Evaluation of the homogenization adjustments applied to European temperature records in the Global Historical Climatology Network dataset

The widely used Global Historical Climatology Network (GHCN) monthly temperature dataset is available in two formats—non-homogenized and homogenized. Since 2011, this homogenized dataset has been updated almost daily by applying the “Pairwise Homogenization Algorithm” (PHA) to the non-homogenized datasets. Previous studies found that the PHA can perform well at correcting synthetic time series when certain artificial biases are introduced. However, its performance with real world data has been less well studied. Therefore, the homogenized GHCN datasets (Version 3 and 4) were downloaded almost daily over a 10-year period (2011–2021) yielding 3689 different updates to the datasets. The different breakpoints identified were analyzed for a set of stations from 24 European countries for which station history metadata were available. A remarkable inconsistency in the identified breakpoints (and hence adjustments applied) was revealed. Of the adjustments applied for GHCN Version 4, 64% (61% for Version 3) were identified on less than 25% of runs, while only 16% of the adjustments (21% for Version 3) were identified consistently for more than 75% of the runs. The consistency of PHA adjustments improved when the breakpoints corresponded to documented station history metadata events. However, only 19% of the breakpoints (18% for Version 3) were associated with a documented event within 1 year, and 67% (69% for Version 3) were not associated with any documented event. Therefore, while the PHA remains a useful tool in the community’s homogenization toolbox, many of the PHA adjustments applied to the homogenized GHCN dataset may have been spurious. Using station metadata to assess the reliability of PHA adjustments might potentially help to identify some of these spurious adjustments

Analysis of Sub-Daily Precipitation for the PannEx Region

The PannEx is a GEWEX-initiated, community driven research network in the Pannonian Basin. One of the main scientific issues to address in PannEx is the investigation of precipitation extremes. Meteorological Services in the PannEx area collected the hourly precipitation data and commonly used a computer program, which was developed in the INTENSE project, to produce a set of global hydro-climatic indices. Calculations are carried out on data aggregated 1-, 3- and 6-h intervals. Selected indices are analyzed in this paper to assess the general climatology of the short-term precipitation in the Pannonian basin. The following indices are illustrated on maps and graphs: the annual mean and maxima of 1-h, 3-h and 6-h sums, the count of 3-hr periods greater than 20 mm thresholds, the maximum length of wet hours, the timing of wettest hour and the 1-h precipitation intensity. The seasonal trends of the 1-h precipitation intensity were tested from 1998 to 2019. Analysis of sub-daily precipitation has been limited by the availability of data on a global or a regional scale. The international effort made in this work through collaboration in the PannEx initiative contributes to enlarging the data availability for regional and global analysis of sub-daily precipitation extremes

Climate of the Carpathian Region in the period 1961–2010: climatologies and trends of 10 variables

The Carpathians are the largest mountain range in Europe and they represent a geographic barrier between Central Europe, Eastern Europe, and the Balkans. In order to investigate the climate of the area, the CARPATCLIM project members compiled the Climate Atlas of the Carpathian Region, which consists of high-resolution daily grids (0.1˚ x 0.1˚) of sixteen meteorological variables and many derived indicators related to 1961-2010. We computed the gridded climatologies for 1961-2010 for eight variables (air pressure, cloudiness, precipitation, relative humidity, minimum and maximum temperature, sunshine duration, and wind speed) and we discuss their spatial patterns. For each variable, we calculated the gridded linear trends related to 1961-2010 both on annual and seasonal basis. In general, temperature was found to increase in every season in 1986-2010, confirming the trends occurring in Europe in the last decades. On the other way, wind speed decreased in every season. Cloudiness and relative humidity decreased in spring, summer, and winter, and increased in autumn, whilst sunshine duration, as expected, behaved in the opposite way. Precipitation slightly increased and air pressure showed no significant trend, except of a few grid points. Then, we dealt with the correlation between the variables: excluding the high elevation points, the most correlated are sunshine duration and temperature. In particular, positive and negative sunshine duration anomalies are found to be respectively correlated with positive and negative temperature anomalies during the global dimming (60’s and 70’s) and brightening (90’s and 2000’s) periods.JRC.H.7-Climate Risk Managemen