Benjamin Lamptey - African weather and climate research.
Two major research challenges of current interest are to reduce and mitigate natural disasters and to realize the societal and economic benefits of improved weather forecasts. Mesoscale numerical models can contribute greatly to improved weather forecasts in a given region. However, the model must be optimized or adapted for that geographical region.
Ben has been working with the Weather Research and Forecasting (WRF) model, the Community Land Model (CLM) as well as using datasets (both remotely sensed and in situ) for various analyses particularly over West Africa. Ben is trying to obtain an optimum WRF model configuration for both weather prediction and climate simulation over the region. The initial step is to assess how the standard model configuration performs over the region before making changes to improve its performance. Ben has performed a series of experiments in this regard using different combinations of parameterization schemes for the weather prediction mode.
Ben has also made a few necessary changes to the model and performed some test climate simulations. He is currently analyzing the model output to enable him obtain an optimum model configuration for climate simulation over the region. This climate version is to be used for regional climate change studies. This will expand on work done during Ben’s doctoral studies. Ben’s interest in how the weather systems over Africa will change in the light of climate change combines his expertise in modeling climate change acquired during his doctoral studies with his expertise in numerical weather prediction acquired during his postdoctoral fellowship. My current interest is in the value of weather and climate information in decision-making at the regional to local scale and for different time scales.
Ben is running the CLM in an offline mode and studying the response of the Model to (a) different atmospheric forcing data and (b) different surface data sets. The aim is to study the impact of the different datasets in reproducing some of the meteorological features (e.g. African Easterly waves) over the region. Planned studies include the impact of a coupled WRF-CLM versus an offline CLM in reproducing specific meteorological features.
To realize the societal and economic benefits of improved weather forecasts requires an end-to-end forecasting system. Ben with colleagues in the Research Applications Laboratory have a real-time modeling system currently generating forecasts over Africa.
The system, which will eventually be replicated in Africa to be maintained by Africans, is currently housed here in NCAR but the products are freely available to forecasters in Africa via the Internet (http://www.ral.ucar.edu/projects/wafrica). I have included still pictures of the real-time forecast below. Microsoft Corporation is using output from the real-time modeling system for a humanitarian project in Sudan. Effort is currently underway to utilize output from the real-time modeling system as input to agricultural models and also hydrological models for river forecasting.
ASP Spotlight September 2007
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