Preliminary climatology of southern Africa extreme weather: 1973–1992

Summary Preliminary climatological statistics of extreme weather events over the southern Africa region are established through analysis of daily weather maps of the South African Weather Bureau for a twenty year peiod, 1973–1992. Influences of global warming and inter-annual variability imposed by El Nino events, amongst others, are sought. Notable trends include a decrease in the frequency of station days with rainfall > 70 mm and an increase in station days with temperature > 38°C. Correlations offer some insights to extreme climate associations. Lows over the land in the west and over the sea to the east display consistent interannual variability, despite opposing rainfall regimes. Agreement in extreme temperature statistics in all regions suggest that drought is widespread over southern Africa. Rainfall in the north is negatively related to lows over the sea to the south. A potential mechanism underlying the inverse relationship between midlatitude and sub-tropical storminess is the development of a vorticity dipole associated with the westerly jet stream. This is investigated in an El Nino-influenced case study.With 9 Figures     

Atmosphere-land surface interactions and their influence on extreme rainfall and potential abrupt climate change over southern Africa

In a changing climate, changes in rainfall variability and, in particular, extreme rainfall events are likely to be highly significant for environmentally vulnerable regions such as southern Africa. It is generally accepted that sea-surface temperatures play an important role in modulating rainfall variability, thus the majority work to date has focused on these mechanisms. However past research suggests that land surface processes are also critical for rainfall variability. In particular, work has suggested that the atmosphere-land surface feedback has been important for past abrupt climate changes, such as those which occurred over the Sahara during the mid-Holocene or, more recently, the prolonged Sahelian drought. Therefore the primary aim of this work is to undertake idealised experiments using both a regional and global climate model, to test the sensitivity of rainfall variability to land surface changes over a location where such abrupt climate changes are projected to occur in the future, namely southern Africa. In one experiment, the desert conditions currently observed over southwestern Africa were extended to cover the entire subcontinent. This is based on past research which suggests a remobilisation of sand dune activity and spatial extent under various scenarios of future anthropogenic global warming. In the second experiment, savanna conditions were imposed over all of southern Africa, representing an increase in vegetation for most areas except the equatorial regions. The results suggest that a decrease in rainfall occurs in the desert run, up to 27% of total rainfall in the regional model (relative to the control), due to a reduction in available moisture, less evaporation, less vertical uplift and therefore higher near surface pressure. This result is consistent across both the regional and global model experiments. Conversely an increase in rainfall occurs in the savanna run, because of an increase in available moisture giving an increase in latent heat and therefore surface temperature, increasing vertical uplift and lowering near surface pressure. These experiments, however, are only preliminary, and form the first stage of a wider study into how the atmosphere-land surface feedback influences rainfall extremes over southern Africa in the past (when surface i.e. vegetation conditions were very different) and in the future under various scenarios of future climate change. Future work will examine how other climate models simulate the atmosphere-land surface feedback, using more realistic vegetation types based on past and future surface conditions.     

A comparison of three multi-site statistical downscaling models for daily rainfall in the North China Plain

Three statistical downscaling methods (conditional resampling statistical downscaling model: CR-SDSM, the generalised linear model for daily climate time series: GLIMCLIM, and the non-homogeneous hidden Markov model: NHMM) for multi-site daily rainfall were evaluated and compared in the North China Plain (NCP). The comparison focused on a range of statistics important for hydrological studies including rainfall amount, extreme rainfall, intra-annual variability, and spatial coherency. The results showed that no single model performed well over all statistics/timescales, suggesting that the user should chose appropriate methods after assessing their advantages and limitations when applying downscaling methods for particular purposes. Specifically, the CR-SDSM provided relatively robust results for annual/monthly statistics and extreme characteristics, but exhibited weakness for some daily statistics, such as daily rainfall amount, dry-spell length, and annual wet/dry days. GLIMCLIM performed well for annual dry/wet days, dry/wet spell length, and spatial coherency, but slightly overestimated the daily rainfall. Additionally, NHMM performed better for daily rainfall and annual wet/dry days, but slightly underestimated dry/wet spell length and overestimated the daily extremes. The results of this study could be applied when investigating climate change impact on hydrology and water availability for the NCP, which suffers from intense water shortages due to climate change and human activities in recent years.     

Adaptation to climate change in Africa: Challenges and opportunities identified from Ethiopia

Africa is widely held to be highly vulnerable to future climate change and Ethiopia is often cited as one of the most extreme examples. With this in mind we seek to identify entry points to integrate short- to medium-term climate risk reduction within development activities in Africa, drawing from experiences in Ethiopia. To achieve this we employ a range of data and methods. We examine the changing nature of climate risks using analysis of recent climate variability, future climate scenarios and their secondary impacts. We assess the effects of climate variability on agricultural production and national GDP. Entry points and knowledge gaps in relation to mainstreaming climate risks in Ethiopia are identified using the Government's plan for poverty reduction. We end with a case study incorporating climate risks through drought insurance within the current social protection programme in Ethiopia, which provides support to 8.3 million people.Rainfall behaviour in Ethiopia shows no marked emergent changes and future climate projections show continued warming but very mixed patterns of rainfall change. Economic analysis highlights sensitivities within the economy to large-scale drought, however, while the effects are clear in major drought years in other years the relationship is weak. For social protection fairly small positive and negative effects on the number of recipients and frequency of cash payments during drought occur under the extreme range of climate model rainfall projections (2020s).Our analysis highlights several important challenges and opportunities for addressing climate risks. Challenges primarily relate to the large uncertainties in climate projections for parts of Africa, a weak evidence base of complex, often non-deterministic, climate-society interactions and institutional issues. Opportunities relate to the potential for low-regrets measures to reduce vulnerability to current climate variability which can be integrated with relatively modest effort within a shift in Africa from a disaster-focused view of climate to a long-term perspective that emphasises livelihood security and vulnerability reduction.     

Tropical deforestation and climate variability

A new tropical deforestation experiment has been performed, with the ARPEGE-Climat atmospheric global circulation model associated with the ISBA land surface scheme. Simulations are forced with observed monthly mean sea surface temperatures and thus inter-annual variability of the ocean system is taken into account. The local mean response to deforestation over Amazonia and Africa is relatively weak compared with most published studies and compensation effects are particularly important. However, a large increase in daily maximum temperatures is obtained during the dry season when soil water stress dominates. The analysis of daily variability shows that the distributions of daily minimum and maximum temperatures are noticeably modified with an increase in extreme temperatures. Daily precipitation amounts also indicate a weakening of the convective activity. Conditions for the onset of convection are less frequently gathered, particularly over southern Amazonia and western equatorial Africa. At the same time, the intensity of convective events is reduced, especially over equatorial deforested regions. The inter-annual variability is also enhanced. For instance, El Niño events generally induce a large drying over northern Amazonia, which is well reproduced in the control simulation. In the deforested experiment, a positive feedback effect leads to a strong intensification of this drying and a subsequent increase in surface temperature. The change in variability as a response to deforestation can be more crucial than the change of the mean climate since more intense extremes could be more detrimental for agriculture than an increase in mean temperatures.     

Monsoon rainfall extreme indices and tendencies from 1954–2003 in Kerala,India

Climate change has the potential ability to alter the occurrence and severity of extreme events. Though predicting changes of such extreme events is difficult, understanding them is important to determine the impacts of climate change in various sectors. This paper presents the change in rainfall extremes in the monsoon season in south-west Indian peninsula. Daily rainfall data were analysed for the entire Kerala state in India to determine if the extreme rainfall had changed over the 50-year period. Several indices were derived from the data to identify the extreme rainfalls. The trends of all the extreme indices were assessed by parametric ordinary least square regression technique, which were tested for significance at 95% level. Results showed significant decrease in monsoon rainfall extremes in Kerala that would affect the tendency of change in seasonal total rainfall. This study provides a comprehensive knowledge on extreme monsoon precipitation in Kerala, which could also be employed to study changing climate at local scale in other regions.     

Climate-change effects on extreme precipitation in central Europe: uncertainties of scenarios based on regional climate models

Observations as well as most climate model simulations are generally in accord with the hypothesis that the hydrologic cycle should intensify and become highly volatile with the greenhouse-gas-induced climate change, although uncertainties of these projections as well as the spatial and seasonal variability of the changes are much larger than for temperature extremes. In this study, we examine scenarios of changes in extreme precipitation events in 24 future climate runs of ten regional climate models, focusing on a specific area of the Czech Republic (central Europe) where complex orography and an interaction of other factors governing the occurrence of heavy precipitation events result in patterns that cannot be captured by global models. The peaks-over-threshold analysis with increasing threshold censoring is applied to estimate multi-year return levels of daily rainfall amounts. Uncertainties in scenarios of changes for the late 21st century related to the inter-model and within-ensemble variability and the use of the SRES-A2 and SRES-B2 greenhouse gas emission scenarios are evaluated. The results show that heavy precipitation events are likely to increase in severity in winter and (with less agreement among models) also in summer. The inter-model and intra-model variability and related uncertainties in the pattern and magnitude of the change is large, but the scenarios tend to agree with precipitation trends recently observed in the area, which may strengthen their credibility. In most scenario runs, the projected change in extreme precipitation in summer is of the opposite sign than a change in mean seasonal totals, the latter pointing towards generally drier conditions in summer. A combination of enhanced heavy precipitation amounts and reduced water infiltration capabilities of a dry soil may severely increase peak river discharges and flood-related risks in this region.     

Simulation of the variability and extremes of daily rainfall during the Indian summer monsoon for present and future times in a global time-slice experiment

In this study the simulation of the variability and extremes of daily rainfall during the Indian summer monsoon for the present-day and the future climate is investigated. This is done on the basis of a global time-slice experiment (TSL) with the ECHAM4 atmospheric general circulation model (GCM) at a high horizontal resolution of T106. The first time-slice (period: 1970–1999) represents the present-day climate and the second (2060–2089) the future climate. Moreover, observational rainfall data from the Global Precipitation Climatology Project (GPCP, 1997–2002) and rainfall data from the ECMWF re-analysis (ERA, 1958–2001) are considered. ERA reveals serious deficiencies in its representation of the variability and extremes of daily rainfall during the Indian summer monsoon. These are mainly a severe overestimation of the frequency of wet days over the oceans and in the Himalayas, where also the rainfall intensity is overestimated. Further, ERA shows unrealistically heavy rainfall events over the tropical Indian Ocean. The ECHAM4 atmospheric GCM at a horizontal resolution of T106, on the other hand, simulates the variability and extremes of daily rainfall in good agreement with the observations. The only marked deficiencies are an underestimation of the rainfall intensity on the west coast of the Indian peninsula and in Bangladesh, an overestimation over the tropical Indian Ocean, due to an erroneous northwestward extension of the tropical convergence zone, and an overestimation of the frequency of wet days in Tibet. Further, heavy rainfall events are relatively strong in the centre of the Indian peninsula. For the future, TSL predicts large increases in the rainfall intensity over the tropical Indian Ocean as well as in northern Pakistan and northwest India, but decreases in southern Pakistan, in the centre of the Indian peninsula, and over the western part of the Bay of Bengal. The frequency of wet days is markedly increased over the tropical Indian Ocean and decreased over the northern part of the Arabian Sea and in Tibet. The intensity of heavy rainfall events is generally increased in the future, with large increases over the Arabian Sea and the tropical Indian Ocean, in northern Pakistan and northwest India as well as in northeast India, Bangladesh, and Myanmar.     

Climatic change over the Lowveld of South Africa

There has been a 38% decrease in expected annual rainfall totals over the Lowveld, in the eastern part of South Africa, during the last two decades. The downward trend in mean annual rainfall is not replicated in the rest of the summer rainfall region above the escarpment. Rainfall variability over the Lowveld has been increasing since about the 1950s, although the increase in variability appears to have been slowing down in more recent years. Changes in the frequency and intensity of El Niño/Southern Oscillation extreme events are only partly responsible for the observed desiccation and increase in rainfall variability. The CSIRO 9-level general circulation model simulates, for 2 × CO₂ conditions, an insignificant decrease of 10% in the annual mean and a slight increase in the inter-annual variability of rainfall over the Lowveld. Other general circulation models likewise simulate only small changes in annual mean rainfall over the region. However, the simulated increase in rainfall variability by the CSIRO 9-level model is likely to be conservative since the model, being linked to a slab ocean, is unable to represent important features of ocean-atmosphere coupling in the region. Significant changes in the frequencies of extreme drought events and of heavy rains in the Lowveld are likely to occur even with only small changes in the rainfall climatology of the region.     

Downscaling daily precipitation time series using a combined circulation- and regression-based approach

The aim of this paper is to introduce a new conditional statistical model for generating daily precipitation time series. The generated daily precipitation can thus be used for climate change impact studies, e.g., crop production, rainfall–runoff, and other water-related processes. It is a stochastic model that links local rainfall events to a continuous atmospheric predictor, moisture flux, in addition to classified atmospheric circulation patterns. The coupled moisture flux is proved to be capable of capturing continuous property of climate system and providing extra information to determine rainfall probability and rainfall amount. The application was made to simultaneously downscale daily precipitation at multiple sites within the Rhine River basin. The results show that the model can well reproduce statistical properties of daily precipitation time series. Especially for extreme rainfall events, the model is thought to better reflect rainfall variability compared to the pure CP-based downscaling approach.     

Scenarios of extreme temperature events

Based on the principles of the probability theory a statistical model has been developed assessing the likelihood of occurrence of extreme temperature events from the knowledge of the statistical characteristics of the daily temperature extremes. It is demonstrated that the probability of such events is more sensitive to changes in the variability of climate than to changes in its average. Further, this sensitivity increases at a nonlinear rate the more extreme the event. The applicability of the model has been verified by comparing the simulated frequencies of a large spectrum of temperature events with the observed numbers derived from a long time series of daily temperature extremes at Potsdam. Accordingly, the relative simulation errors increase significantly as the events become more extreme. A correction is possible, because most of these errors are systematic rather than random. Moreover, in accordance with the climate observations the simulations reveal statistically significant linear trends in the number of extreme events since the end of the last century. Local scenarios of extreme temperature events have been derived for the city of Berlin by considering both hypothetical new climate states and climate changes simulated by a General Circulation Model (GCM). As a consequence of an increase in the atmospheric concentration of greenhouse gases up to the end of the next century according to the IPCC Scenario A the repetition rate of extreme events in summer (e.g., hot days) is expected to rise considerably relative to the current climate. Moreover, in the winter season cold days will become extremely rare.     

Trends in Precipitation Concentration and Extremes in the Mediterranean Penedès-Anoia Region, Ne Spain

The high variability of the Mediterranean climate from year to year and within each year makes it difficult to assess changes that could be associated with a climate change. In this paper some indices, such as changes in the precipitation concentration during the year, maximum 1-day and 5-day precipitation, number of wet days (total and those with precipitation higher than the 75th and 95th percentile), magnitude and frequency of extreme events (considered as the rainfall higher than that corresponding to the 99th percentile), fraction of annual total precipitation due to events exceeding the 95th and 99th percentile, strength of the events, and length and frequency of dry period (days between consecutive rains) are evaluated for the Penedès-Anoia region (NE Spain). A 80-year daily dataset (1923–2002) and two 40-year series were used to assess possible trends. The indices indicate an increase in precipitation in winter and summer and a positive trend of concentration in autumn, with a higher number of extreme events separated by longer dry periods. The total number of wet days per year increased, although it was irregularly distributed over the year, with an increase in the extremes and in the fraction of total rainfall that these events represent in autumn and winter, and with an increase of the strength of the events in autumn. These changes in rainfall distribution have negative effects on water availability for crops and contribute to accelerate erosion processes in the area.     

Assessing future climatic changes of rainfall extremes at small spatio-temporal scales

Climate change is expected to influence the occurrence and magnitude of rainfall extremes and hence the flood risks in cities. Major impacts of an increased pluvial flood risk are expected to occur at hourly and sub-hourly resolutions. This makes convective storms the dominant rainfall type in relation to urban flooding. The present study focuses on high-resolution regional climate model (RCM) skill in simulating sub-daily rainfall extremes. Temporal and spatial characteristics of output from three different RCM simulations with 25 km resolution are compared to point rainfall extremes estimated from observed data. The applied RCM data sets represent two different models and two different types of forcing. Temporal changes in observed extreme point rainfall are partly reproduced by the RCM RACMO when forced by ERA40 re-analysis data. Two ECHAM forced simulations show similar increases in the occurrence of rainfall extremes of over a 150-year period, but significantly different changes in the magnitudes. The physical processes behind convective rainfall extremes generate a distinctive spatial inter-site correlation structure for extreme events. All analysed RCM rainfall extremes, however, show a clear deviation from this correlation structure for sub-daily rainfalls, partly because RCM output represents areal rainfall intensities and partly due to well-known inadequacies in the convective parameterization of RCMs. The results highlight the problem urban designers are facing when using RCM output. The paper takes the first step towards a methodology by which RCM performance and other downscaling methods can be assessed in relation to the simulation of short-duration rainfall extremes.     

SST versus Climate Change Signals in West African Rainfall: 20th-Century Variations and Future Projections

Rainfall variability is a crucial factor in food production,water resource planning and ecosystems, especially in regions with scarce freshwaterresources. In West Africa rainfall has been subject to largedecadal and interdecadal variations during the 20th century. The most prominent feature is thereduction in rainfall amount throughout the second half of the century with somerecovery at the end. Among the conceivable mechanisms, which might inducesuch low-frequency variability in West African precipitation, this study isfocussed onsea surface temperature (SST) variations and increasing greenhouse gas (GHG)concentrations. A tool is presented to distinguish between both impacts bymeans of various climate model simulations, which are found to reproduce theobserved rainfall characteristics over West Africa reasonably well.Further, a multi-model approach is usedto evaluate the expected future greenhouse signal in West African rainfall with respect to natural variability and intermodel variations.It is found that observed SST fluctuations, forcing two different atmospheric climate models, are able to reproduce the main features ofobserved decadal rainfall anomalies in the southern part of West Africathroughout the second half of the 20th century. The seasonal response to varying SST isstrongest in summer when the region is undergoing intensive monsoondynamics. Whereas both atmospheric models simulate the observeddrought tendency,following the 1960s, there is some indication that the additional GHG forcing in one model inducessome significantly different rainfall anomalies in recent years, re-initiatingeven positive anomalies relative to the climatological mean which has alsobeen observed since the 1990s. However, thisresult is still subject to model uncertainty.Coupled climate model integrations with different climate change scenariosalsopredict that precipitation, particularly over the Guinea Coast and Sahelregion, will steadily increase into the 21st century. The model-comprehensive signal isstatistically significant with respect to natural variability and modeluncertainty, suggesting that the observed recovery of yearly rainfall overparts of West Africa might actually reflect the beginning impact of risinganthropogenic GHG. The physical mechanism, linking the radiative forcing tothe monsoonal rainfall, probably works via warming of the tropicalAtlantic Ocean.     

Trends of precipitation extremes during 1960–2008 in Xinjiang, the Northwest China

The spatial–temporal variability of the precipitation extremes defined by eight precipitation indices based on daily precipitation dataset was analyzed using the linear regression method and the Mann–Kendall test. The results indicate that increasing trends in the precipitation amount, rainy days, and the intensity of the extreme precipitation were identified at above 70 % of the total rain stations considered in this study, with more than 30 % of them were significant, while most stations show notable decreasing trend in the annual maximum consecutive no-rain days. Significantly increasing trends of the precipitation extremes are observed mainly in the northern Xinjiang and the north of the southern Xinjiang. Most extreme precipitation indices show a potential regime shift starting from the middle of 1980s. The magnitude of the trends is compatible with their pattern of spatial stability. The generally increasing trends in precipitation extremes are found in this study.     

2021: A Year of Unprecedented Climate Extremes in Eastern Asia,North America,and Europe

The year 2021 was recorded as the 6th warmest since 1880. In addition to large-scale warming, 2021 will be remembered for its unprecedented climate extremes. Here, a review of selected high-impact climate extremes in 2021, with a focus on China, along with an extension to extreme events in North America and Europe is presented. Nine extreme events that occurred in 2021 in China are highlighted, including a rapid transition from cold to warm extremes and sandstorms in spring, consecutive drought in South China and severe thunderstorms in eastern China in the first half of the year, extremely heavy rainfall over Henan Province and Hubei Province during summer, as well as heatwaves, persistent heavy rainfall, and a cold surge during fall. Potential links of extremes in China to four global-scale climate extremes and the underlying physical mechanisms are discussed here, providing insights to understand climate extremes from a global perspective. This serves as a reference for climate event attribution, process understanding, and high-resolution modeling of extreme events.     

Internal variability in a regional climate model over West Africa

Sensitivity studies with regional climate models are often performed on the basis of a few simulations for which the difference is analysed and the statistical significance is often taken for granted. In this study we present some simple measures of the confidence limits for these types of experiments by analysing the internal variability of a regional climate model run over West Africa. Two 1-year long simulations, differing only in their initial conditions, are compared. The difference between the two runs gives a measure of the internal variability of the model and an indication of which timescales are reliable for analysis. The results are analysed for a range of timescales and spatial scales, and quantitative measures of the confidence limits for regional model simulations are diagnosed for a selection of study areas for rainfall, low level temperature and wind. As the averaging period or spatial scale is increased, the signal due to internal variability gets smaller and confidence in the simulations increases. This occurs more rapidly for variations in precipitation, which appear essentially random, than for dynamical variables, which show some organisation on larger scales.     

Projections of Extreme Rainfall in Hong Kong in the 21st Century

The possible changes in the frequency of extreme rainfall events in Hong Kong in the 21st century wereinvestigated by statistically downscaling 30 sets of the daily global climate model projections (involvinga combination of 12 models and 3 greenhouse gas emission scenarios,namely,A2,A1B,and B1) of theFourth Assessment Report of the Intergovernmental Panel on Climate Change.To cater for the intermittentand skewed character of the daily rainfall,multiple stepwise logistic regression and multiple stepwise linearregression were employed to develop the downscaling models for predicting rainfall occurrence and rainfallamount,respectively.Verification of the simulation of the 1971-2000 climate reveals that the models ingeneral have an acceptable skill in reproducing past statistics of extreme rainfall events in Hong Kong.Theprojection results suggest that,in the 21st century,the annual number of rain days in Hong Kong is expectedto decrease while the daily rainfall intensity will increase,concurrent with the expected increase in annualrainfall.Based on the multi-model scenario ensemble mean,the annual number of rain day is expected todrop from 104 days in 1980-1999 to about 77 days in 2090-2099.For extreme rainfall events,about 90% ofthe model-scenario combinations indicate an increase in the annual number of days with daily rainfall 100mm (R100) towards the end of the 21st century.The mean number of R100 is expected to increase from 3.5days in 1980-1999 to about 5.3 days in 2090-2099.The projected changes in other extreme rainfall indicesalso suggest that the rainfall in Hong Kong in the 21st century may also become more extreme with moreuneven distributions of wet and dry periods.While most of the model-emission scenarios in general projectconsistent trends in the change of rainfall extremes in the 21st century,there is a large divergence in theprojections among different model/emission scenarios.This reflects that there are still large uncertainties inmodel simulations of future extreme rainfall events.