Application of Multiple Analysis of Series for Homogenization to Beijing Daily Temperature Series (1960-2006)

Homogenization of climate observations remains a challenge to climate change researchers, especially in cases where metadata （e.g., probable dates of break points） are not always available. To examine the inffuence of metadata on homogenizing climate data, the authors applied the recently developed Multiple Analysis of Series for Homogenization （MASH） method to the Beijing （BJ） daily temperature series for 1960- 2006 in three cases with different references： （1） 13M-considering metadata at BJ and 12 nearby stations; （2） 13NOM-considering the same 13 stations without metadata; and （3） 21NOM-considering 20 further stations and BJ without metadata. The estimated mean annual, seasonal, and monthly inhomogeneities are similar between the 13M and 13NOM cases, while those in the 21NOM case are slightly different. The detected biases in the BJ series corresponding to the documented relocation dates are as low as -0.71~0C, -0.79~0C, and -0.5~0C for the annual mean in the 3 cases, respectively. Other biases, including those undocumented in metadata, are minor. The results suggest that any major inhomogeneity could be detected via MASH, albeit with minor differences in estimating inhomogeneities based on the different references. The adjusted annual series showed a warming trend of 0.337, 0.316, and 0.365~0C （10 yr）^（-1） for the three cases, respectively, smaller than the estimate of 0.453~0C （10 yr）^（-1） in the original series, mainly due to the relocation-induced biases. The impact of the MASH-type homogenization on estimates of climate extremes in the daily temperature series is also discussed.

Homogenized Daily Mean/Maximum/Minimum Temperature Series for China from 1960-2008

Inhomogeneities in the daily mean/maximum/ minimum temperature （Tm/Tmax/Tmin） series from 1960- 2008 at 549 National Standard Stations （NSSs） in China were analyzed by using the Multiple Analysis of Series for Homogenization （MASH） software package. Typical biases in the dataset were illustrated via the cases of Beijing （B J）, Wutaishan （WT）, Urumqi （UR） and Henan （HN） stations. The homogenized dataset shows a mean warming trend of 0.261/0.193/0.344℃/decade for the annual series of Tm/Tmax/Tmin, slightly smaller than that of the original dataset by 0.006/0.009/0.007℃/decade. However, considerable differences between the adjusted and original datasets were found at the local scale. The adjusted Tmin series shows a significant warming trend almost everywhere for all seasons, while there are a number of stations with an insignificant trend in the original dataset. The adjusted Tm data exhibit significant warming trends annually as well as for the autumn and winter seasons in northern China, and cooling trends only for the summer in the middle reaches of the Yangtze River and parts of central China and for the spring in southwestern China, while the original data show cooling trends at several stations for the annual and seasonal scales in the Qinghai, Shanxi, Hebei, and Xinjiang provinces. The adjusted Tmax data exhibit cooling trends for summers at a number of stations in the mid-lower reaches of the Yangtze and Yellow Rivers and for springs and winters at a few stations in southwestern China, while the original data show cooling trends at three/four stations for the annual/autumn periods in the Qinghai and Yunnan provinces. In general, the number of stations with a cooling trend was much smaller in the adjusted Tm and Tmax dataset than in the original dataset. The cooling trend for summers is mainly due to cooling in August. The results of homogenization using MASH appear to be robust; in particular, different groups of stations with consideration of elevation led to minor effects in the results.

Adapted Caussinus-Mestre Algorithm for Networks of Temperature series (ACMANT)

Any change in technical or environmental conditions of observations may result in bias from the precise values of observed climatic variables. The common name of these biases is inhomogeneity (IH). IHs usually appear in a form of sudden shift or gradual trends in the time series of any variable, and the timing of the shift indicates the date of change in the conditions of observation. The seasonal cycle of radiation intensity often causes marked seasonal cycle in the IHs of observed temperature time series, since a substantial portion of them has direct or indirect connection to radiation changes in the micro-environment of the thermometer. Therefore the magnitudes of temperature IHs tend to be larger in summer than in winter. A new homogenisation method (ACMANT) has recently been developed which treats in a special way the seasonal changes of IH-sizes in temperature time series. The ACMANT is a further development of the Caussinus-Mestre method, that is one of the most effective tool among the known homogenising methods. The ACMANT applies a bivariate test for searching the timings of IHs, the two variables are the annual mean temperature and the amplitude of seasonal temperature-cycle. The ACMANT contains several further innovations whose efficiencies are tested with the benchmark of the COST ES0601 project. The paper describes the properties and the operation of ACMANT and presents some verification results. The results show that the ACMANT has outstandingly high performance. The ACMANT is a recommended method for homogenising networks of monthly temperature time series that observed in mid- or high geographical latitudes, because the harmonic seasonal cycle of IH-size is valid for these time series only.

Surface air temperature change in the Wuyi Mountains,southeast China

Detecting changes in surface air temperature in mid-and low-altitude mountainous regions is essential for a comprehensive understanding of warming trend with altitude.We use daily surface air temperature data from 64 meteorological stations in Wuyi Mountains and its adjacent regions to analyze the spatio-temporal patterns of temperature change.The results show that Wuyi Mountains have experienced significant warming from 1961 to 2018.The warming trend of the mean temperature is 0.20℃/decade,the maximum temperature is 0.17℃/decade,and the minimum temperature is 0.26℃/decade.In 1961-1990,more than 63%of the stations showed a decreasing trend in annual mean temperature,mainly because the maximum temperature decreased during this period.However,in 1971-2000,1981-2010 and 1991-2018,the maximum,minimum and mean temperatures increased.The fastest increasing trend of mean temperature occurred in the southeastern coastal plains,the quickest increasing trend of maximum temperature occurred in the northwestern mountainous region,and the increase of minimum temperature occurred faster in the southeastern coastal and northwestern mountainous regions than that in the central area.Meanwhile,this study suggests that elevation does not affect warming in the Wuyi Mountains.These results are beneficial for understanding climate change in humid subtropical middle and low mountains.

Impacts of Climate Change on Seawater Temperature and Total Dissolved Solids: Challenges and Sustainable Solutions for Reverse Osmosis Desalination in the Arabian Gulf Region

This article examines the influence of seawater temperature and total dissolved solids (TDS) on reverse osmosis (RO) desalination in the Arabian Gulf region, with a focus on the impact of climate change. The study highlights the changes in seawater temperature and TDS levels over the years and discusses their effects on the efficiency and productivity of RO desalination plants. It emphasizes the importance of monitoring TDS levels and controlling seawater temperature to optimize water production. The article also suggests various solutions, including intensive pre-treatment, development of high-performance membranes, exploration of alternative water sources, and regulation of discharges into the Gulf, to ensure sustainable water supply in the face of rising TDS levels and seawater temperature. Further research and comprehensive monitoring are recommended to understand the implications of these findings and develop effective strategies for the management of marine resources in the Arabian Gulf.

Comparative Analysis of Climatic Change Trend and Change-Point Analysis for Long-Term Daily Rainfall Annual Maximum Time Series Data in Four Gauging Stations in Niger Delta

The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta region of Nigeria. Using daily or 24-hourly annual maximum series (AMS) data with the Indian Meteorological Department (IMD) and the modified Chowdury Indian Meteorological Department (MCIMD) models were adopted to downscale the time series data. Mann-Kendall (MK) trend and Sen’s Slope Estimator (SSE) test showed a statistically significant trend for Uyo and Benin, while Port Harcourt and Warri showed mild trends. The Sen’s Slope magnitude and variation rate were 21.6, 10.8, 6.00 and 4.4 mm/decade, respectively. The trend change-point analysis showed the initial rainfall change-point dates as 2002, 2005, 1988, and 2000 for Uyo, Benin, Port Harcourt, and Warri, respectively. These prove positive changing climatic conditions for rainfall in the study area. Erosion and flood control facilities analysis and design in the Niger Delta will require the application of Non-stationary IDF modelling.

Construction of the homogenized temperature series during 1910-2014 and its changes in Hunan Province

Based on the statistical method and the historical evolution of meteorological sta- tions, the temperature time series for each station in Hunan Province during 1910-2014 are tested for their homogeneity and then corrected. The missing data caused by war and other reasons at the 8 meteorological stations which had records before 1950 is filled by interpola- tion using adjacent observations, and complete temperature time series since the estab- lishment of stations are constructed. After that, according to the representative analysis of each station in different time periods, the temperature series of Hunan Province during 1910-2014 are built and their changes are analyzed. The results indicate that the annual mean temperature has a significant warming trend during 1910-2014 and the seasonal mean temperature has the largest rising amplitude in winter and spring, followed by autumn, but no significant change in summer. Temperature variation over Hunan Province has several sig- nificant warm-cold alternations and more frequent than that in whole China. Annual and seasonal mean temperatures except summer and autumn have abrupt warming changes in the recent 100 years. The wavelet analysis suggests that the annual and four seasonal mean temperatures in recent 100 years have experienced two climatic shifts from cold to warm.

Assessment of future Antarctic amplification of surface temperature change under different Scenarios from CMIP6

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.

Homogenised Monthly and Daily Temperature and Precipitation Time Series in China and Greece since 1960

In this paper,we describe and analyze two datasets entitled“Homogenised monthly and daily temperature and precipitation time series in China during 1960–2021”and“Homogenised monthly and daily temperature and precipitation time series in Greece during 1960–2010”.These datasets provide the homogenised monthly and daily mean(TG),minimum(TN),and maximum(TX)temperature and precipitation(RR)records since 1960 at 366 stations in China and 56stations in Greece.The datasets are available at the Science Data Bank repository and can be downloaded from https://doi.org/10.57760/sciencedb.01731 and https://doi.org/10.57760/sciencedb.01720.For China,the regional mean annual TG,TX,TN,and RR series during 1960–2021 showed significant warming or increasing trends of 0.27℃(10 yr)^(-1),0.22℃(10 yr)^(-1),0.35℃(10 yr)^(-1),and 6.81 mm(10 yr)-1,respectively.Most of the seasonal series revealed trends significant at the 0.05level,except for the spring,summer,and autumn RR series.For Greece,there were increasing trends of 0.09℃(10 yr)-1,0.08℃(10 yr)^(-1),and 0.11℃(10 yr)^(-1)for the annual TG,TX,and TN series,respectively,while a decreasing trend of–23.35 mm(10 yr)^(-1)was present for RR.The seasonal trends showed a significant warming rate for summer,but no significant changes were noted for spring(except for TN),autumn,and winter.For RR,only the winter time series displayed a statistically significant and robust trend[–15.82 mm(10 yr)^(-1)].The final homogenised temperature and precipitation time series for both China and Greece provide a better representation of the large-scale pattern of climate change over the past decades and provide a quality information source for climatological analyses.

Analysis of Change Point in Surface Temperature Time Series Using Cumulative Sum Chart and Bootstrapping for Asansol Weather Observation Station, West Bengal, India

This paper aims to detect the short-term as well as long-term change point in the surface air temperature time series for Asansol weather observation station, West Bengal, India. Temperature data for the period from 1941 to 2010 of the said weather observatory have been collected from Indian Meteorological Department, Kolkata. Variations and trends of annual mean temperature, annual mean maximum temperature and annual minimum temperature time series were examined. The cumulative sum charts (CUSUM) and bootstrapping were used for the detection of abrupt changes in the time series data set. Statistically significant abrupt changes and trends have been detected. The major change point in the annual mean temperatures occurred around 1986 (0.57°C) at the period of 25 years in the long-term regional scale. On the other side, the annual mean maximum and annual mean minimum temperatures have distinct change points at level 1. There are abrupt changes in the year 1961 (Confidence interval 1961, 1963) for the annual mean maximum and 1994 (Confidence interval 1993, 1996) for the annual mean minimum temperatures at a confidence level of 100% and 98%, respectively. Before the change, the annual mean maximum and annual mean minimum temperatures were 30.90°C and 23.99°C, respectively, while after the change, the temperatures became 33.93°C and 24.84°C, respectively. Over the entire period of consideration (1941-2010), 11 forward and backward changes were found in total. Out of 11, there are 3 changes (1961, 1986 and 2001) in annual mean temperatures, 4 changes (1957, 1961, 1980 and 1994) in annual mean maximum temperatures, and rest 4 changes (1968, 1981, 1994 and 2001) are associated with annual mean minimum temperature data set.

The Influence of Climate Change and Variability on Spatio-Temporal Rainfall and Temperature Distribution in Zanzibar

Climate change has resulted in serious social-economic ramifications and extremely catastrophic weather events in the world, Tanzania and Zanzibar in particular, with adaptation being the only option to reduce impacts. The study focuses on the influence of climate change and variability on spatio-temporal rainfall and temperature variability and distribution in Zanzibar. The station observation datasets of rainfall, Tmax and Tmin acquired from Tanzania Meteorological Authority (TMA) and the Coordinated Regional Climate Downscaling Experiment program (CORDEX) projected datasets from the Regional climate model HIRHAM5 under driving model ICHEC-EC-EARH, for the three periods of 1991-2020 used as baseline (HS), 2021-2050 as near future (NF) and 2051-2080 far future (FF), under two representative concentration pathways (RCP) of 4.5 and 8.5, were used. The long-term observed Tmax and Tmin were used to produce time series for observing the nature and trends, while the observed rainfall data was used for understanding wet and dry periods, trends and slope (at p ≤ 0.05) using the Standardized Precipitation Index (SPI) and the Mann Kendall test (MK). Moreover, the Quantum Geographic Information System (QGIS) under the Inverse Distance Weighting (IDW) interpolation techniques were used for mapping the three decades of 1991-2000 (hereafter D1), 2001-2010 (hereafter D2) and 2011-2020 (hereafter D3) to analyze periodical spatial rainfall distribution in Zanzibar. As for the projected datasets the Climate Data Operator Commands (CDO), python scripts and Grid analysis and Display System (GrADS) soft-wares were used to process and display the results of the projected datasets of rainfall, Tmax and Tmin for the HS, NF and FF, respectively. The results show that the observed Tmax increased by the rates of 0.035℃ yr-1 and 0.0169℃ yr-1, while the Tmin was increased by a rate of 0.064℃ yr-1 and 0.104℃ yr-1 for Unguja and Pemba, respectively. The temporal distribution of wetness and dryness indices showed a climate shift from near normal to moderate wet during 2005 at Zanzibar Airport, while normal to moderately dry conditions, were observed in Pemba at Matangatuani. The decadal rainfall variability and distributions revealed higher rainfall intensity with an increasing trend and good spatial distribution in D3 from March to May (MAM) and October to December (OND). The projected results for Tmax during MAM and OND depicted higher values ranging from 1.7℃ - 1.8℃ to 1.9℃ - 2.0℃ and 1.5℃ to 2.0℃ in FF compared to NF under both RCPs. Also, higher Tmin values of 1.12℃ - 1.16℃ was projected in FF for MAM and OND under both RCPs. Besides, the rainfall projection generally revealed increased rainfall intensity in the range of 0 - 25 mm for Pemba and declined rainfall in the range of 25 - 50 mm in Unguja under both RCPs in perspectives of both NF and FF. Conclusively the study has shown that the undergoing climate change has posed a significant impact on both rainfall and temperature spatial and temporal distributions in Zanzibar (Unguja and Pemba), with Unguja being projected to have higher rainfall deficits while increasing rainfall strengths in Pemba. Thus, the study calls for more studies and formulation of effective adaptation, strategies and resilience mechanisms to combat the projected climate change impacts especially in the agricultural sector, water and food security.

Changes in Rainfall and Temperature and Its Impact on Crop Production in Moyamba District, Southern Sierra Leone

Rainfall and temperature are the important variables that are often used to trace climate variability and change. A Perception study and analysis of climatic data were conducted to assess the changes in rainfall and temperature and their impact on crop production in Moyamba district, Sierra Leone. For the perception study, 400 farmers were randomly selected from Farmer-Based Organizations (FBOs) in 4 chiefdoms and 30 Agricultural Extension Workers (AWEs) in the Moyamba district were purposely selected as respondents. Descriptive statistics and Kendall’s test of concordance was used to analyze the data collected from the farmers and AEWs. Data for the analysis of variability and trends of rainfall and temperature from 1991 to 2020 were obtained from the Sierra Leone Meteorological Agency and Njala University and grouped into monthly, seasonal and annual time series. Regression analyses were used to determine the statistical values and trend lines for the seasonal and annual time series data. The Mann-Kendall test and Sen’s Slope Estimator were used to analyze the significance and magnitude of the trends respectively. The results of both studies show evidence of climate change in the Moyamba district. A substantial number of farmers and AEWs perceived a decrease in the annual rainfall amount, length of the rainy season, a late start and end of the rainy season, an increase in the temperature during the day and night, and a shortened harmattan period over the last 30 years. Analysis of the meteorological data shows evidence of variability in the seasonal and annual distribution of rainfall and temperature, a decreasing and non-significant trend in the rainy season and annual rainfall and an increasing and significant trend in seasonal and annual temperature from 1991 to 2020. However, the observed changes in rainfall and temperature by the farmers and AEWs partially agree with the results of the analyzed meteorological data. The majority of the farmers perceived that;adverse weather conditions have negatively affected crop production in the district. Droughts, high temperatures, and irregular rainfall are the three major adverse weather events that farmers perceived to have contributed to a substantial loss in the yields of the major crops cultivated in the district. In response to the negative effects of adverse weather events, a substantial number of farmers take no action due to their lack of knowledge, technical or financial capacity to implement climate-sensitive agricultural (CSA) practices. Even though few farmers are practicing some CSA practices on their farms, there is an urgent need to build the capacity of farmers and AEWs to adapt to and mitigate the negative impacts of climate change. The most priority support needed by farmers is the provision of climate-resilient crop varieties whilst the AEWs need training on CSA practices.

Analysis on Climatic Characteristics of High Temperature Weather in Longdong Region

Using meteorological data from 8 national basic meteorological observation stations in Qingyang City of Longdong region from 1972 to 2021,the causes and change characteristics of high-temperature weather were analyzed,and targeted countermeasures and suggestions were proposed for residents' production,life,and energy security supply affected by high-temperature weather.The results showed that①affected by global warming,the annual average temperature,annual average maximum temperature,annual extreme maximum temperature,days of daily maximum temperature≥30℃,and days of daily maximum temperature≥35℃in Longdong region were all showing an upward trend;②due to the different terrain and soil properties of the underlying surface,the increase in high temperature weather varied in different regions.Due to the influence of desert and hilly terrain,the frequency and days of high temperature occurrence were relatively high in the central and northern parts of Qingyang City.Due to the climate regulation of the Ziwuling Mountains,the days of high temperature in the central and southern parts was significantly less than that in the central and northern parts;③if the warm high pressure ridge on the Qinghai-Tibet Plateau developed strongly in summer,the temperature of the closed warm center reached 0-4℃on the 500 hPa of high-altitude weather map.If the warm air mass developed eastward,it often led to sustained high temperature weather in Longdong region;④when the El Nino phenomenon occurred,the subtropical high in the western Pacific developed strongly in summer,with a center located northward,which was stable,with little movement.It was dry,sunny,hot,and rainless in Longdong region,and the high temperature weather was more significant than that in normal years.

Detecting Climate Change Trend, Size, and Change Point Date on Annual Maximum Time Series Rainfall Data for Warri, Nigeria

The study focused on the detection of indicators of climate change in 24-hourly annual maximum series (AMS) rainfall data collected for 36 years (1982-2017) for Warri Township, using different statistical methods yielded a statistically insignificant positive mild trend. The IMD and MCIMD downscaled model’s time series data respectively produced MK statistics varying from 1.403 to 1.4729, and 1.403 to 1.463 which were less than the critical Z-value of 1.96. Also, the slope magnitude obtained showed a mild increasing trend in variation from 0.0189 to 0.3713, and 0.0175 to 0.5426, with the rate of change in rainfall intensity at 24 hours duration as 0.4536 and 0.42 mm/hr.year (4.536 and 4.2 mm/decade) for the IMD and the MCIMD time series data, respectively. The trend change point date occurred in the year 2000 from the distribution-free CUSUM test with the trend maintaining a significant and steady increase from 2010 to 2015. Thus, this study established the existence of a trend, which is an indication of a changing climate, and satisfied the condition for rainfall Non-stationary intensity-duration-frequency (NS-IDF) modeling required for infrastructural design for combating flooding events.

Heat exposure and hospitalizations for chronic kidney disease in China: a nationwide time series study in 261 major Chinese cities

Background:Climate change profoundly shapes the population health at the global scale.However,there was still insufficient and inconsistent evidence for the association between heat exposure and chronic kidney disease(CKD).Methods:In the present study,we studied the association of heat exposure with hospitalizations for cause-specific CKD using a national inpatient database in China during the study period of hot season from 2015 to 2018.Standard time-series regression models and random-effects Meta-analysis were developed to estimate the city-specific and national averaged associations at a 7 lag-day span,respectively.Results:A total of 768,129 hospitalizations for CKD was recorded during the study period.The results showed that higher temperature was associated with elevated risk of hospitalizations for CKD,especially in sub-tropical cities.With a 1℃ increase in daily mean temperature,the cumulative relative risks(RR)over lag 0-7 d were 1.008[95% confidence interval(CI)1.003-1.012]for nationwide.The attributable fraction of CKD hospitalizations due to high temperatures was 5.50%.Stronger associations were observed among younger patients and those with obstructive nephropathy.Our study also found that exposure to heatwaves was associated with added risk of hospitalizations for CKD compared to non-heatwave days(RR=1.116,95%CI 1.069-1.166)above the effect of daily mean temperature.Conclusions:Short-term heat exposure may increase the risk of hospitalization for CKD.Our findings provide insights into the health effects of climate change and suggest the necessity of guided protection strategies against the adverse effects of high temperatures.

Phenology of different types of vegetation and their response to climate change in the Qilian Mountains,China

The Qilian Mountains(QM)possess a delicate vegetation ecosystem,amplifying the evident response of vegetation phenology to climate change.The relationship between changes in vegetation growth and climate remains complex.To this end,we used MODIS NDVI data to extract the phenological parameters of the vegetation including meadow(MDW),grassland(GSD),and alpine vegetation(ALV))in the QM from 2002 to 2021.Then,we employed path analysis to reveal the direct and indirect impacts of seasonal climate change on vegetation phenology.Additionally,we decomposed the vegetation phenology in a time series using the trigonometric seasonality,Box-Cox transformation,ARMA errors,and Trend Seasonal components model(TBATS).The findings showed a distinct pattern in the vegetation phenology of the QM,characterized by a progressive shift towards an earlier start of the growing season(SOS),a delayed end of the growing season(EOS),and an extended length of the growing season(LOS).The growth cycle of MDW,GSD,and ALV in the QM species is clearly defined.The SOS for MDW and GSD occurred earlier,mainly between late April and August,while the SOS for ALVs occurred between mid-May and mid-August,a one-month delay compared to the other vegetation.The EOS in MDW and GSD were concentrated between late August and April and early September and early January,respectively.Vegetation phenology exhibits distinct responses to seasonal temperature and precipitation patterns.The advancement and delay of SOS were mainly influenced by the direct effect of spring temperatures and precipitation,which affected 19.59%and 22.17%of the study area,respectively.The advancement and delay of EOS were mainly influenced by the direct effect of fall temperatures and precipitation,which affected 30.18%and 21.17%of the area,respectively.On the contrary,the direct effects of temperature and precipitation in summer and winter on vegetation phenology seem less noticeable and were mainly influenced by indirect effects.The indirect effect of winter precipitation is the main factor affecting the advance or delay of SOS,and the area proportions were 16.29%and 23.42%,respectively.The indirect effects of fall temperatures and precipitation were the main factors affecting the delay and advancement of EOS,respectively,with an area share of 15.80%and 21.60%.This study provides valuable insight into the relationship between vegetation phenology and climate change,which can be of great practical value for the ecological protection of the Qinghai-Tibetan Plateau as well as for the development of GSD ecological animal husbandry in the QM alpine pastoral area.

Climate warming is significantly influenced by rising summer maximum temperatures: insights from tree-ring evidence of the Western Tianshan Mountains, China

As one of the regions most affected by global cli-mate warming,the Tianshan mountains has experienced sev-eral ecological crises,including retreating glaciers and water deficits.Climate warming in these mountains is considered mainly to be caused by increases in minimum temperatures and winter temperatures,while the influence of maximum temperatures is unclear.In this study,a 300-year tree-ring chronology developed from the Western Tianshan Moun-tains was used to reconstruct the summer(June-August)maximum temperature(T_(max6-8))variations from 1718 to 2017.The reconstruction explained 53.1% of the variance in the observed T_(max6-8).Over the past 300 years,the T_(max6-8)reconstruction showed clear interannual and decadal vari-abilities.There was a significant warming trend(0.18°C/decade)after the 1950s,which was close to the increasing rates of the minimum and mean temperatures.The increase in maximum temperature was also present over the whole Tianshan mountains and its impact on climate warming has increased.The T_(max6-8) variations in the Western Tianshan mountains were influenced by frequent volcanic eruptions combined with the influence of solar activity and the sum-mer North Atlantic Oscillation.This study reveals that cli-mate warming is significantly influenced by the increase in maximum temperatures and clarifies possible driving mech-anisms of temperature variations in the Western Tianshan mountains which should aid climate predictions.

Climate warming is significantly influenced by rising summer maximum temperatures:insights from tree-ring evidence of the Western Tianshan Mountains,China

As one of the regions most affected by global climate warming,the Tianshan mountains has experienced several ecological crises,including retreating glaciers and water deficits.Climate warming in these mountains is considered mainly to be caused by increases in minimum temperatures and winter temperatures,while the influence of maximum temperatures is unclear.In this study,a 300-year tree-ring chronology developed from the Western Tianshan Mountains was used to reconstruct the summer(June-August)maximum temperature(Tmax6-8) variations from 1718 to2017.The reconstruction explained 53.1% of the variance in the observed Tmax6-8.Over the past 300 years,the Tmax6-8reconstruction showed clear interannual and decadal variabilities.There was a significant warming trend(0.18 ℃/decade) after the 1950s,which was close to the increasing rates of the minimum and mean temperatures.The increase in maximum temperature was also present over the whole Tianshan mountains and its impact on climate warming has increased.The Tmax6-8variations in the Western Tianshan mountains were influenced by frequent volcanic eruptions combined with the influence of solar activity and the summer North Atlantic Oscillation.This study reveals that climate warming is significantly influenced by the increase in maximum temperatures and clarifies possible driving mechanisms of temperature variations in the Western Tianshan mountains which should aid climate predictions.

April-September minimum temperature reconstruction based on Sabina tibetica ring-width chronology in the central eastern Tibetan Plateau,China

Minimum temperatures have remarkable impacts on tree growth at high-elevation sites on the Tibetan Plateau,but the shortage of long-term and high-resolution paleoclimate records inhibits understanding of recent minimum temperature anomalies.In this study,a warm season(April–September)reconstruction is presented for the past 467 years(1550–2016)based on Sabina tibetica ring-width chronology on the Lianbaoyeze Mountain of the central eastern Tibetan Plateau.Eight warm periods and eight cold periods were identified.Long-term minimum temperature variations revealed a high degree of coherence with nearby reconstructions.Spatial correlations between our reconstruction and global sea surface temperatures suggest that warm season minimum temperature anomalies in the central eastern Tibetan Plateau were strongly influenced by large-scale ocean atmospheric circulations,such as the El Ni?o-Southern Oscillation and the Atlantic Multidecadal Oscillation.

A Bibliometric Analysis Unveils Valuable Insights into the Past,Present,and Future Dynamics of Plant Acclimation to Temperature

Plant temperature acclimation is closely related to maintaining a positive carbon gain under future climate change.However,no systematic summary of the field has been conducted.Based on this,we analyzed data on plant temperature acclimation from the Web of Science Core Collection database using bibliometric software R,RStudio and VOSviewer.Our study demonstrated that a stabilized upward trajectory was noted in publications(298 papers)from 1986 to 2011,followed by a swift growth(373 papers)from 2012 to 2022.The most impactful journals were Plant Cell and Environment,boasting the greatest count of worldwide citations and articles,the highest H-index and G-index,followed by Global Change Biology and New Phytologist,and Frontiers in Plant Science which had the highest M-index.The USA and China were identified as the most influential countries,while Atkin was the most influential author,and the Chinese Academy of Sciences was the most influential research institution.The most cited articles were published in the Annual Review of Plant Biology in 1999.“Cold acclimation”was the most prominent keyword.Future plant temperature acclimation research is expected to focus on thermal acclimation and photosynthesis,which have important significance for future agricultural production,forestry carbon sequestration,and global food security.In general,this study provides a systematic insight of the advancement,trend,and future of plant temperature acclimation research,enhancing the comprehension of how plants will deal with forthcoming climate change.