Mike Hulme

Representing Twentieth-Century Space-Time Climate Variability. Part II: Development of 1901-96 Monthly Grids of Terrestrial Surface Climate

The authors describe the construction of a 0.58 lat‐long gridded dataset of monthly terrestrial surface climate for the period of 1901‐96. The dataset comprises a suite of seven climate elements: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapor pressure, cloud cover, and ground frost frequency. The spatial coverage extends over all land areas, including oceanic islands but excluding Antarctica. Fields of monthly climate anomalies, relative to the 1961‐90 mean, were interpolated from surface climate data. The anomaly grids were then combined with a 1961‐90 mean monthly climatology (described in Part I) to arrive at grids of monthly climate over the 96-yr period. The primary variables—precipitation, mean temperature, and diurnal temperature range—were interpolated directly from station observations. The resulting time series are compared with other coarser-resolution datasets of similar temporal extent. The remaining climatic elements, termed secondary variables,were interpolated from merged datasets comprising station observations and, in regions where there were no station data, synthetic data estimated using predictive relationships with the primary variables. These predictive relationships are described and evaluated. It is argued that this new dataset represents an advance over other products because (i) it has higher spatial resolution than other datasets of similar temporal extent, (ii) it has longer temporal coverage than other products of similar spatial resolution, (iii) it encompasses a more extensive suite of surface climate variables than available elsewhere, and (iv) the construction method ensures that strict temporal fidelity is maintained. The dataset should be of particular relevance to a number of applications in applied climatology, including large-scale biogeochemical and hydrological modeling, climate change scenario construction, evaluation of regional climate models, and comparison with satellite products. The dataset is available from the Climatic Research Unit and is currently being updated to 1998.

Representing Twentieth-Century Space–Time Climate Variability. Part I: Development of a 1961–90 Mean Monthly Terrestrial Climatology

Abstract The construction of a 0.5° lat × 0.5° long surface climatology of global land areas, excluding Antarctica, is described. The climatology represents the period 1961–90 and comprises a suite of nine variables: precipitation, wet-day frequency, mean temperature, diurnal temperature range, vapor pressure, sunshine, cloud cover, ground frost frequency, and wind speed. The climate surfaces have been constructed from a new dataset of station 1961–90 climatological normals, numbering between 19 800 (precipitation) and 3615 (wind speed). The station data were interpolated as a function of latitude, longitude, and elevation using thin-plate splines. The accuracy of the interpolations are assessed using cross validation and by comparison with other climatologies. This new climatology represents an advance over earlier published global terrestrial climatologies in that it is strictly constrained to the period 1961–90, describes an extended suite of surface climate variables, explicitly incorporates elevation...

Adaptation to climate change in the developing world

The world’s climate is changing and will continue to change into the coming century at rates projected to be unprecedented in recent human history. The risks associated with these changes are real but highly uncertain. Societal vulnerability to the risks associated with climate change may exacerbate ongoing social and economic challenges, particularly for those parts of societies dependent on resources that are sensitive to changes in climate. Risks are apparent in agriculture, fisheries and many other components that constitute the livelihood of rural populations in developing countries. In this paper we explore the nature of risk and vulnerability in the context of climate change and review the evidence on present-day adaptation in developing countries and on coordinated international action on future adaptation. We argue that all societies are fundamentally adaptive and there are many situations in the past where societies have adapted to changes in climate and to similar risks. But some sectors are more sensitive and some groups in society more vulnerable to the risks posed by climate change than others. Yet all societies need to enhance their adaptive capacity to face both present and future climate change outside their experienced coping range. The challenges of climate change for development are in the present. Observed climate change, present-day climate variability and future expectations of change are changing the course of development strategies - development agencies and governments are now planning for this adaptation challenge. The primary challenge, therefore, posed at both the scale of local natural resource management and at the scale of international agreements and actions, is to promote adaptive capacity in the context of competing sustainable development objectives.

Observed trends in the daily intensity of United Kingdom precipitation

The intensity distribution of daily precipitation amounts in the UK has changed over the period 1961–1995, becoming on average more intense in winter and less intense in summer. This result is based on an analysis of 110 UK station records. In winter, and in terms of their relative contributions to total winter precipitation, there has been a decline in light and medium events and an increase in the heaviest events. This change is fairly uniform across the whole country and is apparent even when longer records (with reduced spatial coverage/detail) are analysed back to 1931 or 1908. The reverse is found in summer: over 1961–1995 there has been a decline in the proportion of the seasonal total being provided by the heaviest events. In the longer term context, however, the summer changes appear to be a return to earlier levels after a period in the 1960s when heavy summer rainfall made a greater than normal contribution. More complex changes have occurred in the intensity distribution of spring and autumn precipitation, with opposite changes in different regions of the UK. Copyright

Does climate adaptation policy need probabilities

Abstract Estimating the likelihood of future climate change has become a priority objective within the research community. This is the case because of the advancement of science, because of user demand and because of the central role played by climate prediction in guiding adaptation policy. But are probabilities what climate policy really needs? This article reviews three key questions: (1) Why might we (not) need probabilities of climate change? (2) What are the problems in estimating probabilities? (3) How are researchers estimating probabilities? These questions are analysed within the context of adaptation to climate change. Overall, we conclude that the jury is still out on whether probabilities are useful for climate adaptation policy. The answer is highly context dependent and thus is a function of the goals and motivation of the policy analysis, the unit of analysis, timescale and the training of the analyst. Probability assessment in the context of climate change is always subjective, conditional and provisional. There are various problems in estimating the probability of future climate change, but reflexive human behaviour (i.e. actions explicitly influenced by information) is largely intractable in the context of prediction. Nonetheless, there is considerable scope to develop novel methodologies that combine conditional probabilities with scenarios and which are relevant for climate decision-making.

Precipitation sensitivity to global warming: Comparison of observations with HadCM2 simulations

Recent century-long experiments performed with global climate models have simulated observed trends in global-mean temperature quite successfully when both greenhouse gas and aerosol forcing has been included. The performance of these same experiments in simulating observed global-scale changes in precipitation has not previously been examined. Here we use a gridded terrestrial precipitation dataset for the period 1900 to 1996 to examine the extent to which observed global and zonal-mean precipitation sensitivities to global warming have been captured by a series of model simulations recently completed by the UK Hadley Centre. There are signs that the model has been able to reproduce at least some of the observed zonal-mean variations in the precipitation sensitivity to warming. Questions remain both about the quality of the observed precipitation data and about the spatial scale at which anthropogenically-forced global climate models can be expected to reproduce observed variations in precipitation.

Evaporation and potential evapotranspiration in India under conditions of recent and future climate change

Abstract Long-term changes in evaporation and potential evapotranspiration can have profound implications for hydrologic processes as well as for agricultural crop performance. This paper analyses evaporation time series data for different stations in India, and for the country as a whole, for different seasons on both a short-term (15 years) and long-term (32 years) basis for pan evaporation and on a short-term basis alone for potential evapotranspiration. The analysis shows that both pan evaporation and potential evapotranspiration have decreased during recent years in India. The likely causative meteorological parameters for such changes are identified. Future scenarios of potential evapotranspiration, and its component energy and aerodynamic terms, for India based on results from six global climate model climate change experiments are also calculated and intercompared. Future warming seems likely to lead in general to increased potential evapotranspiration over India, although this increase will be unequal between regions and seasons. Such changes could have marked implications for economic and environmental welfare in the country, especially if the increases in evaporation are not compensated by adequate increases in rainfall.

CALCULATING REGIONAL CLIMATIC TIME SERIES FOR TEMPERATURE AND PRECIPITATION: METHODS AND ILLUSTRATIONS

Various methods for combining station temperature and precipitation time series into regional series are examined. Interpolation of the station series on to regular grid-boxes of some kind reduces the effects of both spatial and temporal changes in station coverage. Regional time series are best produced by using anomaly or standardized anomaly values rather than the raw values. For temperature, and for spatially coherent regions in terms of precipitation variance, the exact method does not seriously affect the resulting time series, provided anomalies are used, although the magnitudes of trends may differ. For regions with large spatial variations in precipitation variance, the additional step of standardizing the anomaly values is recommended. Both anomaly and standardized anomaly series can be easily transformed back to the original units, although the exact method for doing so can alter the resulting time series in non-trivial ways.

A 1951–80 global land precipitation climatology for the evaluation of general circulation models

Previous evaluations of model precipitation fields have suffered from two weaknesses; they have used only mean observed climatologies which have prevented an explicit evaluation of interannual variability, and they have generally failed to quantify the significance of differences between model and observed fields. To rectify these weaknesses, a global precipitation climatology is required which is designed with model evaluation in mind. This paper describes such a climatology representative of the period 1951–80. The climatology is based on historical gauge-precipitation measurements from over 2500 land-based station time series representing over 28% of the Earths surface. It is necessarily biased towards terrestrial areas. The climatology (CRU5180) is derived from month-by-month gridbox precipitation estimates at 5° resolution. Although other global precipitation climatologies exist, this is the first one to have used a consistent reference period for each station, and to include the details of interannual variability. Fields of mean seasonal and annual precipitation and mean temporal variability are presented, and the variability of global-mean precipitation over 1951–80 assessed. The resulting mean monthly global precipitation fields are compared briefly with two other observed climatologies used for model evaluation, those prepared by Jaeger and Legates and Willmott. The global and hemispheric means, mean seasonal cycles, and spatial patterns of the three cimatologies are compared. Although based on a smaller set of stations than Legates and Willmott, the CRU5180 precipitation estimates agree closely with their uncorrected climatology.

Relative impacts of human-induced climate change and natural climate variability

Assessments of the regional impacts of human-induced climate change on a wide range of social and environmental systems are fundamental for determining the appropriate policy responses to climate change. Yet regional-scale impact assessments are fraught with difficulties, such as the uncertainties of regional climate-change prediction, the specification of appropriate environmental-response models, and the interpretation of impact results in the context of future socio-economic and technological change. The effects of such confounding factors on estimates of climate-change impacts have only been poorly explored. Here we use results from recent global climate simulations and two environmental response models, to consider systematically the effects of natural climate variability (30-year timescales) and future climate-change uncertainties on river runoff and agricultural potential in Europe. We find that, for some regions, the impacts of human-induced climate change by 2050 will be undetectable relative to those due to natural multi-decadal climate variability. If misleading assessments of—and inappropriate adaptation strategies to—climate-change impacts are to be avoided, future studies should consider the impacts of natural multi-decadal climate variability alongside those of human-induced climate change.