scholarly journals Grassland Phenology’s Sensitivity to Extreme Climate Indices in the Sichuan Province, Western China

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1650
Author(s):  
Benjamin Adu ◽  
Gexia Qin ◽  
Chunbin Li ◽  
Jing Wu
Keyword(s):  
Climate Change ◽  
Vegetation Type ◽  
Temporal Distribution ◽  
Sensitivity Coefficient ◽  
Scientific Basis ◽  
Sichuan Province ◽  
Western China ◽  
Climate Indices ◽  
Extreme Climate ◽  
Minimum Daily Temperature

Depending on the vegetation type, extreme climate and drought events have a greater impact on the end of the season (EOS) and start of the season (SOS). This study investigated the spatial and temporal distribution characteristics of grassland phenology and its responses to seasonal and extreme climate changes in Sichuan Province from 2001 to 2020. Based on the data from 38 meteorological stations in Sichuan Province, this study calculated the 15 extreme climate indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The results showed that SOS was concentrated in mid-March to mid-May (80–140 d), and 61.83% of the area showed a significant advancing trend, with a rate of 0–1.5 d/a. The EOS was concentrated between 270–330 d, from late September to late November, and 71.32% showed a delayed trend. SOS was strongly influenced by the diurnal temperature range (DTR), yearly maximum consecutive five-day precipitation (RX5), and the temperature vegetation dryness index (TVDI), while EOS was most influenced by the yearly minimum daily temperature (TNN), yearly mean temperature (TEMP_MEAN), and TVDI. The RX5 day index showed an overall positive sensitivity coefficient for SOS. TNN index showed a positive sensitivity coefficient for EOS. TVDI showed positive and negative sensitivities for SOS and EOS, respectively. This suggests that extreme climate change, if it causes an increase in vegetation SOS, may also cause an increase in vegetation EOS. This research can provide a scientific basis for developing regional vegetation restoration and disaster prediction strategies in Sichuan Province.

scholarly journals The Sensitivity of Vegetation Phenology to Extreme Climate Indices in the Loess Plateau, China

2021 ◽  
Vol 13 (14) ◽  
pp. 7623
Author(s):  
Tingting Pei ◽  
Zhenxia Ji ◽  
Ying Chen ◽  
Huawu Wu ◽  
Qingqing Hou ◽  
...  
Keyword(s):  
Loess Plateau ◽  
Growing Season ◽  
Sensitivity Coefficient ◽  
Scientific Basis ◽  
Maximum Temperature ◽  
Climate Indices ◽  
Vegetation Phenology ◽  
The Loess Plateau ◽  
Extreme Climate ◽  
Yearly Maximum

Climate changes, especially increased temperatures, and precipitation changes, have significant impacts on vegetation phenology. However, the response of vegetation phenology to the extreme climate in the Loess Plateau in Northwest China remains poorly quantified. The research described here analyzed the spatial change in vegetation phenology and the response of vegetation phenology to climate change in the Loess Plateau from 2001 to 2018, using data from seven extreme climate indices based on the ridge regression method. The results showed that extreme climate indexes, TNn (yearly minimum value of the daily minimum temperature), TXx (yearly maximum value of the daily maximum temperature), and RX5day (yearly maximum consecutive five-day precipitation) progressively increased from 2001 to 2018 in the Loess Plateau region, but decrease trend was found in DRT (diurnal temperature range). The start of the growing season (SOS) of vegetation gradually advanced with precipitation from northwest to southeast, and the rate was +0.38 d/a. The overall vegetation end of the growing season (EOS) was delayed, and the trend was −2.83 d/a. The sensitivity of the different vegetation phenology to different extreme weather indices showed obvious spatial differences, the sensitivity coefficient of SOS being mainly positive in the region, whereas the sensitivity coefficient of EOS was negative generally. More sensitivity was found in the EOS to extreme climate indexes than in the SOS. Forest, shrubland and grassland have similar responses to DRT and TNn; namely, both SOS and EOS are advanced with the increase in DRT and delayed with the increase in TNn (the sensitivity coefficient is quite different) but have different responses to RX5day and TXx. These results reveal that extreme climate events have a greater impact on vegetation EOS than on vegetation SOS, with these effects varying with vegetation types. This research can provide a scientific basis for formulating a scientific basis for regional vegetation restoration strategies and disaster prediction on the Loess Plateau.

scholarly journals Trends in Extreme Climate Indices in Cherrapunji for the period 1979 to 2020

2021 ◽  
Author(s):  
Raju Kalita ◽  
Dipangkar Kalita ◽  
Atul Saxena
Keyword(s):  
Climate Change ◽  
Negative Trend ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Trend Test ◽  
Climate Indices ◽  
Daily Maximum ◽  
Positive Trend ◽  
Extreme Climate

Abstract We have used Mann-Kendall trend test and Sen’s slope estimator method to find out significant changes in extreme climate indices for daily temperature as well as precipitation over the period 1979 to 2020 in Cherrapunji. In the present study, a total of 24 precipitation and temperature based extreme climate indices were calculated using RClimDex v 1.9-3. Among 24 indices, 7 were derived from number of days above nn mm rainfall (Rnn) according to Indian Meteorological Department (IMD) convention and the rest were in accordance with the Expert Team on Climate Change Detection and Indices (ETCCDI). It was observed that, among all the indices, consecutive dry days (CDD), summer days (SU25) and very light rainfall (VLR) days increased significantly with 0.54, 1.58 and 0.14 days/year respectively, while only consecutive wet days (CWD) decreased significantly with 0.36 days/year. A slight negative trend was also observed in case of tropical nights (TR20) and among the other precipitation indices as well. Again, the indices associated with daily maximum temperature increased significantly with annual change of 0.06 to 0.07 ⁰C/year. And for indices associated with daily minimum temperature, almost no change or a slight negative change was observed, except a significant positive trend in February and significant negative trend in November for TNN only. The analysis reveals that some of the extreme climate indices which explains the climatic conditions of Cherrapunji has changed a lot over the period of 42 years and if this trend continues then Cherrapunji will be under threat when it comes to climate change.

scholarly journals No changes in Northern Vietnam’s precipitation extremes during rainy season for the time period from 1975 to 2006

2018 ◽  
Vol 10 (2) ◽  
pp. 72-78
Author(s):  
Sebastian Goihl
Keyword(s):  
Climate Change ◽  
Climate Indices ◽  
Viet Nam ◽  
Climate Change Research ◽  
Extreme Climate ◽  
North East ◽  
Area Of Interest ◽  
Time Period ◽  
Geographical Regions ◽  
Rain Season

A consequence of Climate Change may be higher frequencies and intensities of extreme climate events all over the world. This paper takes a closer look on the Northern Vietnam climate conditions. The area of interest are the geographical regions North East, North West, Red River Delta and North Central Coast. For research extreme climate, the data from 72 meteorological stations for the time period 1975 to 2006 were used and tested for the rain season with the highly recommended method of indices for climate change research after ETCCDI. It is said, that there is a linkage between the indices and topics of social and economical impacts, but this is not a clear fact. The climate change and extreme precipitation indices R95p, R99p, SDII, PRCPTOT and a modified R50mm are used in this study. The question, if there are statistic significant trends is answered by the Mann-Kendall Trend test. The results show, that the indices are strongly influenced by the variations of the Vietnamese climate. Many stations have no significant trends. For the investigated time period, most of significance trends were decreasing. But there is a positive correlation between the total rain sum at rain season PRCPTOT and the extreme climate indices R95p and R99p, so more extreme climate intensities can be expect in a changing climate, because climate models show, that higher precipitations totals are probably for the area of interest. Biến đổi khí hậu có thể dẫn đến sự gia tăng về tần số và cường độ của các hiện tượng thời tiết cực đoan trên toàn thế giới. Nghiên cứu này sẽ xem xét kỹ hơn về các điều kiện khí hậu ở miền Bắc Việt Nam. Địa điểm nghiên cứu bao gồm các khu vực địa lý Đông Bắc, Tây Bắc, Đồng bằng sông Hồng và Bắc Trung Bộ. Để nghiên cứu về khí hậu cực đoan, các dữ liệu trong khoảng thời gian từ 1975 đến 2006 đã được thu thập từ 72 trạm khí tượng. Những dữ liệu này được dùng để kiểm chứng đối với mùa mưa theo phương pháp chỉ số nghiên cứu biến đổi khí hậu của Nhóm chuyên gia về phát hiện biến đổi khí hậu (ETCCCDI). Hiển nhiên có một mối liên hệ giữa các chỉ số với các chủ đề về tác động kinh tế và xã hội, tuy nhiên thực tế này vẫn chưa rõ ràng. Các chỉ số biến đổi khí hậu và mưa cực đoan của tổng mưa hằng năm trên 95 phần trăm (R95p), tổng mưa hằng năm trên 99 phần trăm (R99p), chỉ số cường độ mưa trên ngày (SDII), tổng mưa hằng năm vào những ngày ẩm ướt – mùa mưa (PRCPTOT) và tổng mưa hằng năm biến đổi trên 50mm (R50mm) được sử dụng trong nghiên cứu này. Câu hỏi về sự tồn tại của các xu hướng quan trọng về mặt thống kê được trả lời bằng phương pháp Mann-Kendall Trend. Các kết quả chỉ ra rằng các chỉ số chịu ảnh hưởng lớn từ sự biến đổi của khí hậu Việt Nam. Do vậy, ở một số trạm khí tượng không có các xu hướng có ý nghĩa. Trong khoảng thời gian nghiên cứu, các xu hướng quan trọng đều giảm. Tuy nhiên, có một mối tương quan thuận giữa tổng lượng mưa trong mùa mưa (PRCPTOT) và cường độ của các hiện tượng thời tiết cực đoan trên các cực của chỉ số từ R95P và R99p. Kết luận, các mô hình thời tiết cho thấy tổng lượng mưa lớn hơn có khả năng sẽ xảy ra trên địa bàn nghiên cứu. Vì vậy, có thể phỏng đoán rằng khi thay đổi khí hậu, sẽ diễn ra nhiều hiện tượng thời tiết cực đoan với cường độ cao.​

scholarly journals Spatial and Temporal Variability in Positive Degree Day in Western China under Climate Change

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 443
Author(s):  
Guohua Liu ◽  
Rensheng Chen ◽  
Xiqiang Wang
Keyword(s):  
Climate Change ◽  
Warm Season ◽  
Temporal Distribution ◽  
Cold Season ◽  
Western China ◽  
Spatial And Temporal Variability ◽  
Positive Temperature ◽  
Degree Day ◽  
Positive Degree ◽  
North East

Positive degree day (PDD) indicates the accumulated positive temperature in a given time period; it directly relates to the melting of snow and ice, and it is a key parameter between global warming and cryosphere changes. In this study, we calculated the PDD based on the daily mean temperatures from1960 to 2018 at meteorological stations, and we used measured and interpolated data to determine spatial and temporal distribution and changes in PDD in western China (WC). Results show that the mean annual, warm season, and cold season PDD values at 209 meteorological stations were 3652.2, 2832.9, and 819.3 °C, respectively. PDD spatial distribution in WC is similar to that of air temperature. In WC, PDD mainly ranged from 0 to 5000, 1000 to 4000, and 0 to 1000 °C year−1, respectively for annual, warm season, and cold season. From 1960 to 2018, the observed mean initial day of PDD moved forward by 8.3 days, and the final day was delayed by 8.2 days, with the duration expanding to 16.6 days; the trend in PDD reversed in the 1980s and the change rate in PDD for annual, warm season and cold season was 6.6, 3.8, and 2.7 °C year−1 higher, respectively. Regionally, PDD increased in almost all areas; the high PDD advanced from south to north, east to west, desert to mountain, and low to high altitudes. The results also showed that the warming rate of PDD was lower in the cold season and in high-altitude areas, which was opposite to the observed temperature patterns, however, the non-linear relationship between PDD and mean temperature over a period of time is the main reason for this phenomenon. This study adds more details for the understanding of climate change in WC, and suggests that more attention should be paid to PDD in the study of cryosphere changes.

scholarly journals Characterization of the variability in climate extremes in the Ferkessédougou sugar complexes (Northern Côte d'Ivoire)

2021 ◽  
Vol 384 ◽  
pp. 203-211
Author(s):  
Affoué Berthe Yao ◽  
Sampah Georges Eblin ◽  
Loukou Alexis Brou ◽  
Kouakou Lazare Kouassi ◽  
Gla Blaise Ouede ◽  
...  
Keyword(s):  
Climate Change ◽  
Methodological Approach ◽  
Extreme Temperature ◽  
Daily Rainfall ◽  
Climate Extremes ◽  
Climate Indices ◽  
Intense Rainfall ◽  
Adaptation To Climate Change ◽  
Average Decrease ◽  
Extreme Climate

Abstract. This study aims to analyse the frequency, intensity and duration of extreme climate events in order to optimise sugarcane production in the Ferkessédougou sugar complexes. The methodological approach is based on the calculation of extreme climate indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) from daily rainfall and temperature data observed at the Ferké 2 station over the period 1999–2018. The results show that the rainfall indices are negative, except for the number of consecutive dry days (CDD); this shows a decreasing trend in rainfall with, however, insignificant trends. Over the period 1999–2006, the number of intense rainfall days (R10 mm) decreased from 40 to 28 d with an average decrease of 0.3 d yr−1 and the number of very intense rainfall days (R20 mm) fluctuated between 26 and 2 d, with a slope of 0.083. The extreme temperature indices show statistically significant positive trends for the warm sequences; this confirms the rising of temperatures on both a local and national scale. This study could enable the Ferkessédougou sugar complexes managers to develop strategies for adaptation to climate change.

scholarly journals Evaluating the impact of climate change on extreme temperature and precipitation events over the Kashmir Himalaya

2021 ◽  
Author(s):  
Shafkat Ahsan ◽  
M. Sultan Bhat ◽  
Akhtar Alam ◽  
Hakim Farooq ◽  
Hilal Ahmad Shiekh
Keyword(s):  
Climate Change ◽  
Extreme Temperature ◽  
Climate Indices ◽  
General Tendency ◽  
Kashmir Himalaya ◽  
Impact Of Climate Change ◽  
Extreme Climate ◽  
Temperature And Precipitation ◽  
The Future ◽  
The Impact

AbstractThe frequency and severity of climatic extremes is expected to escalate in the future primarily because of the increasing greenhouse gas concentrations in the atmosphere. This study aims to assess the impact of climate change on the extreme temperature and precipitation scenarios using climate indices in the Kashmir Himalaya. The analysis has been carried out for the twenty-first century under different representative concentration pathways (RCPs) through the Statistical Downscaling Model (SDSM) and ClimPACT2. The simulation reveals that the climate in the region will get progressively warmer in the future by increments of 0.36–1.48 °C and 0.65–1.07 °C in mean maximum and minimum temperatures respectively, during 2080s (2071–2100) relative to 1980–2010 under RCP8.5. The annual precipitation is likely to decrease by a maximum of 2.09–6.61% (2080s) under RCP8.5. The seasonal distribution of precipitation is expected to alter significantly with winter, spring, and summer seasons marking reductions of 9%, 5.7%, and 1.7%, respectively during 2080s under RCP8.5. The results of extreme climate evaluation show significant increasing trends for warm temperature-based indices and decreasing trends for cold temperature-based indices. Precipitation indices on the other hand show weaker and spatially incoherent trends with a general tendency towards dry regimes. The projected scenarios of extreme climate indices may result in large-scale adverse impacts on the environment and ecological resource base of the Kashmir Himalaya.

scholarly journals Multiscale Spatiotemporal Analysis of Extreme Events in the Gomati River Basin, India

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 480
Author(s):  
AVS Kalyan ◽  
Dillip Kumar Ghose ◽  
Rahul Thalagapu ◽  
Ravi Kumar Guntu ◽  
Ankit Agarwal ◽  
...  
Keyword(s):  
Climate Change ◽  
Power Spectrum ◽  
River Basin ◽  
Extreme Events ◽  
Univariate Analysis ◽  
Regional Scale ◽  
Climate Indices ◽  
Extreme Climate ◽  
Study Results ◽  
Gomati River

Accelerating climate change is causing considerable changes in extreme events, leading to immense socioeconomic loss of life and property. In this study, we investigate the characteristics of extreme climate events at a regional scale to -understand these events’ propagation in the near future. We have considered sixteen extreme climate indices defined by the World Meteorological Organization’s Expert Team on Climate Change Detection and Indices from a long-term dataset (1951–2018) of 53 locations in Gomati River Basin, North India. We computed the present and future spatial variation of theses indices using the Sen’s slope estimator and Hurst exponent analysis. The periodicities and non-stationary features were estimated using the continuous wavelet transform. Bivariate copulas were fitted to estimate the joint probabilities and return periods for certain combinations of indices. The study results show different variation in the patterns of the extreme climate indices: D95P, R95TOT, RX5D, and RX showed negative trends for all stations over the basin. The number of dry days (DD) showed positive trends over the basin at 36 stations out of those 17 stations are statistically significant. A sustainable decreasing trend is observed for D95P at all stations, indicating a reduction in precipitation in the future. DD exhibits a sustainable decreasing trend at almost all the stations over the basin barring a few exceptions highlight that the basin is turning drier. The wavelet power spectrum for D95P showed significant power distributed across the 2–16-year bands, and the two-year period was dominant in the global power spectrum around 1970–1990. One interesting finding is that a dominant two-year period in D95P has changed to the four years after 1984 and remains in the past two decades. The joint return period’s resulting values are more significant than values resulting from univariate analysis (R95TOT with 44% and RTWD of 1450 mm). The difference in values highlights that ignoring the mutual dependence can lead to an underestimation of extremes.

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