No abstract

Abstract.We describe the construction of a new version of the Europewide E-OBS temperature (daily minimum, mean and maximum values) and precipitation dataset. This version provides an improved estimation of interpolation uncertainty through the calculation of a 100-member ensemble of realizations of each daily field. The dataset covers the period back to 1950, and provides gridded fields at a spacing of 0.25• x 0.25 • in regular latitude/longitude coordinates. As with the original E-OBS dataset, the ensemble version is based on the station series collated as part of the ECA&D initiative. Station density varies significantly over the domain, and over time, and a reliable estimation of interpolation uncertainty in the gridded fields is therefore important for users of the dataset. The uncertainty quantified by the ensemble dataset is more realistic than the uncertainty estimates in the original version, although uncertainty is still underestimated in data-sparse regions. The new dataset is compared against the earlier version of E-OBS and against regional gridded datasets produced by a selection of National Meteorological Services (NMSs). In terms of both climatological averages and extreme values, the new version of E-OBS is broadly comparable to the earlier version. Nonetheless, users will notice differences between the two E-OBS versions, especially for precipitation, which arises from the different gridding method used. Keypoints:• An improved uncertainty estimate is provided through the generation of multiple realizations• The new dataset is broadly consistent with the original version

An atlas of megadroughts in Europe and in the Mediterranean Basin during the Common Era provides insights into climate variability.

The El Niño-Southern Oscillation (ENSO) is the main driver of interannual climate extremes in Amazonia and other tropical regions. The current 2015/2016 EN event was expected to be as strong as the EN of the century in 1997/98, with extreme heat and drought over most of Amazonian rainforests. Here we show that this protracted EN event, combined with the regional warming trend, was associated with unprecedented warming and a larger extent of extreme drought in Amazonia compared to the earlier strong EN events in 1982/83 and 1997/98. Typical EN-like drought conditions were observed only in eastern Amazonia, whilst in western Amazonia there was an unusual wetting. We attribute this wet-dry dipole to the location of the maximum sea surface warming on the Central equatorial Pacific. The impacts of this climate extreme on the rainforest ecosystems remain to be documented and are likely to be different to previous strong EN events.

[1] Global maps of monthly self-calibrating Palmer Drought Severity Index (scPDSI) have been calculated for the period 1901-2009 based on the CRU TS 3.10.01 data sets. This work addresses some concerns with regard to monitoring of global drought conditions using the traditional Palmer Drought Severity Index. First, the scPDSI has a similar range of variability in diverse climates making it a more suitable metric for comparing the relative availability of moisture in different regions. Second, the more physically based Penman-Monteith parameterization for potential evapotranspiration is used, calculated using the actual vegetation cover rather than a reference crop. Third, seasonal snowpack dynamics are considered in the water balance model. The leading mode of variability in the new data set represents a trend towards drying conditions in some parts of the globe between 1950 and 1985 but accounts for less than 9% of the total variability. Increasing temperature and potential evapotranspiration explain part of the drying trend. However, local trends in most of the drying regions are not significant. Previously published evidence of unusually strong or widespread drying is not supported by the evidence in this work. A fundamental aspect of the calculation of scPDSI is the selection of a calibration period. When this period does not include the most recent part of the record, trends towards more extreme conditions are amplified. It is shown that this is the principal reason for different published interpretations of the scale of recent global drying and not, as recently claimed, the use of simplified forcing data.Citation: van der Schrier, G., J. Barichivich, K. R. Briffa, and P. D. Jones (2013), A scPDSI-based global data set of dry and wet spells for

We present the second update to a data set of gridded land‐based temperature and precipitation extremes indices: HadEX3. This consists of 17 temperature and 12 precipitation indices derived from daily, in situ observations and recommended by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). These indices have been calculated at around 7,000 locations for temperature and 17,000 for precipitation. The annual (and monthly) indices have been interpolated on a 1.875°×1.25° longitude‐latitude grid, covering 1901–2018. We show changes in these indices by examining ”global”‐average time series in comparison with previous observational data sets and also estimating the uncertainty resulting from the nonuniform distribution of meteorological stations. Both the short and long time scale behavior of HadEX3 agrees well with existing products. Changes in the temperature indices are widespread and consistent with global‐scale warming. The extremes related to daily minimum temperatures are changing faster than the maximum. Spatial changes in the linear trends of precipitation indices over 1950–2018 are less spatially coherent than those for temperature indices. Globally, there are more heavy precipitation events that are also more intense and contribute a greater fraction to the total. Some of the indices use a reference period for calculating exceedance thresholds. We present a comparison between using 1961–1990 and 1981–2010. The differences between the time series of the temperature indices observed over longer time scales are shown to be the result of the interaction of the reference period with a warming climate. The gridded netCDF files and, where possible, underlying station indices are available from http://www.metoffice.gov.uk/hadobs/hadex3 and http://www.climdex.org.

Abstract. In this study we analyzed the sensitivity of four drought indices to precipitation (P) and

No abstract