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- Author or Editor: Gregor Pante x
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Abstract
Climate models struggle to realistically represent the West African monsoon (WAM), which hinders reliable future projections and the development of adequate adaption measures. Low-level clouds over southern West Africa (5°–10°N, 8°W–8°E) during July–September are an integral part of the WAM through their effect on the surface energy balance and precipitation, but their representation in climate models has received little attention. Here 30 (20) years of output from 18 (8) models participating in phase 5 of the Coupled Model Intercomparison Project (Year of Tropical Convection) are used to identify cloud biases and their causes. Compared to ERA-Interim reanalyses, many models show large biases in low-level cloudiness of both signs and a tendency to too high elevation and too weak diurnal cycles. At the same time, these models tend to have too strong low-level jets, the impact of which is unclear because of concomitant effects on temperature and moisture advection as well as turbulent mixing. Part of the differences between the models and ERA-Interim appear to be related to the different subgrid cloud schemes used. While nighttime tendencies in temperature and humidity are broadly realistic in most models, daytime tendencies show large problems with the vertical transport of heat and moisture. Many models simulate too low near-surface relative humidities, leading to insufficient low cloud cover and abundant solar radiation, and thus a too large diurnal cycle in temperature and relative humidity. In the future, targeted model sensitivity experiments will be needed to test possible feedback mechanisms between low clouds, radiation, boundary layer dynamics, precipitation, and the WAM circulation.
Abstract
Climate models struggle to realistically represent the West African monsoon (WAM), which hinders reliable future projections and the development of adequate adaption measures. Low-level clouds over southern West Africa (5°–10°N, 8°W–8°E) during July–September are an integral part of the WAM through their effect on the surface energy balance and precipitation, but their representation in climate models has received little attention. Here 30 (20) years of output from 18 (8) models participating in phase 5 of the Coupled Model Intercomparison Project (Year of Tropical Convection) are used to identify cloud biases and their causes. Compared to ERA-Interim reanalyses, many models show large biases in low-level cloudiness of both signs and a tendency to too high elevation and too weak diurnal cycles. At the same time, these models tend to have too strong low-level jets, the impact of which is unclear because of concomitant effects on temperature and moisture advection as well as turbulent mixing. Part of the differences between the models and ERA-Interim appear to be related to the different subgrid cloud schemes used. While nighttime tendencies in temperature and humidity are broadly realistic in most models, daytime tendencies show large problems with the vertical transport of heat and moisture. Many models simulate too low near-surface relative humidities, leading to insufficient low cloud cover and abundant solar radiation, and thus a too large diurnal cycle in temperature and relative humidity. In the future, targeted model sensitivity experiments will be needed to test possible feedback mechanisms between low clouds, radiation, boundary layer dynamics, precipitation, and the WAM circulation.
Abstract
Two extreme, high-impact events of heavy rainfall and severe floods in West African urban areas (Ouagadougou on 1 September 2009 and Dakar on 26 August 2012) are investigated with respect to their atmospheric causes and statistical return periods. In terms of the synoptic–convective dynamics, the Ouagadougou case is truly extraordinary. A succession of two slow-moving African easterly waves (AEWs) caused record-breaking values of tropospheric moisture. The second AEW, one of the strongest in recent decades, provided the synoptic forcing for the nighttime genesis of mesoscale convective systems (MCSs). Ouagadougou was hit by two MCSs within 6 h, as the strong convergence and rotation in the AEW-related vortex allowed a swift moisture refueling. An AEW was also instrumental in the overnight development of MCSs in the Dakar case, but neither the AEW vortex nor the tropospheric moisture content was as exceptional as in the Ouagadougou case. Tropical Rainfall Measuring Mission (TRMM) 3B42 precipitation data show some promise in estimating centennial return values (RVs) using the “peak over threshold” approach with a generalized Pareto distribution fit, although indications for errors in estimating extreme rainfall over the arid Sahel are found. In contrast, the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) dataset seems less suitable for this purpose despite the longer record. Notably, the Ouagadougou event demonstrates that highly unusual dynamical developments can create extremes well outside of RV estimates from century-long rainfall observations. Future research will investigate whether such developments may become more frequent in a warmer climate.
Abstract
Two extreme, high-impact events of heavy rainfall and severe floods in West African urban areas (Ouagadougou on 1 September 2009 and Dakar on 26 August 2012) are investigated with respect to their atmospheric causes and statistical return periods. In terms of the synoptic–convective dynamics, the Ouagadougou case is truly extraordinary. A succession of two slow-moving African easterly waves (AEWs) caused record-breaking values of tropospheric moisture. The second AEW, one of the strongest in recent decades, provided the synoptic forcing for the nighttime genesis of mesoscale convective systems (MCSs). Ouagadougou was hit by two MCSs within 6 h, as the strong convergence and rotation in the AEW-related vortex allowed a swift moisture refueling. An AEW was also instrumental in the overnight development of MCSs in the Dakar case, but neither the AEW vortex nor the tropospheric moisture content was as exceptional as in the Ouagadougou case. Tropical Rainfall Measuring Mission (TRMM) 3B42 precipitation data show some promise in estimating centennial return values (RVs) using the “peak over threshold” approach with a generalized Pareto distribution fit, although indications for errors in estimating extreme rainfall over the arid Sahel are found. In contrast, the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) dataset seems less suitable for this purpose despite the longer record. Notably, the Ouagadougou event demonstrates that highly unusual dynamical developments can create extremes well outside of RV estimates from century-long rainfall observations. Future research will investigate whether such developments may become more frequent in a warmer climate.
