Convection Parametrization and Multi-Nesting Dependence of a Heavy Rainfall Event over Namibia with Weather Research and Forecasting (WRF) Model

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.

Sensitivity of Simulations of Zambian Heavy Rainfall Events to the Atmospheric Boundary Layer Schemes

“…Given that the three events were selected because at least one ground observation reported over 90 mm of rainfall, we conclude that IMERG provides the best estimate of extreme rainfall. The QPE from TAMSAT for the 17 December 2016 and 21 January 2017 case studies is consistent with other recent studies in the region, in the sense that values were severely underestimated in simulating heavy rainfall associated with an ex-tropical cyclone [64] and a cut-off low system [66]. It may be noted that the ZMD station rainfall was used to calibrate the TAMSAT QPE [10,55].…”

“…All of the model configurations underestimated rainfall in the outer domain for all three case studies. Somses et al [66], who used the same convection scheme as in the current study, and Champion and Hodges [71] found similar results, that switching on the convection scheme results in lower rainfall intensities. Steeneveld and Peerlings [75] compared simulations of a hail storm over the Netherlands using different convection schemes, and concluded that scale-aware convection schemes can be beneficial for the representation of deep convection in the gray zone.…”

“…The rainfall amounts, however, are generally smaller compared to IMERG. In previous heavy rainfall studies with strong synoptic forcing from an ex-tropical cyclone over Botswana [64] and a cut-off low [65] over Namibia [66], TAMSAT was found to severely underestimate rainfall compared to ERA5 and IMERG. Thorne et al [67] found TAMSAT to perform well over plateau, but to underestimate rainfall in mountainous regions.…”

Sensitivity of Tropical Cyclone Idai Simulations to Cumulus Parametrization Schemes

“…The timing of the peak is found to be informed by the global model providing lateral boundary conditions, indicating a need to use global models with good skill when running dynamical downscalers. Previous other studies have shown that switching off the convection schemes results in higher rainfall intensity (e.g., [33,34]).…”

“…Some of the newer parameterization schemes were developed in a way that allows their behaviour to adapt with changing resolution, and these are called scale aware schemes, e.g., [31,32]. Somses et al [33] and Champion and Hodges [34] showed that switching off the convection scheme when a grid length of less than 5 km is used results in higher rainfall intensity being simulated. Furthermore, Steeneveld and Peerlings [29] indicated that the use of scale-aware schemes is beneficial for the representation of deep convection in the grey zones.…”