Spatial and Temporal Analysis of Maximum and Minimum Temperature Trends in Northern Sudan during (1990-2019)

The study addresses an urgent and globally significant issue of climate change by focusing on the detailed spatial and temporal analysis of temperature trends in Northern Sudan. It fills a critical research gap by providing localized data over a substantial period (1990-2019), which could help in understanding the nuanced impacts of climate change in Sahel regions like Northern Sudan. In addition, the comprehensive coverage of both spatial and temporal dimensions, supported by a substantial dataset from five meteorological stations, provides a thorough understanding of the subject area. The utilization of robust statistical methods (Mann-Kendall test and Sen’s slope analysis) for analyzing temperature trends adds scientific rigor and credibility to the findings. Our results reveal a consistently increasing trend in maximum temperatures across most stations, particularly during the hot season (AMJ). However, the wet season (JAS) shows high maximum temperatures but no significant trend. Moreover, significant increasing trends in minimum temperatures were observed in all stations except Abu Hamed, where the trend, although increasing, did not reach statistical significance during the hot and cold seasons, and the coldest temperatures were observed during the cold season. These findings underscore the complex temperature dynamics in Northern Sudan and highlight the need for continued monitoring and adaptive measures in response to ongoing climate changes in the region.

Effects of temperature and precipitation on drought trends in Xinjiang, China

The characteristics of drought in Xinjiang Uygur Autonomous Region(Xinjiang),China have changed due to changes in the spatiotemporal patterns of temperature and precipitation,however,the effects of temperature and precipitation—the two most important factors influencing drought—have not yet been thoroughly explored in this region.In this study,we first calculated the standard precipitation evapotranspiration index(SPEI)in Xinjiang from 1980 to 2020 based on the monthly precipitation and monthly average temperature.Then the spatiotemporal characteristics of temperature,precipitation,and drought in Xinjiang from 1980 to 2020 were analyzed using the Theil-Sen median trend analysis method and Mann-Kendall test.A series of SPEI-based scenario-setting experiments by combining the observed and detrended climatic factors were utilized to quantify the effects of individual climatic factor(i.e.,temperature and precipitation).The results revealed that both temperature and precipitation had experienced increasing trends at most meteorological stations in Xinjiang from 1980 to 2020,especially the spring temperature and winter precipitation.Due to the influence of temperature,trends of intensifying drought have been observed at spring,summer,autumn,and annual scales.In addition,the drought trends in southern Xinjiang were more notable than those in northern Xinjiang.From 1980 to 2020,temperature trends exacerbated drought trends,but precipitation trends alleviated drought trends in Xinjiang.Most meteorological stations in Xinjiang exhibited temperature-dominated drought trend except in winter;in winter,most stations exhibited precipitation-dominated wetting trend.The findings of this study highlight the importance of the impact of temperature on drought in Xinjiang and deepen the understanding of the factors influencing drought.

Zonally Asymmetric Temperature Trends near the Northern Middle and High Latitude Stratopause during Winter

The temperature trend near the stratopause is rarely evaluated owing to the limited long-term observations of global temperature. In this study, the spatial patterns of the temperature trends near the northern stratopause are investigated by using satellite and reanalysis datasets. Our analysis reveals a zonally asymmetric temperature trend pattern near the northern mid-to-high latitude stratopause during January, and this pattern underwent an evident transition around the 2000s. From 1980 to 2003, there was a cooling trend in the Western Hemisphere and a warming trend in the Eastern Hemisphere. In contrast, a reversed zonally asymmetric temperature trend pattern existed in the east–west direction from 2003 to 2020. Although the warming trends are statistically insignificant, they contrasted with the overall cooling trend in the upper stratosphere due to ozone depletion and an increase in well-mixed greenhouse gases in recent decades. The zonally asymmetric temperature trends were induced by the transition in the intensity of quasi-stationary planetary wavenumber 1(wave 1) near the stratopause. The increasing(decreasing) trend of the intensity of wave 1 enhanced(weakened) its meridional temperature advection near the stratopause before(after) the 2000s;consequently, a zonally asymmetric temperature trend pattern exists in the east–west direction near the stratopause. The transition in the intensity of the stratospheric wave 1 around the 2000s is most likely caused by the transition in the intensity of wave 1 activity in the troposphere.

Analysis of Sampling Error Uncertainties and Trends in Maximum and Minimum Temperatures in China

In this paper we report an analysis of sampling error uncertainties in mean maximum and minimum temperatures （Tmax and Tmin） carried out on monthly,seasonal and annual scales,including an examination of homogenized and original data collected at 731 meteorological stations across China for the period 1951-2004.Uncertainties of the gridded data and national average,linear trends and their uncertainties,as well as the homogenization effect on uncertainties are assessed.It is shown that the sampling error variances of homogenized Tmax and Tmin,which are larger in winter than in summer,have a marked northwest-southeast gradient distribution,while the sampling error variances of the original data are found to be larger and irregular.Tmax and Tmin increase in all months of the year in the study period 1951-2004,with the largest warming and uncertainties being 0.400℃ （10 yr）-1 ＋ 0.269℃ （10 yr）-1 and 0.578℃ （10 yr）-1 ＋ 0.211℃ （10 yr）-1 in February,and the least being 0.022℃ （10 yr）-1 ＋ 0.085℃ （10 yr）-1 and 0.104℃ （10 yr）-1 ＋0.070℃ （10 yr）-1 in August.Homogenization can remove large uncertainties in the original records resulting from various non-natural changes in China.

Evolution of temperature indices in the periglacial environment of the European Alps in the period 1990-2019

Air temperature in the European Alps shows warming over recent decades at an average rate of 0.3℃/10 years,therebyoutpacing the global warming rate of 0.2℃/10 years.The periglacial environment of the Alps is particularly important for several aspects(i.e.hydropower production,tourism,natural hazards,indicator of global warming).However,there is a lack of specific and updated studies relating to temperature change in this environment.In order to fill this gap,the recent temperature trends in the periglacial environment of the Alps were analyzed.Mean/maximum/minimum daily air temperatures recorded by 14 land-based meteorological stations were used,and the temperature indices for the period 1990-2019 were calculated.The periglacial environment of the Alps showed a warming rate of 0.4℃/10 years,0.6℃/10 years and 0.8℃/10 years for the mean/maximum/minimum temperatures,respectively.These warming rates are higher than that observed for the entire Alpine area.In 2050 many glaciers of the Alps below 3000 m altitude are expected to be extinct,and all the areas previously occupied by glaciers will become periglacial.In order to manage and adapt to these changes,more in-depth climate analyses are needed.This is necessary for all the mountainous areas of the world,which are undergoing similar changes.

Characterizing the Urban Temperature Trend Using Seasonal Unit Root Analysis:Hong Kong from 1970 to 2015

This paper explores urban temperature in Hong Kong using long-term time series. In particular, the characterization of the urban temperature trend was investigated using the seasonal unit root analysis of monthly mean air temperature data over the period January 1970 to December 2013. The seasonal unit root test makes it possible to determine the stochastic trend of monthly temperatures using an autoregressive model. The test results showed that mean air temperature has increased by 0.169~ C （10 yr） - 1 over the past four decades. The model of monthly temperature obtained from the seasonal unit root analysis was able to explain 95.9% of the variance in the measured monthly data -- much higher than the variance explained by the ordinary least-squares model using annual mean air temperature data and other studies alike. The model accurately predicted monthly mean air temperatures between January 2014 and December 2015 with a root-mean-square percentage error of 4.2%. The correlation between the predicted and the measured monthly mean air temperatures was 0.989. By analyzing the monthly air temperatures recorded at an urban site and a rural site, it was found that the urban heat island effect led to the urban site being on average 0.865~C warmer than the rural site over the past two decades. Besides, the results of correlation analysis showed that the increase in annual mean air temperature was significantly associated with the increase in population, gross domestic product, urban land use, and energy use, with the R2 values ranging from 0.37 to 0.43.

The Role of Ozone Depletion in the Lack of Cooling in the Antarctic Upper Stratosphere during Austral Winter

Temperature trends in the upper stratosphere are investigated using satellite measurements from Stratospheric Sounding Unit(SSU)outputs and simulations from chemistry-climate models(CCMs)and the Coupled Model Intercomparison Project Phase 6(CMIP6).Observational evidence shows a lack of cooling in the Antarctic,in contrast to strong cooling at other latitudes,during austral winter over 1979-97.Analysis of CCM simulations for a longer period of1961-97 also shows a significant contrast in the upper stratospheric temperature trends between the Antarctic and lower latitudes.Results from two sets of model integrations with fixed ozone-depleting substances(ODSs)and fixed greenhouse gases(GHGs)at their 1960 levels suggest that the ODSs have made a major contribution to the lack of cooling in the Antarctic upper stratosphere.Results from CMIP6 simulations with prescribed GHGs and ozone confirm that changes in the dynamical processes associated with observed ozone depletion are largely responsible for the lack of cooling in the Antarctic upper stratosphere.The lack of cooling is found to be dynamically induced through increased upward wave activity into the upper stratosphere,which is attributed mainly to ODSs forcing.Specifically,the radiative cooling caused by the ozone depletion results in a stronger meridional temperature gradient between middle and high latitudes in the upper stratosphere,allowing more planetary waves propagating upward to warm the Antarctic upper stratosphere.These findings improve our understanding of the chemistry-climate coupling in the southern upper stratosphere.

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.

Long-term ocean temperature trend and marine heatwaves

Marine heatwaves(MHWs)can cause irreversible damage to marine ecosystems and livelihoods.Appropriate MHW characterization remains difficult,because the choice of a sea surface temperature(SST)temporal baseline strongly influences MHW identification.Following a recent work suggesting that there should be a communicating baseline for long-term ocean temperature trends(LTT)and MHWs,we provided an effective and quantitative solution to calculate LTT and MHWs simultaneously by using the ensemble empirical mode decomposition(EEMD)method.The long-term nonlinear trend of SST obtained by EEMD shows superiority over the traditional linear trend in that the data extension does not alter prior results.The MHWs identified from the detrended SST data exhibited low sensitivity to the baseline choice,demonstrating the robustness of our method.We also derived the total heat exposure(THE)by combining LTT and MHWs.The THE was sensitive to the fixed-period baseline choice,with a response to increasing SST that depended on the onset time of a perpetual MHW state(identified MHW days equal to the year length).Subtropical areas,the Indian Ocean,and part of the Southern Ocean were most sensitive to the long-term global warming trend.

20世纪全球增暖最显著的区域(英文)

Having analyzed a global grid temperature anomaly data set and some sea level pressure data during the last century, we found the following facts. Firstly, the annual temperature change with a warming trend of about 0.6°C/ 100 years in the tropical area over Indian to the western Pacific Oceans was most closely correlated to the global mean change. Therefore, the temperature change in this area might serve as an indi-cator of global mean change at annual and longer time scales. Secondly, a cooling of about -0.3°C/ 100 years occurred over the northern Atlantic. Thirdly, a two-wave pattern of temperature change, warming over northern Asia and northwestern America and cooling over the northern Atlantic and the northern Pa-cific, occurred during the last half century linked to strengthening westerlies over the northern Atlantic and the weakening Siberian High. Fourthly, a remarkable seasonal difference occurred over the Eurasian con-tinent, with cooling (warming) in winter (summer) during 1896–1945, and warming (cooling) in winter (summer) during 1946-1995. The corresponding variations of the North Atlantic Oscillation and the South-ern Oscillation were also discussed. Key words Temperature trend - Mann-Kendall’s Test - Significance - Regional difference - Correlation coefficient This study was supported by the Ministry of Science and Technology Projects G1999043400 and Na-tional Key Project- “Studies on Short-Term Climate Prediction System in China” under Grant No.96-908-01-04.

Trends and Uncertainties in Surface Air Temperature over the Tibetan Plateau,1951–2013

Trends and uncertainties of surface air temperature over the Tibetan Plateau（TP）are evaluated by using observations at 100 meteorological stations during the period 1951–2013.The sampling error variances of gridded monthly data are estimated for every month and every grid box of data.The gridded data and their sampling error variances are used to calculate TP averages,their trends,and associated uncertainties.It is shown that large sampling error variances dominate northern and western TP,while small variances appear over southern and eastern TP.Every month from January to December has a positive linear trend during the study period.February has the largest trend of 0.34±0.18°C（10 yr）^（–1）,and April the smallest at 0.15±0.11°C（10 yr）^（–1）.The uncertainties decrease steadily with time,implying that they are not large enough to alter the TP warming trend.

Winter sea ice albedo variations in the Bohai Sea of China

Sea ice conditions in the Bohai Sea of China are sensitive to large-scale climatic variations. On the basis of CLARA-A1-SAL data, the albedo variations are examined in space and time in the winter（December, January and February） from 1992 to 2008 in the Bohai Sea sea ice region. Time series data of the sea ice concentration（SIC）, the sea ice extent（SIE） and the sea surface temperature（SST） are used to analyze their relationship with the albedo. The sea ice albedo changed in volatility appears along with time, the trend is not obvious and increases very slightly during the study period at a rate of 0.388% per decade over the Bohai Sea sea ice region.The interannual variation is between 9.93% and 14.50%, and the average albedo is 11.79%. The sea ice albedo in years with heavy sea ice coverage, 1999, 2000 and 2005, is significantly higher than that in other years; in years with light sea ice coverage, 1994, 1998, 2001 and 2006, has low values. For the monthly albedo, the increasing trend（at a rate of 0.988% per decade） in December is distinctly higher than that in January and February. The mean albedo in January（12.90%） is also distinctly higher than that in the other two months. The albedo is significantly positively correlated with the SIC and is significantly negatively correlated with the SST（significance level 90%）.

The regime shift in the 1960s and associated atmospheric change over the southern Indian Ocean

The change of sea surface temperature（SST） in the southern Indian Ocean（SIO） during the recent six decades has been analyzed based on oceanic reanalysis and model, as well as atmospheric data. The results show that a thermal regime shift in SIO during the 1960 s, which is not caught enough attentions, has been of equal magnitude to the linear warming since 1970. Empirical Orthogonal Function（EOF） analyses reveal that a thermal shift is combined with atmospheric changes such as the weakening of westerly during the period of 1960–1967. Inner dynamic connections can be defined that when the westerly winds turn weak, the anticyclonic wind circulation between westerly winds and the trade winds decreases, which further reduces the SST to a negative peak in this period. It is noted that the shifts in the 1960 s are also evident for Southern Hemisphere. For example, subtropical high and the entire westerly winds belt at high latitudes both change dramatically in the 1960 s. This large-scaled process maybe link to the change of southern annular mode（SAM）.

Validation and Application of Reanalysis Temperature Data over the Tibetan Plateau

The Tibetan Plateau has substantial impacts on the weather and climate of the Northern Hemisphere, due in large part to the thermal effects of the plateau surface. Surface temperature over the Tibetan Plateau is the most important parameter in determining these thermal effects. We present a method for verifying widely used reanalysis temperature products from NCEP-R2, ERA-Interim, and JRA-25 over the Tibetan Plateau, with the aim of obtaining a reliable picture of surface temperature and its changes over the plateau. Reanalysis data are validated against the topography elevation, satellite observations, and radiosonde data. ERA-Interim provides the most reliable estimates of Tibetan Plateau surface temperature among these three reanalyses. We therefore use this dataset to study the climatology and trends of surface temperature over the Tibetan Plateau. ERA-Interim data indicate a dramatic warming over the Tibetan Plateau from 1979 to 2010, with warming rates of 0.33℃ per decade in annual mean temperature, 0.22℃ per decade in summer and 0.4℃ per decade in winter mean temperatures. Comparison with the results of previous studies suggests that surface warming over the Tibetan Plateau has accelerated during the past 30 years. This warming is distributed heterogeneously across the Tibetan Plateau, possibly due to topographic effects.

A Comparative Assessment of Temperature Data from Different Sources for Dehradun, Uttarakhand, India

A comparative study of extreme temperature parameters from different sources is carried out by examining standardized anomalies, trends, correlation, and equivalence of datasets. Maximum temperature （Tmax） and minimum temperature （Wmln） for Dehradun, from two different sources such as computed and gridded data from Climatic Research Unit （CRU） and observed data from India Meteorological Department （IMD） are used for 1901-2012. The CRU data are compared initially with IMD, by graphical assessment of standardized anomalies. Subsequently, change points are identified by using Cumulative Sum （CUSUM）-chart technique for trend analysis. The magnitude and significance of trends are determined by applying Sen＇s slope test, and on the basis of these, trends are compared. Further, correlation analysis is carried out and datasets are tested for equivalence by using Wileoxon-Mann Whitney test. The result shows that annual standardized anomalies of CRU data follow the pattern of annual standardized anomalies of IMD data. The CRU data exhibit similar trends and are well correlated with IMD dataset. Moreover, CRU anomaly data are identical with IMD anomaly data in the recent decades. High resolution gridded CRU data have open access and may be more useful due to its spatio-temporal continuity for land areas of the world.

Long-Term Trend of Temperature Derived by Statistical Downscaling Based on EOF Analysis

This study analyzes the ability of statistical downscaling models in simulating the long-term trend of temperature and associated causes at 48 stations in northern China in January and July 1961-2006. The statistical downscaling models are established through multiple stepwise regressions of predictor principal components （PCs）. The predictors in this study include temperature at 850 hPa （T850）, and the combination of geopotential height and temperature at 850 hPa （H850＋T850）. For the combined predictors, Empirical Orthogonal Function （EOF） analysis of the two combined fields is conducted. The modeling results from HadCM3 and ECHAM5 under 20C3M and SERS A1B scenarios are applied to the statistical downscaling models to construct local present and future climate change scenarios for each station, during which the projected EOF analysis and the common EOF analysis are utilized to derive EOFs and PCs from the two general circulation models （GCMs）. The results show that （1） the trend of temperature in July is associated with the first EOF pattern of the two combined fields, not with the EOF pattern of the regional warming; （2） although HadCM3 and ECHAM5 have simulated a false long-term trend of temperature, the statistical downscaling method is able to well reproduce a correct long-term trend of temperature in northern China due to the successful simulation of the trend of main PCs of the GCM predictors; （3） when the two-field combination and the projected EOF analysis are used, temperature change scenarios have a similar seasonal variation to the observed one; and （4） compared with the results of the common EOF analysis, those of the projected EOF analysis have been much more strongly determined by the observed large-scale atmospheric circulation patterns.

Possible Impact of Spatial and Temporal Non-Uniformity in Land Surface Temperature Data on Trend Estimation

The present work investigates possible impact of the non-uniformity in observed land surface temperature on trend estimation, based on Climatic Research Unit （CRU） Temperature Version 4 （CRUTEM4） monthly temperature data-sets from 1900 to 2012. The CRU land temperature data exhibit remarkable non-uniformity in spatial and temporal features. The data are characterized by an uneven spatial distribution of missing records and station density, and dis-play a significant increase of available sites around 1950. Considering the impact of missing data, the trends seem to be more stable and reliable when estimated based on data with 〈 40% missing percent, compared to the data with above 40% missing percent. Mean absolute error （MAE） between data with 〈 40% missing percent and global data is only 0.011℃ （0.014℃） for 1900-50 （1951-2012）. The associated trend estimated by reliable data is 0.087℃ decade^-1 （0.186℃ decade^-l） for 1900-50 （1951-2012）, almost the same as the trend of the global data. However, due to non-uniform spatial distribution of missing data, the global signal seems mainly coming from the regions with good data coverage, especially for the period 1900-50. This is also confirmed by an extreme test conducted with the records in the United States and Africa. In addition, the influences of spatial and temporal non-uniform features in observation data on trend estimation are significant for the areas with poor data coverage, such as Africa, while insig-nificant for the countries with good data coverage, such as the United States.

ANALYSIS OF SURFACE AIR TEMPERATURE RECORDED IN LAHORE AND MIANWALI OVER THE PAST THREE DECADES

Surface air temperatures recorded over the past three decades at the weather stations located in Lahore (an industrialized and densely populated city) and Mianwali (a small and sparsely populated city) were analyzed in order to study their climatic trend.Lahore,where meteorological data are recorded at two weather stations (city station and air- port station) indicates a cooling trend,of about 0.5℃ per record period of 1953—1992,for the airport station (31°31′N, 74°24′E) and a slight warming trend,of about 0.2℃,for the city station (31°33′N,74°20′E) for the record period of 1950 —1992.The Mianwali weather station (32°33′N,71°31′E) also shows a slight cooling trend,of about 0.4℃ per record period of 1959—1992.The climatic variability at these stations was studied by computing seasonal and annual tempera- ture anomalies.The results are explained in terms of the local environmental conditions.

加拿大北极地区航运对气候变暖的影响

This paper presents a detailed account of the effect of shipping activity on the increasing trends of air temperatures in the Canadian Arctic region for the period of 1980–2018.Increasing trend of temperature has gained significant attention with respect to shipping activities and sea ice area in the Canadian Arctic.Temperature,sea ice area and shipping traffic datasets were investigated,and simple linear regression analyses were conducted to predict the rate of change(per decade)of the average temperature,considering winter(January)and summer(July)seasons.The results indicate that temperature generally increased over the studied region.Significant warming trend was observed during July,with an increase of up to 1℃,for the Canadian Arctic region.Such increasing trend of temperature was observed during July from the lower to higher latitudes.The increase in temperature during July is speculated to increase the melting of ice.Results also show a decline in sea ice area has a significant positive effect on the shipping traffic,and the numbers of marine vessel continue to increase in the region.The increase in temperature causes the breaking of sea ice due to shipping activities over northern Arctic Canada.