast skill of the water cycle and of precipitation progresses very slowly• Lessons learned during the forecasting exercise and some research results being put in the

West African Forecasting guide• New Metrics and better diagnostics adapted to Tropics (and Africa) in the framework of

MISVA but need for more particularly for Ensemble prediction• Recommendations: Seamlessness means also that any place in the world get

advantage of improvement and availability of weather products to predict particularly for HIW prediction by first easing access to NWP products .

Documents

Challenges for numerical weather prediction in the tropics: AMMA legacy Aida Diongue NIANG ANACIM METEOROLOGY Senegal