Search

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.

The Maritime Continent experiences some of the world’s most severe convective rainfall, with an intense diurnal cycle. Akey feature is offshore propagation of convection overnight, having peaked over land during the evening. Existing hypotheses suggest this propagation is due to the nocturnal land breeze and environmental wind causing low-level convergence; and/or gravity waves triggering convection as they propagate. We use a convection-permitting configuration of the Met Office Unified Model over Sumatra to test these hypotheses, verifying against observations from the Japanese Years of the Maritime Continent field campaign. In selected case studies there is an organized squall line propagating with the land breeze density current, possibly reinforced by convective cold pools, at ∼3 m s−1 to around 150–300 km offshore. Propagation at these speeds is also seen in a composite mean diurnal cycle. The density current is verified by observations, with offshore low-level wind and virtual potential temperature showing a rapid decrease consistent with a density current front, accompanied by rainfall. Gravity waves are identified in the model with a typical phase speed of 16 m s−1. They trigger isolated cells of convection, usually further offshore and with much weaker precipitation than the squall line. Occasionally, the isolated convection may deepen and the rainfall intensify, if the gravity wave interacts with a substantial pre-existing perturbation such as shallow cloud. The localized convection triggered by gravity waves does not generally propagate at the wave’s own speed, but this phenomenon may appear as propagation along a wave trajectory in a composite that averages over many days of the diurnal cycle.

The first experiment studying the effect of irrigation on pre-monsoon rainfall in India using a high-resolution convection-permitting model has been carried out. This study includes both short (3-day) experiments and month-long free-running simulations, enabling investigation of the effect of irrigation on mesoscale circulations and associated rainfall. In the pre-monsoon, it is found that irrigation increases rainfall in our simulations. Intriguingly, the rainfall increase found in the high-resolution model mostly occurs on the mountains near the irrigation rather than over the irrigated region itself. This is because our applied irrigation is in low-lying regions, and so it enhances the mountain-valley flows leading to enhancement of diurnally driven orographic rainfall. Because Ganges basin irrigation occurs near mountains which already have some of the highest rainfall rates in the world, and which are subject to flash flooding and landslides, this has significant implications for hazards in mountainous regions during the pre-monsoon and early monsoon period.

Children (< 5 years) are highly vulnerable during hot weather, however the impacts of past and future warming on child mortality has never been estimated. Here, we use CMIP6 global climate models to quantify, for the first time, the heat-related child mortality that has already occurred (1995 – 2020) in Africa due to climate change, as well as estimate future burdens (2020 – 2050). By 2009, heat-related child mortality was already double what it would have been without climate change and outweighed any contributions from general improvements in development. Under a high emission scenario (SSP585) mortality will double by 2049 compared to 2005 - 2014. Mitigation will save lives; if 2050 temperature increases are kept to 1.5ºC, approx. 3900 – 6300 children could be saved annually in Africa compared to the SSP585 scenario. Our findings support the need for urgent mitigation and adaptation measures to save lives now and in the future.

Africa is poised for a revolution in the quality and relevance of weather predictions, with potential for great benefits in terms of human and economic security. This revolution will be driven by recent international progress in nowcasting, numerical weather prediction, theoretical tropical dynamics, and forecast communication, but will depend on suitable scientific investment being made. The commercial sector has recognized this opportunity and new forecast products are being made available to African stakeholders. At this time, it is vital that robust scientific methods are used to develop and evaluate the new generation of forecasts. The Global Challenges Research Fund (GCRF) African Science for Weather Information and Forecasting Techniques (SWIFT) project represents an international effort to advance scientific solutions across the fields of nowcasting, synoptic and short-range severe weather prediction, subseasonal-to-seasonal (S2S) prediction, user engagement, and forecast evaluation. This paper describes the opportunities facing African meteorology and the ways in which SWIFT is meeting those opportunities and identifying priority next steps. Delivery and maintenance of weather forecasting systems exploiting these new solutions requires a trained body of scientists with skills in research and training, modeling and operational prediction, and communications and leadership. By supporting partnerships between academia and operational agencies in four African partner countries, the SWIFT project is helping to build capacity and capability in African forecasting science. A highlight of SWIFT is the coordination of three weather forecasting “Testbeds”—the first of their kind in Africa—which have been used to bring new evaluation tools, research insights, user perspectives, and communications pathways into a semioperational forecasting environment.

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 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 summarised for each location as a reference for forecasters.

This paper investigates the value of weather and climate information at different timescales for decision making in the Tanzanian disaster risk reduction sector using non-monetary approaches. Interviews and surveys were conducted with institutions responsible for disaster management at national, regional and district level. A range of values were identified including: 1) making informed decisions for disaster preparedness, response, recovery and restoration related activities; 2) tailoring of directives and actions based on sectoral impacts; 3) identification of hotspot areas for diseases outbreaks and surplus food production. However, while, a number of guidelines, policies, acts and regulations for disaster risk reduction exist it is not clear how well they promote the use of weather and climate information across climate sensitive sectors. Nonetheless, we find that well-structured disaster risk reduction coordination across sectors and institutions from the national to district level exists, although there is a need for further development of integrated Early Warning Systems, and a common platform to evaluate effectiveness and usefulness of weather warnings and advisories. Key challenges to address in increasing the uptake of weather warnings and advisories include language barriers, limited dissemination to rural areas, and limited awareness of forecasts. Based on the findings of this study, we recommend further quantitative evaluation of the skill of the severe weather warnings issued by the Tanzania Meteorological Authority, and an assessment of how decisions and actions are made by recipients of the warnings in the disaster risk reduction sector at different stages in the warning, response and recovery process.

Tropical cyclones (TCs) in the Bay of Bengal can be extremely destructive when they make landfall in India and Bangladesh. Accurate prediction of their track and intensity is essential for disaster management. This study evaluates simulations of Bay of Bengal TCs using a regional convection-permitting atmosphere-ocean coupled model. The Met Office Unified Model atmosphere-only configuration (4.4 km horizontal grid spacing) is compared with a configuration coupled to a three-dimensional dynamical ocean model (2.2 km horizontal grid spacing). Simulations of six TCs from 2016–2019 show that both configurations produce accurate TC tracks for lead times of up to 6 days before landfall. Both configurations underestimate high wind speeds and high rain rates, and overestimate low wind speeds and low rain rates. The ocean-coupled configuration improves landfall timing predictions and reduces wind speed biases relative to observations outside the eyewall but underestimates maximum wind speeds in the eyewall for the most intense TCs. The coupled configuration produces weaker TCs than the atmosphere-only configuration, consistent with lower sea surface temperatures in the coupled model and an overestimated cooling response in TC wakes. Both model configurations accurately predict rain rate asymmetry, suggesting a good representation of TC dynamics. Much of the rain rate asymmetry variation in the simulations is related to wind shear variations, with a preference for higher rain rates in the down-shear left quadrant.

Pan-Africa convection-permitting regional climate model simulations have been performed to study the impact of high resolution and the explicit representation of atmospheric moist convection on the present and future climate of Africa. These unique simulations have allowed European and African climate scientists to understand the critical role that the representation of convection plays in the ability of a contemporary climate model to capture climate and climate change, including many impact-relevant aspects such as rainfall variability and extremes. There are significant improvements in not only the small-scale characteristics of rainfall such as its intensity and diurnal cycle, but also in the large-scale circulation. Similarly, effects of explicit convection affect not only projected changes in rainfall extremes, dry spells, and high winds, but also continental-scale circulation and regional rainfall accumulations. The physics underlying such differences are in many cases expected to be relevant to all models that use parameterized convection. In some cases physical understanding of small-scale change means that we can provide regional decision-makers with new scales of information across a range of sectors. We demonstrate the potential value of these simulations both as scientific tools to increase climate process understanding and, when used with other models, for direct user applications. We describe how these ground-breaking simulations have been achieved under the U.K. Government’s Future Climate for Africa Programme. We anticipate a growing number of such simulations, which we advocate should become a routine component of climate projection, and encourage international coordination of such computationally and human-resource expensive simulations as effectively as possible.

Seasonal forecasts of rainfall are considered the priority timescale by many users in the tropics. In East Africa, the primary operational seasonal forecast for the region is produced by the Greater Horn of Africa Climate Outlook Forum (GHACOF), and issued ahead of each rainfall season. This study evaluates and compares the GHACOF consensus forecasts with dynamical model forecasts from the UK Met Office GloSea5 seasonal prediction system for the two rainy seasons. GloSea demonstrates positive skill (r = 0.69) for the short rains at 1 month lead. In contrast, skill is low for the long rains due to lack of predictability of driving factors. For both seasons GHACOF forecasts show generally lower levels of skill than GloSea. Several systematic errors within the GHACOF forecasts are identified; the largest being the tendency to over-estimate the likelihood of near normal rainfall, with over 70% (80%) of forecasts giving this category the highest probability in the short (long) rains. In a more detailed evaluation of GloSea, a large wet bias, increasing with forecast lead time, is identified in the short rains. This bias is attributed to a developing cold SST bias in the eastern Indian Ocean, driving an easterly wind bias across the equatorial Indian Ocean. These biases affect the mean state moisture availability, and could act to reduce the ability of the dynamical model in predicting interannual variability, which may also be relevant to predictions from coupled models on longer timescales.

Tropical cyclones (TCs) forming over the Bay of Bengal can cause devastation when they make landfall in India and Bangladesh; accurate prediction of their track and intensity is essential for disaster management. TC intensity is moderated by heat, momentum and moisture exchanges between the atmosphere and ocean. In recent years there have been significant improvements in the skill of TC forecasts due to the implementation of coupled atmosphere-ocean models and high-resolution models capable of explicitly resolving small-scale physical processes influencing storm development. This study evaluates the representation of six TCs in the Bay of Bengal from 2016 to 2019, using both a Met Office Unified Model atmosphere-only configuration (ATM) with 4.4 km grid spacing, and coupled to a 2.2 km resolution NEMO (Nucleus for European Models of the Ocean) ocean model (CPL). To determine the impact of coupling on wind-driven mixing and ocean-atmosphere heat exchange, forecast sea surface temperature (SST) is compared to observations. The impact of coupling on track position and storm intensity is evaluated using predictions of minimum sea level pressure (MSLP) and 10 m maximum sustained winds (MSW). Representation of TC dynamics is assessed by analysing storm structure, using radius of maximum winds and rain rate asymmetry. Results from the three most intense TC case studies (Fani, Titli, and Vardah) show that SSTs in ATM are too high, while SSTs in CPL are slightly too low, with an overestimation of the cooling response in TC wakes. TC track position errors are small, but intensity error metrics for MSLP and MSW show biases relative to observations. Peak intensity is overestimated for Titli and Vardah in the ATM model configuration; the CPL model configuration generally produces weaker storms than the ATM model configuration. Wind speeds outside the storm centre are high compared to observations, with a greater bias in the ATM model configuration. Both model configurations produce accurate predictions of radius of maximum winds and rain rate asymmetry, suggesting a good representation of TC dynamics. Much of the variation in rain rate asymmetry in the forecasts can be explained by variations in wind shear.

Sub-Saharan Africa is one of the most food-insecure regions in the world, and is particularly vulnerable to the impacts of extreme climate events and climate change. To gain a better understanding of the present-day likelihood of extreme seasonal temperature and rainfall events, and their joint occurrence, we apply the UNprecedented Simulated Extremes using ENsembles (UNSEEN) approach to a large ensemble of high-resolution initialised climate simulations in three countries of Sub-Saharan Africa: Tanzania, Zambia and South Africa. We assess the annual likelihood of unprecedented seasonal temperature and precipitation extremes during the maize growing season (October-April), as key variables for maize productivity , and investigate the large-scale dynamics of the climate system that govern their occurrence. We estimate that there is a 3-4% chance per year of exceeding the present-day seasonal temperature records in the maize growing regions of these countries, and a 1-3.5% chance per year of exceeding the present-day seasonal precipitation records. Conversely, whilst we find a 2% and 5% chance per year of subceeding the present-day seasonal precipitation records in Zambia and Tanzania respectively, we find a very low chance (0-1% per year) of subceeding the present-day seasonal precipitation records in South Africa. We also use the large ensemble to investigate the large-scale dynamics of the climate extremes, finding that high temperature extremes tend to be associated with El Niño and positive IOD/SIOD events and low temperature extremes with La Niña and negative IOD/SIOD events. The drivers of precipitation extremes, however, differ between the countries. In South Africa, high (low) precipitation extremes are associated with La Niña (El Niño) events but otherwise the influence on extremes of ENSO, and even more so the IOD/SIOD, is weak or not seen in the ensemble, which invites further investigation. To explore implications for growing maize in these regions, we convert our unprecedented seasonal temperature estimates to daily maximum temperatures and our seasonal precipitation estimates to monthly precipitation indices and compare to climatic thresholds for maize. Combined with projected changes to crop suitability in much of sub-Saharan Africa, our analysis suggests the need for significant adaptation strategies that build food system resilience in the near and longer term.

The societal relevance of droughts in Africa underscores the need for improved understanding of the atmospheric processes that drive them. This study examined drought characteristics across Malawi, and the associated atmospheric circulation patterns, in observations, reanalysis and global climate models. Droughts were identified using the Standardised Precipitation and Evapotranspiration Index (SPEI) for the period 1965 to 2018. Atmospheric circulation patterns during droughts were examined and the main moisture fluxes into Malawi were identified. Despite differences in the frequency, and events being asynchronous at times, droughts exhibited characteristics that were statistically similar between northern and southern Malawi. Droughts in both regions were associated with anomalous circulation that typically worked to diminish moisture advection and thus convection. Differences in the structure of the anomalies were indicative of differences in mechanisms associated with droughts in the north and south of Malawi. Three main moisture flux pathways were identified, and categorized as northeasterly, southeasterly, and northwesterly, each with a unique correlation structure with precipitation and global SSTs. Positive and negative biases of varying magnitudes were noted for drought and rainfall characteristics across the range of CMIP5 models. Such biases can be attributed to biases in moisture fluxes whose variability was found to be a key driver of summer precipitation variability across Malawi. Despite biases in moisture fluxes and their influence on precipitation biases, the majority of models exhibited moisture flux-precipitation correlations consistent with observations and reanalysis. Results from the study highlight the extent to which climate models are reliable in simulating droughts and therefore of value in developing narratives of climate variability essential for long-term development planning.

Mean temperatures and their extremes have increased over Africa since the latter half of the 20th century and this trend is projected to continue, with very frequent, intense and often deadly heatwaves likely to occur very regularly over much of Africa by 2100. It is crucial that we understand the scale of the future increases in extremes and the driving mechanisms. We diagnose daily maximum wet bulb temperature heatwaves, which allows for both the impact of temperature and humidity, both critical for human health and survivability. During wet bulb heatwaves, humidity and cloud cover increase, which limits the surface shortwave radiation flux but increases longwave warming. It is found from observations and ERA5 reanalysis that approximately 30% of wet bulb heatwaves over Africa are associated with daily rainfall accumulations of more than 1 mm/day on the first day of the heatwave. The first ever pan-African convection-permitting climate model simulations of present-day and RCP8.5 future climate are utilised to illustrate the projected future change in heatwaves, their drivers and their sensitivity to the representation of convection. Compared to ERA5, the convection-permitting model better represents the frequency and magnitude of present-day wet bulb heatwaves than a version of the model with more traditional parameterised convection. The future change in heatwave frequency, duration and magnitude is also larger in the convective-scale simulation, suggesting CMIP-style models may underestimate the future change in wet bulb heat extremes over Africa. The main reason for the larger future change appears to be the ability of the model to produce larger anomalies relative to its climatology in precipitation, cloud and the surface energy balance.

East Africa has high rates of soil erosion which negatively impact agricultural yields. Climate projections suggest that rainfall intensity will increase in East Africa, which may increase soil erosion. Soil erosion estimates require information on rainfall erosivity, which is calculated using sub-daily storm characteristics that are known to be biased in traditional parameterized convection climate models. Convection-permitting climate models, which are run at higher resolution to negate the need for convection parameterisation, generally better represent rainfall intensity and frequency. We use a novel convection-permitting pan-Africa regional climate model (CP4A) to estimate rainfall erosivity in Tanzania and Malawi, and compare it to its parameterized counterpart (P25), to determine if there is a benefit to using convection permitting climate models to look at rainfall erosivity. We use 8-year historical and end-of-century RCP8.5 simulations to examine the impact of climate change on rainfall erosivity. We then apply the Revised Universal Soil Loss Equation (RUSLE), using the rainfall erosivity estimates from CP4A and P25, to calculate soil erosion in Tanzania and Malawi. The distribution of rainfall intensity and duration was closer to the TRMM rainfall observations in the convection permitting model than in the parameterized model before and after bias-correction. We found that rainfall erosivity was lower in the parameterized convection model than in CP4A due to differences in storm characteristics, even after bias-correction. These results suggest that parameterized convection regional and global climate models might under-estimate rainfall erosivity, and the associated soil erosion. We found high values of present day erosion associated with mountainous regions in Tanzania and Malawi in CP4A. Under climate change, areas at high risk of soil erosion expanded due to increases in rainfall intensity in CP4A. The levels of soil erosion were high enough to negatively impact on agricultural yields. Soil management was less effective in the future at reducing soil erosion risk than in the present day, and more extensive soil management may be required in the future to manage soil erosion and reduce the negative impacts of soil erosion on agriculture.

The key physical processes responsible for inner-core structural changes and associated fluctuations in the intensification rate for a recent, high-impact western North Pacific tropical cyclone that underwent rapid intensification [Nepartak (2016)] are investigated using a set of convection-permitting ensemble simulations. Fluctuations in the inner-core structure between ringlike and monopole states develop in 60% of simulations. A tangential momentum budget analysis of a single fluctuation reveals that during the ringlike phase, the tangential wind generally intensifies, whereas during the monopole phase, the tangential wind remains mostly constant. In both phases, the mean advection terms spin up the tangential wind in the boundary layer, whereas the eddy advection terms deepen the storm’s cyclonic circulation by spinning up the tangential wind between 1.5 and 4 km. Calculations of the azimuthally averaged, radially integrated vertical mass flux suggest that periods of near-constant tangential wind tendency are accompanied by a weaker eyewall updraft, which is unable to evacuate all the mass converging in the boundary layer. Composite analyses calculated from 18 simulations produce qualitatively similar results to those from the single case, a finding that is also in agreement with some previous observational and modeling studies. Above the boundary layer, the integrated contribution of the eddy term to the tangential wind tendency is over 80% of the contribution from the mean term, irrespective of inner-core structure. Our results strongly indicate that to fully understand the storm’s three-dimensional evolution, the contribution of the eddies must be quantified.

Convection-permitting ensemble prediction systems (CP-ENS) have been implemented in themid-latitudes for weather forecasting timescales over the past decade, enabled by the increase incomputational resources. Recently, efforts are being made to study the benefits of CP-ENS fortropical regions. This study examines CP-ENS forecasts produced by the UK Met Office overtropical East Africa, for 24 cases in the period April-May 2019. The CP-ENS, an ensemble withparametrized convection (Glob-ENS), and their deterministic counterparts are evaluated againstrainfall estimates derived from satellite observations (GPM-IMERG). The CP configurations havethe best representation of the diurnal cycle, although heavy rainfall amounts are overestimatedcompared to observations. Pairwise comparisons between the different configurations reveal thatthe CP-ENS is generally the most skilful forecast for both 3-h and 24-h accumulations of heavyrainfall (97th percentile), followed by the CP deterministic forecast. More precisely, probabilisticforecasts of heavy rainfall, verified using a neighbourhood approach, show that the CP-ENS isskilful at scales greater than 100 km, significantly better than the Glob-ENS, although not as goodas found in the mid-latitudes. Skill decreases with lead time and varies diurnally, especially forCP forecasts. The CP-ENS is under-spread both in terms of forecasting the locations of heavyrainfall and in terms of domain-averaged rainfall. This study demonstrates potential benefits inusing CP-ENS for operational forecasting of heavy rainfall over tropical Africa and gives specificsuggestions for further research and development, including probabilistic forecast guidance.

A novel technique to produce reasonable worst‐case rainfall scenarios from ensemble forecasts is presented. This type of scenario is relevant for predicting the risk of localized, intense rainfall events with a duration between 15 min and several hours. Such rainfall events can cause surface‐water (pluvial) flooding. Producing useful forecasts of these events at lead times of more than a few hours is challenging due to the precision and accuracy in rainfall intensity, duration and location that is required. The technique described here addresses these challenges by constructing appropriate scenarios using a neighbourhood technique in combination with ensemble forecasting. It is similar to the distance‐dependent depth–duration analysis described in earlier studies, but it introduces an additional post‐processing step based on probability distribution functions of rainfall accumulation near a location of interest. This additional step makes the reasonable worst‐case scenarios less dependent on grid‐scale behaviour, and helps to generate scenarios with a consistent interpretation. The method is used to compare forecasts with a lead time of 6–36 hr to radar data for several case studies that occurred in Yorkshire. These comparisons also introduce new techniques to present maps of the reasonable worst‐case rainfall accumulation at each location.

Some of the highest summer monsoon rainfall in South Asia falls on the windward slopes of the Western Ghats mountains on India’s west coast and offshore over the eastern Arabian Sea. Understanding of the processes determining the spatial distribution and temporal variability of this region remains incomplete. In this paper, new Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) aircraft and ground-based measurements of the summer monsoon over the Western Ghats and upstream of them are presented and placed within the context of remote sensing observations and reanalysis. The transition from widespread rainfall over the eastern Arabian Sea to rainfall over the Western Ghats is documented in high spatial and temporal resolution. Heavy rainfall offshore during the campaign was associated primarily with mid-tropospheric humidity, secondarily with sea surface temperature, and only weakly with orographic blocking. A mid-tropospheric dry intrusion suppressed deep convection offshore in the latter half of the campaign, allowing the build-up of low-level humidity in the onshore flow and enhancing rainfall over the mountains. Rainfall on the lee side of the Western Ghats occurred during the latter half of the campaign in association with enhanced mesoscale easterly upslope flow. Diurnal cycles in rainfall offshore (maximum in the morning) and on the mountains (maximum in the afternoon) were observed. Considerable zonal and temporal variability was seen in the offshore boundary layer, suggesting the presence of convective downdrafts and cold pools. Persistent drying of the subcloud mixed layer several hundred kilometres off the coast was observed, suggesting strong mixing between the boundary layer and the free troposphere. These observations provide quantitative targets to test models and suggest hypotheses on the physical mechanisms determining the distribution and variability in rainfall in the Western Ghats region.

Sub-Saharan Africa is one of the most food insecure regions in the world and is highly vulnerable to climate change. We use a comprehensive set of bias-corrected global (CMIP5) and regional (CORDEX-Africa) models and a new convection-permitting pan-Africa simulation (and its parameterized counterpart) to examine changes in rainfall and temperature and the impact on agricultural suitability of maize, cassava and soy in sub-Saharan Africa by 2100 (RCP8.5). This is the first time a convection-permitting projection has been used to examine agricultural suitability in Africa. Increasing temperatures and declining rainfall led to large parts of sub-Saharan Africa becoming unsuitable for multiple staple crops, which may necessitate a transition to more heat and drought resistant crops to ensure food and nutrition security. Soy was resilient to temperature increases, however maize and cassava were not, leading to declines in crop suitability. Inclusion of sensitivity to extreme temperatures led to larger declines in maize suitability than when this was excluded. The variation in rainfall projections within the multi-model ensemble was examined in detail for Tanzania, Malawi, Zambia and South Africa. In each country the range of projections included wetting and drying, but the majority of models projected rainfall declines, except in Tanzania, leading to declines in crop suitability. Overall, the CORDEX and CMIP5 models gave similar results for agricultural suitability. Explicit-convection led to more temperature extremes, but had little systematic impact on temperature and rainfall, and the resulting suitability analysis. Global model uncertainty, rather than convection parameterizations, still makes up the largest part of the uncertainty in future climate. Explicit-convection may have more impact if suitability included a more comprehensive treatment of extremes. This work highlights the key uncertainty from global climate projections for crop suitability projections, and the need for improved information on sensitivities of African crops to extremes, in order to give better predictions and make better use of the new generation of explicit-convection models.

Mid‐level clouds, located between 2 and 9 km height, are ubiquitous in the tropical belt. However, few studies have documented their characteristics and tried to identify the associated thermodynamic properties, particularly in West Africa. This region is characterized by a strong seasonality with precipitation occurring in the Sahel from June to September (monsoon season). This period also coincides with the annual maximum of the cloud cover. Here, we document the macro‐ and microphysical properties of mid‐level clouds, the environment in which such clouds occur, as well as their radiative properties across West Africa. To do so, we combined high‐resolution observations from two ground‐based sites (including lidar and cloud radar) in contrasted environments: one in the Sahel (Niamey, AMMA campaign, 2006) and the other in the Sahara (Bordj Badji Mokhtar, Fennec campaign, June 2011) along with the merged CloudSat‐CALIPSO satellite products. The results show that mid‐level clouds are found throughout the year with a predominance around the monsoon season early in the morning. They also are preferentially observed in the southern and western parts of West Africa. They are usually thin (most of them are less than 1000 m deep) and as observed in Niamey, mainly composed of liquid water. A clustering method applied to Niamey data allows us to distinguish three different types of cloud: one with low bases, one with high bases and another with large thicknesses. The two first cloud families are capped by an inversion. The last family is associated with a large vertical moisture transport and likely has the highest radiative effect at the Earth's surface among the three cloud types.

East Africa is highly reliant on agriculture and has high rates of soil erosion which negatively impact agricultural yields. Climate projections suggest that rainfall intensity will increase in East Africa, which is likely to increase soil erosion. Soil erosion estimates require information on rainfall erosivity, which is calculated using sub-daily storm characteristics that are known to be biased in traditional parameterized convection climate models. Convection-permitting climate models, which are run at higher resolution to negate the need for convection parameterization, generally better represent rainfall intensity and frequency. We use a novel convection-permitting pan-Africa regional climate model (CP4A) to estimate rainfall erosivity in Tanzania and Malawi, and compare it to its parameterized counterpart (P25), to determine if there is a benefit to using convection-permitting climate models to look at rainfall erosivity. We use eight year historical and end-of-century (RCP8.5) climate simulations to examine the impact of climate change on soil erosion in Tanzania and Malawi based on rainfall erosivity estimates from CP4A and P25 applied to the Revised Universal Soil Loss Equation. The effectiveness of soil conservation measures was also evaluated. Rainfall erosivity was lower in P25 than in CP4A and was a poorer match to observational storm characteristics, even after bias-correction. These results suggest that parameterized convection regional and global climate models might under-estimate rainfall erosivity, and the associated soil erosion. We found high values of present day erosion in mountainous regions in Tanzania and Malawi in CP4A. Under climate change, areas at high risk of soil erosion expanded due to increases in rainfall intensity in CP4A. Terracing was less effective at reducing soil erosion risk in the future than in the present day, and more extensive soil management may be required to manage soil erosion and reduce the negative impacts of soil erosion on agriculture.

From May to July 2016, as part of the INCOMPASS project, the Facility for Airborne Atmospheric Measurements (FAAM, jointly funded by the Met Office and Natural Environment Research Council (NERC)) BAe-146 research aircraft travelled to India to record key aspects of the Indian summer monsoon onset and evolution. As part of the planning for the campaign, partners in the UK and India took part in a ‘dry-run’ forecasting exercise during 2015, to assess the reliability of the forecast products and develop a set of flight plans, in advance of the real campaign, and to get a real-time feel for the monsoon onset. The 5-day forecasts from the Met Office and the Indian National Centre for Medium Range Weather Forecasting (NCMRWF) showed good skill in terms of predicting the advance of rainfall in regions key for the campaign in north and south India, and captured transitions from active (wet) monsoon conditions to break (dry) periods and back again. Key phenomena seen during the dry-run exercise include (1) a ‘western disturbance’, which had a major effect on the extreme pre-monsoon heatwave conditions over India, (2) dry intrusions, which are thought to be important in the progression of the monsoon onset against the synoptic flow, and (3) cyclones Ashobaa and Komen.

The Lake Victoria region in East Africa is a hot spot for intense convective storms that are responsible for the deaths of thousands of fishermen each year. The processes responsible for the initiation, development, and propagation of the storms are poorly understood and forecast skill is limited. Key processes for the life cycle of two storms are investigated using Met Office Unified Model convection-permitting simulations with 1.5 km horizontal grid spacing. The two cases are analyzed alongside a simulation of a period with no storms to assess the roles of the lake–land breeze, downslope mountain winds, prevailing large-scale winds, and moisture availability. While seasonal changes in large-scale moisture availability play a key role in storm development, the lake–land-breeze circulation is a major control on the initiation location, timing, and propagation of convection. In the dry season, opposing offshore winds form a bulge of moist air above the lake surface overnight that extends from the surface to ~1.5 km and may trigger storms in high CAPE/low CIN environments. Such a feature has not been explicitly observed or modeled in previous literature. Storms over land on the preceding day are shown to alter the local atmospheric moisture and circulation to promote storm formation over the lake. The variety of initiation processes and differing characteristics of just two storms analyzed here show that the mean diurnal cycle over Lake Victoria alone is inadequate to fully understand storm formation. Knowledge of daily changes in local-scale moisture variability and circulations are keys for skillful forecasts over the lake.

The advance of the onset of the Indian monsoon is here explained in terms of a balance between the low-level monsoon flow and an over-running intrusion of mid-tropospheric dry air. The monsoon advances, over a period of about 6 weeks, from the south of the country to the northwest. Given that the low-level monsoon winds are westerly or southwesterly, and the midlevel winds northwesterly, the monsoon onset propagates upwind relative to midlevel flow, and perpendicular to the low-level flow, and is not directly caused by moisture flux toward the northwest. Lacking a conceptual model for the advance means that it has been hard to understand and correct known biases in weather and climate prediction models. The mid-level northwesterlies form a wedge of dry air that is deep in the far northwest of India and over-runs the monsoon flow. The dry layer is moistened from below by shallow cumulus and congestus clouds, so that the profile becomes much closer to moist adiabatic, and the dry layer is much shallower in the vertical, toward the southeast of India. The profiles associated with this dry air show how the most favourable environment for deep convection occurs in the south, and onset occurs here first. As the onset advances across India, the advection of moisture from the Arabian Sea becomes stronger, and the mid-level dry air is increasingly moistened from below. This increased moistening makes the wedge of dry air shallower throughout its horizontal extent, and forces the northern limit of moist convection to move toward the northwest. Wetting of the land surface by rainfall will further reinforce the north-westward progression, by sustaining the supply of boundary layer moisture and shallow cumulus. The local advance of the monsoon onset is coincident with weakening of the mid-level northwesterlies, and therefore weakened mid-level dry advection.

Cold pools are integral components of squall-line mesoscale convective systems and the West African monsoon, but are poorly represented in operational global models. Observations of 38 cold pools made at Niamey, Niger, during the 2006 African Monsoon Multidisciplinary Analysis (AMMA) campaign (1 June–30 September 2006), are used to generate a seasonal characterization of cold pool properties by quantifying related changes in surface meteorological variables. Cold pools were associated with temperature decreases of 2°–14°C, pressure increases of 0–8 hPa, and wind gusts of 3–22 m s−1. Comparison with published values of similar variables from the U.S. Great Plains showed comparable differences. The leading part of most cold pools had decreased water vapor mixing ratios compared to the environment, with moister air, likely related to precipitation, approximately 30 min behind the gust front. A novel diagnostic used to quantify how consistent observed cold pool temperatures are with saturated or unsaturated descent from midlevels [fractional evaporational energy deficit (FEED)] shows that early season cold pools are consistent with less saturated descents. Early season cold pools were relatively colder, windier, and wetter, consistent with drier midlevels, although this was only statistically significant for the change in moisture. Late season cold pools tended to decrease equivalent potential temperature from the pre–cold pool value, whereas earlier in the season changes were smaller, with more increases. The role of cold pools may therefore change through the season, with early season cold pools more able to feed subsequent convection.

Due to high present-day temperatures and reliance on rainfed agriculture, sub-Saharan Africa is highly vulnerable to climate change. We use a comprehensive set of global (CMIP5) and regional (CORDEX-Africa) climate projections and a new convection-permitting pan-Africa simulation (and its parameterized counterpart) to examine changes in rainfall and temperature and the impact on crop suitability of maize, cassava and soybean in sub-Saharan Africa by 2100 (RCP8.5). This is the first time an explicit-convection simulation has been used to examine crop suitability in Africa. Increasing temperatures and declining rainfall led to large parts of sub-Saharan Africa becoming unsuitable for multiple staple crops, which may necessitate a transition to more heat and drought resistant crops to ensure food and nutrition security. Soybean was resilient to temperature increases, however maize and cassava were not, leading to declines in crop suitability. Inclusion of sensitivity to extreme temperatures led to larger declines in maize suitability than when this was excluded. The results were explored in detail for Tanzania, Malawi, Zambia and South Africa. In each country the range of projections included wetting and drying, but the majority of models projected rainfall declines leading to declines in crop suitability, except in Tanzania. Explicit-convection was associated with more high temperature extremes, but had little systematic impact on average temperature and total rainfall, and the resulting suitability analysis. Global model uncertainty, rather than convection parameterizations, still makes up the largest part of the uncertainty in future climate. Explicit-convection may have more impact if suitability included a more comprehensive treatment of extremes. This work highlights the key uncertainty from global climate projections for crop suitability projections, and the need for improved information on sensitivities of African crops to extremes, in order to give better predictions and make better use of the new generation of explicit-convection models.

Forecasting convective rainfall in the tropics is a major challenge for numerical weather prediction. The use of convection-permitting (CP) forecast models in the tropics has lagged behind the midlatitudes, despite the great potential of such models in this region. In the scientific literature, there is very little evaluation of CP models in the tropics, especially over an extended time period. This paper evaluates the prediction of convective storms for a period of 2 years in the Met Office operational CP model over East Africa and the global operational forecast model. A novel localized form of the fractions skill score is introduced, which shows variation in model skill across the spatial domain. Overall, the CP model and the global model both outperform a 24-h persistence forecast. The CP model shows greater skill than the global model, in particular on subdaily time scales and for storms over land. Forecasts over Lake Victoria are also improved in the CP model, with an increase in hit rate of up to 20%. Contrary to studies in the midlatitudes, the skill of both models shows a large dependence on the time of day and comparatively little dependence on the forecast lead time within a 48-h forecast. Although these results provide more motivation for forecasters to use the CP model to produce subdaily forecasts with increased detail, there is a clear need for more in situ observations for data assimilation into the models and for verification. A move toward ensemble forecasting could have further benefits.

The diurnal cycle of precipitation in the Tropics is represented poorly in general circulation models (GCMs), which is primarily attributed to the representation of moist convection. Nonetheless, in areas where precipitation is driven by the diurnal cycle in the synoptic‐scale flow, GCMs may represent that circulation–rainfall relationship well. Over northwest Australia there is a tendency for precipitation to peak overnight where the diurnal cycle of the heat low circulation leads to the development of strong convergence after local sunset. In order to assess the heat low–precipitation relationship in more detail, a case‐study approach is used to investigate the actual ‘weather’ that is responsible for night‐time precipitation. The study shows that, where there is sufficient moisture, precipitation typically forms along convergence zones that coincide with boundaries between relatively moist and dry air masses (termed a ‘dryline’). A convergence line detection algorithm is then used to identify the fraction of observed nocturnal rainfall that is associated with any convergence zones. The same evaluation is then undertaken for a relatively high‐resolution (MetUM) and low‐resolution (ACCESS1.0) GCM, which simulate rainfall‐generation processes similar to the observations. Finally, the convergence line detection/precipitation algorithm is run on other GCM data (from CMIP5) to see whether the same processes occur despite different model configurations (i.e. physics), which appears to be the case."This is the pre-peer reviewed version of the following article: [Ackerley, D. , Birch, C. E., Garcia‐Carreras, L. , Lavender, S. L. and Weller, E. (2018), The physical processes causing nocturnal rainfall over northwest Australia and their representation in high‐ and low‐resolution models with parametrized convection. Q.J.R. Meteorol. Soc., 144: 511-528. doi:10.1002/qj.3223], which has been published in final form. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions."

Global climate and weather models are a key tool for the prediction of future crop productivity, but they all rely on parameterizations of atmospheric convection, which often produce significant biases in rainfall characteristics over the tropics. The authors evaluate the impact of these biases by driving the General Large Area Model for annual crops (GLAM) with regional-scale atmospheric simulations of one cropping season over West Africa at different resolutions, with and without a parameterization of convection, and compare these with a GLAM run driven by observations. The parameterization of convection produces too light and frequent rainfall throughout the domain, as compared with the short, localized, high-intensity events in the observations and in the convection-permitting runs. Persistent light rain increases surface evaporation, and much heavier rainfall is required to trigger planting. Planting is therefore delayed in the runs with parameterized convection and occurs at a seasonally cooler time, altering the environmental conditions experienced by the crops. Even at high resolutions, runs driven by parameterized convection underpredict the small-scale variability in yields produced by realistic rainfall patterns. Correcting the distribution of rainfall frequencies and intensities before use in crop models will improve the process-based representation of the crop life cycle, increasing confidence in the predictions of crop yield. The rainfall biases described here are a common feature of parameterizations of convection, and therefore the crop-model errors described are likely to occur when using any global weather or climate model, thus remaining hidden when using climate-model intercomparisons to evaluate uncertainty.

Cold pool outflows, generated by downdrafts from moist convection, can generate strong winds and therefore uplift of mineral dust. These so-called haboob convective dust storms occur over all major dust source areas worldwide and contribute substantially to emissions in northern Africa, the world’s largest source. Most large-scale models lack convective dust storms because they do not resolve moist convection, relying instead on convection schemes. The authors suggest a parameterization of convective dust storms to account for their contribution in such large-scale models. The parameterization is based on a simple conceptual model, in which the downdraft mass flux from the convection scheme spreads out radially in a cylindrical cold pool. The parameterization is tested with a set of Met Office Unified Model runs for June and July 2006 over West Africa. It is calibrated with a convection-permitting run and applied to a convection-parameterized run. The parameterization successfully produces the extensive area of dust-generating winds from cold pool outflows over the southern Sahara. However, this area extends farther to the east and dust-generating winds occur earlier in the day than in the convection-permitting run. These biases are caused by biases in the convection scheme. It is found that the location and timing of dust-generating winds are weakly sensitive to the parameters of the conceptual model. The results demonstrate that a simple parameterization has the potential to correct a major and long-standing limitation in global dust models.

The organization of deep convection and its misrepresentation in many global models is the focus of much current interest. A new method is presented for quantifying convective organization based on the identification of convective objects and subsequent derivation of object numbers, areas, and separation distances to describe the degree of convective organization. These parameters are combined into a “convection organization potential” based on the physical principle of an interaction potential between pairs of convective objects. This technique is applied to simulated and observed fields of outgoing longwave radiation (OLR) over the West African monsoon region using data from Met Office Unified Model simulations and satellite observations made by the Geostationary Earth Radiation Budget (GERB) instrument. The method is evaluated by using it to quantify differences between models with different horizontal grid lengths and representations of convection. Distributions of OLR, precipitation and organization parameters, the diurnal cycle of convection, and relationships between the meteorology in different states of organization are compared. Switching from a configuration with parameterized convection to one that allows the model to resolve convective processes at the model grid scale is the leading-order factor improving some aspects of model performance, while increased model resolution is the dominant factor for others. However, no single model configuration performs best compared to observations, indicating underlying deficiencies in both model scaling and process understanding.

Journal: Weather Manuscript ID: WEA-13-0098.R1 Wiley Manuscript type: Research Article Date Submitted by the Author: n/a Complete List of Authors: Procter, Nathan; University of Leeds, School of Earth and Environment Birch, Cathryn; University of Leeds, School of Earth and Environment Monk, Geoffrey; The Weather Centre, Mountain Weather Information Service Marsham, John; University of Leeds, National Centre for Atmospheric Science

Loss of summertime Arctic sea ice will lead to a large increase in the emission of aerosols and precursor gases from the ocean surface. It has been suggested that these enhanced emissions will exert substantial aerosol radiative forcings, dominated by the indirect effect of aerosol on clouds. Here, we investigate the potential for these indirect forcings using a global aerosol microphysics model evaluated against aerosol observations from the Arctic Summer Cloud Ocean Study (ASCOS) campaign to examine the response of Arctic cloud condensation nuclei (CCN) to sea-ice retreat. In response to a complete loss of summer ice, we find that north of 70° N emission fluxes of sea salt, marine primary organic aerosol (OA) and dimethyl sulfide increase by a factor of ~ 10, ~ 4 and ~ 15 respectively. However, the CCN response is weak, with negative changes over the central Arctic Ocean. The weak response is due to the efficient scavenging of aerosol by extensive drizzling stratocumulus clouds. In the scavenging-dominated Arctic environment, the production of condensable vapour from oxidation of dimethyl sulfide grows particles to sizes where they can be scavenged. This loss is not sufficiently compensated by new particle formation, due to the suppression of nucleation by the large condensation sink resulting from sea-salt and primary OA emissions. Thus, our results suggest that increased aerosol emissions will not cause a climate feedback through changes in cloud microphysical and radiative properties.

Links between convergence and convection are poor in global models, and poor representation of convection is the source of many model biases in the tropics. State-of-the-art convection-permitting simulations allow us to analyze realistic convection statistically. The analysis of fractal dimension is used to show that in convection-permitting simulations (grid spacings 1.5, 4, and 12 km) of the West African monsoon, 50% of deep convective initiations occur in the near vicinity of low-level boundary layer convergence lines that are orientated along the mean wind. In these simulations, more than 80% of the initiations occur within large-scale (300 × 300 km) convergence, with some 20% in large-scale divergence, and almost all cases occur within local scale (60 × 60 km) convergence. The behavior alters in a simulation with a convection scheme and a grid spacing of 12 km; initiation is less frequent over convergence lines, and there is less dependency on high-magnitude low-level local convergence.

Meteosat visible satellite images between 2006 and 2011 show wave-cloud lines over the Arabian Sea in all months outside the summer monsoon (June–September). These lines are most frequent between January and May (2–3 per month in a given year). All wave-cloud lines in the region propagate offshore. As these wave-cloud lines are associated with coherent convergence lines, the objective technique described by Berry and Reeder is applied to the ERA-Interim reanalysis and a climatology of convergence lines at 850 hPa developed. Despite the coarse resolution of the ERA-Interim reanalysis, the statistical properties of these lines are broadly constant with those deduced from the Meteosat visible satellite images. The generation mechanism is investigated in a simulation with the Met Office Unified Model of a particular wave-cloud line (12 March 2011). The process appears to be similar to that over northwestern Australia, which has been documented previously. During the day, a synoptic-scale northeasterly flow opposes the inland advection of the sea breeze on the west coast of India. However, as the daytime turbulence decays and the boundary layer stabilizes, the northeasterly flow accelerates, pushing offshore the leading edge of the sea breeze during the late evening and early hours of the morning. A wave is generated as the northeasterlies penetrate the marine boundary layer, and this wave propagates westward, producing cloud at its leading edge where there is strong ascent.

A suite of 40 day UK Met Office Unified Model simulations over West Africa during summer 2006 are analyzed to investigate the causes of biases in the position of the rainbelt and to understand the role of convection in the regional water budget. The simulations include climate, global operational, and limited area runs (grid spacings from 1.5 to 40 km), including two 12 km runs, one with parameterized and one with explicit convection. The most significant errors in the water cycle terms occur in the simulations with parameterized convection, associated with the diurnal cycle and the location of the convection. Errors in the diurnal cycle increase the northward advection of moisture out of the Sahel toward the Sahara but decrease the advection of moisture into the Sahel from further south, which limits the availability of moisture for Sahelian rainfall. These biases occur within the first 24 h, showing that they originate from the representation of fast physical processes, specifically, the convection scheme. Once these rainfall regimes have been established, the terms of the water budgets act to reinforce the biases, effectively locking the rainbelt's latitude. One of the simulations with parameterized convection does, however, produce a better latitudinal distribution of rainfall because on the first day it is better able to trigger convection in the Sahel. Accurate representation of the diurnal cycle of convection and the ability to trigger convection in a high convective inhibition environment is key to capturing the water cycle of the region and will improve the representation of the West African Monsoon.

We present the results of simulations carried out with the Met Office Unified Model at 12, 4 and 1.5 km resolution for a large region centred on West Africa using several different representations of the convection processes. These span a range of resolutions from much coarser than the size of the convection processes to cloud-system-resolving and thus encompass the intermediate ‘grey zone’. The diurnal cycle in the extent of convective regions in the models is tested against observations from the Geostationary Earth Radiation Budget instrument on Meteosat-8. By this measure, the two best-performing simulations are a 12 km model without convective parametrization, using Smagorinsky-style subgrid-scale mixing in all three dimensions, and a 1.5 km simulation with two-dimensional Smagorinsky mixing. Of these, the 12 km model produces a better match to the magnitude of the total cloud fraction but the 1.5 km one results in better timing for its peak value. The results suggest that the previously reported improvement in the representation of the diurnal cycle of convective organization in the 4 km model compared with the standard 12 km configuration is principally a result of the convection scheme employed rather than the improved resolution per se. The details of this result and implications for high-resolution model simulations are discussed.

[1] Predicting the West African monsoon (WAM) remains a major challenge for weather and climate models. We compare multiday continental-scale simulations of the WAM that explicitly resolve moist convection with simulations which parameterize convection. Simulations with the same grid spacing but differing representations of convection isolate the impact of the representation of convection. The more realistic explicit convection gives greater latent and radiative heating farther north, with latent heating later in the day. This weakens the Sahel-Sahara pressure gradient and the monsoon flow, delaying its diurnal cycle and changing interactions between the monsoon and boundary layer convection. In explicit runs, cold storm outflows provide a significant component of the monsoon flux. In an operational global model, biases resemble those in our parameterized case. Improved parameterizations of convection that better capture storm structures, their diurnal cycle, and rainfall intensities will therefore substantially improve predictions of the WAM and coupled aspects of the Earth system.

A mesoscale convective system (MCS) case study was observed over northeast Mali as part of the African Monsoon Multidisciplinary Analysis (AMMA) on 31 July 2006. Observations of this case suggest that the soil-moisture heterogeneity and atmospheric gravity waves emitted from a ‘parent’ MCS were important trigger mechanisms for this system. This study uses high-resolution Met Office Unified Model (MetUM) simulations to assess the importance of the synoptic circulation, land-surface and gravity waves in the initiation and development of the MCS. During the early afternoon shallow convection developed over a region of dry soil within a synoptic-scale convergence zone, which was caused by the confluence of the southerly monsoon flow with winds associated with the circulation around the Saharan heat low. Two pronounced waves were emitted from a nearby ‘parent’ storm and propagated towards the convergence zone. When the second wave reached the location of the shallow convection, deep convection was immediately initiated. Further convective cells developed later in the afternoon over dry soil, many adjacent to strong soil moisture gradients; these aggregated with the main storm, which later developed into the case study MCS. A comparison of model simulations with/without the soil-moisture heterogeneity and gravity waves shows that the synoptic-scale circulation and convergence zones, specified by the atmospheric analysis, were the most important factors for the successful simulation of the MCS. If the location of the initiation of the system is to be forecast accurately, the land-surface, that is, the soil moisture, must be represented adequately. In order to reproduce the timing of the secondary initiation of convection correctly the model must be able to capture gravity waves that are emitted by existing systems.

State-of-the-art regional climate model simulations that are able to resolve key mesoscale circulations are used, for the first time, to understand the interaction between the large-scale convective environment of the MJO and processes governing the strong diurnal cycle over the islands of the Maritime Continent (MC). Convection is sustained in the late afternoon just inland of the coasts because of sea breeze convergence. Previous work has shown that the variability in MC rainfall associated with the MJO is manifested in changes to this diurnal cycle; land-based rainfall peaks before the active convective envelope of the MJO reaches the MC, whereas oceanic rainfall rates peak while the active envelope resides over the region. The model simulations show that the main controls on oceanic MC rainfall in the early active MJO phases are the large-scale environment and atmospheric stability, followed by high oceanic latent heat flux forced by high near-surface winds in the later active MJO phases. Over land, rainfall peaks before the main convective envelope arrives (in agreement with observations), even though the large-scale convective environment is only moderately favorable for convection. The causes of this early rainfall peak are strong convective triggers from land–sea breeze circulations that result from high surface insolation and surface heating. During the peak MJO phases cloud cover increases and surface insolation decreases, which weakens the strength of the mesoscale circulations and reduces land-based rainfall, even though the large-scale environment remains favorable for convection at this time. Hence, scale interactions are an essential part of the MJO transition across the MC.

The frequency of occurrence and formation mechanisms of wave-cloud lines off the northwest coast of Australia are investigated. Prior to the present study, little was known about these wave-cloud lines. Apart from being spectacular atmospheric phenomenon in their own right, these wave clouds can have a role in the secondary initiation of convection and can be a hazard to low-flying aircraft. A climatology of wave clouds, produced from visible satellite imagery, suggests two main types of cloud lines form over northwest Australia. The first are bore-like waves, similar in structure to the ‘morning glory’ of northeast Australia, and occur at least 2 to 3 times per month throughout the entire year. The second type are convectively generated cloud lines, which are more circular in shape, appear to originate from convective storms and occur at least 0.5 to 1.5 times per month during the wet season. High-resolution, nested simulations are performed with the Met Office Unified Model for case-studies of each type of wave. The bore-like waves occurred in the presence of synoptic-scale, low-level southeasterly flow and a heat low along the northwest coast of Australia. At night, the offshore southeasterlies accelerate into the heat low and collide with the onshore sea breeze. The southeasterlies override the sea breeze and the wave-cloud lines form at the leading edge of this front. The convectively generated waves radiate outwards from the convective storms producing compensating subsidence and adiabatic warming. These waves take the form of n=2 mode wave fronts, which span the entire depth of the troposphere and are similar in structure to waves produced by deep convection which are described in previous studies.