The efficacy of Kriging spatial interpolation for filling temporal gaps in daily air temperature data: A case study in northeast China

Quality-controlled and serially complete daily air temperature data are essential to evaluating and modelling the influences of climate change on the permafrost in cold regions. Due to malfunctions and location changes of observing stations, temporal gaps （i.e., missing data） are common in collected datasets. The objective of this study was to assess the efficacy of Kriging spatial interpolation for estimating missing data to fill the temporal gaps in daily air temperature data in northeast China. A cross-validation experiment was conducted. Daily air temperature series from 1960 to 2012 at each station were estimated by using the universal Kriging （UK） and Kriging with an external drift （KED）, as appropriate, as if all the ob-servations at a given station were completely missing. The temporal and spatial variation patterns of estimation uncertainties were also checked. Results showed that Kriging spatial interpolation was generally desirable for estimating missing data in daily air temperature, and in this study KED performed slightly better than UK. At most stations the correlation coefficients （R2） between the observed and estimated daily series were 〉0.98, and root mean square errors （RMSEs） of the estimated daily mean （Tmean）, maximum （Tmax）, and minimum （Tmin） of air temperature were 〈3 ℃. However, the estimation quality was strongly affected by seasonality and had spatial variation. In general, estimation uncertainties were small in summer and large in winter. On average, the RMSE in winter was approximately 1 ℃ higher than that in summer. In addition, estimation uncertainties in mountainous areas with complex terrain were significantly larger than those in plain areas.

Spatial and Temporal Variations of Climate in Europe

Temperature series of the original individual measurements of the minimum and maximum daily temperatures from 24 stations located in different regions of Europe are considered with the objective of studying the stability or the variability of the “climate” in time and space. The patterns of the temperature statistics, the shapes of probability density functions, in particular, at different places and times allow comparisons based on the Kolmogorov-Smirnov test, the Shannon entropy, and cluster analysis, used separately or in combination for the purposes of quantitative climate classification.

Variations of the thermal growing season during the period 1961–2015 in northern China

Researching into changes in thermal growing season has been one of the most important scientific issues in studies of the impact of global climate change on terrestrial ecosystems. However, few studies investigated the differences under various definitions of thermal growing season and compared the trends of thermal growing season in different parts of China. Based on the daily mean air temperatures collected from 877 meteorological stations over northern China from 1961 to 2015, we investigated the variations of the thermal growing season parameters including the onset, ending and duration of the growing season using the methods of differential analysis, trend analysis, comparative analysis, and Kriging interpolation technique. Results indicate that the differences of the maximum values of those indices for the thermal growing season were significant, while they were insignificant for the mean values. For indices with the same length of the spells exceeding 5°C, frost criterion had a significant effect on the differences of the maximum values. The differences of the mean values between frost and non-frost indices were also slight, even smaller than those from the different lengths of the spells. Temporally, the starting date of the thermal growing season advanced by 10.0–11.0 days, while the ending dates delayed by 5.0–6.0 days during the period 1961–2015. Consequently, the duration of the thermal growing season was prolonged 15.0–16.0 days. Spatially, the advanced onset of the thermal growing season occurred in the southwestern, eastern, and northeastern parts of northern China, whereas the delayed ending of the thermal growing season appeared in the western part, and the length of the thermal growing season was prolonged significantly in the vast majority of northern China. The trend values of the thermal growing season were affected by altitude. The magnitude of the earlier onset of the thermal growing season decreased, and that of the later ending increased rapidly as the altitude increased, causing the magnitude of the prolonged growing season increased correspondingly. Comparing the applicability of selected indices and considering the impacts of frost on the definitions are important and necessary for determining the timing and length of the thermal growing season in northern China.

Opposing Trends of Winter Cold Extremes over Eastern Eurasia and North America under Recent Arctic Warming

Under recent Arctic warming,boreal winters have witnessed severe cold surges over both Eurasia and North America,bringing about serious social and economic impacts.Here,we investigated the changes in daily surface air temperature(SAT)variability during the rapid Arctic warming period of 1988/89–2015/16,and found the daily SAT variance,mainly contributed by the sub-seasonal component,shows an increasing and decreasing trend over eastern Eurasia and North America,respectively.Increasing cold extremes(defined as days with daily SAT anomalies below 1.5 standard deviations)dominated the increase of the daily SAT variability over eastern Eurasia,while decreasing cold extremes dominated the decrease of the daily SAT variability over North America.The circulation regime of cold extremes over eastern Eurasia(North America)is characterized by an enhanced high-pressure ridge over the Urals(Alaska)and surface Siberian(Canadian)high.The data analyses and model simulations show the recent strengthening of the high-pressure ridge over the Urals was associated with warming of the Barents–Kara seas in the Arctic region,while the high-pressure ridge over Alaska was influenced by the offset effect of Arctic warming over the East Siberian–Chukchi seas and the Pacific decadal oscillation(PDO)–like sea surface temperature(SST)anomalies over the North Pacific.The transition of the PDO-like SST anomalies from a positive to negative phase cancelled the impact of Arctic warming,reduced the occurrence of extreme cold days,and possibly resulted in the decreasing trend of daily SAT variability in North America.The multi-ensemble simulations of climate models confirmed the regional Arctic warming as the driver of the increasing SAT variance over eastern Eurasia and North America and the overwhelming effect of SST forcing on the decreasing SAT variance over North America.Therefore,the regional response of winter cold extremes at midlatitudes to the Arctic warming could be different due to the distinct impact of decadal SST anomalies.