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 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 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 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 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.

scholarly journals Contrasting Evolution Patterns of Endorheic and Exorheic Lakes on the Central Tibetan Plateau and Climate Cause Analysis during 1988–2017

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1962
Author(s):  
Zhilong Zhao ◽  
Yue Zhang ◽  
Zengzeng Hu ◽  
Xuanhua Nie
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Climatic Factors ◽  
Global Climate ◽  
Rapid Expansion ◽  
Annual Precipitation ◽  
The Tibetan Plateau ◽  
Lake Area ◽  
Climate Change Research ◽  
Mean Temperature

The alpine lakes on the Tibetan Plateau (TP) are indicators of climate change. The assessment of lake dynamics on the TP is an important component of global climate change research. With a focus on lakes in the 33° N zone of the central TP, this study investigates the temporal evolution patterns of the lake areas of different types of lakes, i.e., non-glacier-fed endorheic lakes and non-glacier-fed exorheic lakes, during 1988–2017, and examines their relationship with changes in climatic factors. From 1988 to 2017, two endorheic lakes (Lake Yagenco and Lake Zhamcomaqiong) in the study area expanded significantly, i.e., by more than 50%. Over the same period, two exorheic lakes within the study area also exhibited spatio-temporal variability: Lake Gaeencuonama increased by 5.48%, and the change in Lake Zhamuco was not significant. The 2000s was a period of rapid expansion of both the closed lakes (endorheic lakes) and open lakes (exorheic lakes) in the study area. However, the endorheic lakes maintained the increase in lake area after the period of rapid expansion, while the exorheic lakes decreased after significant expansion. During 1988–2017, the annual mean temperature significantly increased at a rate of 0.04 °C/a, while the annual precipitation slightly increased at a rate of 2.23 mm/a. Furthermore, the annual precipitation significantly increased at a rate of 14.28 mm/a during 1995–2008. The results of this study demonstrate that the change in precipitation was responsible for the observed changes in the lake areas of the two exorheic lakes within the study area, while the changes in the lake areas of the two endorheic lakes were more sensitive to the annual mean temperature between 1988 and 2017. Given the importance of lakes to the TP, these are not trivial issues, and we now need accelerated research based on long-term and continuous remote sensing data.

Twitter Users’ Displays of Affect in the Global Warming Debate

2021 ◽  
pp. 004728162110078
Author(s):  
Shanna Cameron ◽  
Alexandra Russell ◽  
Luke Brake ◽  
Katherine Fredlund ◽  
Angela Morris
Keyword(s):  
Climate Change ◽  
Social Media ◽  
Global Warming ◽  
Content Analysis ◽  
Technical Communication ◽  
Research Team ◽  
Future Research ◽  
Climate Change Research ◽  
Quantitative Content ◽  
Twitter Users

This article engages with recent discussions in the field of technical communication that call for climate change research that moves beyond the believer/denier dichotomy. For this study, our research team coded 900 tweets about climate change and global warming for different emotions in order to understand how Twitter users rely on affect rhetorically. Our findings use quantitative content analysis to challenge current assumptions about writing and affect on social media, and our results indicate a number of arenas for future research on affect, global warming, and rhetoric.

scholarly journals Shared socioeconomic pathways for climate change research in Finland: co-developing extended SSP narratives for agriculture

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Heikki S. Lehtonen ◽  
Jyrki Aakkula ◽  
Stefan Fronzek ◽  
Janne Helin ◽  
Mikael Hildén ◽  
...  
Keyword(s):  
Climate Change ◽  
National Level ◽  
Global Scale ◽  
Change Scenario ◽  
Policy Makers ◽  
Climate Change Research ◽  
Food And Agriculture ◽  
Agriculture And Food ◽  
Farm Subsidies

AbstractShared socioeconomic pathways (SSPs), developed at global scale, comprise narrative descriptions and quantifications of future world developments that are intended for climate change scenario analysis. However, their extension to national and regional scales can be challenging. Here, we present SSP narratives co-developed with stakeholders for the agriculture and food sector in Finland. These are derived from intensive discussions at a workshop attended by approximately 39 participants offering a range of sectoral perspectives. Using general background descriptions of the SSPs for Europe, facilitated discussions were held in parallel for each of four SSPs reflecting very different contexts for the development of the sector up to 2050 and beyond. Discussions focused on five themes from the perspectives of consumers, producers and policy-makers, included a joint final session and allowed for post-workshop feedback. Results reflect careful sector-based, national-level interpretations of the global SSPs from which we have constructed consensus narratives. Our results also show important critical remarks and minority viewpoints. Interesting features of the Finnish narratives compared to the global SSP narratives include greater emphasis on environmental quality; significant land abandonment in SSPs with reduced livestock production and increased plant-based diets; continued need for some farm subsidies across all SSPs and opportunities for diversifying domestic production under scenarios of restricted trade. Our results can contribute to the development of more detailed national long-term scenarios for food and agriculture that are both relevant for local stakeholders and researchers as well as being consistent with global scenarios being applied internationally.

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