Variation characteristics of temperature and precipitation on the northern slopes of the Himalaya region from 1979 to 2018

2021 ◽  
Author(s):  
Yizhe Han ◽  
Yaoming Ma ◽  
Zhongyan Wang ◽  
Weiqiang Ma
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Temperature Increase ◽  
Southern Oscillation ◽  
Monsoon Season ◽  
Western Pacific Subtropical High ◽  
Warming Trend ◽  
Seasonal Temperature ◽  
Temperature And Precipitation ◽  
The World

<p>The northern slopes of Himalaya (NSH) have the highest average elevation in the world. It is difficult to assess how climate change has affected this region because only a few observations are available from the high terrain and harsh environment. This study investigates the long-term characteristics of temperature and precipitation in the NSH. Further, the association of these variations with atmospheric circulation patterns is also investigated. Our results indicated that the warming trend in this region is almost 1.5 times that of the TP region, 2 times that of China, and 3.5 times that of the world. Additionally, the warming rate of the NSH is more obvious than other regions in the Himalayas, which shows that different regions of the Himalayas have different sensitivity to climate change. Although the warming trend in the NSH region does not show obvious seasonal differences like the TP, the temperature increase rate in autumn and winter is still higher than that in spring and summer. The abrupt change point for the temperature increase in summer was about 5 years later than that in other seasons, indicating that the NSH region is more sensitive to climate warming in cooler seasons, which is similar to the western and northwestern Himalaya. Furthermore, the Southern Oscillation Index (SOI) displays significant relationships with the temperature in the NSH, meanwhile, the North Atlantic Oscillation index (NAO) and Western Pacific Subtropical High Intensity Index (WPI) also exist some correlations with seasonal temperature change. This indicating that the atmospheric circulation would also have affected the temperature increase in this region, especially in summer and winter. The changes in precipitation are only affected by the SOI during the monsoon season (June to September), indicating that ENSO influences precipitation changes through water vapor transmission. In contrast, the precipitation in the TP is correlated with NAO, SOI and WPI, which indicating the precipitation of the TP might be affected by multiple circulation systems.</p><p> </p><p> </p>

scholarly journals Detection of annual and seasonal temperature variability and change using non-parametric test- A case study of Bundelkhand region of central India

2021 ◽  
Vol 23 (4) ◽  
pp. 402-408
Author(s):  
SUCHIT K. RAI ◽  
SUNIL KUMAR ◽  
MANOJ CHAUDHARY
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Monsoon Season ◽  
Economic Status ◽  
Winter Season ◽  
Central India ◽  
Warming Trend ◽  
Temperature Variability ◽  
Seasonal Temperature ◽  
Economic Activities

Consequences of global warming and climate change are major threat to humans and their socio-economic activities. Agriculture of Bundelkhand region is supposed to be more vulnerable due to emerging scenario of climate change and poor socio-economic status of farming community. Many studies carried out elsewhere have shown evidence of regional temperature variability along with global climate changes. This study focuses on the temporal variability and trend in annual and seasonal temperature (1901-2012) at six locations of Bundelkhand region. The results of the analysis reveal that the annual maximum (TMax) and minimum (TMin) temperature has significantly increasing trend in all the locations in the range of 0.5 to 2.0oC 100 year-1 and 0.5 to 1.1 oC 100 year-1, respectively. Seasonal analysis revealed warming trend in both TMax (0.6-2.6oC100 year-1) and TMin (0.9 to 2.3 oC 100 year-1) during post-monsoon and winter season in all the locations. Majority of the locations showed cooling trend (0.3-1.0 oC 100 year-1), in the mean maximum and minimum temperature during monsoon season except at two locations i.e Jhansi and Banda. However, a significant positive trends (2.9 oC) in the TMin was found for the period of hundred years at Banda district during monsoon season.

scholarly journals Impact of Climate Change on Water Availability and Food Security of Nepal

2012 ◽  
pp. 59-63
Author(s):  
Roshan Kumar Mehta ◽  
Shree Chandra Shah
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Climatic Factors ◽  
Monsoon Season ◽  
Groundwater Table ◽  
Maximum Temperature ◽  
Aquatic Life ◽  
Temperature And Precipitation ◽  
Average Maximum ◽  
Water Scarce

The increase in the concentration of greenhouse gases (GHGs) in the atmosphere is widely believed to be causing climate change. It affects agriculture, forestry, human health, biodiversity, and snow cover and aquatic life. Changes in climatic factors like temperature, solar radiation and precipitation have potential to influence agrobiodiversity and its production. An average of 0.04°C/ year and 0.82 mm/year rise in annual average maximum temperature and precipitation respectively from 1975 to 2006 has been recorded in Nepal. Frequent droughts, rise in temperature, shortening of the monsoon season with high intensity rainfall, severe floods, landslides and mixed effects on agricultural biodiversity have been experienced in Nepal due to climatic changes. A survey done in the Chitwan District reveals that lowering of the groundwater table decreases production and that farmers are attracted to grow less water consuming crops during water scarce season. The groundwater table in the study area has lowered nearly one meter from that of 15 years ago as experienced by the farmers. Traditional varieties of rice have been replaced in the last 10 years by modern varieties, and by agricultural crops which demand more water for cultivation. The application of groundwater for irrigation has increased the cost of production and caused severe negative impacts on marginal crop production and agro-biodiversity. It is timely that suitable adaptive measures are identified in order to make Nepalese agriculture more resistant to the adverse impacts of climate change, especially those caused by erratic weather patterns such as the ones experienced recently.DOI: http://dx.doi.org/10.3126/hn.v11i1.7206 Hydro Nepal Special Issue: Conference Proceedings 2012 pp.59-63

scholarly journals Climate change and landscape-use patterns influence recent past distribution of giant pandas

2020 ◽  
Vol 287 (1929) ◽  
pp. 20200358
Author(s):  
Junfeng Tang ◽  
Ronald R. Swaisgood ◽  
Megan A. Owen ◽  
Xuzhe Zhao ◽  
Wei Wei ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climatic Factors ◽  
Ailuropoda Melanoleuca ◽  
Seasonal Temperature ◽  
Negative Consequences ◽  
Giant Pandas ◽  
Use Patterns ◽  
Changing Climate ◽  
Temperature And Precipitation

Climate change is one of the most pervasive threats to biodiversity globally, yet the influence of climate relative to other drivers of species depletion and range contraction remain difficult to disentangle. Here, we examine climatic and non-climatic correlates of giant panda ( Ailuropoda melanoleuca ) distribution using a large-scale 30 year dataset to evaluate whether a changing climate has already influenced panda distribution. We document several climatic patterns, including increasing temperatures, and alterations to seasonal temperature and precipitation. We found that while climatic factors were the most influential predictors of panda distribution, their importance diminished over time, while landscape variables have become relatively more influential. We conclude that the panda's distribution has been influenced by changing climate, but conservation intervention to manage habitat is working to increasingly offset these negative consequences.

scholarly journals Analyses of temperature and precipitation in the Indian Jammu and Kashmir region for the 1980–2016 period: implications for remote influence and extreme events

2019 ◽  
Vol 19 (1) ◽  
pp. 15-37 ◽  
Author(s):  
Sumira Nazir Zaz ◽  
Shakil Ahmad Romshoo ◽  
Ramkumar Thokuluwa Krishnamoorthy ◽  
Yesubabu Viswanadhapalli
Keyword(s):  
Climate Change ◽  
Statistical Tests ◽  
Wrf Model ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Seasonal Temperature ◽  
Western Himalayas ◽  
Jammu And Kashmir ◽  
Temperature And Precipitation ◽  
Average Annual Temperature

Abstract. The local weather and climate of the Himalayas are sensitive and interlinked with global-scale changes in climate, as the hydrology of this region is mainly governed by snow and glaciers. There are clear and strong indicators of climate change reported for the Himalayas, particularly the Jammu and Kashmir region situated in the western Himalayas. In this study, using observational data, detailed characteristics of long- and short-term as well as localized variations in temperature and precipitation are analyzed for these six meteorological stations, namely, Gulmarg, Pahalgam, Kokarnag, Qazigund, Kupwara and Srinagar during 1980–2016. All of these stations are located in Jammu and Kashmir, India. In addition to analysis of stations observations, we also utilized the dynamical downscaled simulations of WRF model and ERA-Interim (ERA-I) data for the study period. The annual and seasonal temperature and precipitation changes were analyzed by carrying out Mann–Kendall, linear regression, cumulative deviation and Student's t statistical tests. The results show an increase of 0.8 ∘C in average annual temperature over 37 years (from 1980 to 2016) with higher increase in maximum temperature (0.97 ∘C) compared to minimum temperature (0.76 ∘C). Analyses of annual mean temperature at all the stations reveal that the high-altitude stations of Pahalgam (1.13 ∘C) and Gulmarg (1.04 ∘C) exhibit a steep increase and statistically significant trends. The overall precipitation and temperature patterns in the valley show significant decreases and increases in the annual rainfall and temperature respectively. Seasonal analyses show significant increasing trends in the winter and spring temperatures at all stations, with prominent decreases in spring precipitation. In the present study, the observed long-term trends in temperature (∘Cyear-1) and precipitation (mm year−1) along with their respective standard errors during 1980–2016 are as follows: (i) 0.05 (0.01) and −16.7 (6.3) for Gulmarg, (ii) 0.04 (0.01) and −6.6 (2.9) for Srinagar, (iii) 0.04 (0.01) and −0.69 (4.79) for Kokarnag, (iv) 0.04 (0.01) and −0.13 (3.95) for Pahalgam, (v) 0.034 (0.01) and −5.5 (3.6) for Kupwara, and (vi) 0.01 (0.01) and −7.96 (4.5) for Qazigund. The present study also reveals that variation in temperature and precipitation during winter (December–March) has a close association with the North Atlantic Oscillation (NAO). Further, the observed temperature data (monthly averaged data for 1980–2016) at all the stations show a good correlation of 0.86 with the results of WRF and therefore the model downscaled simulations are considered a valid scientific tool for the studies of climate change in this region. Though the correlation between WRF model and observed precipitation is significantly strong, the WRF model significantly underestimates the rainfall amount, which necessitates the need for the sensitivity study of the model using the various microphysical parameterization schemes. The potential vorticities in the upper troposphere are obtained from ERA-I over the Jammu and Kashmir region and indicate that the extreme weather event of September 2014 occurred due to breaking of intense atmospheric Rossby wave activity over Kashmir. As the wave could transport a large amount of water vapor from both the Bay of Bengal and Arabian Sea and dump them over the Kashmir region through wave breaking, it probably resulted in the historical devastating flooding of the whole Kashmir valley in the first week of September 2014. This was accompanied by extreme rainfall events measuring more than 620 mm in some parts of the Pir Panjal range in the south Kashmir.

scholarly journals Toward Assessing NARCCAP Regional Climate Model Credibility for the North American Monsoon: Future Climate Simulations*

2015 ◽  
Vol 28 (17) ◽  
pp. 6707-6728 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
Carlos M. Carrillo ◽  
David J. Gochis ◽  
Dorit M. Hammerling ◽  
Rachel R. McCrary ◽  
...  
Keyword(s):  
Climate Change ◽  
North American ◽  
Southern Oscillation ◽  
Monsoon Season ◽  
Regional Climate ◽  
Global Climate Models ◽  
North American Monsoon ◽  
The North ◽  
Climate Simulations ◽  
Projected Changes

Abstract This study presents climate change results from the North American Regional Climate Change Assessment Program (NARCCAP) suite of dynamically downscaled simulations for the North American monsoon system in the southwestern United States and northwestern Mexico. The focus is on changes in precipitation and the processes driving the projected changes from the regional climate simulations and their driving coupled atmosphere–ocean global climate models. The effect of known biases on the projections is also examined. Overall, there is strong ensemble agreement for a large decrease in precipitation during the monsoon season; however, this agreement and the magnitude of the ensemble-mean change is likely deceiving, as the greatest decreases are produced by the simulations that are the most biased in the baseline/current climate. Furthermore, some of the greatest decreases in precipitation are being driven by changes in processes/phenomena that are less credible (e.g., changes in El Niño–Southern Oscillation, when it is initially not simulated well). In other simulations, the processes driving the precipitation change may be plausible, but other biases (e.g., biases in low-level moisture or precipitation intensity) appear to be affecting the magnitude of the projected changes. The most and least credible simulations are clearly identified, while the other simulations are mixed in their abilities to produce projections of value.

scholarly journals The influence of atmospheric circulation on the mid-Holocene climate of Europe: a data–model comparison

2014 ◽  
Vol 10 (5) ◽  
pp. 1925-1938 ◽  
Author(s):  
A. Mauri ◽  
B. A. S. Davis ◽  
P. M. Collins ◽  
J. O. Kaplan
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Data Model ◽  
Atmospheric Dynamics ◽  
Future Climate Change ◽  
Seasonal Temperature ◽  
Holocene Climate ◽  
Model Simulations ◽  
Recent Climate

Abstract. The atmospheric circulation is a key area of uncertainty in climate model simulations of future climate change, especially in mid-latitude regions such as Europe where atmospheric dynamics have a significant role in climate variability. It has been proposed that the mid-Holocene was characterized in Europe by a stronger westerly circulation in winter comparable with a more positive AO/NAO, and a weaker westerly circulation in summer caused by anti-cyclonic blocking near Scandinavia. Model simulations indicate at best only a weakly positive AO/NAO, whilst changes in summer atmospheric circulation have not been widely investigated. Here we use a new pollen-based reconstruction of European mid-Holocene climate to investigate the role of atmospheric circulation in explaining the spatial pattern of seasonal temperature and precipitation anomalies. We find that the footprint of the anomalies is entirely consistent with those from modern analogue atmospheric circulation patterns associated with a strong westerly circulation in winter (positive AO/NAO) and a weak westerly circulation in summer associated with anti-cyclonic blocking (positive SCAND). We find little agreement between the reconstructed anomalies and those from 14 GCMs that performed mid-Holocene experiments as part of the PMIP3/CMIP5 project, which show a much greater sensitivity to top-of-the-atmosphere changes in solar insolation. Our findings are consistent with data–model comparisons on contemporary timescales that indicate that models underestimate the role of atmospheric circulation in recent climate change, whilst also highlighting the importance of atmospheric dynamics in explaining interglacial warming.

scholarly journals Climate Change and Implications for Agriculture Sector in Sindh Province of Pakistan

2020 ◽  
Vol 39 (3) ◽  
pp. 668-677
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Institutional Reforms ◽  
Adaptation Measures ◽  
Agriculture Sector ◽  
Temperature And Precipitation ◽  
Sindh Province ◽  
Average Annual Temperature ◽  
The World ◽  
Weather Changes

Pakistan is a highly vulnerable country in the world to climate change. It is ranked among the five most affected countries in the world. Sindh, among the provinces of Pakistan, is located in the southern part and it stands to suffer not only directly from local climatic and weather changes but also from the weather activities in the upstream Indus River and from the coastal environments. This study aims to examine the past trend and future projections of climate variables, assess the climate change impacts on agriculture sector, and recommend adaptation measures for Sindh. The results show that there is statistically significant trend in the temperature and precipitation in some parts of Sindh. The results from climate change projections show that the average annual temperature in Sindh by the end of 21st century may increase by 2 to 5 0C depending on various emission scenarios. Furthermore, the climate change in Sindh is likely to decrease productivity of agriculture and household income. The study recommends infrastructural development, technological change, institutional reforms, information sharing, and effective regulations to make agriculture sector and other related sectors resilient to climate change.

scholarly journals Do Farmers Adapt to Climate Change? A Macro Perspective

Agriculture ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 212 ◽  
Author(s):  
Shahzad Alvi ◽  
Faisal Jamil ◽  
Roberto Roson ◽  
Martina Sartori
Keyword(s):  
Climate Change ◽  
Agricultural Sector ◽  
Central Africa ◽  
Developed Countries ◽  
Temperature And Precipitation ◽  
Weather And Climate ◽  
The World ◽  
Potential Damage ◽  
Using Data ◽  
Cereal Yields

Greenhouse gas emissions cause climate change, and agriculture is the most vulnerable sector. Farmers do have some capability to adapt to changing weather and climate, but this capability is contingent on many factors, including geographical and socioeconomic conditions. Assessing the actual adaptation potential in the agricultural sector is therefore an empirical issue, to which this paper contributes by presenting a study examining the impacts of climate change on cereal yields in 55 developing and developed countries, using data from 1991 to 2015. The results indicate that cereal yields are affected in all regions by changes in temperature and precipitation, with significant differences in certain macro-regions in the world. In Southern Asia and Central Africa, farmers fail to adapt to climate change. The findings suggest that the world should focus more on enhancing adaptive capacity to moderate potential damage and on coping with the consequences of climate change.

scholarly journals Multidecadal ENSO Amplitude Variability in a 1000-yr Simulation of a Coupled Global Climate Model: Implications for Observed ENSO Variability

2013 ◽  
Vol 26 (23) ◽  
pp. 9399-9407 ◽  
Author(s):  
Simon Borlace ◽  
Wenju Cai ◽  
Agus Santoso
Keyword(s):  
Climate Change ◽  
Time Scales ◽  
Climate Model ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Model ◽  
Warming Trend ◽  
Recent Change ◽  
Climate Change Signal ◽  
Coupled Global Climate Model

The amplitude of the El Niño–Southern Oscillation (ENSO) can vary naturally over multidecadal time scales and can be influenced by climate change. However, determining the mechanism for this variation is difficult because of the paucity of observations over such long time scales. Using a 1000-yr integration of a coupled global climate model and a linear stability analysis, it is demonstrated that multidecadal modulation of ENSO amplitude can be driven by variations in the governing dynamics. In this model, the modulation is controlled by the underlying thermocline feedback mechanism, which in turn is governed by the response of the oceanic thermocline slope across the equatorial Pacific to changes in the overlying basinwide zonal winds. Furthermore, the episodic strengthening and weakening of this coupled interaction is shown to be linked to the slowly varying background climate. In comparison with the model statistics, the recent change of ENSO amplitude in observations appears to be still within the range of natural variability. This is despite the apparent warming trend in the mean climate. Hence, this study suggests that it may be difficult to infer a climate change signal from changes in ENSO amplitude alone, particularly given the presently limited observational data.

scholarly journals Does An ENSO-Conditional Skill Mask Improve Seasonal Predictions?

2013 ◽  
Vol 141 (12) ◽  
pp. 4515-4533 ◽  
Author(s):  
Kathy Pegion ◽  
Arun Kumar
Keyword(s):  
Southern Oscillation ◽  
Seasonal Temperature ◽  
Model Framework ◽  
Temperature And Precipitation ◽  
Skill Scores ◽  
Perfect Model ◽  
Optimal Weighting ◽  
Environmental Prediction ◽  
Model Context ◽  
Climate Prediction Center

Abstract The National Centers for Environmental Prediction Climate Prediction Center uses statistical tools together with the Climate Forecast System (CFS) to produce forecasts for seasonal outlooks of U.S. temperature and precipitation. They are combined using an optimal weighting procedure that depends on a skill mask consisting of the average historical forecast skill of each tool. However, it is likely that skill during El Niño–Southern Oscillation events is higher and the use of this information in developing forecasts could lead to improved seasonal predictions. This study explores the potential to improve the skill of seasonal predictions by developing an ENSO-conditional skill mask. The conditional masks are developed in a perfect-model framework using the CFS version 2 hindcasts and two indices of ENSO. The skill of the indices in forecasting variations in conditional skill is evaluated. The ENSO-conditional skill masks provide improvements in correlation skill over the unconditional mask when averaged over the globe. The masks are applied to tercile forecasts of seasonal temperature and precipitation during the spring and forecasts are verified in a perfect-model context. Application of the conditional masks to tercile forecasts results in modified Heidke skill scores of more than 10% less than using the average mask for temperature and little difference in skill for precipitation. This is attributed to the larger number of equal chances forecasts when using the conditional masks, particularly for temperature. For precipitation, the skill predicted by the average and conditional masks is frequently below 0.3, leading to low skill regardless of which mask is used.

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