ETCCDI, SUNChinaChina3 January12quirements. For example, some drought indicators, such as thePalmer drought Severity index PDSI, standardized precipi-tation index SPI, and comprehensive meteorological drought* Corresponding author.E-mail address YIN H..Peer review under responsibility of National Climate Center ChinaMeteorological Administration.Available online at ScienceDirectAdvances in Climate Changehttps//doi.org/10.1016/j.accre.2019.01.0011. IntroductionThe Fifth Assessment Report AR5 of the Intergovern-mental Panel on Climate Change IPCC, 2013 concludesthat “The globally averaged combined land and ocean surfacetemperature data showed a warming of 0.85C14C[0.65e1.06C14C] over the period 1880e2012 and warming ofthe climate system is unequivocal.” Climate warming candirectly affect extremes in climate, increasing atmosphericwater holding capacity and the probability of occurrence ofglobal abnormal extreme weather and climatic events, such ashigh temperature, heat waves, floods, hail, tornadoes. In-creases in extreme climatic events have significant impacts onagriculture, energy, ecosystems, and human health, and attractworldwide attention IPCC, 2007.Extreme weather and climate events are defined as smallprobability events where the value of a weather or climatevariable is higher or lower than a certain upper or lowerthreshold of the range of the observed variable value, for whichthe probability of occurrence is generally less than 10 Qin,2015. There are many criteria for determining whether anextreme weather or climate event has occurred basedon different geographical locations and related research re-AbstractBased on the homogenized daily data in 2419 stations in China from 1961 to 2017, we calculated 26 extreme temperature and precipitationindices as defined by the Expert Team on Climate Change Detection and Indices ETCCDI, and analyzed the characteristics of extremetemperature and precipitation in China in 2017. For China average, all the high temperature indices were above the 30-year average of1961e1990 and the extreme low temperature indices are lower than their corresponding 1961e1990 average. The most extreme precipitations in2017 were within the range of one standard deviation of precipitation change during 1961e2017. The annual minima of daily maximumtemperature TXn and daily minimum temperature TNn reached the recorded highest level, while the number of cold nights TN10p, colddays TX10p, and cold spell duration index CSDI reached the recorded lowest values. Some indices were ranked at the second or third placesince 1961, including annual maxima of daily maximum temperature TXx and of daily minimum temperature TNx, warm nights TN90p,frost days FD, icing days ID, summer days SU, and growing season length GSL. Other extreme temperature indices were ranked in the top10 since 1961. Meanwhile, for the averaged extreme precipitation indices in China, seven out of the 10 extreme precipitation indices in 2017were located within the range of one standard deviation, indicating a normal situation for extreme precipitation in 2017.Keywords Climate warming; Extreme temperature; Extreme precipitation; 2017Characteristics of extreme temperature2017 based onYIN Honga,*aLaboratory for Climate Studies, National Climate Center,bCollaborative Innovation Center on Forecast and uation of Meteorological210044,Received 17 December 2018; revisedAvailable online1674-9278/Copyright 2019, National Climate Center China Meteorological AThis is an open access article under the CC BY-NC-ND license http//creativecommons.orand precipitation in China inindicesYinga,bMeteorological Administration, Beijing 100081, ChinaDisasters, Nanjing University of Ination Science accepted 8 January 2019January 2019Research 9 2018 Production and hosting by Elsevier B.V. on behalf of KeAi.g/licenses/by-nc-nd/4.0/.219Change Research 9 2018 218e226index CI, are used to study extreme drought events indifferent regions of the world Dai et al., 1998; Wang et al.,2003; Li et al., 2006; Zhang et al., 2006. In China, a seriesof popular indicators and thresholds have been defined to judgethe occurrence of extreme weather and climate events such ashigh temperatures, rainstorms, blizzards, gale winds, and coldwaves, according to the requirements of climate business andrelated research Qin, 2015. Due to a lack of long-series globalclimate data and a unified definition of extreme event in-dicators and thresholds in various countries, further research ofglobal extreme weather and climate events has been hinderedto some extent. In order to address this situation, the WorldMeteorological Organization WMO and the World ClimateResearch Program WCRP jointly established the ExpertTeam on Climate Change Detection and Indices ETCCDI inthe early 21st century, and defined 27 representative climateindices to assess extreme climate change globally and region-ally. The extreme climate indices defined by ETCCDI havepromoted research of observed extreme climate events, andaccelerated further research in model simulation and attributionof such events Alexander et al., 2006; Donat et al., 2013b;Kim et al., 2016; Yin and Sun, 2018.For the past 25 years, the WMO has published an annualStatement on the State of the Global Climate inorder to provideauthoritative scientific ination about global climate andsignificant weather and climate events occurring around theworld. The latest WMO statement on the state of the globalclimate 2017 WMO, 2018 indicated that the global meantemperature in 2017 was about 1.1C14C above pre-industrial eraand was the second warmest on record, ranking only behind2016. Every year, the National Climate Center NCC, ChinaMeteorological Administration CMA, issues the ChinaClimate Bulletin to summarize Chinas climate for the previousyear.TheChinaClimateBulletinon2017showedCMA,2018that “temperaturein2017averagedoverChinais0.84C14Chigherthan normal and is the third warmest on record. Precipitation isslightly more than normal.” The Bulletin of the AmericanMeteorological Society BAMS has published a state of theclimateeveryyearsince1996.ThelatestreleaseBlundenetal.,2018, “State of the Climate in 2017,” provided a detailedanalysis of global climate. Extreme temperatures and precipi-tation over the global land surface were analyzed based onindices recommended by ETCCDI. Land surface temperatureextremes during 2017 were characterized by overall increasedoccurrences of warm temperatures and reduced occurrences ofcooler temperatures compared to long-term averages. However,due to the limitations of protection policies about meteorolog-ical data-sharing from many countries, the data obtained by theGlobal Historical Climate Network GHCN has been greatlyreduced in recent years. For this reason, the American Meteo-rological Society encourages countries to take advantage ofmultiple datasets to carry out research on climate extremes. Inrecent year, BAMS has also launched a special issue aboutdetection and attribution of global extreme climate events,which greatly promoted research on global climate extremes.YIN H., SUN Y. / Advances in ClimateThe purpose of this study is to analyze characteristics ofextreme temperature and precipitation averaged over China inDue to the uneven distribution of meteorological stations inChina, the stations in eastern China are denser than those inthe west. Moreover, many stations meteorological recordshave different starting years. In order to obtain various seriesof extreme climate indices averaged over China, we firstcalculated the anomaly of extreme climate indices for everystation relative to 1961e1990, then calculated the averages ofall indices over the 5C14C2 5C14latitude and longitude grid to getthe extreme climate indices for China across the grid. Finally,extreme climate indices in China were obtained by area-weighted averages for all series. This gridded approach hasbeen widely used in climate change research, such as in theestablishment of the HadCRU dataset. This has alsobeen widely used in Chinas previous studies on climateextremes, which better reflects generally climate change in2.2. sCharacteristics of extreme climate events were used todescribe their frequency, intensity, and duration. In this paper,26 indices defined by ETCCDI were analyzed, including 16temperature indices and 10 precipitation indices. The defini-tions of the 26 indices are shown in Table 1. The other index,Rnnmm, refers to the number of days when the daily precip-itation was greater than a certain user-defined threshold that isnot used in this study. The data used includes daily minimumtemperature, daily maximum temperature, and daily precipi-tation during the period 1951e2017 at 2419 stationsthroughout China from the National Meteorological Ina-tion Center NMIC, CMA. These daily data have been uni-ly adjusted by removing the non-homogeneity caused bystation relocation and instrument replacement Cao et al.,2016. We calculated 26 indices defined by ETCCDI inTable 1 using these data. We then carried out the characteristicanalysis of extreme temperature and precipitation in China for2017. Due to the small number of stations available before the1960s, the analysis period selected was 1961e2017.2.1. Extreme climate indices and data2017 using the 26 extreme temperature and precipitationindices recommended by ETCCDI Table 1. These indicescan be divided into intensity indices, absolute thresholdindices, relative threshold indices, duration indices, and soon.1Extreme climate indices unified by ETCCDI effectivelypromote detection research of extreme weather and climatechange, allowing for comparison between extreme weatherand climate change in different regions. This study not onlyprovides fundamental characteristics analysis of extremeclimate in China in 2017 and fundamental support for scien-tific research and services work, but also provides importantunified background ination for related research aboutextreme climate change in China.2. Data and s1https//www.wcrp-climate.org/etccdialuealuewhenwhenof days whenof days whenwhen dailyID Icing days Annual count when dailydailydailydayswithwithdaysdays1-dayconsecutiChangeSU Summer days Annual count whenTR Tropical nights Annual count whenGSL Growing season length Annual number of6 consecutive daysconsecutive 6 daysDTR Diurnal temperature range Annual mean differenceWSDI Warm spell duration index Annual number ofCSDI Cold spell duration index Annual number ofRx1day Max 1-day precipitation amount Annual maximumRx5day Max 5-day precipitation amount Annual maximumTN90p Warm nights PercentageTX90p Warm days PercentageFD Frost days Annual countTable 1Definition of extreme temperature and precipitation indices.Code Name DefinitionTXx Annual maxima of dailymaximum temperatureAnnual maxima vTNx Annual maxima of dailyminimum temperatureAnnual maxima vTXn Annual minima of dailymaximum temperatureAnnual minima valueTNn Annual minima of dailyminimum temperatureAnnual minima valueTN10p Cold nights Percentage of daysTX10p Cold days Percentage of days220 YIN H., SUN Y. / Advances in ClimateChina Sun et al., 2014; Yin et al., 2017. The trend analysesof the extreme index changes from 1961 to 2017 were carriedout using the Sen 1968 trend analysis . This does not require data to con to normal distribution, andcan better estimate the trend changes of extreme temperatureand precipitation.3. Results3.1. Characteristics of extreme temperature indices in2017Fig. 1 shows the time series of extreme temperature in-tensity indices averaged over China during 1961e2017 andtheir spatial distribution in 2017. All the extreme temperatureintensity indices TXx, TNx, TXn, and TNn showed clearincreasing trends during 1961e2017. The increasing trends ofTXx, TNx, TXn, and TNn were 0.21, 0.29, 0.30, and 0.51C14Cper decade p 90th percentile daily maximum temperature 90th percentile minimum temperature 25C14minimum temperature 20C14between the first occurrence ofTmean 5C14C and first occurrence ofTmean 90th percentile dwith at least 6 consecutive days when Tmin 95th percentile mmfrom days 99th percentile mmon C2110 mm don C2120 mm dconsecutive days when precipitation 1mm dconsecutive days when precipitation C211mm dfrom days C211mm mmprecipitation to the number of wet days C211 mm mmChangeYIN H., SUN Y. / Advances in ClimateTN90p were larger than those for daytime extremes TX10pand TX90p. In 2017, the frequency of TN10p and TX10paveraged over China reached their lowest since 1961, and thereduced frequency of cold nights was great than cold days.Spatial distribution of frequency indices for 2017 showed thatthe frequencies of cold night extreme indices in the TibetanPlateau were lower than those of the same latitude. The fre-quencies of warm nights TN90p and warm days TX90pwere close to the historical maximum, which ranked secondand fifth, respectively. The frequency of warm nights TN90pwas higher than that of warm days TX90p. The spatial dis-tribution of warm indices was similar to that of cold indices,where the frequencies of warm nights and warm days in theTibetan Plateau was higher than those at the same latitude.Previous research has shown that there are generally strongertrends for frequency of extremes in the Tibetan Plateau Luet al., 2016. The frequency of warm days in 2017 was about15 higher than the average for 1961e1990, and the frequencyof warm nights was about 20 higher in the Tibetan Plateau.Frost days FD and icing days ID indices averaged overChina Fig. 3 showed clear decreasing trends duringFig. 1. Change in anomaly series a, b of extreme temperature intensity indices TXx,spatial distribution cC0f in 2017 relative to the 1961e1990 mean.221Research 9 2018 218e2261961e2017 with trends of 3.31 and 1.53 d per decade,respectively p 0.01. Meanwhile, summer days SU andtropical days TR indices averaged over China showed clearincreasing trends with rates of 2.63 and 2.26 d per decade,respectively p 0.01. In general, the cold indices FD andID displayed decreasing trends, whereas the warm indicesSU and TR displayed increasing trends over most of theglobal land Donat et al., 2013a; Yin and Sun, 2018, althoughthere were differences in rates of warming across some regionsand a regional cooling trend was found for SU indices overNorth America in earlier studies Knutson et al., 2017; Yin andSun, 2018. FD, ID and TR indices in 2017 ranked in the topthree since 1961, and SU indices ranked sixth. The warm spellduration index WSDI averaged over China Fig. 3 showed asignificant increasing trend with a rate of 2.39 d per decadesince 1961 p 0.01. The WSDI indices in 2017 ranked thetenth. In contrast, the cold spell duration index CSDI showeda clear decrease, wi