CRU05 0.5 Degree 1961-1990 Mean Monthly Climatology

A dataset of mean monthly surface climate over global land areas, excluding Antarctica. Interpolated from station data to 0.5 degree lat/lon for a range of variables: precipitation and wet-day frequency, mean temperature and diurnal temperature range (from which maximum temperature and minimum temperature can be determined), vapour pressure, sunshine, cloud cover, ground-frost frequency and windspeed. The data are described in New, M., M. Hulme and P. Jones, 1999: Representing twentieth-century space-time climate variability. Part I: Development of a 1961-90 mean monthly terrestrial climatology. J. Climate, 12, 829-856.

This is available free of charge and without restriction from the IPCC Data Distribution Centre (http://ipcc-ddc.cru.uea.ac.uk).

CRU05 0.5 Degree 1901-1995 Monthly Climate Time-Series

A 0.5 degree lat/lon dataset of monthly surface climate extending from 1901 to near real-time (currently 1995) over global land areas, excluding Antarctica. Primary variables are interpolated directly from station time-series: precipitation, mean temperature and diurnal temperature range. Secondary variables are interpolated from station series where data are available and estimated using relationships with primary variables in regions with no data: wet-day frequency, vapour pressure, cloud cover and ground-frost frequency. The data are described in New, M. G., M. Hulme and P. D. Jones, 2000: Representing twentieth-century space-time climate variability. Part II: Development of 1901-1996 monthly grids of terrestrial surface climate. J. Climate, 13, 2217-2238.

Available on request from the Climatic Research Unit.

Data Release Agreement

You will be required to fill in a data release agreement (and pay the appropriate fee) before you can access the monthly data. In the agreement you will have to fill in details of the project(s) in which you intend to use the data. If, in future, you wish to use the data for different research, you should re-apply for permission - there will be no additional charge, but it helps us keep a record of users and applications. In return, you will be made aware of any new releases or updates to the dataset. The release form for the monthly time-series can be downloaded from http://www.cru.uea.ac.uk/~markn/cru05/licence.htm – this form also has details of the handling charge associated with the dataset.

All queries should be directed to CRU (cru@uea.ac.uk).

Journal of Climate: Vol. 12, No. 3, pp. 829–856.

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

Mark New, Mike Hulme, and Phil Jones

Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom

(Manuscript received 22 December 1997, in final form 3 April 1998)

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 19800 (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 as a predictor variable, and contains an evaluation of regional errors associated with this and other commonly used climatologies. The climatology is already being used by researchers in the areas of ecosystem modelling, climate model evaluation, and climate change impact assessment.

The data are available from the Climatic Research Unit and images of all the monthly fields can be accessed via the World Wide Web.

© Copyright by American Meteorological Society 1999

Journal of Climate: Vol. 13, No. 13, pp. 2217–2238.

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

Mark New, ^* Mike Hulme, and Phil Jones

Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom

(Manuscript received 21 July 1998, in final form 19 August 1999)

ABSTRACT

The authors describe the construction of a 0.5° 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.