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Stepwise introduction of regional NWP

Transfer of Regional NWP Capabilities to Developing Countries Detlev Majewski, Deutscher Wetterdienst, Germany e-mail: detlev.majewski@dwd.de. Stepwise introduction of regional NWP. Defined at the WMO Workshops in Pretoria (2002) and Casablanca (2005):

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Stepwise introduction of regional NWP

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  1. Transfer of Regional NWP Capabilities to Developing CountriesDetlev Majewski, Deutscher Wetterdienst, Germanye-mail: detlev.majewski@dwd.de GEO CBC Hannover

  2. Stepwise introduction of regional NWP • Defined at the WMO Workshops in Pretoria (2002) and Casablanca (2005): • Acquiring and using existing NWP grid point products; • Acquiring and running a local NWP model without data analysis, but with verification; • Running a local model, without data analysis, fine tuning the system for the local region; with statistical adaptation; • Running a local model with local analysis of data. GEO CBC Hannover

  3. Observations atmosph. / surface Topographical data Lateral boundary conditions Verification Model diagnosis Data assimilation Regional NWP model DMO M O S Statistics Graphical applications Environmental predictions Sea wave prediction Other application models Agro-meteoro- logical models Meteorologists (public and private) Customers (public and private) Main components of a regional forecasting system and corresponding data flow GEO CBC Hannover

  4. Key issues for NWP capacity building • Defined at the WMO Workshops in Pretoria (2002) and Casablanca (2005) • Hardware (computer, internet access) • Software (operating system, compilers, regional NWP model, graphics) • Data (initial and lateral boundary data files; local observations) • Manpower (computer skills (Unix, Fortran, Web), meteorologist) • Training of NWP staff and forecasters • Modernization of complete forecasting process • Sustainability (involve universities, form regional co-operations) GEO CBC Hannover

  5. GME data as lateral boundary data of HRM The global model GME covers the Earth with an icosahedral-hexagonal grid; grid spacing: 40 km and 40 layers. 368642 grid points / layer Grid cell area of GME: 1384 km2 To cover a given HRM domain, only a small part of GME grid points is needed. If the HRM domain is 3000 x 3000 km2, the number of GME grid points is given by 3000 x 3000 / 1384 = 6500 only! Only these GME grid points are being transferred to the National Weather Service via the internet for running HRM. HRM GEO CBC Hannover

  6. HRM at KMD, Kenya Grid spacing: 0.25° ~ 28 km 26°E - 50°E 12°S - 12°N 97x97 grid points, 40 layers Linux PC server 1 processor Intel P4 1 GB RAM 2 scientists from 2001 until 2005. 3 scientists since 2006. http://www.meteo.go.ke/nwp/ GEO CBC Hannover

  7. Lessons learned, next steps • Introduce NWP stepwise, taking the local knowledge into account. • Build up a team of dedicated scientists, encourage networking with the HRM community worldwide, e.g. via http://groups.google.de/group/hrm_help. • Aim for early “showpieces” to convince local users. • Try to streamline the total forecasting process, not only the NWP part; involve the local forecasters quite early, e.g. in the definition of forecast products and graphics. • Start objective verification of the NWP model against local observations as soon as possible. • Try to involve local universities by offering the NWP model, data for case studies and computer resources. • Overall goal: Achieve a sustainable improvement of the forecasting process at the service. • Regional NWP Training in Botswana: 3 – 9 April 08 • Next Regional NWP Training Workshop at DWD: 14 - 25 July 08 GEO CBC Hannover

  8. Building blocks for regional NWP • Topographical data of region at ~ 1 km x 1 km resolution • Regional NWP model (e.g. ALADIN, HRM, MM5/WRF/ETA, RAMS) • Initial and lateral boundary data from global NWP model (e.g. GFS, GME, JMA, ECMWF) • Reliable and reasonable fast data connection between global centre and national weather service running the regional model • Computer system (Linux PC cluster) to run regional model • Graphical display of forecasts (e.g. GrADS, DIANA: Open Source Visualization of the Norwegian Met. Service); Web pages • Verification package (e.g. ORMVERIF) • Regional NWP training by advanced centres (e.g. Météo France, DWD, KMA, NCEP, UKMO, SAWS, ACMAD, WMO) • Training of computer skills (Linux, Fortran, html) • Training of local forecasters in model interpretation GEO CBC Hannover

  9. Questions? Any questions? HRM is used at: Bosnia, Botswana, Brazil (INMET, DHN), Bulgaria, China (Guangdong), India (SPL), Israel, Italy, Jordan, Kenya, Libya, Malawi, Mozambique, Nigeria, Oman, Pakistan, Philippines, Romania, Senegal, Spain, Tanzania, United Arab Emirates and Vietnam. http://www.met.gov.om/hrm/ Graphics by B. Ritter (DWD) GEO CBC Hannover

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