This paper describes the construction of an updated gridded climate dataset (referred to as CRU TS3.10) from monthly observations at meteorological stations across the world's land areas. Station anomalies (from 1961 to 1990 means) were interpolated into 0.5° latitude/longitude grid cells covering the global land surface (excluding Antarctica), and combined with an existing climatology to obtain absolute monthly values. The dataset includes six mostly independent climate variables (mean temperature, diurnal temperature range, precipitation, wet‐day frequency, vapour pressure and cloud cover). Maximum and minimum temperatures have been arithmetically derived from these. Secondary variables (frost day frequency and potential evapotranspiration) have been estimated from the six primary variables using well‐known formulae. Time series for hemispheric averages and 20 large sub‐continental scale regions were calculated (for mean, maximum and minimum temperature and precipitation totals) and compared to a number of similar gridded products. The new dataset compares very favourably, with the major deviations mostly in regions and/or time periods with sparser observational data. CRU TS3.10 includes diagnostics associated with each interpolated value that indicates the number of stations used in the interpolation, allowing determination of the reliability of values in an objective way. This gridded product will be publicly available, including the input station series (http://www.cru.uea.ac.uk/ and http://badc.nerc.ac.uk/data/cru/). © 2013 Royal Meteorological Society

Abstract. We describe new reconstructions of northern extratropical summer temperatures for nine subcontinental-scale regions and a composite series representing quasi "Northern Hemisphere" temperature change over the last 600 years. These series are based on tree ring density data that have been processed using a novel statistical technique (age band decomposition) designed to preserve greater long-timescale variability than in previous analyses. We provide time-dependent and timescale-dependent uncertainty estimates for all of the reconstructions. The new regional estimates are generally cooler in almost all precalibration periods, compared to estimates obtained using earlier processing methods, particularly during the 17th century. One exception is the reconstruction for northern Siberia, where 15th century summers are now estimated to be warmer than those observed in the 20th century. In producing a new Northern Hemisphere series we demonstrate the sensitivity of the results to the methodology used once the number of regions with data, and the reliability of each regional series, begins to decrease. We compare our new hemisphere series to other published large-regional temperature histories, most of which lie within the 1 • confidence band of our estimates over most of the last 600 years. The 20th century is clearly shown by all of the palaeoseries composites to be the warmest during this period.

No abstract

Abstract. We develop methods for adjusting grid box average temperature time series for the effects on variance of changing numbers of contributing data. Owing to the different sampling characteristics of the data, we use different techniques over land and ocean. The result is to damp average temperature anomalies over a grid box by an amount inversely related to the number of contributing stations or observations. Variance corrections influence all grid box time series but have their greatest effects over data sparse oceanic regions. After adjustment, the grid box land and ocean surface temperature data sets are unaffected by artificial variance changes which might affect, in particular, the results of analyses of the incidence of extreme values. We combine the adjusted land surface air temperature and sea surface temperature data sets and apply a limited spatial interpolation. The effects of our procedures on hemispheric and global temperature anomaly series are small.

The purpose of this short paper is to provide background information about the North Atlantic Oscillation (NAO) as context for the other papers in this issue of Weather that focus on seasonal forecasts of UK and European winter climate, for which variations in the NAO are especially important.