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Emily Black, Julia Slingo, and Kenneth R. Sperber

Abstract

Composites of SST, wind, rainfall, and humidity have been constructed for years of high rainfall during September, October, and November (SON) in equatorial and southern-central East Africa. These show that extreme East African short rains are associated with large-scale SST anomalies in the Indian Ocean that closely resemble those that develop during Indian Ocean dipole or zonal mode (IOZM) events. This is corroborated by the observation that strong IOZM events produce enhanced East African rainfall. However, it is also shown that the relationship between the IOZM and East African rainfall is nonlinear, with only IOZM events that reverse the zonal SST gradient for several months (extreme events) triggering high rainfall.

Comparison of the wind anomalies that develop during extreme IOZM events with those that develop during weaker (moderate) events shows that strong easterly anomalies in the northern-central Indian Ocean are a persistent feature of extreme, but not of moderate, IOZM years. It is suggested that these anomalies weaken the westerly flow that normally transports moisture away from the African continent, out over the Indian Ocean. Thus, during extreme IOZM years, rainfall is enhanced over East Africa and reduced in the central and eastern Indian Ocean basin.

It is also shown that the IOZM cannot be viewed in isolation from the El Niño–Southern Oscillation (ENSO). Instead it is postulated that in some years, a strong ENSO forcing can predispose the Indian Ocean coupled system to an IOZM event and is therefore a contributory factor in extreme East African rainfall. The results of this study imply that the relationship between El Niño and the IOZM explains the previously described association between El Niño and high East African rainfall. Thus, understanding the way that ENSO drives Indian Ocean dynamics may aid the development of predictive scenarios for East African climate that could have significant economic implications.

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Emily Black, Helen Greatrex, Matthew Young, and Ross Maidment
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Caroline M. Dunning, Emily Black, and Richard P. Allan

Abstract

Changes in the seasonality of precipitation over Africa have high potential for detrimental socioeconomic impacts due to high societal dependence upon seasonal rainfall. Here, for the first time we conduct a continental-scale analysis of changes in wet season characteristics under the RCP4.5 and RCP8.5 climate projection scenarios across an ensemble of CMIP5 models using an objective methodology to determine the onset and cessation of the wet season. A delay in the wet season over West Africa and the Sahel of over 5–10 days on average, and later onset of the wet season over southern Africa, is identified and associated with increasing strength of the Saharan heat low in late boreal summer and a northward shift in the position of the tropical rain belt over August–December. Over the Horn of Africa rainfall during the “short rains” season is projected to increase by over 100 mm on average by the end of the twenty-first century under the RCP8.5 scenario. Average rainfall per rainy day is projected to increase, while the number of rainy days in the wet season declines in regions of stable or declining rainfall (western and southern Africa) and remains constant in central Africa, where rainfall is projected to increase. Adaptation strategies should account for shorter wet seasons, increasing rainfall intensity, and decreasing rainfall frequency, which will have implications for crop yields and surface water supplies.

Open access
Caroline M. Wainwright, John H. Marsham, David P. Rowell, Declan L. Finney, and Emily Black

Abstract

The East African precipitation seasonal cycle is of significant societal importance, and yet the current generation of coupled global climate models fails to correctly capture this seasonality. The use of convective parameterization schemes is a known source of precipitation bias in such models. Recently, a high-resolution regional model was used to produce the first pan-African climate change simulation that explicitly models convection. Here, this is compared with a corresponding parameterized-convection simulation to explore the effect of the parameterization on representation of East Africa precipitation seasonality. Both models capture current seasonality, although an overestimate in September–October in the parameterized simulation leads to an early bias in the onset of the boreal autumn short rains, associated with higher convective instability and near-surface moist static energy. This bias is removed in the explicit model. Under future climate change both models show the short rains getting later and wetter. For the boreal spring long rains, the explicit convection simulation shows the onset advancing but the parameterized simulation shows little change. Over Uganda and western Kenya both simulations show rainfall increases in the January–February dry season and large increases in boreal summer and autumn rainfall, particularly in the explicit convection model, changing the shape of the seasonal cycle, with potential for pronounced socioeconomic impacts. Interannual variability is similar in both models. Results imply that parameterization of convection may be a source of uncertainty for projections of changes in seasonal timing from global models and that potentially impactful changes in seasonality should be highlighted to users.

Open access
Mathew Barlow, Benjamin Zaitchik, Shlomit Paz, Emily Black, Jason Evans, and Andrew Hoell

Abstract

The Middle East and southwest Asia are a region that is water stressed, societally vulnerable, and prone to severe droughts. Large-scale climate variability, particularly La Niña, appears to play an important role in regionwide droughts, including the two most severe of the last 50 years—1999–2001 and 2007/08—with implications for drought forecasting. Important dynamical factors include orography, thermodynamic influence on vertical motion, storm-track changes, and moisture transport. Vegetation in the region is strongly impacted by drought and may provide an important feedback mechanism. In future projections, drying of the eastern Mediterranean region is a robust feature, as are temperature increases throughout the region, which will affect evaporation and the timing and intensity of snowmelt. Vegetation feedbacks may become more important in a warming climate. There are a wide range of outstanding issues for understanding, monitoring, and predicting drought in the region, including dynamics of the regional storm track, the relative importance of the range of dynamical mechanisms related to drought, the regional coherence of drought, the relationship between synoptic-scale mechanisms and drought, the predictability of vegetation and crop yields, the stability of remote influences, data uncertainty, and the role of temperature. Development of a regional framework for cooperative work and dissemination of information and existing forecasts would speed understanding and make better use of available information.

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Hilary Spencer, Rowan T. Sutton, Julia M. Slingo, Malcolm Roberts, and Emily Black

Abstract

Prediction of Indian Ocean interannual variability may be limited by the systematic biases in coupled GCMs or by a lack of resolution of the processes involved. In particular, little is known about the impact of ocean resolution on simulated climate variability. The simulation of Indian Ocean climate and dipole is investigated in Hadley Centre coupled models with different horizontal and vertical ocean resolutions.

The mean state of the Indian Ocean is found to improve only slightly when horizontal resolution is increased from 1.25° to ⅓° and when vertical resolution is increased from 20 to 40 vertical levels due to a small reduction of the Maritime Continent warm bias. However, improvements in the simulation of the dipole are more substantial. All versions of the model realistically simulate dipole onset between April and June, peak in September to October, and then rapidly decay between October and January. The SST anomalies are accompanied by realistic equatorial easterly wind anomalies with thermocline shoaling in the east and deepening in the southwest.

In the model with the 1.25° ocean and 20 vertical levels, the dipoles do not terminate completely but persist through the austral summer and then frequently reinvigorate the following year. This unrealistic behavior is eliminated when the ocean vertical resolution is increased from around 20 m in the thermocline to 10 m in the whole of the top 135 m and when Java is represented (even at 1.25° resolution). It is hypothesized that the improvement is due to the resolution of the separation between the thermocline and the surface and also due to the small reduction of the Maritime Continent warm bias.

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Elena Tarnavsky, David Grimes, Ross Maidment, Emily Black, Richard P. Allan, Marc Stringer, Robin Chadwick, and Francois Kayitakire

Abstract

Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) rainfall monitoring products have been extended to provide spatially contiguous rainfall estimates across Africa. This has been achieved through a new, climatology-based calibration, which varies in both space and time. As a result, cumulative estimates of rainfall are now issued at the end of each 10-day period (dekad) at 4-km spatial resolution with pan-African coverage. The utility of the products for decision making is improved by the routine provision of validation reports, for which the 10-day (dekadal) TAMSAT rainfall estimates are compared with independent gauge observations. This paper describes the methodology by which the TAMSAT method has been applied to generate the pan-African rainfall monitoring products. It is demonstrated through comparison with gauge measurements that the method provides skillful estimates, although with a systematic dry bias. This study illustrates TAMSAT’s value as a complementary method of estimating rainfall through examples of successful operational application.

Open access
Richard Washington, Mike Harrison, Declan Conway, Emily Black, Andrew Challinor, David Grimes, Richard Jones, Andy Morse, Gillian Kay, and Martin Todd

Numerous factors are associated with poverty and underdevelopment in Africa, including climate variability. Rainfall, and climate more generally, are implicated directly in the United Nations “Millennium Development Goals” to eradicate extreme poverty and hunger, and reduce child mortality and incidence of diseases such as malaria by the target date of 2015. But, Africa is not currently on target to meet these goals. We pose a number of questions from a climate science perspective aimed at understanding this background: Is there a common origin to factors that currently constrain climate science? Why is it that in a continent where human activity is so closely linked to interannual rainfall variability has climate science received little of the benefit that saw commercialization driving meteorology in the developed world? What might be suggested as an effective way for the continent to approach future climate variability and change? We make the case that a route to addressing the challenges of climate change in Africa rests with the improved management of climate variability. We start by discussing the constraints on climate science and how they might be overcome. We explain why the optimal management of activities directly influenced by interannual climate variability (which include the development of scientific capacity) has the potential to serve as a forerunner to engagement in the wider issue of climate change. We show this both from the perspective of the climate system and the institutions that engage with climate issues. We end with a thought experiment that tests the benefits of linking climate variability and climate change in the setting of smallholder farmers in Limpopo Province, South Africa.

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Felipe M. de Andrade, Matthew P. Young, David MacLeod, Linda C. Hirons, Steven J. Woolnough, and Emily Black

Abstract

This paper evaluates subseasonal precipitation forecasts for Africa using hindcasts from three models (ECMWF, UKMO, and NCEP) participating in the Subseasonal to Seasonal (S2S) prediction project. A variety of verification metrics are employed to assess weekly precipitation forecast quality at lead times of one to four weeks ahead (weeks 1–4) during different seasons. Overall, forecast evaluation indicates more skillful predictions for ECMWF over other models and for East Africa over other regions. Deterministic forecasts show substantial skill reduction in weeks 3–4 linked to lower association and larger underestimation of predicted variance compared to weeks 1–2. Tercile-based probabilistic forecasts reveal similar characteristics for extreme categories and low quality in the near-normal category. Although discrimination is low in weeks 3–4, probabilistic forecasts still have reasonable skill, especially in wet regions during particular rainy seasons. Forecasts are found to be overconfident for all weeks, indicating the need to apply calibration for more reliable predictions. Forecast quality within the ECMWF model is also linked to the strength of climate drivers’ teleconnections, namely, El Niño–Southern Oscillation, Indian Ocean dipole, and the Madden–Julian oscillation. The impact of removing all driver-related precipitation regression patterns from observations and hindcasts shows reduction of forecast quality compared to including all drivers’ signals, with more robust effects in regions where the driver strongly relates to precipitation variability. Calibrating forecasts by adding observed regression patterns to hindcasts provides improved forecast associations particularly linked to the Madden–Julian oscillation. Results from this study can be used to guide decision-makers and forecasters in disseminating valuable forecasting information for different societal activities in Africa.

Open access
Gabriele C. Hegerl, Emily Black, Richard P. Allan, William J. Ingram, Debbie Polson, Kevin E. Trenberth, Robin S. Chadwick, Phillip A. Arkin, Beena Balan Sarojini, Andreas Becker, Aiguo Dai, Paul J. Durack, David Easterling, Hayley J. Fowler, Elizabeth J. Kendon, George J. Huffman, Chunlei Liu, Robert Marsh, Mark New, Timothy J. Osborn, Nikolaos Skliris, Peter A. Stott, Pier-Luigi Vidale, Susan E. Wijffels, Laura J. Wilcox, Kate M. Willett, and Xuebin Zhang

Abstract

Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time series over land, but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols and because of the large climate variability presently limits confidence in attribution of observed changes.

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