Abstract
Namibia is considered to be one of the countries that are most vulnerable to climate change due to its generally dry climate and the percentage of its population that rely on subsistence agriculture for their livelihoods. Early-warning systems are an important aspect of adapting to climate change. Weather forecasting relies on the use of numerical weather prediction models and these need to be configured properly. In this study, we investigate the effects of using multi-nests and a convection scheme on the simulation of a heavy rainfall event over the north-western region of Kunene, Namibia. The event, which was associated with a cut-off low system, was short-lived and resulted in over 45 mm of rainfall in one hour. For the multi-nest, a 9 km grid-length parent domain is nested within the Global Forecast System (GFS) simulations, which in turn forces a 3 km grid spacing child domain. A different set of simulations are produced using a single nest of 3 km grid spacing, nested directly inside the GFS data. The simulations are produced with the convection scheme switched on and off. The impact of a single versus multi-nest is found to be small in general, with slight differences in the location of high rainfall intensity. Switching off the convection schemes results in high rainfall intensity and increased detail in the simulations, including when a grid spacing of 9 km is used. Using a grid spacing of 3 km with the convection scheme on, results in a loss of detail in the simulations as well as lower rainfall amounts. The study shows a need for different configurations to be tested before an optimum configuration can be selected for operational forecasting. We recommend further tests with different synoptic forcing and convection schemes to be conducted to identify a suitable configuration for Namibia.
Highlights
Namibia is considered one of the most vulnerable countries to climate change, with annual losses due to impacts on the country’s natural resources expected to be up to 5% of the country’sGross Domestic Product (GDP) [1]
We investigate a heavy rainfall event over the north-western parts of Namibia in the Kunene region as simulated by the Weather Research and Forecasting (WRF) model
To our knowledge moisture converging over the region from the northeast and east of the sub-region and southwest no other numerical weather prediction (NWP) study has been published with a focus on the Kunene region or on Namibia in general
Summary
Namibia is considered one of the most vulnerable countries to climate change, with annual losses due to impacts on the country’s natural resources expected to be up to 5% of the country’s. Regional modelling or limited area modelling [22,23] allows forecasts to be produced with higher resolution than what is affordable with global models, over a limited area of interest, with a global model providing time-dependent lateral boundary conditions (LBCs) This procedure is used extensively both in numerical weather prediction (NWP) and the projection of regional future climate [13,24]. Convection-permitting models (CPMs) have been in use for several years producing operational weather forecasts especially by big meteorological centers (e.g., [27,28]) These systems have been found to improve rainfall forecasting skill compared to lower resolution models including over some parts of Africa (e.g., [29]). The Global Forecast System (GFS) [43] which has a grid length of 0.25◦ is used to provide the initial conditions as well as lateral boundary conditions for WRF, every three hours of model
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