73 research outputs found

    Cross Saharan transport of water vapour via recycled cold-pool outflows from moist convection

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    Very sparse data has previously limited observational studies of meteorological processes in the Sahara. We present an observed case of convectively-driven water vapour transport crossing the Sahara over 2.5 days in June 2012, from the Sahel in the south to the Atlas in the north. A daily cycle is observed, with deep convection in the evening generating moist cold pools that fed the next dayā€™s convection; the convection then generated new cold pools, providing a vertical recycling of moisture. Trajectories driven by analyses were able to capture the direction of the transport but not its full extent, particularly at night when cold pools are most active, and analyses missed much of the water content of cold pools. The results highlight the importance of cold pools for moisture transport, dust and clouds, and demonstrate the need to include these processes in models in order to improve the representation of Saharan atmospher

    Observations of increased cloud cover over irrigated agriculture in an arid environment

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    Irrigated agriculture accounts for 20% of global cropland area and may alter climate locally and globally, but feedbacks on clouds and rainfall remain highly uncertain, particularly in arid regions. Non-renewable groundwater in arid regions accounts for 20% of global irrigation water demand, and quantifying these feedbacks is crucial for the prediction of long-term water use in a changing climate. Here we use satellite data to show how irrigated crops in an arid environment alter land-surface properties, cloud cover and rainfall patterns. Land surface temperatures (LST) over the cropland are 5-7 K lower than their surroundings, despite a lower albedo, suggesting that Bowen ratio is strongly reduced (and latent heat fluxes increased) over the irrigated cropland. Daytime cloud cover is increased by up to 15% points (a relative increase of 60%), with increased cloud development in the morning, and a greater afternoon peak in cloud. Cloud cover is significantly correlated with interannual variations in vegetation and LST. Afternoon rainfall also appears to be enhanced around the irrigation. The cloud feedback is the opposite of what has been previously observed in tropical and semiarid regions, suggesting different processes drive land-atmosphere feedbacks in very dry environments. Increased cloud and rainfall, and associated increases in diffuse radiation and reductions in temperature, are likely to benefit vegetation growth. Predictions of changes in crop productivity due to climate change and the impacts of global land-use change on climate and the use of water-resources would therefore benefit from including these effects

    A climatology of dust emission events from Northern Africa using long-term surface observations

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    Long-term (1984-2012) surface observations from 70 stations in the Sahara and Sahel are used to explore the diurnal, seasonal and geographical variations in dust emission events and thresholds. The frequency of dust emission (FDE) is calculated using the present weather codes of SYNOP reports. Thresholds are estimated as the wind speed for which there is a 50% probability of dust emission and are then used to calculate strong wind frequency (SWF) and dust uplift potential (DUP), where the latter is an estimate of the dust-generating power of winds. Stations are grouped into six coherent geographical areas for more in-depth analysis. FDE is highest at stations in Sudan and overall peaks in spring north of 23deg; N. South of this, where stations are directly influenced by the summer monsoon, the annual cycle in FDE is more variable. Thresholds are highest in northern Algeria, lowest in the latitude band 16-21deg; N and have greatest seasonal variations in the Sahel. Spatial variability in thresholds partly explain spatial variability in frequency of dust emission events on an annual basis. However, seasonal variations in thresholds for the six grouped areas are not the main control on seasonal variations in FDE. This is demonstrated by highly correlated seasonal cycles of FDE and SWF which are not significantly changed by using a fixed, or seasonally varying, threshold. The likely meteorological mechanisms generating these patterns such as low-level jets and haboobs are discussed

    Are vegetation-related roughness changes the cause of the recent decrease in dust emission from the Sahel?

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    Since the 1980s, a dramatic downward trend in North African dustiness and transport to the tropical Atlantic Ocean has been observed by different data sets and methods. The precise causes of this trend have previously been difficult to understand, partly due to the sparse observational record. Here we show that a decrease in surface wind speeds associated with increased roughness due to more vegetation in the Sahel is the most likely cause of the observed drop in dust emission. Associated changes in turbulence and evapotranspiration, and changes in large-scale circulation, are secondary contributors. Past work has tried to explain negative correlations between North African dust and precipitation through impacts on emission thresholds due to changes in soil moisture and vegetation cover. The use of novel diagnostic tools applied here to long-term surface observations suggests that this is not the dominating effect. Our results are consistent with a recently observed global decrease in surface wind speed, known as "stilling", and demonstrate the importance of representing vegetation-related roughness changes in models. They also offer a new mechanism of how land-use change and agriculture can impact the Sahelian climate. Key Points Decadal Sahel dust trends analyzed with surface observations and new diagnosticsWind-speed changes dominate over soil changes in recent dust emission decreaseVegetation-induced roughness changes are the main control on wind-speed trends

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

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    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

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    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 lakeā€“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 lakeā€“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

    Effects of Explicit Convection on Future Projections of Mesoscale Circulations, Rainfall, and Rainfall Extremes over Eastern Africa

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    Eastern Africaā€™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 āˆ’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 decisionsā€”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

    Importance of Maddenā€“Julian oscillation phase to the interannual variability of East African rainfall

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    Precipitation across East Africa shows marked interannual variability. Seasonal forecast skill for the OND short rains is significantly higher than for the MAM long rains, which also exhibit poorly understood decadal variability. On sub-seasonal time-scales rainfall is influenced strongly by the phase of the Maddenā€“Julian Oscillation (MJO); here we investigate whether this influence extends to interannual and decadal scales. We show that the number of days that the MJO is active and in phases 1ā€“3 has a greater influence than the mean amplitude of the MJO on interannual long rains variability (Ļ = 0.59 for the count of phases 1ā€“3, compared to Ļ = 0.40 for amplitude). The frequency of these days is linked to a newly identified gradient in Pacific sea-surface temperatures (SSTs), whose influence on long rains variability we show is itself mediated by the MJO. We develop a statistical model estimating East African rainfall from MJO state, and show that the influence of the MJO on seasonal rainfall extends to the short rains, and to a lesser extent also into January and February. Our results show the importance of capturing the SST-MJO phase relationship in models used for predictions of East African rainfall across time-scales, and motivate investigating this further

    Regional differences in the response of rainfall to convectively coupled Kelvin waves over tropical Africa

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    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 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 which 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
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