Status of THORPEX Africa and related activities. Data Assimilation and Observing Systems (DAOS) Perspective

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1 Status of THORPEX Africa and related activities Data Assimilation and Observing Systems (DAOS) Perspective Sharanya J. Majumdar (University of Miami, USA) on behalf of DAOS THORPEX Africa Regional Committee Meeting Geneva, Switzerland, May 8 th 2012

2 Outline of Presentation Review of recent activities AMMA radiosondes, satellite data Ongoing activities Challenges and Questions

3 AMMA: Radiosondes

4 Mean ECMWF analysis for AMMA. Total column water vapor (kg m 2 ) from the 0000 and 1200 UTC analyses during August Difference between AMMA and pre AMMA experiments. (Agusti Panareda et al. 2010, WAF)

5 RMSEs of forecasts with respect to radiosonde observations, within a region between 10 and 20 N and 20 W and 20 E. Radiosondes are the only observing system that provides a full description of the atmospheric profile in the lower and mid tropospherein ECMWF analyses. AMMA radiosonde observations have a significant impact on the ECMWF analyses. Unfortunately, the influence on the forecast is very short lived due to large model biases (low level T, cloud cover, precipitation). AMMA radiosonde observations crucial to detecting model biases. (Agusti Panareda et al. 2010, WAF)

6 Météo France: radiosondes Observedmonthlymeanpre cipitation With a 2005 network Similar to ECMWF results With AMMA radiosondes andbias correction (Faccani et al. 2010, WAF)

7 Météo France: low level Satellite Microwave Observations Average of the 24 h forecast cumulative rain rate difference between 1 Aug 14 Sep 2006, due to assimilation of AMSU B data. The forecast scores with respect to ECMWF analyses have been found to be positive for geopotential and temperature for forecast ranges up to 72 h. These results are very encouraging and suggest that it is possible to take advantage of the information content of the surface sensitive observations over land if an adequate modeling of the emissivity and/or skin temperature is introduced. (Karbou et al. 2010, WAF)

8 Satellite Atmospheric Motion Vectors (Genkova et al. 2010; Cotton et al. 2012)

9 Current capabilities and efforts

10 In situ capabilities From Fink et al. (2010): 1. Surface station data and upper air information from radiosondes remain an essential source of information over land for weather forecast models Large volume of satellite data limited to cloud free pixels; Satellites provide indirect information, coarse vertical resolution; Limited use of satellite channels with peak sensitivity in lower troposphere. 2. Low level vertical profiles of temperature, humidity and wind are necessary to accurately predict the organisation of West African rainy systems and are crucial for determining oceanic moisture influx. Main GCOS Cooperation Mechanism (GCM) donors: Japan, Switzerland, KNMI (Netherlands), USA, Germany, Spain, Canada, UK. Renovation projects for radiosondes / telecommunications Mauritius, Tanzania, Sudan, Angola, Madagascar, DR Congo, Zambia, Sierra Leone

11 Remote Sensing Capabilities EUMETSAT Better defined moisture: AMSU B/MHS and IASI/AIRS SEVIRI radiances AMVs Coastal; Fire; Green monitoring (soil / vegetation) Radar network UK Met Office (used by S. Africa) and ECMWF Assimilation of aerosol optical depth, using SEVIRI and MODIS aerosol retrievals Assimilation of soil moisture using ASCAT, validation using SMOS satellite

12 Regional NWP: Africa model Aim to give African NMSs access to state of the art NWP Support through WMO Voluntary Cooperation Programme (WCP) 12 km resolution, 70 levels 3d Var Web products available (password required) Crown copyright Met Office New data assimilative 4km Lake Victoria model (based on UK4 config) for hazard warning: wind and lightning.

13 Challenges and Questions

14 Challenges Biases in radiosondes Different manufacturers different biases Biases in modeling systems Affects precipitation forecasts Information from observations lost rapidly Physical parameterizations require evaluation Unsuccessful bids for resources Make more directly relevant to operations need to exploit satellite data further

15 Evaluating data impact Data denial experiments time consuming Results take a few years to produce, by which time the observational network, models and DA will all have changed Heavy dependence on numerical model, data assimilation scheme, treatment / QC of data To what extent can results be generalized? Explore adjoint based observation impact?

16 Rolf Langland, NRL Monterey

17 AMMA: Phase 2 How to ensure that the increased radiosonde coverage introduced during AMMA is maintained? Phase 2 Pull through knowledge from Phase 1 Improve dynamical models Make use of available obs. (in situ; remote sensing) Suggest new observations (for MCS, AEWs) Maintain link with THORPEX

18 High impact weather events Have event based verifications been made? Is the spatial and temporal density of the observational network commensurate with the space and time scales of mesoscale systems? What is the state of regional mesoscale modeling? Global models are approaching mesoscale (ECMWF 16 km, ECMWF EPS 30 km, NCEP 27 km) Is there a need for regional modeling? Convective scale modeling and DA is a work in progress and requires a lot of research.

19 New observation types? Extend AMDAR capability? Automated radiosonde stations? HYMEX? Adhere to climate monitoring principles where possible Need cost benefit analyses of the impact of observing systems?

20 Extra Slides

21 Scientific Questions on Observing Systems from THORPEX Africa Science Plan How to consolidate and maintain existing observing systems in Africa? Manageable telecommunications? What is the optimal combination and resolution of atmospheric, oceanic and land variables for highquality analyses and forecasts? What level of increase in observational coverage and quality is most important? How do we make observing systems more adaptive to changing needs? Cost effective way to mix platforms to optimize contribution to global systems?

22 Data Assimilation and Observing Strategies Questions from THORPEX Africa Science Plan How to contribute to better assimilation of remote sensing and aircraft observations? How can new observations contribute to better monitoring and forecasting of high impact weather? What are the suitable DA systems for African circulations, and how to we contribute to and support their improvement?

23 References : WAF Special Collection. Agustí Panareda A, Beljaars A, Cardinali C, Genkova I, Thorncroft C. 2010a. Impact of assimilating AMMA soundings on ECMWF analyses and forecasts. Weather and Forecasting 25: DOI: /2010WAF Agustí Panareda A, Beljaars A, Ahlgrimm M, Balsamo G, Bock O, Forbes R, Ghelli A, Guichard F, Koehler M, Meynadier R, Morcrette JJ. 2010b. The ECMWF re analysis for the AMMA observational campaign. Quarterly Journal of Royal Meterological Society 136: Bauer P D Var assimilation of MERIS total column water vapour retrievals over land. Quarterly Journal of Royal Meterological Society 135: Faccani, C., and Coauthors, 2009: The impact of the AMMA radiosonde data on the French global assimilation and forecast system. Wea. Forecasting, 24, Fink AH, Agustí Panareda A, Parker DJ, Lafore J P, Ngamini N B, Afiesimama E, Beljaars A, Bock O, Christoph M, Didé F, Faccani C, Fourrié N, Karbou F, Polcher J, Mumba Z, Nuret M, Pohle S, Rabier F, Tompkins AM, Wilson G Operational meteorology in West Africa: observational networks, weather analysis and forecasting. Atmospheric Science Letters 12: DOI: /asl.324. Karbou F, Gérard E, Rabier F. 2010a. Global 4D Var assimilation and forecast experiments using AMSU observations over land. Part I: impact of various land surface emissivity parameterizations. Weather and Forecasting 25: 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: Lafore J P, Flamant C, Guichard F, Parker DJ, Bouniol D, Fink AH, Giraud V, Gosset M, Hall N, Höller H, Jones SC, Protat A, Roca R, Roux F, Saïd F, Thorncroft C Progress in understanding of weather systems in West Africa. Atmospheric Science Letters 12: 7 12, DOI: /asl.335. Parker DJ, Fink AH, Janicot S, Ngamini JB, Douglas M, Afiesimama E, Agustí Panareda A, Beljaars A, Dide F, Diedhiou A, Lebel T, Polcher J, Redelsperger JL, Thorncroft C, Wilson GA The AMMA radiosonde program and its implications for the future of atmospheric monitoring over Africa. Bulletin of the American Meteorological Society 89:

24 Resources : ~13,500 hi res soundings in AMMA database international.org/ Recent initiatives to revitalize GCOS upper air and surface networks /5.5_Implementation_Projects.pdf MACC: monitoring atmospheric composition and climate atmosphere.eu

25 Recent DAOS WG meetings tations_thorpex_daos4_2011.html

26 Relative effectiveness of observations? Special rawinsondes Dropwindsondes From aircraft From driftsonde balloons AMDAR Radar winds and reflectivity Wind profilers?

27 UK Met Office (Iley/Saunders) Our work involved re establishing the Sierra Leone Observing Network and re starting weather forecast production by the Sierra Leone Met Department to both government & general public. At the moment the Obs from Lungi, Forbay College (Freetown), Kabala, Kenama, Rokupr &Njala are only available locally. The equipment is the same spec as used by the UKMO and all of the sites where in use until The UNDP, who paid the project did not have enough funds in FY11/12 for the next stage of making the obs available internationally (either via or message switch). We hope this will be funded sometime this year. One thing we are looking at here is soil moisture assimilation using ASCAT and validation of it using SMOS. The hope is that we will get improved precip forecasts particularly over Africa.

28 Comments from Rolf Langland Relative magnitude of uncertainty in atmospheric analyses (temperature etc) compared with developed nations? How well can we monitor climate change if the uncertainty in upper air observations is 2 3 times larger than in N. America or Europe?