A parameterization of convective dust storms for models with mass-flux convective schemes

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. We 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 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 due to 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

Moist convection and its upscale effects in simulations of the Indian monsoon with explicit and parametrised convection

In common with many global models, the Met Office Unified Model (MetUM) climate simulations show large errors in Indian summer monsoon rainfall, with a wet bias over the equatorial Indian Ocean, a dry bias over India, and with too weak low-level flow into India. The representation of moist convection is a dominant source of error in global models, where convection must be parametrised, with the errors growing quickly enough to affect both weather and climate simulations. Here we use the first multi- week continental-scale MetUM simulations over India, with grid-spacings that allow explicit convection, to examine how convective parametrisation contributes to model biases in the region. Some biases are improved in the convection-permitting simulations with more intense rainfall over India, a later peak in the diurnal cycle of convective rainfall over land, and a reduced positive rainfall bias over the Indian Ocean. The simulations suggest that the reduced rainfall over the Indian Ocean leads to an enhanced monsoon circulation and transport of moisture into India. Increases in latent heating associated with increased convection over land deepen the monsoon trough and enhance water vapour transport into the continent. In addition, delayed continental convection allows greater surface insolation and, along with the same rain falling in more intense bursts, generates a drier land surface. This increases land-sea temperature contrasts, and further enhances onshore flow. Changes in the low-level water vapour advection into India are dominated by these changes to the flow, rather than to the moisture content in the flow. The results demonstrate the need to improve the representations of convection over both land and oceans to improve simulations of the monsoon

Identifying key controls on storm formation over the Lake Victoria Basin

The Lake Victoria region in East Africa is a hotspot for intense convective storms that are responsible for the deaths of thousands of fisherman 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 lifecycle of two storms are investigated using Met Office Unified Model convection-permitting simulations with 1.5 km horizontal gridspacing. The two cases are analysed 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. Whilst 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 modelled 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 analysed 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 key for skilful forecasts over the lake

The effect of westerlies on East African rainfall and the associated role of tropical cyclones and the Madden–Julian Oscillation

Variability of rainfall in East Africa has major impacts on lives and livelihoods. From floods to droughts, this variability is important on short daily time‐scales to longer decadal time‐scales, as is apparent from the devastating effects of droughts in East Africa over recent decades. Past studies have highlighted the Congo airmass in enhancing East African rainfall. Our detailed analysis of the feature shows that days with a westerly moisture flow, bringing the Congo airmass, enhance rainfall by up to 100% above the daily mean, depending on the time of year. Conversely, there is a suppression of rainfall on days with a strong easterly flow. Days with a westerly moisture flux are in a minority in all seasons but we show that long rains with more westerly days are wetter, and that during the most‐recent decade which has had more frequent droughts (associated with the “Eastern African climate paradox”), there has been few days with such westerlies. We also investigate the influence of the Madden–Julian Oscillation (MJO) and tropical cyclones, and their interaction with the westerly flow. We show that days of westerly moisture flux are more likely during phases 3 and 4 of the MJO and when there are one or more tropical cyclones present. In addition, tropical cyclones are more likely to form during these phases of the MJO, and more likely to be coincident with westerlies when forming to the east of Madagascar. Overall, our analysis brings together many different processes that have been discussed in the literature but not yet considered in complete combination. The results demonstrate the importance of the Congo airmass on daily to climate time‐scales, and in doing so offers useful angles of investigation for future studies into prediction of East African rainfall

Austral summer droughts and their driving mechanisms in observations and present‐day climate simulations over Malawi

Droughts are a key feature of weather systems over Malawi and southern Africa. Their societal relevance in Malawi underscores the need for improved understanding of drought characteristics and atmospheric processes that drive them. We use the Standardized Precipitation and Evapotranspiration Index with the run theory to identify and characterize droughts in observations (1961–2017) and CMIP5 models across Malawi. We find no major differences in drought duration, severity, and intensity between the northern and southern parts of Malawi. However, circulation patterns associated with droughts in the two regions are different, and typically organized in such a way that droughts in one region coincide with wetter conditions in the other. Anomalous circulation patterns diminishing moisture convergence and convection over the affected region are a typical feature of summer droughts. We show that precipitation variability is principally governed by advected moisture, transported via three main tracks of northwesterly, northeasterly, and southeasterly moisture fluxes. The three tracks interact to form a convergence zone with a peak situated over Malawi. Variability in the respective moisture flux tracks influences the variability in the location and intensity of the convergence zone, and thus the location of the ensuing drought. We note links between variability in the moisture advection tracks and El Nino Southern Oscillations and other modes of variability including the Indian Ocean Dipole and Subtropical Indian Ocean Dipole. Both negative and positive biases in drought frequency are apparent in CMIP5 models but the majority overestimate drought duration and severity. The relationship between precipitation and net total moisture flux is consistently simulated. However, we note significant model inconsistencies in the relationship between precipitation and moisture flux from the southeasterly track, which potentially undermines the confidence in model simulation of drought processes over Malawi

A percentile‐based approach to rainfall scenario construction for surface‐water flood forecasts

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

The Turbulent Structure of the Arctic Summer Boundary Layer During The Arctic Summer Cloud‐Ocean Study

The mostly ice covered Arctic Ocean is dominated by low‐level liquid‐ or mixed‐phase clouds. Turbulence within stratocumulus is primarily driven by cloud top cooling that induces convective instability. Using a suite of in situ and remote sensing instruments we characterize turbulent mixing in Arctic stratocumulus, and for the first time we estimate profiles of the gradient Richardson number at relatively high resolution in both time (10 min) and altitude (10 m). It is found that the mixing occurs both within the cloud, as expected, and by wind shear instability near the surface. About 75% of the time these two layers are separated by a stably stratified inversion at 100–200 m altitude. Exceptions are associated with low cloud bases that allow the cloud‐driven turbulence to reach the surface. The results imply that turbulent coupling between the surface and the cloud is sporadic or intermittent

Common Mechanism for Interannual and Decadal Variability in the East African Long Rains

The East African long rains constitute the main crop‐growing season in the region. Interannual predictability of this season is low in comparison to the short rains, and recent decadal drying contrasts with climate projections of a wetter future (the “East African climate paradox”). Here, we show that long rains rainfall totals are strongly correlated with 700 hPa zonal winds across the Congo basin and Gulf of Guinea ( urn:x-wiley:grl:media:grl61425:grl61425-math-0001). Westerly anomalies align with more rainfall, with the same mechanism controlling covariability on interannual and decadal time scales. On both time scales wind anomalies are linked to geopotential anomalies over the Sahel and Sahara, and warming there. Rainfall and wind are significantly correlated with the Madden‐Julian Oscillation (MJO) amplitude, and around 18% of the decadal drying can be explained by MJO amplitude variability. This work shows that predictions of East African rainfall across time scales require robust prediction of both zonal winds and MJO activity

The physical processes that cause nocturnal rainfall over north-west Australia and their representation in high- and low-resolution models with parametrized convection

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