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- Author or Editor: John H. Marsham x
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Abstract
The East African precipitation seasonal cycle is of significant societal importance, and yet the current generation of coupled global climate models fails to correctly capture this seasonality. The use of convective parameterization schemes is a known source of precipitation bias in such models. Recently, a high-resolution regional model was used to produce the first pan-African climate change simulation that explicitly models convection. Here, this is compared with a corresponding parameterized-convection simulation to explore the effect of the parameterization on representation of East Africa precipitation seasonality. Both models capture current seasonality, although an overestimate in September–October in the parameterized simulation leads to an early bias in the onset of the boreal autumn short rains, associated with higher convective instability and near-surface moist static energy. This bias is removed in the explicit model. Under future climate change both models show the short rains getting later and wetter. For the boreal spring long rains, the explicit convection simulation shows the onset advancing but the parameterized simulation shows little change. Over Uganda and western Kenya both simulations show rainfall increases in the January–February dry season and large increases in boreal summer and autumn rainfall, particularly in the explicit convection model, changing the shape of the seasonal cycle, with potential for pronounced socioeconomic impacts. Interannual variability is similar in both models. Results imply that parameterization of convection may be a source of uncertainty for projections of changes in seasonal timing from global models and that potentially impactful changes in seasonality should be highlighted to users.
Abstract
The East African precipitation seasonal cycle is of significant societal importance, and yet the current generation of coupled global climate models fails to correctly capture this seasonality. The use of convective parameterization schemes is a known source of precipitation bias in such models. Recently, a high-resolution regional model was used to produce the first pan-African climate change simulation that explicitly models convection. Here, this is compared with a corresponding parameterized-convection simulation to explore the effect of the parameterization on representation of East Africa precipitation seasonality. Both models capture current seasonality, although an overestimate in September–October in the parameterized simulation leads to an early bias in the onset of the boreal autumn short rains, associated with higher convective instability and near-surface moist static energy. This bias is removed in the explicit model. Under future climate change both models show the short rains getting later and wetter. For the boreal spring long rains, the explicit convection simulation shows the onset advancing but the parameterized simulation shows little change. Over Uganda and western Kenya both simulations show rainfall increases in the January–February dry season and large increases in boreal summer and autumn rainfall, particularly in the explicit convection model, changing the shape of the seasonal cycle, with potential for pronounced socioeconomic impacts. Interannual variability is similar in both models. Results imply that parameterization of convection may be a source of uncertainty for projections of changes in seasonal timing from global models and that potentially impactful changes in seasonality should be highlighted to users.
Abstract
The onset of the West African monsoon (WAM) marks a vital time for local and regional stakeholders. While the seasonal progression of monsoon winds and the related migration of precipitation from the Guinea Coast toward the Sudan/Sahel is apparent, there exist contrasting man-made definitions of what the WAM onset means. Broadly speaking, onset can be analyzed regionally, locally, or over a designated intermediate scale. There are at least 18 distinct definitions of the WAM onset in publication, with little work done on comparing observed onset from different definitions or comparing onset realizations across different datasets and resolutions. Here, nine definitions have been calculated using multiple datasets of different metrics at different resolutions. It is found that mean regional onset dates are consistent across multiple datasets and different definitions. There is low interannual variability in regional onset, suggesting that regional seasonal forecasting of the onset provides few benefits over climatology. In contrast, local onsets show high spatial, interannual, and interdefinition variability. Furthermore, it is found that there is little correlation between local onset dates and regional onset dates across West Africa, implying a disharmony between regional measures of onset and the experience on a local scale. The results of this study show that evaluation of seasonal monsoon onset forecasts is far from straightforward. Given a seasonal forecasting model, it is possible to simultaneously have a good and a bad prediction of monsoon onset simply through selection of the onset definition and observational dataset used for comparison.
Abstract
The onset of the West African monsoon (WAM) marks a vital time for local and regional stakeholders. While the seasonal progression of monsoon winds and the related migration of precipitation from the Guinea Coast toward the Sudan/Sahel is apparent, there exist contrasting man-made definitions of what the WAM onset means. Broadly speaking, onset can be analyzed regionally, locally, or over a designated intermediate scale. There are at least 18 distinct definitions of the WAM onset in publication, with little work done on comparing observed onset from different definitions or comparing onset realizations across different datasets and resolutions. Here, nine definitions have been calculated using multiple datasets of different metrics at different resolutions. It is found that mean regional onset dates are consistent across multiple datasets and different definitions. There is low interannual variability in regional onset, suggesting that regional seasonal forecasting of the onset provides few benefits over climatology. In contrast, local onsets show high spatial, interannual, and interdefinition variability. Furthermore, it is found that there is little correlation between local onset dates and regional onset dates across West Africa, implying a disharmony between regional measures of onset and the experience on a local scale. The results of this study show that evaluation of seasonal monsoon onset forecasts is far from straightforward. Given a seasonal forecasting model, it is possible to simultaneously have a good and a bad prediction of monsoon onset simply through selection of the onset definition and observational dataset used for comparison.
Abstract
The West African monsoon (WAM) is the dominant feature of West African climate providing the majority of annual rainfall. Projections of future rainfall over the West African Sahel are deeply uncertain, with a key reason likely to be moist convection, which is typically parameterized in global climate models. Here, we use a pan-African convection-permitting simulation (CP4), alongside a parameterized convection simulation (P25), to determine the key processes that underpin the effect of explicit convection on the climate change of the central West African Sahel (12°–17°N, 8°W–2°E). In current climate, CP4 affects WAM processes on multiple scales compared to P25. There are differences in the diurnal cycles of rainfall, moisture convergence, and atmospheric humidity. There are upscale impacts: the WAM penetrates farther north, there is greater humidity over the northern Sahel and the Saharan heat low regions, the subtropical subsidence rate over the Sahara is weaker, and ascent within the tropical rain belt is deeper. Under climate change, the WAM shifts northward and Hadley circulation weakens in P25 and CP4. The differences between P25 and CP4 persist, however, underpinned by process differences at the diurnal scale and large scale. Mean rainfall increases 17.1% in CP4 compared to 6.7% in P25 and there is greater weakening in tropical ascent and subtropical subsidence in CP4. These findings show the limitations of parameterized convection and demonstrate the value that explicit convection simulations can provide to climate modelers and climate policy decision makers.
Abstract
The West African monsoon (WAM) is the dominant feature of West African climate providing the majority of annual rainfall. Projections of future rainfall over the West African Sahel are deeply uncertain, with a key reason likely to be moist convection, which is typically parameterized in global climate models. Here, we use a pan-African convection-permitting simulation (CP4), alongside a parameterized convection simulation (P25), to determine the key processes that underpin the effect of explicit convection on the climate change of the central West African Sahel (12°–17°N, 8°W–2°E). In current climate, CP4 affects WAM processes on multiple scales compared to P25. There are differences in the diurnal cycles of rainfall, moisture convergence, and atmospheric humidity. There are upscale impacts: the WAM penetrates farther north, there is greater humidity over the northern Sahel and the Saharan heat low regions, the subtropical subsidence rate over the Sahara is weaker, and ascent within the tropical rain belt is deeper. Under climate change, the WAM shifts northward and Hadley circulation weakens in P25 and CP4. The differences between P25 and CP4 persist, however, underpinned by process differences at the diurnal scale and large scale. Mean rainfall increases 17.1% in CP4 compared to 6.7% in P25 and there is greater weakening in tropical ascent and subtropical subsidence in CP4. These findings show the limitations of parameterized convection and demonstrate the value that explicit convection simulations can provide to climate modelers and climate policy decision makers.
Abstract
Climate change is expected to increase the frequency and intensity of rainfall extremes. Understanding future changes in rainfall is necessary for adaptation planning. Eastern Africa is vulnerable to rainfall extremes because of low adaptive capacity and high future population growth. Convection-permitting climate models have been found to better represent moderate (yearly) rainfall extremes than parameterized convection models, but there is limited analysis of rare extremes that occur less frequently than once per year. These events often have the largest socioeconomic impacts. We use extreme value theory and regional frequency analysis to quantify rare rainfall extremes over East Africa in a convection-permitting climate model (CP4A). We compare the results with its parameterized counterpart (P25), the Coordinated Regional Climate Downscaling Experiment for the African region (CORDEX-Africa) ensemble, and observations to understand how the convection parameterization impacts the results. We find that CP4A better matches observations than the parameterized models. With climate change, we find the parameterized convection models have unrealistically high changes in the shape parameter of the extreme value distribution, which controls the tail behavior (i.e., the most extreme events), leading to large increases in return levels of events with a return period of >20 years. This suggests that parameterized convection models may not be suitable for looking at relative changes in rare rainfall events with climate change and that convection-permitting models should be preferred for this type of work. With the more realistic CP4A, RCP8.5 end-of-century climate change leads to 1-in-100-yr events becoming 1-in-23-yr events, which will necessitate serious adaptation efforts to avoid devastating socioeconomic impacts.
Significance Statement
We use a new, high-resolution climate model to examine how rare extreme rainfall events in East Africa might change in the future with climate change and compare the results with those from standard-resolution climate models. We find that the standard-resolution models have unrealistically large increases in rainfall for events that occur less frequently than every 20 years. The high-resolution model is more realistic and is required to illustrate possible future changes in rare rainfall extremes. Extreme events will become more common with climate change, and in the more realistic model we show that a 1-in-100-yr event may become a 1-in-23-yr event by the end of the century if greenhouse gas emissions are not significantly reduced.
Abstract
Climate change is expected to increase the frequency and intensity of rainfall extremes. Understanding future changes in rainfall is necessary for adaptation planning. Eastern Africa is vulnerable to rainfall extremes because of low adaptive capacity and high future population growth. Convection-permitting climate models have been found to better represent moderate (yearly) rainfall extremes than parameterized convection models, but there is limited analysis of rare extremes that occur less frequently than once per year. These events often have the largest socioeconomic impacts. We use extreme value theory and regional frequency analysis to quantify rare rainfall extremes over East Africa in a convection-permitting climate model (CP4A). We compare the results with its parameterized counterpart (P25), the Coordinated Regional Climate Downscaling Experiment for the African region (CORDEX-Africa) ensemble, and observations to understand how the convection parameterization impacts the results. We find that CP4A better matches observations than the parameterized models. With climate change, we find the parameterized convection models have unrealistically high changes in the shape parameter of the extreme value distribution, which controls the tail behavior (i.e., the most extreme events), leading to large increases in return levels of events with a return period of >20 years. This suggests that parameterized convection models may not be suitable for looking at relative changes in rare rainfall events with climate change and that convection-permitting models should be preferred for this type of work. With the more realistic CP4A, RCP8.5 end-of-century climate change leads to 1-in-100-yr events becoming 1-in-23-yr events, which will necessitate serious adaptation efforts to avoid devastating socioeconomic impacts.
Significance Statement
We use a new, high-resolution climate model to examine how rare extreme rainfall events in East Africa might change in the future with climate change and compare the results with those from standard-resolution climate models. We find that the standard-resolution models have unrealistically large increases in rainfall for events that occur less frequently than every 20 years. The high-resolution model is more realistic and is required to illustrate possible future changes in rare rainfall extremes. Extreme events will become more common with climate change, and in the more realistic model we show that a 1-in-100-yr event may become a 1-in-23-yr event by the end of the century if greenhouse gas emissions are not significantly reduced.
Abstract
Eastern Africa’s fast-growing population is vulnerable to changing rainfall and extremes. Using the first pan-African climate change simulations that explicitly model the rainfall-generating convection, we investigate both the climate change response of key mesoscale drivers of eastern African rainfall, such as sea and lake breezes, and the spatial heterogeneity of rainfall responses. The explicit model shows widespread increases at the end of the century in mean (~40%) and extreme (~50%) rain rates, whereas the sign of changes in rainfall frequency has large spatial heterogeneity (from −50% to over +90%). In comparison, an equivalent parameterized simulation has greater moisture convergence and total rainfall increase over the eastern Congo and less over eastern Africa. The parameterized model also does not capture 1) the large heterogeneity of changes in rain frequency; 2) the widespread and large increases in extreme rainfall, which result from increased rainfall per humidity change; and 3) the response of rainfall to the changing sea breeze, even though the sea-breeze change is captured. Consequently, previous rainfall projections are likely inadequate for informing many climate-sensitive decisions—for example, for infrastructure in coastal cities. We consider the physics revealed here and its implications to be relevant for many other vulnerable tropical regions, especially those with coastal convection.
Abstract
Eastern Africa’s fast-growing population is vulnerable to changing rainfall and extremes. Using the first pan-African climate change simulations that explicitly model the rainfall-generating convection, we investigate both the climate change response of key mesoscale drivers of eastern African rainfall, such as sea and lake breezes, and the spatial heterogeneity of rainfall responses. The explicit model shows widespread increases at the end of the century in mean (~40%) and extreme (~50%) rain rates, whereas the sign of changes in rainfall frequency has large spatial heterogeneity (from −50% to over +90%). In comparison, an equivalent parameterized simulation has greater moisture convergence and total rainfall increase over the eastern Congo and less over eastern Africa. The parameterized model also does not capture 1) the large heterogeneity of changes in rain frequency; 2) the widespread and large increases in extreme rainfall, which result from increased rainfall per humidity change; and 3) the response of rainfall to the changing sea breeze, even though the sea-breeze change is captured. Consequently, previous rainfall projections are likely inadequate for informing many climate-sensitive decisions—for example, for infrastructure in coastal cities. We consider the physics revealed here and its implications to be relevant for many other vulnerable tropical regions, especially those with coastal convection.
Abstract
The canonical view of the Maritime Continent (MC) diurnal cycle is deep convection occurring over land during the afternoon and evening, tending to propagate offshore overnight. However, there is considerable day-to-day variability in the convection, and the mechanism of the offshore propagation is not well understood. We test the hypothesis that large-scale drivers such as ENSO, the MJO, and equatorial waves, through their modification of the local circulation, can modify the direction or strength of the propagation, or prevent the deep convection from triggering in the first place. Taking a local-to-large scale approach, we use in situ observations, satellite data, and reanalyses for five MC coastal regions, and show that the occurrence of the diurnal convection and its offshore propagation is closely tied to coastal wind regimes that we define using the k-means cluster algorithm. Strong prevailing onshore winds are associated with a suppressed diurnal cycle of precipitation, while prevailing offshore winds are associated with an active diurnal cycle, offshore propagation of convection, and a greater risk of extreme rainfall. ENSO, the MJO, equatorial Rossby waves, and westward mixed Rossby–gravity waves have varying levels of control over which coastal wind regime occurs, and therefore on precipitation, depending on the MC coastline in question. The large-scale drivers associated with dry and wet regimes are summarized for each location as a reference for forecasters.
Abstract
The canonical view of the Maritime Continent (MC) diurnal cycle is deep convection occurring over land during the afternoon and evening, tending to propagate offshore overnight. However, there is considerable day-to-day variability in the convection, and the mechanism of the offshore propagation is not well understood. We test the hypothesis that large-scale drivers such as ENSO, the MJO, and equatorial waves, through their modification of the local circulation, can modify the direction or strength of the propagation, or prevent the deep convection from triggering in the first place. Taking a local-to-large scale approach, we use in situ observations, satellite data, and reanalyses for five MC coastal regions, and show that the occurrence of the diurnal convection and its offshore propagation is closely tied to coastal wind regimes that we define using the k-means cluster algorithm. Strong prevailing onshore winds are associated with a suppressed diurnal cycle of precipitation, while prevailing offshore winds are associated with an active diurnal cycle, offshore propagation of convection, and a greater risk of extreme rainfall. ENSO, the MJO, equatorial Rossby waves, and westward mixed Rossby–gravity waves have varying levels of control over which coastal wind regime occurs, and therefore on precipitation, depending on the MC coastline in question. The large-scale drivers associated with dry and wet regimes are summarized for each location as a reference for forecasters.
Abstract
The representation of convection remains one of the most important sources of bias in global models, and evaluation methods are needed that show that models provide the correct mean state and variability, both for the correct reasons. Here we develop a novel approach for evaluating rainfall variability due to convectively coupled Kelvin waves (CCKWs) in this region. A phase cycle was defined for the CCKW cycle in OLR and used to composite rainfall anomalies. We characterize the observed (TRMM) rainfall response to CCKWs over tropical Africa in April and evaluate the performance of regional climate model (RCM) simulations: a parameterized convection simulation (P25) and the first pan-Africa convection-permitting simulation (CP4). TRMM mean rainfall is enhanced and suppressed by CCKW activity, and the occurrence of extreme rainfall and dry days is coupled with CCKW activity. Focusing on regional differences, we show for the first time that there is a dipole between West Africa and the Gulf of Guinea involving onshore/offshore shifts in rainfall, and the transition to enhanced rainfall over west equatorial Africa occurs one phase before the transition over east equatorial Africa. The global model used to drive the RCMs simulated CCKWs with mean amplitudes of 75%–82% of observations. The RCMs simulated coherent responses to the CCKWs and captured the large-scale spatial patterns and phase relationships in rainfall although the simulated rainfall response is weaker than observations and there are regional biases that are bigger away from the equator. P25 produced a closer match to TRMM mean rainfall anomalies than CP4 although the response in dry days was more closely simulated by CP4.
Abstract
The representation of convection remains one of the most important sources of bias in global models, and evaluation methods are needed that show that models provide the correct mean state and variability, both for the correct reasons. Here we develop a novel approach for evaluating rainfall variability due to convectively coupled Kelvin waves (CCKWs) in this region. A phase cycle was defined for the CCKW cycle in OLR and used to composite rainfall anomalies. We characterize the observed (TRMM) rainfall response to CCKWs over tropical Africa in April and evaluate the performance of regional climate model (RCM) simulations: a parameterized convection simulation (P25) and the first pan-Africa convection-permitting simulation (CP4). TRMM mean rainfall is enhanced and suppressed by CCKW activity, and the occurrence of extreme rainfall and dry days is coupled with CCKW activity. Focusing on regional differences, we show for the first time that there is a dipole between West Africa and the Gulf of Guinea involving onshore/offshore shifts in rainfall, and the transition to enhanced rainfall over west equatorial Africa occurs one phase before the transition over east equatorial Africa. The global model used to drive the RCMs simulated CCKWs with mean amplitudes of 75%–82% of observations. The RCMs simulated coherent responses to the CCKWs and captured the large-scale spatial patterns and phase relationships in rainfall although the simulated rainfall response is weaker than observations and there are regional biases that are bigger away from the equator. P25 produced a closer match to TRMM mean rainfall anomalies than CP4 although the response in dry days was more closely simulated by CP4.
Abstract
The Hadley circulation and tropical rain belt are dominant features of African climate. Moist convection provides ascent within the rain belt, but must be parameterized in climate models, limiting predictions. Here, we use a pan-African convection-permitting model (CPM), alongside a parameterized convection model (PCM), to analyze how explicit convection affects the rain belt under climate change. Regarding changes in mean climate, both models project an increase in total column water (TCW), a widespread increase in rainfall, and slowdown of subtropical descent. Regional climate changes are similar for annual mean rainfall but regional changes of ascent typically strengthen less or weaken more in the CPM. Over a land-only meridional transect of the rain belt, the CPM mean rainfall increases less than in the PCM (5% vs 14%) but mean vertical velocity at 500 hPa weakens more (17% vs 10%). These changes mask more fundamental changes in underlying distributions. The decrease in 3-hourly rain frequency and shift from lighter to heavier rainfall are more pronounced in the CPM and accompanied by a shift from weak to strong updrafts with the enhancement of heavy rainfall largely due to these dynamic changes. The CPM has stronger coupling between intense rainfall and higher TCW. This yields a greater increase in rainfall contribution from events with greater TCW, with more rainfall for a given large-scale ascent, and so favors slowing of that ascent. These findings highlight connections between the convective-scale and larger-scale flows and emphasize that limitations of parameterized convection have major implications for planning adaptation to climate change.
Abstract
The Hadley circulation and tropical rain belt are dominant features of African climate. Moist convection provides ascent within the rain belt, but must be parameterized in climate models, limiting predictions. Here, we use a pan-African convection-permitting model (CPM), alongside a parameterized convection model (PCM), to analyze how explicit convection affects the rain belt under climate change. Regarding changes in mean climate, both models project an increase in total column water (TCW), a widespread increase in rainfall, and slowdown of subtropical descent. Regional climate changes are similar for annual mean rainfall but regional changes of ascent typically strengthen less or weaken more in the CPM. Over a land-only meridional transect of the rain belt, the CPM mean rainfall increases less than in the PCM (5% vs 14%) but mean vertical velocity at 500 hPa weakens more (17% vs 10%). These changes mask more fundamental changes in underlying distributions. The decrease in 3-hourly rain frequency and shift from lighter to heavier rainfall are more pronounced in the CPM and accompanied by a shift from weak to strong updrafts with the enhancement of heavy rainfall largely due to these dynamic changes. The CPM has stronger coupling between intense rainfall and higher TCW. This yields a greater increase in rainfall contribution from events with greater TCW, with more rainfall for a given large-scale ascent, and so favors slowing of that ascent. These findings highlight connections between the convective-scale and larger-scale flows and emphasize that limitations of parameterized convection have major implications for planning adaptation to climate change.
Abstract
The precipitation and diabatic heating resulting from moist convection make it a key component of the atmospheric water budget in the tropics. With convective parameterization being a known source of uncertainty in global models, convection-permitting (CP) models are increasingly being used to improve understanding of regional climate. Here, a new 10-yr CP simulation is used to study the characteristics of rainfall and atmospheric water budget for East Africa and the Lake Victoria basin. The explicit representation of convection leads to a widespread improvement in the intensities and diurnal cycle of rainfall when compared with a parameterized simulation. Differences in large-scale moisture fluxes lead to a shift in the mean rainfall pattern from the Congo to Lake Victoria basin in the CP simulation—highlighting the important connection between local changes in the representation of convection and larger-scale dynamics and rainfall. Stronger lake–land contrasts in buoyancy in the CP model lead to a stronger nocturnal land breeze over Lake Victoria, increasing evaporation and moisture flux convergence (MFC), and likely unrealistically high rainfall. However, for the mountains east of the lake, the CP model produces a diurnal rainfall cycle much more similar to satellite estimates, which is related to differences in the timing of MFC. Results here demonstrate that, while care is needed regarding lake forcings, a CP approach offers a more realistic representation of several rainfall characteristics through a more physically based realization of the atmospheric dynamics around the complex topography of East Africa.
Abstract
The precipitation and diabatic heating resulting from moist convection make it a key component of the atmospheric water budget in the tropics. With convective parameterization being a known source of uncertainty in global models, convection-permitting (CP) models are increasingly being used to improve understanding of regional climate. Here, a new 10-yr CP simulation is used to study the characteristics of rainfall and atmospheric water budget for East Africa and the Lake Victoria basin. The explicit representation of convection leads to a widespread improvement in the intensities and diurnal cycle of rainfall when compared with a parameterized simulation. Differences in large-scale moisture fluxes lead to a shift in the mean rainfall pattern from the Congo to Lake Victoria basin in the CP simulation—highlighting the important connection between local changes in the representation of convection and larger-scale dynamics and rainfall. Stronger lake–land contrasts in buoyancy in the CP model lead to a stronger nocturnal land breeze over Lake Victoria, increasing evaporation and moisture flux convergence (MFC), and likely unrealistically high rainfall. However, for the mountains east of the lake, the CP model produces a diurnal rainfall cycle much more similar to satellite estimates, which is related to differences in the timing of MFC. Results here demonstrate that, while care is needed regarding lake forcings, a CP approach offers a more realistic representation of several rainfall characteristics through a more physically based realization of the atmospheric dynamics around the complex topography of East Africa.
Abstract
Extreme rainfall is expected to increase under climate change, carrying potential socioeconomic risks. However, the magnitude of increase is uncertain. Over recent decades, extreme storms over the West African Sahel have increased in frequency, with increased vertical wind shear shown to be a cause. Drier midlevels, stronger cold pools, and increased storm organization have also been observed. Global models do not capture the potential effects of lower- to midtropospheric wind shear or cold pools on storm organization since they parameterize convection. Here we use the first convection-permitting simulations of African climate change to understand how changes in thermodynamics and storm dynamics affect future extreme Sahelian rainfall. The model, which simulates warming associated with representative concentration pathway 8.5 (RCP8.5) until the end of the twenty-first century, projects a 28% increase of the extreme rain rate of MCSs. The Sahel moisture change on average follows Clausius–Clapeyron scaling, but has regional heterogeneity. Rain rates scale with the product of time-of-storm total column water (TCW) and in-storm vertical velocity. Additionally, prestorm wind shear and convective available potential energy both modulate in-storm vertical velocity. Although wind shear affects cloud-top temperatures within our model, it has no direct correlation with precipitation rates. In our model, projected future increase in TCW is the primary explanation for increased rain rates. Finally, although colder cold pools are modeled in the future climate, we see no significant change in near-surface winds, highlighting avenues for future research on convection-permitting modeling of storm dynamics.
Abstract
Extreme rainfall is expected to increase under climate change, carrying potential socioeconomic risks. However, the magnitude of increase is uncertain. Over recent decades, extreme storms over the West African Sahel have increased in frequency, with increased vertical wind shear shown to be a cause. Drier midlevels, stronger cold pools, and increased storm organization have also been observed. Global models do not capture the potential effects of lower- to midtropospheric wind shear or cold pools on storm organization since they parameterize convection. Here we use the first convection-permitting simulations of African climate change to understand how changes in thermodynamics and storm dynamics affect future extreme Sahelian rainfall. The model, which simulates warming associated with representative concentration pathway 8.5 (RCP8.5) until the end of the twenty-first century, projects a 28% increase of the extreme rain rate of MCSs. The Sahel moisture change on average follows Clausius–Clapeyron scaling, but has regional heterogeneity. Rain rates scale with the product of time-of-storm total column water (TCW) and in-storm vertical velocity. Additionally, prestorm wind shear and convective available potential energy both modulate in-storm vertical velocity. Although wind shear affects cloud-top temperatures within our model, it has no direct correlation with precipitation rates. In our model, projected future increase in TCW is the primary explanation for increased rain rates. Finally, although colder cold pools are modeled in the future climate, we see no significant change in near-surface winds, highlighting avenues for future research on convection-permitting modeling of storm dynamics.
