Bruce Hewitson

Evidence of trends in daily climate extremes over southern and west Africa

Received 31 May 2005; revised 10 January 2006; accepted 23 March 2006; published 21 July 2006. [1] There has been a paucity of information on trends in daily climate and climate extremes, especially from developing countries. We report the results of the analysis of daily temperature (maximum and minimum) and precipitation data from 14 south and west African countries over the period 1961–2000. Data were subject to quality control and processing into indices of climate extremes for release to the global community. Temperature extremes show patterns consistent with warming over most of the regions analyzed, with a large proportion of stations showing statistically significant trends for all temperature indices. Over 1961 to 2000, the regionally averaged occurrence of extreme cold (fifth percentile) days and nights has decreased by � 3.7 and � 6.0 days/decade, respectively. Over the same period, the occurrence of extreme hot (95th percentile) days and nights has increased by 8.2 and 8.6 days/decade, respectively. The average duration of warm (cold) has increased (decreased) by 2.4 (0.5) days/decade and warm spells. Overall, it appears that the hot tails of the distributions of daily maximum temperature have changed more than the cold tails; for minimum temperatures, hot tails show greater changes in the NW of the region, while cold tails have changed more in the SE and east. The diurnal temperature range (DTR) does not exhibit a consistent trend across the region, with many neighboring stations showing opposite trends. However, the DTR shows consistent increases in a zone across Namibia, Botswana, Zambia, and Mozambique, coinciding with more rapid increases in maximum temperature than minimum temperature extremes. Most precipitation indices do not exhibit consistent or statistically significant trends across the region. Regionally averaged total precipitation has decreased but is not statistically significant. At the same time, there has been a statistically significant increase in regionally averaged daily rainfall intensity and dry spell duration. While the majority of stations also show increasing trends for these two indices, only a few of these are statistically significant. There are increasing trends in regionally averaged rainfall on extreme precipitation days and in maximum annual 5-day and 1-day rainfall, but only trends for the latter are statistically significant.

Emerging patterns of simulated regional climatic changes for the 21st century due to anthropogenic forcings

We analyse temperature and precipitation changes for the late decades of the 21st century (with respect to present day conditions) over 23 land regions of the world from 18 recent transient climate change experiments with coupled atmosphere-ocean General Circulation Models (AOGCMs). The analysis involves two different forcing scenarios and nine models, and it focuses on model agreement in the simulated regional changes for the summer and winter seasons. While to date very few conclusions have been presented on regional climatic changes, mostly limited to some broad latitudinal bands, our analysis shows that a number of consistent patterns of regional change across models and scenarios are now emerging. For temperature, in addition to maximum winter warming in northern high latitudes, warming much greater than the global average is found over Central Asia, Tibet and the Mediterranean region in summer. Consistent warming lower than the global average is found in some seasons over Southern South America, Southeast Asia and South Asia, while cases of inconsistent warming amplification compared to the global average occur mostly in some tropical and southern sub-tropical regions. Consistent increase in winter precipitation is found in northern high latitude regions, as well as Central Asia, Tibet, Western and Eastern North America, and Western and Eastern Africa regions. The experiments also indicate an increase in South Asia and East Asia summer monsoon precipitation. A number of regions show a consistent decrease in precipitation, such as Southern Africa and Australia in winter, the Mediterranean region in summer and Central America in both seasons. Possible physical mechanisms that lead to the simulated changes are discussed.

The Interannual Variability of the Onset of the Maize Growing Season over South Africa and Zimbabwe

Abstract Subsistence farmers within southern Africa have identified the onset of the maize growing season as an important seasonal characteristic, advance knowledge of which would aid preparations for the planting of rain-fed maize. Onset over South Africa and Zimbabwe is calculated using rainfall data from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the Computing Center for Water Research (CCWR). The two datasets present similar estimates of the mean, standard deviation, and trend of onset for the common period (1979–97) over South Africa. During this period, onset has been tending to occur later in the season, in particular over the coastal regions and the Limpopo valley. However, the CCWR data (1950–97) indicate that this is part of long-term (decadal) variability. Characteristic rainfall patterns associated with late and early onset are estimated using a self-organizing map (SOM). Late onset is associated with heavier rainfall over the subcontinent. When onset is ea...

Evaluation of the CORDEX-Africa multi-RCM hindcast: systematic model errors

Monthly-mean precipitation, mean (TAVG), maximum (TMAX) and minimum (TMIN) surface air temperatures, and cloudiness from the CORDEX-Africa regional climate model (RCM) hindcast experiment are evaluated for model skill and systematic biases. All RCMs simulate basic climatological features of these variables reasonably, but systematic biases also occur across these models. All RCMs show higher fidelity in simulating precipitation for the west part of Africa than for the east part, and for the tropics than for northern Sahara. Interannual variation in the wet season rainfall is better simulated for the western Sahel than for the Ethiopian Highlands. RCM skill is higher for TAVG and TMAX than for TMIN, and regionally, for the subtropics than for the tropics. RCM skill in simulating cloudiness is generally lower than for precipitation or temperatures. For all variables, multi-model ensemble (ENS) generally outperforms individual models included in ENS. An overarching conclusion in this study is that some model biases vary systematically for regions, variables, and metrics, posing difficulties in defining a single representative index to measure model fidelity, especially for constructing ENS. This is an important concern in climate change impact assessment studies because most assessment models are run for specific regions/sectors with forcing data derived from model outputs. Thus, model evaluation and ENS construction must be performed separately for regions, variables, and metrics as required by specific analysis and/or assessments. Evaluations using multiple reference datasets reveal that cross-examination, quality control, and uncertainty estimates of reference data are crucial in model evaluations.

North Atlantic climate variability from a self‐organizing map perspective

[1] North Atlantic variability in general, and the North Atlantic Oscillation (NAO) in particular, is a long-studied, very important but still not well-understood problem in climatology. The recent trend to a higher wintertime NAO index was accompanied by an additional increase in the Azores High not coupled to changes in the Icelandic Low, as shown by a self-organizing maps (SOMs) analysis of monthly mean DJF mean sea level pressure data from 1957 to 2002. SOMs are a nonlinear tool to optimally extract a user-specified number of patterns or icons from an input data set and to uniquely relate any input data field to an icon, allowing analyses of occurrence frequencies and transitions complementary to principal component analysis (PCA). SOMs analysis of ERA-40 data finds a North Atlantic ‘‘monopole’’ roughly colocated with the mean position of the Azores High, as well as the well-known NAO dipole involving the Icelandic Low and the subtropical high. Little trend is shown in December, but the Azores High increased along with the NAO in January and February over the study interval, with implications for storminess in northwestern Europe. In short, our SOM-based analyses of winter MSLP have both confirmed prior knowledge and expanded it through the relative ease of use and power with nonlinear systems of the SOM-based approach to climatological analysis.

Large‐scale atmospheric controls on local precipitation in tropical Mexico

Sixty-five percent of the short term variability in southern Mexican precipitation is accounted for by the large-scale circulation. Empirical relationships between sea level and 500 mb circulation fields, and the local precipitation in Chiapas, Mexico, are derived using a neural net. Although much of the rainfall is a result of convective processes, the neural net captures the onset of the precipitation season, and the phase of individual precipitation events. The analysis indicates that both of these aspects of the precipitation regime are controlled to a large extent by the atmospheric circulation.

Assessment of the Performance of CORDEX Regional Climate Models in Simulating East African Rainfall

AbstractThis study evaluates the ability of 10 regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in simulating the characteristics of rainfall patterns over eastern Africa. The seasonal climatology, annual rainfall cycles, and interannual variability of RCM output have been assessed over three homogeneous subregions against a number of observational datasets. The ability of the RCMs in simulating large-scale global climate forcing signals is further assessed by compositing the El Nino–Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events. It is found that most RCMs reasonably simulate the main features of the rainfall climatology over the three subregions and also reproduce the majority of the documented regional responses to ENSO and IOD forcings. At the same time the analysis shows significant biases in individual models depending on subregion and season; however, the ensemble mean has better agreement with observation than individual models....

Gridded Area-Averaged Daily Precipitation via Conditional Interpolation

Abstract A growing need for gridded observational datasets of area-average values to support research, specifically in relation to climate models, raises questions about the adequacy of traditional interpolation techniques. Conventional interpolation techniques (particularly for precipitation) suffer from not recognizing the changing spatial representivity of stations as a function of the driving synoptic state, nor the bounded nature of the precipitation field—that the precipitation field is spatially discontinuous. Further, many interpolation techniques explicitly estimate new point location values, and do not directly address the need arising from climate modeling for area-average values. A new procedure, termed conditional interpolation, is presented to estimate daily gridded area-average precipitation from station observations. The approach explicitly recognizes that the point observations represent a mixture of synoptic forcing shared in common with surrounding stations, and a response that is uniqu...

Interrogating empirical-statistical downscaling

The delivery of downscaled climate information is increasingly seen as a vehicle of climate services, a driver for impacts studies and adaptation decisions, and for informing policy development. Empirical-statistical downscaling (ESD) is widely used; however, the accompanying responsibility is significant, and predicated on effective understanding of the limitations and capabilities of ESD methods. There remain substantial contradictions, uncertainties, and sensitivity to assumptions between the different methods commonly used. Yet providing decision-relevant downscaled climate projections to help support national and local adaptation is core to the growing global momentum seeking to operationalize what is, in effect, still foundational research. We argue that any downscaled climate information must address the criteria of being plausible, defensible and actionable. Climate scientists cannot absolve themselves of their ethical responsibility when informing adaptation and must, therefore, be diligent in ensuring any information provided adequately addresses these three criteria. Frameworks for supporting such assessment are not well developed. We interrogate the conceptual foundations of statistical downscaling methodologies and their assumptions, and articulate a framework for evaluating and integrating downscaling output into the wider landscape of climate information. For ESD there are key criteria that need to be satisfied to underpin the credibility of the derived product. Assessing these criteria requires the use of appropriate metrics to test the comprehensive treatment of local climate response to large-scale forcing, and to compare across methods. We illustrate the potential consequences of methodological choices on the interpretation of downscaling results and explore the purposes, benefits and limitations of using statistical downscaling.

Daily characteristics of West African summer monsoon precipitation in CORDEX simulations

We analyze and intercompare the performance of a set of ten regional climate models (RCMs) along with the ensemble mean of their statistics in simulating daily precipitation characteristics during the West African monsoon (WAM) period (June–July–August–September). The experiments are conducted within the framework of the COordinated Regional Downscaling Experiments for the African domain. We find that the RCMs exhibit substantial differences that are associated with a wide range of estimates of higher-order statistics, such as intensity, frequency, and daily extremes mostly driven by the convective scheme employed. For instance, a number of the RCMs simulate a similar number of wet days compared to observations but greater rainfall intensity, especially in oceanic regions adjacent to the Guinea Highlands because of a larger number of heavy precipitation events. Other models exhibit a higher wet-day frequency but much lower rainfall intensity over West Africa due to the occurrence of less frequent heavy rainfall events. This indicates the existence of large uncertainties related to the simulation of daily rainfall characteristics by the RCMs. The ensemble mean of the indices substantially improves the RCMs’ simulated frequency and intensity of precipitation events, moderately outperforms that of the 95th percentile, and provides mixed benefits for the dry and wet spells. Although the ensemble mean improved results cannot be generalized, such an approach produces encouraging results and can help, to some extent, to improve the robustness of the response of the WAM daily precipitation to the anthropogenic greenhouse gas warming.