1991-2020 climate normal in the European Alps:focus on high-elevation environments

Alps are an important geographical area of the European continent and,in this area,temperature increase is most evident.However,the 1991-2020 climate normal in the Alps has still not been thoroughly investigated.Aiming to fill this gap with a focus on high-elevation environments,minimum and maximum daily air temperature acquired by 23 automatic weather station were used.The results show that the mean annual values of minimum and maximum temperature for the 1991-2020 climate normal in the Alps are-2.4℃ and 4.4℃,respectively,with a warming rate of 0.5℃/10 years.The mean annual temperature comparison between 1961-1990 and 1971-2000,1961-1990 and 1981-2010,1961-1990 and 1991-2020 climate normal show an increase of 0.3℃,0.5℃ and 0.9℃,respectively.The results also confirm that seasonal and annual temperatures are rising through the whole Alpine arc,mainly in summer and autumn.This work highlights that annual minimum and maximum temperature do not seem to be affected by a positive elevation-dependent warming.Instead,a positive elevation-dependent warming in the maximum values of the annual minimum temperature was found.If anthropogenic emissions maintain the trend of the last decades,the expected mean annual temperature of the 2001-2030 climate normal is-0.2℃,with an increase of 0.5℃ if compared to the 1991-2020 climate normal and with an increase of 1.5℃ if compared to the 1961-1990 climate normal.This study highlights the warming rate that is now present in the European Alps,provides indications on the warming rate that will occur in the coming years and highlights the importance of carrying out investigations that consider not only the last 30-year climate normal,but also the most recent 30-year climate normal by comparing them with each other.

On Multi-Timescale Variability of Temperature in China in Modulated Annual Cycle Reference Frame

The traditional anomaly （TA） reference frame and its corresponding anomaly for a given data span changes with the extension of data length. In this study, the modulated annual cycle （MAC）, instead of the widely used climatological mean annual cycle, is used as an alternative reference frame for computing climate anomalies to study the multi-timescale variability of surface air temperature （SAT） in China based on homogenized daily data from 1952 to 2004. The Ensemble Empirical Mode Decomposition （EEMD） method is used to separate daily SAT into a high frequency component, a MAC component, an interannual component, and a decadal-to-trend component. The results show that the EEMD method can reflect historical events reasonably well, indicating its adaptive and temporally local characteristics. It is shown that MAC is a temporally local reference frame and will not be altered over a particular time span by an exten-sion of data length, thereby making it easier for physical interpretation. In the MAC reference frame, the low frequency component is found more suitable for studying the interannual to longer timescale variability （ILV） than a 13-month window running mean, which does not exclude the annual cycle. It is also better than other traditional versions （annual or summer or winter mean） of ILV, which contains a portion of the annual cycle. The analysis reveals that the variability of the annual cycle could be as large as the magnitude of interannual variability. The possible physical causes of different timescale variability of SAT in China are further discussed.

Features of the new climate normal 1991-2020 and possible influences on climate monitoring and prediction in China

An update on the climate norms each decade is recommended by the World Meteorological Organization(WMO)partly to keep pace with conditions as climate changes over time.In accordance with such update,this study documents the features of the new climate normal defined for 1991-2020 and its impacts on climate monitoring and prediction in China.With on-site observation and model prediction datasets,our analysis reveals that the new normal of national average precipitation of China during winter and summer is respectively 3.0 and 10.8 mm higher than that of the period 1981-2010.As a result,precipitation observations during 1961-2020 consistently fall below the new normal.The adjustment of thresholds for precipitation extremes with new climate normals results in a decrease of extreme precipitation occurrence by 0.2-0.8 d on average over the winter and summer seasons during 1961-2020.Meanwhile,the application of new climate normals induces more pronounced negative temperature anomalies across most areas of China.The adjustments of extreme temperature thresholds have led to an increased occurrence of extremely cold days by 1-2 d on average over 1961-2020,while the frequency of extremely hot days decreases by more than 1.4 d.Furthermore,it is implied that with the development of global warming,the baselines for temperature and precipitation are rising.The application of the new climate normal may result in the omission of relative threshold based extreme events,promoting increased focus on climate risk reduction studies.Additionally,the average anomaly sign consistency rates(Pcs)of precipitation and temperature anomaly predictions,relative to the new normal and produced by the Beijing Climate Center,are consistently lower than those relative to the old normal.This decrease in Pcs implies new challenges for climate prediction,especially for temperature prediction.

HISTORICAL EVIDENCE ON CLIMATIC INSTABILITY ABOVE NORMAL IN COOL PERIODS IN CHINA

Twenty-six sequences of grades of dryness/wetness and a combined sequence of indexes of winter temperature since A.D. 1471 in China were adopted as our data. The fluctuations of variability of precipitation and mean temperature are statistically significant from analyses. It has been found that in middle latitudes of eastern China the distribution of the relation between mean temperature and interannual variability of precipitation in historical time forms a rather complex regional pattern, and the correlation coefficients are not unique in signs. But the negative correlations are dominant either in extent or in magnitude. The authors provide evidence that Little Ice Age was a time of more frequent extremes and support the idea that the climatic instability is above normal in cool periods.