An analysis of the minimum air temperature behavior was carried out for the southern tip of South America and the western side of the Antarctica Peninsula. Punta Arenas shows an overall annual warming of 0.15°C p...An analysis of the minimum air temperature behavior was carried out for the southern tip of South America and the western side of the Antarctica Peninsula. Punta Arenas shows an overall annual warming of 0.15°C per decade during the 1960-2010 period, although this occurred mainly in the summer and winter seasons. The trend of the air temperature in the western side of the Antarctic Peninsula shows an increase until around 2000, but the warming rate during the last 2001-2010 decade has been less than previous decades;in particular, meteorological stations in King George Island show slight cooling. The lineal annual warming per decade as shown by Bellingshausen, Verndsky/Faraday and Rothera stations are 0.26°C ± 0.75°C, 0.55°C ± 1.26°C and 0.69°C ± 1.31°C;for the respectively, 1969-2010, 1951-2010 and 1978-2010 periods. These rates of warming are slightly lower than those found for the same stations but for the 1969-2000, 1951-2000 and 1978-2000 periods.展开更多
Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spat...Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.展开更多
The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects...The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects the ecosystem of this area.This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500-4000 m above sea level.MODIS data were extracted for the period of 2000-2021,and the Mann-Kendall nonparametric test was applied to evaluating the changes in the LST.The results indicated a significant increasing trend for the monthly average LST in May-August along the southern aspect.Both the northern and southern aspects showed decreasing trends for the monthly average LST in October,November,and March and an increasing trend in other months.At all elevations,the average decadal change in the monthly average LST was more severe along the southern aspect(0.60°C)than along the northern aspect(0.37°C).The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months.At the same elevation,the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months.With increasing elevation,the lapse rate between the northern and southern aspects disappeared.Climate change was concluded to greatly decrease the difference in LST at different elevations for April-July.展开更多
The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central ...The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central Taurus Mountains(Bolkar, Aladaglar, Tahtali and Binboga Mountains) from 1981 to 2021. Linear trends of snow cover season(November to April) over the last 41 years showed decreases in SCE primarily at lower elevations. The downward trend in SCE was found to be more pronounced and statistically significant for only November and March. SCE in the Central Taurus Mountains has declined about-6.3% per decade for 2500-3000 m in November and about-6.0% per decade for 1000-1500 m and 3000+ m in March over the last 41 years. The loss of SCE has become evident since the 2000s, and the lowest negative anomalies in SCE have been observed in 2014, 2001, and 2007 in the last 41 years, which are consistent with an increase in air temperature and decreased precipitation. SCE was correlated with both mean temperature and precipitation, with temperature having a greater relative importance at all elevated gradients. Results showed that there is a strong linear relationship between SCE and the mean air temperature(r =-0.80) and precipitation(r = 0.44) for all elevated gradients during the snow season. The Arctic Oscillation(AO), the North Atlantic Oscillation(NAO), and the Mediterranean Oscillation(MO) winter indices were used to explain the year-to-year variability in SCE over the Central Taurus Mountains. The results showed that the inter-annual variability observed in the winter SCE on the Central Taurus Mountains was positively correlated with the phases of the winter AO, NAO and MO, especially below 2000 m elevation.展开更多
The temperature is one of the most important factors in weather and climate forecasting.Studying its behaviour is crucial to understanding climate variability,which could vary spatially and temporally at local,regiona...The temperature is one of the most important factors in weather and climate forecasting.Studying its behaviour is crucial to understanding climate variability,which could vary spatially and temporally at local,regional,and global scales.Several recent studies on air temperature findings show that the Earth’s near surface air temperature increased between 0.6℃ and 0.8℃ throughout the twentieth century.Using temperature records from ten meteorological stations,this study examined climate variability in Rwanda from the 1930s to 2014.The air temperature data were collected from Meteo Rwanda.Before making the analysis,the authors used software,such as Excel 2007 and INSTAT to control the quality of the raw data.The analysis of maxima and minima indicated that the trends of maximum air temperature were positive and significant at height meteorological stations,whereas the trends for minimum air temperature were found to be at 10 meteorological stations.For all parameters analysed,Kigali Airport meteorological station indicated the higher significance of the trends.The majority of meteorological stations showed an increase in both hot days and nights,confirming Rwanda’s warming over time.The analysis of average seasonal air temperature showed almost similar trends even though not all were significant.This similarity in trends could be attributed to the fact that Rwanda’s short and long dry seasons coincide with rainy seasons.展开更多
Air temperature(Ta)datasets with high spatial and temporal resolutions are needed in a wide range of applications,such as hydrology,ecology,agriculture,and climate change studies.Nonetheless,the density of weather sta...Air temperature(Ta)datasets with high spatial and temporal resolutions are needed in a wide range of applications,such as hydrology,ecology,agriculture,and climate change studies.Nonetheless,the density of weather station networks is insufficient,especially in sparsely populated regions,greatly limiting the accuracy of estimates of spatially distributed Ta.Due to their continuous spatial coverage,remotely sensed land surface temperature(LST)data provide the possibility of exploring spatial estimates of Ta.However,because of the complex interaction of land and climate,retrieval of Ta from the LST is still far from straightforward.The estimation accuracy varies greatly depending on the model,particularly for maximum Ta.This study estimated monthly average daily minimum temperature(Tmin),average daily maximum temperature(Tmax)and average daily mean temperature(Tmean)over the Loess Plateau in China based on Moderate Resolution Imaging Spectroradiometer(MODIS)LST data(MYD11A2)and some auxiliary data using an artificial neural network(ANN)model.The data from 2003 to 2010 were used to train the ANN models,while 2011 to 2012 weather station temperatures were used to test the trained model.The results showed that the nighttime LST and mean LST provide good estimates of Tmin and Tmean,with root mean square errors(RMSEs)of 1.04℃ and 1.01℃,respectively.Moreover,the best RMSE of Tmax estimation was 1.27℃.Compared with the other two published Ta gridded datasets,the produced 1 km×1 km dataset accurately captured both the temporal and spatial patterns of Ta.The RMSE of Tmin estimation was more sensitive to elevation,while that of Tmax was more sensitive to month.Except for land cover type as the input variable,which reduced the RMSE by approximately 0.01℃,the other vegetation-related variables did not improve the performance of the model.The results of this study indicated that ANN,a type of machine learning method,is effective for long-term and large-scale Ta estimation.展开更多
Background: Air temperature affects absorptive root traits, which are closely related to species distribution.However, it is still unclear how air temperature regulates species distribution through changes in absorpti...Background: Air temperature affects absorptive root traits, which are closely related to species distribution.However, it is still unclear how air temperature regulates species distribution through changes in absorptive root traits. Seven functional traits of the absorptive roots of 240 individuals of 52 species, soil properties and air temperature were measured along an elevational gradient on Mt. Fanjingshan, Tongren City, Guizhou, and then the direct and indirect effects of these controls on species distribution were detected.Results: Absorptive roots adapted to air temperature with two strategies. The first strategy was positively associated with the specific root area(SRA) and specific root length(SRL) and was negatively associated with the root tissue density(RTD), representing the classic root economics spectrum(RES). The second strategy was represented by the trade-off between root diameter, mycorrhizal fungi colonization(MF) and SRL, representing the collaboration gradient with “do it yourself” resource uptake ranging from “outsourcing” to mycorrhizal resource uptake. Air temperature regulated species distribution in six ways: directly reducing species importance value;indirectly increasing the species importance value by reducing soil nitrogen content or increasing soil pH by reducing soil moisture inducing absorptive roots to change from “do it yourself” resource absorption to “outsourcing” resource absorption;indirectly decreasing the species importance value by decreasing soil moisture to change from“outsourcing”resource absorption to “do it yourself” resource absorption;indirectly increasing the species importance value with increasing soil pH by reducing soil moisture resulting in absorptive root traits turning into nutrient foraging traits;and indirectly decreasing the species importance value by promoting absorptive root traits to nutrient conservation traits.Conclusions: Absorptive root traits play a crucial role in the regulation of species distribution through multiapproaches of air temperature.展开更多
Background:Previous studies have established a link between fluctuations in climate and increased mortality due to coronary artery disease(CAD).However,there remains a need to explore and clarify the evidence for asso...Background:Previous studies have established a link between fluctuations in climate and increased mortality due to coronary artery disease(CAD).However,there remains a need to explore and clarify the evidence for associations between meteorological changes and hospitalization incidences related to CAD and its subtypes,especially in cold regions.This study aimed to systematically investigate the relationship between exposure to meteorological changes,air pollutants,and hospitalization for CAD in cold regions.Methods:We conducted a cross-sectional study using hospitalization records of 86,483 CAD patients between January 1,2009,and December 31,2019.Poisson regression analysis,based on generalized additive models,was applied to estimating the influence of hospitalization for CAD.Results:Significant associations were found between low ambient temperature[-10℃,RR=1.65;95%CI:(1.28-2.13)]and the incidence of hospitalization for CAD within a lag of 0-14 days.Furthermore,O_(3)[95.50μg/m^(3),RR=12;95%CI:(1.03-1.21)]and NO_(2)[48.70μg/m^(3),RR=1.0895%CI:(1.01-1.15)]levels were identified as primary air pollutants affecting the incidence of CAD,ST-segment-elevation myocardial infarction(STEMI),and non-STEMI(NSTEMI)within the same lag period.Furthermore,O_(3)[95.50μg/m^(3),RR=1.12;95%CI:(1.03-1.21)]and NO_(2)[48.70μg/m^(3),RR=1.0895%CI:(1.01-1.15)]levels were identified as primary air pollutants affecting the incidence of CAD,ST-segment-elevation myocardial infarction(STEMI),and non-STEMI(NSTEMI)within the same lag period.The effect curve of CAD hospitalization incidence significantly increased at lag days 2 and 4 when NO_(2)and O_(3)concentrations were higher,with a pronounced effect at 7 days,dissipating by lag 14 days.No significant associations were observed between exposure to PM,SO_(2),air pressure,humidity,or wind speed and hospitalization incidences due to CAD and its subtypes.Conclusion:Our findings suggest a positive correlation between short-term exposure to low ambient temperatures or air pollutants(O_(3)and NO_(2))and hospitalizations for CAD,STEMI,and NSTEMI.These results could aid the development of effective preparedness strategies for frequent extreme weather events and support clinical and public health practices aimed at reducing the disease burden associated with current and future abnormal weather events.展开更多
In this study, the trends of upper-air temperatures are analysed by utilising radiosonde observations for the barometric levels at 700, 500, 300, 200, 150, 100 and 50 hPa from five meteorological stations within the A...In this study, the trends of upper-air temperatures are analysed by utilising radiosonde observations for the barometric levels at 700, 500, 300, 200, 150, 100 and 50 hPa from five meteorological stations within the Arabian Peninsula from January 1986 to August 2015. The mean monthly variations of the temperatures at these levels are characterised and established. The magnitudes of the annual trends of the mean temperatures for each site for the selected barometric levels are studied and statistically tested using Mann-Kendall rank statistics at different significance levels. The temperature trends at different pressure levels show that the upper troposphere and lower stratosphere are warming, while the middle troposphere is cooling which is consistent with the findings of other studies. The variations in upper air temperature observed in this study can be attributed to a range of factors, including increasing greenhouse gas concentrations, changes in atmospheric circulation patterns, variations in solar activity, aerosols and volcanic eruptions, and land use and land cover change.展开更多
An increasing number of palaeo-climatic records have been reported to identify the Holocene climate history in the arid Xinjiang region of northwest China. However, few studies have fully considered the internal linka...An increasing number of palaeo-climatic records have been reported to identify the Holocene climate history in the arid Xinjiang region of northwest China. However, few studies have fully considered the internal linkages within the regional climate system, which may limit our understanding of the forcing mechanisms of Holocene climate change in this region. Here, we systematically consider three major issues of the moisture/precipitation, temperature and near-surface wind relevant to the Holocene climate history of Xinjiang. First, despite there still has debated for the Holocene moisture evolution in this region, more climatic reconstructions from lake sediments, loess, sand-dunes and peats support a long-term regional wetting trend. Second, temperature records from ice cores, peats and stalagmites demonstrate a long-term winter warming trend during the Holocene in middle-to high-latitudes of Asia. Third, recent studies of aeolian sedimentary sequences reveal that the near-surface winds in winter gradually weakened during the Holocene, whereas the winter mid-latitude Westerlies strengthened in the Tienshan Mountains. Based on this evidence, in the arid Xinjiang region we propose an early to middle Holocene relatively cold and dry interval, with strong near-surface winds;and a warmer, wetter interval with weaker near-surface winds in the middle to late Holocene during winter. Additionally,we develop a conceptual model to explain the pattern of Holocene climate changes in this region.From the early to the late Holocene, the increasing atmospheric COcontent and winter insolation,and the shrinking of high-latitude continental ice-sheets, resulted in increasing winter temperatures in middle to high latitudes in the Northern Hemisphere. Subsequently, the increased winter temperature strengthened the winter mid-latitude Westerlies and weakened the Siberian high-pressure system,which caused an increase in winter precipitation and a decrease in near-surface wind strength. This scenario is strongly supported by evidence from geological records, climate simulation results, and modern reanalysis data. Our hypothesis highlights the important contribution of winter temperature in driving the Holocene climatic evolution of the arid Xinjiang region, and it implies that the socio-economic development and water resources security of this region will face serious challenges presented by the increasing winter temperature in the future.展开更多
[Objective]The paper was to explore the influence of near-surface low temperature on cultivation of soft-seed pomegranate,and to provide guidance for planting location of soft-seed pomegranate.[Method]Taking 10 soft-s...[Objective]The paper was to explore the influence of near-surface low temperature on cultivation of soft-seed pomegranate,and to provide guidance for planting location of soft-seed pomegranate.[Method]Taking 10 soft-seed pomegranate planting plots under different site conditions as the research objects,the near-surface low temperature of 45-50 cm was dynamically monitored from December 1,2018 to February 20,2019,and comparative analysis was made based on the local meteorological data over the same period.[Result]The near-surface low temperature of each temperature monitoring point was lower than the local meteorological data,which were all in the range of low temperature causing freezing in-jury of pomegranate trees,but the degree of freezing injury was different.The variation of near-surface low temperature was positively correlated with the altitude of terrain,but negatively correlated with the difference of topography and landform.When the local topography and landform were similar,the accumulation time of near-surface low temperature was negatively correlated with the altitude of terrain,while the duration of low tem-perature directly affected the degree of freezing injury.[Conclusion]The development of soft-seed pomegranate cultivation in Tunisia along Huang Mangling region in Henan Province refers to the local meteorological data.Meantime,it is also necessary to pay attention to the impact of regional microclimate environment,especially early monitoring of near-surface temperature to select suitable site and natural conditions.展开更多
The relationship between the factor of temperature difference of the near-surface layer(T_(1000 hPa)-T_(2m))and sea fog is analyzed using the NCEP reanalysis with a horizontal resolution of l°xl°(2000 to 201...The relationship between the factor of temperature difference of the near-surface layer(T_(1000 hPa)-T_(2m))and sea fog is analyzed using the NCEP reanalysis with a horizontal resolution of l°xl°(2000 to 2011) and the station observations(2010 to 2011).The element is treated as the prediction variable factor in the GRAPES model and used to improve the regional prediction of sea fog on Guangdong coastland.(1) The relationship between this factor and the occurrence of sea fog is explicit:When the sea fog happens,the value of this factor is always large in some specific periods,and the negative value of this factor decreases significantly or turns positive,suggesting the enhancement of warm and moist advection of air flow near the surface,which favors the development of sea fog.(2) The transportation of warm and moist advection over Guangdong coastland is featured by some stages and the jumping among these states.It also gets stronger over time.Meanwhile,the northward propagation of warm and moist advection is quite consistent with the northward advancing of sea fog from south to north along the coastland of China.(3) The GRAPES model can well simulate and realize the factor of near-surface temperature difference.Besides,the accuracy of regional prediction of marine fog,the relevant threat score and Heidke skill score are all improved when the factor is involved.展开更多
The near-surface temperature lapse rates for the core area of the Kunlun Mountains remain critically unresolved due to data scarcity.Here,we revealed the spatial and temporal patterns of nearsurface temperature lapse ...The near-surface temperature lapse rates for the core area of the Kunlun Mountains remain critically unresolved due to data scarcity.Here,we revealed the spatial and temporal patterns of nearsurface temperature lapse rate in the Kunlun Mountain regions based on both long-term meteorological records(1961-2017)and field surveys measured data(2012-2017).The results showed that(1)The near-surface temperature lapse rates(β;)has spatiotemporal distribution patterns on the Northwestern Kunlun Mountains(NWKM),and in complex terrain areas the complexity of the temperature-elevation relationship cannot be explained by the constant environmental temperature lapse rate(0.65℃/100 m)throughout alone.(2)Theβ;for the daily mean,minimum,and maximum temperature on the north slopes in the Kunlun mountain area are 0.41,0.47,and 0.37℃/100 m and on the Tiznafu River(TR)basin are 0.51,0.47 and 0.53℃/100 m,respectively.(3)The variations ofβ;for daily maximum and minimum temperature of the two regions exhibit similar monthly characteristics,which are lower in the winter and spring months than in other months.A greatest variability ofβ;for the daily mean,minimum,and maximum temperature appears in winter and a light variability ofβ;occurs in spring.The seasonal variability ofβ;for daily maximum temperature is greater than that for daily minimum temperature,and the seasonal variability ofβ;for daily average temperature has the smallest variability.(4)There is no significant trend of change occurred in theβ;of NWKM.(5)The spatial and temporal variations ofβ;for the NWKM are linked to the geographic differences and climate factors.The results of Grey Relational Analysis showed that theβ;distribution is mainly influenced by the wind speed and relative humidity of the NWKM.展开更多
Global warming may result in increased polar amplification,but future temperature changes under different climate change scenarios have not been systematically investigated over Antarctica.An index of Antarctic amplif...Global warming may result in increased polar amplification,but future temperature changes under different climate change scenarios have not been systematically investigated over Antarctica.An index of Antarctic amplification(AnA)is defined,and the annual and seasonal variations of Antarctic mean temperature are examined from projections of the Coupled Model Intercomparison Project Phase 6(CMIP6)under scenarios SSP119,SSP126,SSP245,SSP370 and SSP585.AnA occurs under all scenarios,and is strongest in the austral summer and autumn,with an AnA index greater than 1.40.Although the warming over Antarctica accelerates with increased anthropogenic forcing,the magnitude of AnA is greatest in SSP126 instead of in SSP585,which may be affected by strong ocean heat uptake in high forcing scenario.Moreover,future AnA shows seasonal difference and regional difference.AnA is most conspicuous in the East Antarctic sector,with the amplification occurring under all scenarios and in all seasons,especially in austral summer when the AnA index is greater than 1.50,and the weakest signal appears in austral winter.Differently,the AnA over West Antarctica is strongest in austral autumn.Under SSP585,the temperature increase over the Antarctic Peninsula exceeds 0.5℃when the global average warming increases from 1.5℃to 2.0℃above preindustrial levels,except in the austral summer,and the AnA index in this region is strong in the austral autumn and winter.The projections suggest that the warming rate under different scenarios might make a large difference to the future AnA.展开更多
We analyzed the 1961-2006 mean surface air temperature data of 138 stations in China's northwest arid and semi-arid areas(CNASA),to measure climate change in terms of annual mean air temperature changes.We used me...We analyzed the 1961-2006 mean surface air temperature data of 138 stations in China's northwest arid and semi-arid areas(CNASA),to measure climate change in terms of annual mean air temperature changes.We used methods of linear regression analysis,multinomial fitting,Empirical Or-thogonal Function(EOF),Rotated Empirical Orthogonal Function(REOF),Mann-Kendall,Glide T-examination,wavelet analysis and power spectrum analysis.The results show that(1) the warming rate of the annual mean air temperature in CNASA was 0.35oC/10a during the 1961-2006 study period.Some places in the west part of Xinjiang and east part of the Qinghai plateau,which is impacted by the terrain of leeward slope,exhibit smaller increasing trends.However,the majority of region has shown distinct warming in line with general global warming;(2) The standard deviation of the annual mean temperature distribution is non-uniform.The south Xinjiang and east Qinghai-south Gansu areas show relatively small standard deviations,but the inter-annual variation in annual mean air temperature in the greater part of the region is high;(3) Inner Mongolia,Shaanxi,Gansu,Ningxia and Tarim Basin are the areas where the temperature changes are most sensitive to the environment.The degree of uniformity in annual mean air temperature increase is higher in the arid and semi-arid area.From the early 1970s,the trend in tempera-ture changed from a decrease to an increase,and there was a marked increase in mean temperature in 1986.After that mean temperature went through a period of rapid increase.The entire area's 10 hottest years all occurred in or since the 1990s,and 90% of various sub-districts' hottest years also occurred after 1990.The process of temperature change appears to have a roughly 5-year and a 10-year cycle;(4) An-nual mean air temperature variation has regional differences.In Inner Mongolia-Xinjiang and Shaanxi-Gansu-Ningxia-Qinghai areas,the temperature variation in their northern areas was very different from that in their southern areas;(5) Using the REOF method we divided the region into 4 sub-regions:the Northern region,the Plateau region,the Southern Xinjiang region and the Eastern region.The region's annual mean air temperature transition has regional differences.The Plateau and Southern Xinjiang re-gions got warmer steadily without any obvious acceleration in the rate of warming.The Northern region's warming started about 5-years earlier than that of the low latitude Eastern region.The 'Startup region' of the Qinghai-Tibet Plateau,appears to undergo temperature changes 3 to 10 years earlier than the other regions,and exhibits inter-decadal variations 1 to 2 years ahead of the other regions.展开更多
The author investigates the prediction of Northeast China's winter surface air temperature (SAT),and first forecast the year to year increment in the predic-tand and then predict the predictand.Thus,in the first s...The author investigates the prediction of Northeast China's winter surface air temperature (SAT),and first forecast the year to year increment in the predic-tand and then predict the predictand.Thus,in the first step,we determined the predictors for an increment in winter SAT by analyzing the atmospheric variability associated with an increment in winter SAT.Then,multi-linear re-gression was applied to establish a prediction model for an increment in winter SAT in Northeast China.The pre-diction model shows a high correlation coefficient (0.73) between the simulated and observed annual increments in winter SAT in Northeast China throughout the period 1965-2002,with a relative root mean square error of -7.9%.The prediction model makes a reasonable hindcast for 2003-08,with an average relative root mean square error of -7.2%.The prediction model can capture the in-creasing trend of winter SAT in Northeast China from 1965-2008.The results suggest that this approach to forecasting an annual increment in winter SAT in North-east China would be relevant in operational seasonal forecasts.展开更多
Historical simulations of annual mean surface air temperature over China with 25 CMIP5 models were assessed.The observational data from CRUT3v and CN05 were used and further compared with historical simulations of CMI...Historical simulations of annual mean surface air temperature over China with 25 CMIP5 models were assessed.The observational data from CRUT3v and CN05 were used and further compared with historical simulations of CMIP3.The results show that CMIP5 models were able to simulate the observed warming over China from 1906 to 2005(0.84 C per 100 years)with a warming rate of 0.77 C per 100 years based on the multi-model ensemble(MME).The simulations of surface air temperature in the late 20th century were much better than those in the early 20th century,when only two models could reproduce the extreme warming in the 1940s.The simulations for the spatial distribution of the 20-yearmean(1986–2005)surface air temperature over China fit relatively well with the observations.However,underestimations in surface air temperature climatology were still found almost all over China,and the largest cold bias and simulation uncertainty were found in western China.On sub-regional scale,northern China experienced stronger warming than southern China during 1961–1999,for which the CMIP5 MME provided better simulations.With CMIP5 the diference of warming trends in northern and southern China was underestimated.In general,the CMIP5 simulations are obviously improved in comparison with the CMIP3 simulations in terms of the variation in regional mean surface air temperature,the spatial distribution of surface air temperature climatology and the linear trends in surface air temperature all over China.展开更多
文摘An analysis of the minimum air temperature behavior was carried out for the southern tip of South America and the western side of the Antarctica Peninsula. Punta Arenas shows an overall annual warming of 0.15°C per decade during the 1960-2010 period, although this occurred mainly in the summer and winter seasons. The trend of the air temperature in the western side of the Antarctic Peninsula shows an increase until around 2000, but the warming rate during the last 2001-2010 decade has been less than previous decades;in particular, meteorological stations in King George Island show slight cooling. The lineal annual warming per decade as shown by Bellingshausen, Verndsky/Faraday and Rothera stations are 0.26°C ± 0.75°C, 0.55°C ± 1.26°C and 0.69°C ± 1.31°C;for the respectively, 1969-2010, 1951-2010 and 1978-2010 periods. These rates of warming are slightly lower than those found for the same stations but for the 1969-2000, 1951-2000 and 1978-2000 periods.
基金supported by the National Key R&D Program of China (Grant No.2019YFA0607202)the National Natural Science Foundation of China (Grant Nos. 42021004 and 42005143)+2 种基金support by the Postgraduate Research&Practice Innovation Program of Jiangsu Province (Grant No. KYCX21_0978)support by the Open Research Fund Program of the Key Laboratory of Urban Meteorology,China Meteorological Administration (Grant No. LUM-2023-12)the 333 Project of Jiangsu Province (Grant No. BRA2022023)
文摘Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.
基金Acknowledgements This work was supported by the National Natural Science Foundation of China （Grant Nos. 40901202, 40925004）, and the National High Technology Research and Development Program of China （Grant No. 2009AA122104）. The input data for WRF model are from the Research Data Archive （RDA） which is maintained by the Computational and Information Systems Laboratory （CISL） at the National Center for Atmo- spheric Research （NCAR）. The original data are available from the RDA （http：//dss.ucar.edu） in Dataset No. ds083.2.
文摘The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects the ecosystem of this area.This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500-4000 m above sea level.MODIS data were extracted for the period of 2000-2021,and the Mann-Kendall nonparametric test was applied to evaluating the changes in the LST.The results indicated a significant increasing trend for the monthly average LST in May-August along the southern aspect.Both the northern and southern aspects showed decreasing trends for the monthly average LST in October,November,and March and an increasing trend in other months.At all elevations,the average decadal change in the monthly average LST was more severe along the southern aspect(0.60°C)than along the northern aspect(0.37°C).The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months.At the same elevation,the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months.With increasing elevation,the lapse rate between the northern and southern aspects disappeared.Climate change was concluded to greatly decrease the difference in LST at different elevations for April-July.
文摘The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central Taurus Mountains(Bolkar, Aladaglar, Tahtali and Binboga Mountains) from 1981 to 2021. Linear trends of snow cover season(November to April) over the last 41 years showed decreases in SCE primarily at lower elevations. The downward trend in SCE was found to be more pronounced and statistically significant for only November and March. SCE in the Central Taurus Mountains has declined about-6.3% per decade for 2500-3000 m in November and about-6.0% per decade for 1000-1500 m and 3000+ m in March over the last 41 years. The loss of SCE has become evident since the 2000s, and the lowest negative anomalies in SCE have been observed in 2014, 2001, and 2007 in the last 41 years, which are consistent with an increase in air temperature and decreased precipitation. SCE was correlated with both mean temperature and precipitation, with temperature having a greater relative importance at all elevated gradients. Results showed that there is a strong linear relationship between SCE and the mean air temperature(r =-0.80) and precipitation(r = 0.44) for all elevated gradients during the snow season. The Arctic Oscillation(AO), the North Atlantic Oscillation(NAO), and the Mediterranean Oscillation(MO) winter indices were used to explain the year-to-year variability in SCE over the Central Taurus Mountains. The results showed that the inter-annual variability observed in the winter SCE on the Central Taurus Mountains was positively correlated with the phases of the winter AO, NAO and MO, especially below 2000 m elevation.
文摘The temperature is one of the most important factors in weather and climate forecasting.Studying its behaviour is crucial to understanding climate variability,which could vary spatially and temporally at local,regional,and global scales.Several recent studies on air temperature findings show that the Earth’s near surface air temperature increased between 0.6℃ and 0.8℃ throughout the twentieth century.Using temperature records from ten meteorological stations,this study examined climate variability in Rwanda from the 1930s to 2014.The air temperature data were collected from Meteo Rwanda.Before making the analysis,the authors used software,such as Excel 2007 and INSTAT to control the quality of the raw data.The analysis of maxima and minima indicated that the trends of maximum air temperature were positive and significant at height meteorological stations,whereas the trends for minimum air temperature were found to be at 10 meteorological stations.For all parameters analysed,Kigali Airport meteorological station indicated the higher significance of the trends.The majority of meteorological stations showed an increase in both hot days and nights,confirming Rwanda’s warming over time.The analysis of average seasonal air temperature showed almost similar trends even though not all were significant.This similarity in trends could be attributed to the fact that Rwanda’s short and long dry seasons coincide with rainy seasons.
基金Under the auspices of the‘Beautiful China’Ecological Civilization Construction Science and Technology Project(No.XDA23100203)National Natural Science Foundation of China(No.42071289)Henan Postdoctoral Foundation(No.20180087)。
文摘Air temperature(Ta)datasets with high spatial and temporal resolutions are needed in a wide range of applications,such as hydrology,ecology,agriculture,and climate change studies.Nonetheless,the density of weather station networks is insufficient,especially in sparsely populated regions,greatly limiting the accuracy of estimates of spatially distributed Ta.Due to their continuous spatial coverage,remotely sensed land surface temperature(LST)data provide the possibility of exploring spatial estimates of Ta.However,because of the complex interaction of land and climate,retrieval of Ta from the LST is still far from straightforward.The estimation accuracy varies greatly depending on the model,particularly for maximum Ta.This study estimated monthly average daily minimum temperature(Tmin),average daily maximum temperature(Tmax)and average daily mean temperature(Tmean)over the Loess Plateau in China based on Moderate Resolution Imaging Spectroradiometer(MODIS)LST data(MYD11A2)and some auxiliary data using an artificial neural network(ANN)model.The data from 2003 to 2010 were used to train the ANN models,while 2011 to 2012 weather station temperatures were used to test the trained model.The results showed that the nighttime LST and mean LST provide good estimates of Tmin and Tmean,with root mean square errors(RMSEs)of 1.04℃ and 1.01℃,respectively.Moreover,the best RMSE of Tmax estimation was 1.27℃.Compared with the other two published Ta gridded datasets,the produced 1 km×1 km dataset accurately captured both the temporal and spatial patterns of Ta.The RMSE of Tmin estimation was more sensitive to elevation,while that of Tmax was more sensitive to month.Except for land cover type as the input variable,which reduced the RMSE by approximately 0.01℃,the other vegetation-related variables did not improve the performance of the model.The results of this study indicated that ANN,a type of machine learning method,is effective for long-term and large-scale Ta estimation.
基金financially supported by the National Nature Science Foundation of China (No.32001248)the Characteristic Field Project of Department of Education of Guizhou Province (NO.[2019]075)+3 种基金PhD Research Start-up Foundation of Tongren University (No.trxyDH1807)Guizhou Forestry Research Project (No.[2019]014)the Science and Technology Plan Project of Guizhou Province (NO.[2019]1312,NO.[2022]general-556)the Key Laboratory Project of Guizhou Province (No.[2020]2003)
文摘Background: Air temperature affects absorptive root traits, which are closely related to species distribution.However, it is still unclear how air temperature regulates species distribution through changes in absorptive root traits. Seven functional traits of the absorptive roots of 240 individuals of 52 species, soil properties and air temperature were measured along an elevational gradient on Mt. Fanjingshan, Tongren City, Guizhou, and then the direct and indirect effects of these controls on species distribution were detected.Results: Absorptive roots adapted to air temperature with two strategies. The first strategy was positively associated with the specific root area(SRA) and specific root length(SRL) and was negatively associated with the root tissue density(RTD), representing the classic root economics spectrum(RES). The second strategy was represented by the trade-off between root diameter, mycorrhizal fungi colonization(MF) and SRL, representing the collaboration gradient with “do it yourself” resource uptake ranging from “outsourcing” to mycorrhizal resource uptake. Air temperature regulated species distribution in six ways: directly reducing species importance value;indirectly increasing the species importance value by reducing soil nitrogen content or increasing soil pH by reducing soil moisture inducing absorptive roots to change from “do it yourself” resource absorption to “outsourcing” resource absorption;indirectly decreasing the species importance value by decreasing soil moisture to change from“outsourcing”resource absorption to “do it yourself” resource absorption;indirectly increasing the species importance value with increasing soil pH by reducing soil moisture resulting in absorptive root traits turning into nutrient foraging traits;and indirectly decreasing the species importance value by promoting absorptive root traits to nutrient conservation traits.Conclusions: Absorptive root traits play a crucial role in the regulation of species distribution through multiapproaches of air temperature.
基金This research was partially supported by the National Natural Science Foundation of China(No.72074065)the Harbin Medical University Innovative Scientific Research Funding Project(No.0202-31041220023).
文摘Background:Previous studies have established a link between fluctuations in climate and increased mortality due to coronary artery disease(CAD).However,there remains a need to explore and clarify the evidence for associations between meteorological changes and hospitalization incidences related to CAD and its subtypes,especially in cold regions.This study aimed to systematically investigate the relationship between exposure to meteorological changes,air pollutants,and hospitalization for CAD in cold regions.Methods:We conducted a cross-sectional study using hospitalization records of 86,483 CAD patients between January 1,2009,and December 31,2019.Poisson regression analysis,based on generalized additive models,was applied to estimating the influence of hospitalization for CAD.Results:Significant associations were found between low ambient temperature[-10℃,RR=1.65;95%CI:(1.28-2.13)]and the incidence of hospitalization for CAD within a lag of 0-14 days.Furthermore,O_(3)[95.50μg/m^(3),RR=12;95%CI:(1.03-1.21)]and NO_(2)[48.70μg/m^(3),RR=1.0895%CI:(1.01-1.15)]levels were identified as primary air pollutants affecting the incidence of CAD,ST-segment-elevation myocardial infarction(STEMI),and non-STEMI(NSTEMI)within the same lag period.Furthermore,O_(3)[95.50μg/m^(3),RR=1.12;95%CI:(1.03-1.21)]and NO_(2)[48.70μg/m^(3),RR=1.0895%CI:(1.01-1.15)]levels were identified as primary air pollutants affecting the incidence of CAD,ST-segment-elevation myocardial infarction(STEMI),and non-STEMI(NSTEMI)within the same lag period.The effect curve of CAD hospitalization incidence significantly increased at lag days 2 and 4 when NO_(2)and O_(3)concentrations were higher,with a pronounced effect at 7 days,dissipating by lag 14 days.No significant associations were observed between exposure to PM,SO_(2),air pressure,humidity,or wind speed and hospitalization incidences due to CAD and its subtypes.Conclusion:Our findings suggest a positive correlation between short-term exposure to low ambient temperatures or air pollutants(O_(3)and NO_(2))and hospitalizations for CAD,STEMI,and NSTEMI.These results could aid the development of effective preparedness strategies for frequent extreme weather events and support clinical and public health practices aimed at reducing the disease burden associated with current and future abnormal weather events.
文摘In this study, the trends of upper-air temperatures are analysed by utilising radiosonde observations for the barometric levels at 700, 500, 300, 200, 150, 100 and 50 hPa from five meteorological stations within the Arabian Peninsula from January 1986 to August 2015. The mean monthly variations of the temperatures at these levels are characterised and established. The magnitudes of the annual trends of the mean temperatures for each site for the selected barometric levels are studied and statistically tested using Mann-Kendall rank statistics at different significance levels. The temperature trends at different pressure levels show that the upper troposphere and lower stratosphere are warming, while the middle troposphere is cooling which is consistent with the findings of other studies. The variations in upper air temperature observed in this study can be attributed to a range of factors, including increasing greenhouse gas concentrations, changes in atmospheric circulation patterns, variations in solar activity, aerosols and volcanic eruptions, and land use and land cover change.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) (Grant No. 2019QZKK0602)the National Natural Science Foundation of China (Grant Nos. 41401046, 42067049)+1 种基金the Education Science and technology Innovation project of Gansu Province (2021QB-118)the Jiangxi Provincial Natural Science Foundation (Grant No. 20202BABL213035)。
文摘An increasing number of palaeo-climatic records have been reported to identify the Holocene climate history in the arid Xinjiang region of northwest China. However, few studies have fully considered the internal linkages within the regional climate system, which may limit our understanding of the forcing mechanisms of Holocene climate change in this region. Here, we systematically consider three major issues of the moisture/precipitation, temperature and near-surface wind relevant to the Holocene climate history of Xinjiang. First, despite there still has debated for the Holocene moisture evolution in this region, more climatic reconstructions from lake sediments, loess, sand-dunes and peats support a long-term regional wetting trend. Second, temperature records from ice cores, peats and stalagmites demonstrate a long-term winter warming trend during the Holocene in middle-to high-latitudes of Asia. Third, recent studies of aeolian sedimentary sequences reveal that the near-surface winds in winter gradually weakened during the Holocene, whereas the winter mid-latitude Westerlies strengthened in the Tienshan Mountains. Based on this evidence, in the arid Xinjiang region we propose an early to middle Holocene relatively cold and dry interval, with strong near-surface winds;and a warmer, wetter interval with weaker near-surface winds in the middle to late Holocene during winter. Additionally,we develop a conceptual model to explain the pattern of Holocene climate changes in this region.From the early to the late Holocene, the increasing atmospheric COcontent and winter insolation,and the shrinking of high-latitude continental ice-sheets, resulted in increasing winter temperatures in middle to high latitudes in the Northern Hemisphere. Subsequently, the increased winter temperature strengthened the winter mid-latitude Westerlies and weakened the Siberian high-pressure system,which caused an increase in winter precipitation and a decrease in near-surface wind strength. This scenario is strongly supported by evidence from geological records, climate simulation results, and modern reanalysis data. Our hypothesis highlights the important contribution of winter temperature in driving the Holocene climatic evolution of the arid Xinjiang region, and it implies that the socio-economic development and water resources security of this region will face serious challenges presented by the increasing winter temperature in the future.
文摘[Objective]The paper was to explore the influence of near-surface low temperature on cultivation of soft-seed pomegranate,and to provide guidance for planting location of soft-seed pomegranate.[Method]Taking 10 soft-seed pomegranate planting plots under different site conditions as the research objects,the near-surface low temperature of 45-50 cm was dynamically monitored from December 1,2018 to February 20,2019,and comparative analysis was made based on the local meteorological data over the same period.[Result]The near-surface low temperature of each temperature monitoring point was lower than the local meteorological data,which were all in the range of low temperature causing freezing in-jury of pomegranate trees,but the degree of freezing injury was different.The variation of near-surface low temperature was positively correlated with the altitude of terrain,but negatively correlated with the difference of topography and landform.When the local topography and landform were similar,the accumulation time of near-surface low temperature was negatively correlated with the altitude of terrain,while the duration of low tem-perature directly affected the degree of freezing injury.[Conclusion]The development of soft-seed pomegranate cultivation in Tunisia along Huang Mangling region in Henan Province refers to the local meteorological data.Meantime,it is also necessary to pay attention to the impact of regional microclimate environment,especially early monitoring of near-surface temperature to select suitable site and natural conditions.
基金Chinese Special Scientific Research Project for Public Interest(GYHY200906008)Natural Science Foundation of China(41275025)+2 种基金Guangdong Science and Technology Plan Project(2012A061400012)Meteorological Project from Guangdong Meteorological Bureau(201003)Research on Pre-warning and Forecasting Techniques for Marine Meteorology from Guangdong Meteorological Bureau
文摘The relationship between the factor of temperature difference of the near-surface layer(T_(1000 hPa)-T_(2m))and sea fog is analyzed using the NCEP reanalysis with a horizontal resolution of l°xl°(2000 to 2011) and the station observations(2010 to 2011).The element is treated as the prediction variable factor in the GRAPES model and used to improve the regional prediction of sea fog on Guangdong coastland.(1) The relationship between this factor and the occurrence of sea fog is explicit:When the sea fog happens,the value of this factor is always large in some specific periods,and the negative value of this factor decreases significantly or turns positive,suggesting the enhancement of warm and moist advection of air flow near the surface,which favors the development of sea fog.(2) The transportation of warm and moist advection over Guangdong coastland is featured by some stages and the jumping among these states.It also gets stronger over time.Meanwhile,the northward propagation of warm and moist advection is quite consistent with the northward advancing of sea fog from south to north along the coastland of China.(3) The GRAPES model can well simulate and realize the factor of near-surface temperature difference.Besides,the accuracy of regional prediction of marine fog,the relevant threat score and Heidke skill score are all improved when the factor is involved.
基金supported by the National Natural Science Foundation of China(Grant No.41901022,41807445 and 41975010)the National Key Research and Development Program of China(Grant No.2021YFE0100700)。
文摘The near-surface temperature lapse rates for the core area of the Kunlun Mountains remain critically unresolved due to data scarcity.Here,we revealed the spatial and temporal patterns of nearsurface temperature lapse rate in the Kunlun Mountain regions based on both long-term meteorological records(1961-2017)and field surveys measured data(2012-2017).The results showed that(1)The near-surface temperature lapse rates(β;)has spatiotemporal distribution patterns on the Northwestern Kunlun Mountains(NWKM),and in complex terrain areas the complexity of the temperature-elevation relationship cannot be explained by the constant environmental temperature lapse rate(0.65℃/100 m)throughout alone.(2)Theβ;for the daily mean,minimum,and maximum temperature on the north slopes in the Kunlun mountain area are 0.41,0.47,and 0.37℃/100 m and on the Tiznafu River(TR)basin are 0.51,0.47 and 0.53℃/100 m,respectively.(3)The variations ofβ;for daily maximum and minimum temperature of the two regions exhibit similar monthly characteristics,which are lower in the winter and spring months than in other months.A greatest variability ofβ;for the daily mean,minimum,and maximum temperature appears in winter and a light variability ofβ;occurs in spring.The seasonal variability ofβ;for daily maximum temperature is greater than that for daily minimum temperature,and the seasonal variability ofβ;for daily average temperature has the smallest variability.(4)There is no significant trend of change occurred in theβ;of NWKM.(5)The spatial and temporal variations ofβ;for the NWKM are linked to the geographic differences and climate factors.The results of Grey Relational Analysis showed that theβ;distribution is mainly influenced by the wind speed and relative humidity of the NWKM.
基金supported by the National Natural Science Foundation of China(Grant No.42276260,41671073)the 2021 technical support talent project of the Chinese Academy of Sciences。
文摘Global warming may result in increased polar amplification,but future temperature changes under different climate change scenarios have not been systematically investigated over Antarctica.An index of Antarctic amplification(AnA)is defined,and the annual and seasonal variations of Antarctic mean temperature are examined from projections of the Coupled Model Intercomparison Project Phase 6(CMIP6)under scenarios SSP119,SSP126,SSP245,SSP370 and SSP585.AnA occurs under all scenarios,and is strongest in the austral summer and autumn,with an AnA index greater than 1.40.Although the warming over Antarctica accelerates with increased anthropogenic forcing,the magnitude of AnA is greatest in SSP126 instead of in SSP585,which may be affected by strong ocean heat uptake in high forcing scenario.Moreover,future AnA shows seasonal difference and regional difference.AnA is most conspicuous in the East Antarctic sector,with the amplification occurring under all scenarios and in all seasons,especially in austral summer when the AnA index is greater than 1.50,and the weakest signal appears in austral winter.Differently,the AnA over West Antarctica is strongest in austral autumn.Under SSP585,the temperature increase over the Antarctic Peninsula exceeds 0.5℃when the global average warming increases from 1.5℃to 2.0℃above preindustrial levels,except in the austral summer,and the AnA index in this region is strong in the austral autumn and winter.The projections suggest that the warming rate under different scenarios might make a large difference to the future AnA.
基金supported by National Natural Science Foundation of China (40775057)
文摘We analyzed the 1961-2006 mean surface air temperature data of 138 stations in China's northwest arid and semi-arid areas(CNASA),to measure climate change in terms of annual mean air temperature changes.We used methods of linear regression analysis,multinomial fitting,Empirical Or-thogonal Function(EOF),Rotated Empirical Orthogonal Function(REOF),Mann-Kendall,Glide T-examination,wavelet analysis and power spectrum analysis.The results show that(1) the warming rate of the annual mean air temperature in CNASA was 0.35oC/10a during the 1961-2006 study period.Some places in the west part of Xinjiang and east part of the Qinghai plateau,which is impacted by the terrain of leeward slope,exhibit smaller increasing trends.However,the majority of region has shown distinct warming in line with general global warming;(2) The standard deviation of the annual mean temperature distribution is non-uniform.The south Xinjiang and east Qinghai-south Gansu areas show relatively small standard deviations,but the inter-annual variation in annual mean air temperature in the greater part of the region is high;(3) Inner Mongolia,Shaanxi,Gansu,Ningxia and Tarim Basin are the areas where the temperature changes are most sensitive to the environment.The degree of uniformity in annual mean air temperature increase is higher in the arid and semi-arid area.From the early 1970s,the trend in tempera-ture changed from a decrease to an increase,and there was a marked increase in mean temperature in 1986.After that mean temperature went through a period of rapid increase.The entire area's 10 hottest years all occurred in or since the 1990s,and 90% of various sub-districts' hottest years also occurred after 1990.The process of temperature change appears to have a roughly 5-year and a 10-year cycle;(4) An-nual mean air temperature variation has regional differences.In Inner Mongolia-Xinjiang and Shaanxi-Gansu-Ningxia-Qinghai areas,the temperature variation in their northern areas was very different from that in their southern areas;(5) Using the REOF method we divided the region into 4 sub-regions:the Northern region,the Plateau region,the Southern Xinjiang region and the Eastern region.The region's annual mean air temperature transition has regional differences.The Plateau and Southern Xinjiang re-gions got warmer steadily without any obvious acceleration in the rate of warming.The Northern region's warming started about 5-years earlier than that of the low latitude Eastern region.The 'Startup region' of the Qinghai-Tibet Plateau,appears to undergo temperature changes 3 to 10 years earlier than the other regions,and exhibits inter-decadal variations 1 to 2 years ahead of the other regions.
基金supported by the Major State Basic Research Development Program of China (973 Program) under grant No.2009CB421406the Research Program for excellent Ph. D dissertations in the Chinese Academy of Sciences
文摘The author investigates the prediction of Northeast China's winter surface air temperature (SAT),and first forecast the year to year increment in the predic-tand and then predict the predictand.Thus,in the first step,we determined the predictors for an increment in winter SAT by analyzing the atmospheric variability associated with an increment in winter SAT.Then,multi-linear re-gression was applied to establish a prediction model for an increment in winter SAT in Northeast China.The pre-diction model shows a high correlation coefficient (0.73) between the simulated and observed annual increments in winter SAT in Northeast China throughout the period 1965-2002,with a relative root mean square error of -7.9%.The prediction model makes a reasonable hindcast for 2003-08,with an average relative root mean square error of -7.2%.The prediction model can capture the in-creasing trend of winter SAT in Northeast China from 1965-2008.The results suggest that this approach to forecasting an annual increment in winter SAT in North-east China would be relevant in operational seasonal forecasts.
文摘Historical simulations of annual mean surface air temperature over China with 25 CMIP5 models were assessed.The observational data from CRUT3v and CN05 were used and further compared with historical simulations of CMIP3.The results show that CMIP5 models were able to simulate the observed warming over China from 1906 to 2005(0.84 C per 100 years)with a warming rate of 0.77 C per 100 years based on the multi-model ensemble(MME).The simulations of surface air temperature in the late 20th century were much better than those in the early 20th century,when only two models could reproduce the extreme warming in the 1940s.The simulations for the spatial distribution of the 20-yearmean(1986–2005)surface air temperature over China fit relatively well with the observations.However,underestimations in surface air temperature climatology were still found almost all over China,and the largest cold bias and simulation uncertainty were found in western China.On sub-regional scale,northern China experienced stronger warming than southern China during 1961–1999,for which the CMIP5 MME provided better simulations.With CMIP5 the diference of warming trends in northern and southern China was underestimated.In general,the CMIP5 simulations are obviously improved in comparison with the CMIP3 simulations in terms of the variation in regional mean surface air temperature,the spatial distribution of surface air temperature climatology and the linear trends in surface air temperature all over China.
