scholarly journals Trend and Abrupt Regime Shift of Temperature Extreme in Northeast China, 1957–2015

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Patteson Chula Mwagona ◽  
Yunlong Yao ◽  
Yuanqi Shan ◽  
Hongxian Yu ◽  
Yiwen Zhang

Trend and an abrupt regime shift of temperature extremes were investigated based on diurnal data at 116 meteorological stations in the Northeast China region during 1957–2015. A total of 10 temperature indices divided into two categories: extremely cold and warm indices, were used in this study. The Mann–Kendall (MK) test was employed to evaluate the trend in temperature while changepoint, an R package for changepoint analysis, was used to detect changes in the mean levels of temperature extreme data series. The results of this study reveal that occurrence frequencies of the extreme cold night (TN10p) and extreme warm night (TN90p) have decreased and increased by −1.67 and 1.79 days/decade, respectively. Moreover, variations in temperature extremes have not been uniform with warming trends in minimum temperature being rapidly compared to maximum temperature extremes. The diurnal temperature range (DTR) depicted a remarkable decrease as a result of rapid warming in the minimum temperature. Warming in the region led to a reduction in the number of frost days (FD) and icing days (ID) and an increase in the number of growing season length (GSL) and tropical nights (Tr). Seasonally, TN10p largely decreased in winter and spring, while TNn and TN90p largely increased in winter and summer, respectively. Spatially, most of the stations with a significant warming trend in minimum temperatures were located in the Changbai Mountain, Greater Khingan Range, and Lesser Khingan Range. This implies that the mountainous regions are more sensitive and vulnerable to warming than the plain regions. On the contrary, most stations located in the Songnen Plain, Sanjiang Plain, and Liao River Plain displayed significant positive trend GSL and Tr. These climate extreme trends show that the region is experiencing warming which may have an impact on the hydrological process, ecological process, and agricultural production capacity.

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 489
Author(s):  
Jinxiu Liu ◽  
Weihao Shen ◽  
Yaqian He

India has experienced extensive land cover and land use change (LCLUC). However, there is still limited empirical research regarding the impact of LCLUC on climate extremes in India. Here, we applied statistical methods to assess how cropland expansion has influenced temperature extremes in India from 1982 to 2015 using a new land cover and land use dataset and ECMWF Reanalysis V5 (ERA5) climate data. Our results show that during the last 34 years, croplands in western India increased by ~33.7 percentage points. This cropland expansion shows a significantly negative impact on the maxima of daily maximum temperature (TXx), while its impacts on the maxima of daily minimum temperature and the minima of daily maximum and minimum temperature are limited. It is estimated that if cropland expansion had not taken place in western India over the 1982 to 2015 period, TXx would likely have increased by 0.74 (±0.64) °C. The negative impact of croplands on reducing the TXx extreme is likely due to evaporative cooling from intensified evapotranspiration associated with croplands, resulting in increased latent heat flux and decreased sensible heat flux. This study underscores the important influences of cropland expansion on temperature extremes and can be applicable to other geographic regions experiencing LCLUC.


2020 ◽  
Vol 12 (9) ◽  
pp. 1485
Author(s):  
Haoyang Yu ◽  
Wenjian Ni ◽  
Zhongjun Zhang ◽  
Guoqing Sun ◽  
Zhiyu Zhang

Sentinel-1 provides an extraordinary opportunity to explore the temporal behavior of backscattering of C-band synthetic aperture radar (SAR) due to its unique capability of successive observations every 12 days. This study reported new findings on the critical temporal features of Sentinel-1 backscattering over mountainous forested areas in northeast China and their application in regional forest mapping. Two interesting phenomena were discovered through the analysis of 450 scenes of images acquired by Sentinel-1A or Sentinel-1B over an area of 318,898.62 km2. The first phenomenon was that the dates of the largest drops of backscattering coefficients over forest and non-forest plots were different during the transition from autumn to winter. The largest drop of non-forest plots occurred around the date of the minimum temperature decreasing below 0 °C, while that of forest plots occurred around the date of the maximum temperature decreasing below 0 °C. The second phenomenon was that at the dates where these two drops occurred, the magnitude of the drop was negatively correlated with the forest canopy coverage for the first date and positively correlated for the second date. Based on these two phenomena, two methods for the forest mapping, referred to as the direct method and the indirect method, were proposed using only three dates of Sentinel-1 images, i.e., Date1: before the minimum temperature decreased below 0 °C, Date2: after the minimum temperature decreased below 0 °C but before the maximum temperature decreased below 0 °C, and Date3: after the maximum temperature decreased below 0 °C. The results showed that the overall accuracy of the forest map produced by the direct method was 93.60%, while that by the indirect method was 93.80%. Their accuracies were comparable with those of forest maps derived from publicly released land cover maps, which was approximately 94.42% for the best one. This study proposed a new way to do large-scale forest mapping in annually frozen regions using as few Sentinel-1 SAR images as possible.


Author(s):  
Elizangela Selma da Silva ◽  
José Holanda Campelo Júnior ◽  
Francisco De Almeida Lobo ◽  
Ricardo Santos Silva Amorim

The homogeneity investigation of a series can be performed through several nonparametric statistical tests, which serve to detect artificial changes or non-homogeneities in climatic variables. The objective of this work was to evaluate two methodologies to verify the homogeneity of the historical climatological series of precipitation and temperature in Mato Grosso state. The series homogeneity evaluation was performed using the following non-parametric tests: Wald-Wolfowitz (for series with one or no interruption), Kruskal-Wallis (for series with two or more interruptions), and Mann-Kendall (for time series trend analysis). The results of the precipitation series homogeneity analysis from the National Waters Agency stations, analyzed by the Kruskal-Wallis and Wald-Wolfowitz tests, presented 61.54% of homogeneous stations, being well distributed throughout Mato Grosso state, whereas those of the trend analysis allowed to identify that 87.57% of the rainfall-gauging stations showed a concentrated positive trend, mainly in the rainy season. Out of the conventional stations of the National Institute of Meteorology of Mato Grosso, seven were homogeneous for the precipitation variable, five for maximum temperature and four stations were homogeneous for minimum temperature. For the trend analysis in the 11 stations, positive trends of random nature were observed, suggesting increasing alterations in the analyzed variables. Therefore, the trend analysis performed by the Mann-Kendall test in the precipitation, and maximum and minimum temperature climate series, indicated that several data series showed increasing trends, suggesting a possible increase in precipitation and temperature values over the years. The results of the Kruskal-Wallis and Wald-Wolfowitz tests for homogeneity presented more than 87% of homogeneous stations.


2011 ◽  
Vol 11 (9) ◽  
pp. 2583-2603 ◽  
Author(s):  
A. El Kenawy ◽  
J. I. López-Moreno ◽  
S. M. Vicente-Serrano

Abstract. Spatial and temporal characteristics of extreme temperature events in northeastern Spain have been investigated. The analysis is based on long-term, high-quality, and homogenous daily maximum and minimum temperature of 128 observatories spanning the period from 1960 to 2006. A total of 21 indices were used to assess changes in both the cold and hot tails of the daily temperature distributions. The presence of trends in temperature extremes was assessed by means of the Mann-Kendall test. However, the autocorrelation function (ACF) and a bootstrap methodology were used to account for the influence of serial correlation and cross-correlation on the trend assessment. In general, the observed changes are more prevalent in hot extremes than in cold extremes. This finding can largely be linked to the increase found in the mean maximum temperature during the last few decades. The results indicate a significant increase in the frequency and intensity of most of the hot temperature extremes. An increase in warm nights (TN90p: 3.3 days decade−1), warm days (TX90p: 2.7 days decade−1), tropical nights (TR20: 0.6 days decade−1) and the annual high maximum temperature (TXx: 0.27 °C decade−1) was detected in the 47-yr period. In contrast, most of the indices related to cold temperature extremes (e.g. cold days (TX10p), cold nights (TN10p), very cold days (TN1p), and frost days (FD0)) demonstrated a decreasing but statistically insignificant trend. Although there is no evidence of a long-term trend in cold extremes, significant interdecadal variations were noted. Almost no significant trends in temperature variability indices (e.g. diurnal temperature range (DTR) and growing season length (GSL)) are detected. Spatially, the coastal areas along the Mediterranean Sea and the Cantabrian Sea experienced stronger warming compared with mainland areas. Given that only few earlier studies analyzed observed changes in temperature extremes at fine spatial resolution across the Iberian Peninsula, the results of this work can improve our understanding of climatology of temperature extremes. Also, these findings can have different hydrological, ecological and agricultural implications (e.g. crop yields, energy consumption, land use planning and water resources management).


2008 ◽  
Vol 21 (21) ◽  
pp. 5455-5467 ◽  
Author(s):  
Matilde Rusticucci ◽  
Bárbara Tencer

Abstract Extreme temperature events are one of the most studied extreme events since their occurrence has a huge impact on society. In this study, the frequency of occurrence of absolute extreme temperature events in Argentina is analyzed. Four annual extremes are defined based on minimum and maximum daily data: the highest maximum (minimum) temperature of the year, and the lowest maximum (minimum) temperature of the year. Applying the extreme value theory (EVT), a generalized extreme value (GEV) distribution is fitted to these extreme indices and return values are calculated for the period 1956–2003. Its spatial distribution indicates that, for warm extremes, maximum temperature (Tx) is expected to be greater than 32°C at least once every 100 yr throughout the country (reaching values even higher than 46°C in the central region), while minimum temperature (Tn) is expected to exceed 16°C (reaching 30°C in the central and northern regions). Cold annual extremes show larger gradients across the country, with Tx being lower than 8°C at least once every 100 yr, and Tn lower than 0°C every 2 yr, with values even less than −10°C in the southwestern part of the country. However, the frequency of occurrence of climatic extremes has changed throughout the globe during the twentieth century. Changes in return values of annual temperature extremes due to the 1976–77 climatic shift at six long-term datasets are then analyzed. The lowest Tx of the year is the variable in which the 1976–77 shift is less noticeable. At all the stations studied there is a decrease in the probability of occurrence of the highest Tx if the study is based on more recent records, while the frequency of occurrence of the highest Tn increases at some stations and decreases at others. This implies that in the “present climate” (after 1977) there is a greater frequency of occurrence of high values of Tn at Observatorio Central Buenos Aires and Río Gallegos together with a lower frequency of occurrence of high values of Tx, leading to a decrease in the annual temperature range. The most noticeable change in return values due to the 1976–77 shift is seen in Patagonia where the 10-yr return value for the highest Tn increases from 13.7°C before 1976 to 18.6°C after 1977. That is, values of the highest Tn that occurred at least once every 10 yr in the “past climate” (before 1976) now happened more than once every 2 yr.


2020 ◽  
Vol 2020 ◽  
pp. 1-21 ◽  
Author(s):  
Mansour Almazroui

Climate change is posing severe threats to human health through its impacts on food, water supply, and weather. Saudi Arabia has frequently experienced record-breaking climate extremes over the last decade, which have had adverse socioeconomic effects on many sectors of the country. The present study explores the changes in average temperature and temperature extremes over Saudi Arabia using an updated daily temperature dataset for the period 1978–2019. Also, changes in frequency and percentile trends of extreme events, as well as in absolute threshold-based temperature extremes, are analyzed at seasonal and annual time scales. The results are robust in showing an increase in both temperature trends and temperature extremes averaged over the second period (2000–2019) when compared to the first period (1980–1999). Over the period 1978–2019, the minimum temperature for the country increased (0.64°C per decade) at a higher rate than the maximum temperature (0.60°C per decade). The rate of increase in the minimum and maximum temperatures was reported as 0.48 and 0.71°C per decade, respectively, for the period 1978–2009. The minimum temperature increased by 0.81°C per decade for the second period compared to an increase of 0.47°C per decade for the first period. The significant increase in minimum temperature has resulted in a decreasing linear trend in the diurnal temperature range over recent decades. The maximum (minimum) temperature increased at a higher rate for Jan-Mar (Jun-Nov) with the highest increase of 0.82 (0.89)°C per decade occurring in March (August). The analysis shows a substantial increase (decrease) in the number of warm (cold) days/nights over the second period compared to the first period. The number of warm days (nights) significantly increased by about 13 (21) days per decade, and there is a significant decrease of about 11 (13) days per decade of cold days (nights). The seasonal analysis shows that this increase in warm days/nights is enhanced in boreal summer, with a reduction in the number of cold days/nights in winter. These results indicate that the warming climate of Saudi Arabia is accelerating in recent decades, which may have severe socioeconomic repercussions in many sectors of the country.


2013 ◽  
Vol 8 (1-2) ◽  
pp. 49-54
Author(s):  
Saon Banerjee ◽  
Asis Mukherj ◽  
Apurba Mukhopadhayal ◽  
B Saikia ◽  
S Bandyaopadhaya ◽  
...  

Maximum temperature, minimum temperature and rainfall data of Bankura (1992-2007) and Canning (1960-2006) were analyzed for assessing climatic trend and agro-climatic characterization of red-lateritic and coastal Zones of West Bengal respectively. These two zones are the most vulnerable regions to climate change in West Bengal, hence selected for the present study. While average values of annual maximum temperature and annual minimum temperature were used for climatic trend analysis, no definite trend was observed. So, maximum temperature of the hottest month and minimum temperature of the coldest month were used for detecting climatic trend. The maximum temperature shows positive trend for both the stations. An increasing trend of annual rainfall was also observed. In case of agro-climatic characterization the agricultural draught, meteorological draught, seasonal rainfall and rainfall probability using Markov-chain model were analyzed for the said two stations. Kharif crops of Bankura encountered two years (2000 & 2005) agricultural draught within 2000 -2007, whereas kharif crops of Canning encountered agricultural draught in 2006 within the said period. Likewise, the deviation of seasonal rainfall and probability of two consecutive wet weeks with different levels (10, 20,30,40,50 and 60 mm) of weekly total rainfall was worked out. DOI: http://dx.doi.org/10.3329/jsf.v8i1-2.14619 J. Sci. Foundation, 8(1&2): 49-54, June-December 2010


Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 477 ◽  
Author(s):  
Kyu Kyu Sein ◽  
Amnat Chidthaisong ◽  
and Kyaw Lwin Oo

Projected increase in frequency and severity of extreme events are important threat brought by climate change. Thus, there is a need to understand the dynamics and magnitude of climate extreme at local and regional level. This study examines the patterns of annual trends and changes of extreme daily temperature and precipitation in Myanmar for the period of 1981 to 2015 using the RClimDex 1.1 software. The trends of maximum and minimum temperature show significant warming trends (p < 0.001) across Myanmar. From 2009 to 2015, the maximum temperature anomaly has continuously increased by 0.5 °C for all years except 2011. The larger rise in both maximum and minimum temperature observed after 2000 suggests that, overall, days and nights are becoming hotter for the entirety of Myanmar over this recent period. Furthermore, our works also show that the temperature extreme indices of warm days and warm nights have increased, whereas the frequency of cool days and cool nights have decreased. Our analysis also reveals that increasing trends in precipitation anomaly were not significant during 1981–2015. On the contrary, slight increasing trends towards wetter conditions were observed with a rate of 76.52 mm/decade during the study period. The other precipitation extreme indicators—namely, annual total precipitation (PRCPTOT), heavy precipitation days (R20mm), extreme wet days precipitation (R99p), and consecutive wet days (CWD)—are consistent with warming trends. Additionally, the relationship between inter-annual variability in the climate extremes indices and Oceanic Niño Index (ONI) patterns was also examined with a focus on the influence of the El Niño-Southern Oscillation (ENSO) phenomenon.


Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1076 ◽  
Author(s):  
Yang Liu ◽  
Xiu Geng ◽  
Zhixin Hao ◽  
Jingyun Zheng

Changes in climate extremes under 1.5 °C and 2 °C global warming may impact agricultural production across Central Asia. We used the simulated daily data of average temperature, maximum temperature, minimum temperature, and precipitation provided by the Inter-Sectoral Impact Model Intercomparison Project and analyzed the current climate status and future projected changes of a set of climate extreme indices related to agricultural production under 1.5 °C and 2 °C global warming. In addition, the possible impacts of climate change on agricultural production in Central Asia were discussed. The results show that the annual mean temperature in Central Asia will increase by 1.48 °C and 2.34 °C at 1.5 °C and 2 °C warming levels, respectively, compared to the base period (1986–2005), and the increasing trends are significant at the α = 0.01 level for all grids. The number of warm days and growing season length will increase. Under the 1.5 °C scenario, the mean annual total precipitation (PRCPTOT) and heavy precipitation (R95P) will experience increases of 7.68% and 26.55%, respectively, and the consecutive dry days (CDD) will be reduced by 1.1 days. However, the standardized precipitation evapotranspiration index (SPEI) shows significant drought conditions in most of Central Asia (more than 60%). Under the 2 °C scenario, there will be a 3.89% increase in PRCPTOT and a 24.78% increase in R95P. Nevertheless, accompanying the increase in CDD (0.8 day) and the decrease in SPEI, drought conditions will be further exacerbated. These results indicate that Central Asia is likely to face more severe ecological problems in the future, which will threaten the regional agricultural production and the food security. Therefore, adaptation strategies should be implemented immediately to mitigate the negative impacts of climate change on Central Asia’s agriculture.


2021 ◽  
Vol 13 (5) ◽  
pp. 913
Author(s):  
Hua Liu ◽  
Xuejian Li ◽  
Fangjie Mao ◽  
Meng Zhang ◽  
Di’en Zhu ◽  
...  

The subtropical vegetation plays an important role in maintaining the structure and function of global ecosystems, and its contribution to the global carbon balance are receiving increasing attention. The fractional vegetation cover (FVC) as an important indicator for monitoring environment change, is widely used to analyze the spatiotemporal pattern of regional and even global vegetation. China is an important distribution area of subtropical vegetation. Therefore, we first used the dimidiate pixel model to extract the subtropical FVC of China during 2001–2018 based on MODIS land surface reflectance data, and then used the linear regression analysis and the variation coefficient to explore its spatiotemporal variations characteristics. Finally, the partial correlation analysis and the partial derivative model were used to analyze the influences and contributions of climate factors on FVC, respectively. The results showed that (1) the subtropical FVC had obvious spatiotemporal heterogeneity; the FVC high-coverage and medium-coverage zones were concentratedly and their combined area accounted for more than 70% of the total study area. (2) The interannual variation in the average subtropical FVC from 2001 to 2018 showed a significant growth trend. (3) In 76.28% of the study area, the regional FVC showed an increasing trend, and the remaining regional FVC showed a decreasing trend. However, the overall fluctuations in the FVC (increasing or decreasing) in the region were relatively stable. (4) The influences of climate factors to the FVC exhibited obvious spatial differences. More than half of all pixels exhibited the influence of the average annual minimum temperature and the annual precipitation had positive on FVC, while the average annual maximum temperature had negative on FVC. (5) The contributions of climate changes to FVC had obvious heterogeneity, and the average annual minimum temperature was the main contribution factor affecting the dynamic variations of FVC.


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