scholarly journals Modeling of climate change in cold arid regions of north western Himalayas using multiple linear regression (MLR)

2021 ◽  
Vol 21 (4) ◽  
pp. 474-479
Author(s):  
Junaid N. Khan ◽  
Asima Jillani ◽  
Syed Rouhullah Ali ◽  
Zarka Rashid ◽  
Zikra Rehman ◽  
...  

The present study aimed at modeling the impacts of climate change on precipitation and temperature and its trend in the context of changing climate in cold arid regions of north western Himalayas using multiple linear regression (MLR) model. The study was carried out in three different time slices viz., near future (2017-2045), mid future (2046-2072) and far future (2073-2099). The study includes the calibration of the observed climate data (maximum temperature, minimum temperature and precipitation) for fourteen years (2002-2015) and the outputs of downscaled scenario A2 of the Global Climate Model (GCM) data of Hadley Centre Coupled Model, (HadCM3) was used for validation, for the future. Daily climate (maximum temperature, minimum temperature and precipitation) scenarios were generated from 1961 to 2099 under A2 defined by Intergovernmental Panel on Climate Change (IPCC). During calibration, the maximum temperature, minimum temperature and precipitation showed decreasing trend. During validation, the maximum temperature showed an increasing trend in near future (2017- 2045) and decreasing trend in mid (2046-2072) and far future (2073-2099). While as, the minimum temperature and precipitation showed an increasing trend and decreasing trend respectively, in three futuristic phases. After validation, on comparison with the measured data, the variation in maximum temperature was found -2.59 oC in near future, -3.17 oC in mid future and -3.41 oC in far future. Similarly, for minimum temperature and precipitation, the variations with observed data were found 0.91 oC and -32.2 mm, respectively in near future, 2.01 oC and -34.6 mm, respectively in mid future, 4.08 oC and -3.4 mm, respectively in far future. These changes may be found due to global warming which lead to decrease in average annual precipitation and increase in average minimum temperatures causing the melting of glaciers.

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1090 ◽  
Author(s):  
Saima Nauman ◽  
Zed Zulkafli ◽  
Abdul Halim Bin Ghazali ◽  
Badronnisa Yusuf

The study aims to evaluate the long-term changes in meteorological parameters and to quantify their impacts on water resources of the Haro River watershed located on the upstream side of Khanpur Dam in Pakistan. The climate data was obtained from the NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) for MIROC-ESM model under two Representative Concentration Pathway (RCP) scenarios. The model data was bias corrected and the performance of the bias correction was assessed statistically. Soil and Water Assessment Tool was used for the hydrological simulation of watershed followed by model calibration using Sequential Uncertainty Fitting version-2. The study is useful for devising strategies for future management of Khanpur Dam. The study indicated that in the future, at Murree station (P-1), the maximum temperature, minimum temperature and precipitation were anticipated to increase from 3.1 °C (RCP 4.5) to 4.0 °C (RCP 8.5), 3.2 °C (RCP 4.5) to 4.3 °C (RCP 8.5) and 8.6% to 13.5% respectively, in comparison to the baseline period. Similarly, at Islamabad station (P-2), the maximum temperature, minimum temperature and precipitation were projected to increase from 3.3 °C (RCP 4.5) to 4.1 °C (RCP 8.5), 3.3 °C (RCP 4.5) to 4.2 °C (RCP 8.5) and 14.0% to 21.2% respectively compared to baseline period. The streamflows at Haro River basin were expected to rise from 8.7 m3/s to 9.3 m3/s.


2019 ◽  
Vol 19 (1) ◽  
pp. 15-37 ◽  
Author(s):  
Sumira Nazir Zaz ◽  
Shakil Ahmad Romshoo ◽  
Ramkumar Thokuluwa Krishnamoorthy ◽  
Yesubabu Viswanadhapalli

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.


Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 973
Author(s):  
Azfar Hussain ◽  
Jianhua Cao ◽  
Ishtiaq Hussain ◽  
Saira Begum ◽  
Mobeen Akhtar ◽  
...  

Having an extreme topography and heterogeneous climate, the Upper Indus Basin (UIB) is more likely to be affected by climate change and it is a crucial area for climatological studies. Based on the monthly minimum temperature (Tmin), maximum temperature (Tmax) and precipitation from nine meteorological stations, the spatiotemporal variability of temperature and precipitation were analyzed on monthly, seasonal, and annual scales. Results show a widespread significant increasing trend of 0.14 °C/decade for Tmax, but a significant decreasing trend of −0.08 °C/decade for Tmin annually, during 1955–2016 for the UIB. Seasonally, warming in Tmax is stronger in winter and spring, while the cooling in Tmin is greater in summer and autumn. Results of seasonal Tmax indicate increasing trends in winter, spring and autumn at rates of 0.38, 0.35 and 0.05 °C/decade, respectively, while decreasing in summer with −0.14 °C/decade. Moreover, seasonal Tmin results indicate increasing trends in winter and spring at rates of 0.09 and 0.08 °C/decade, respectively, while decreasing significantly in summer and autumn at rates of −0.21 and −0.22 °C/decade respectively for the whole the UIB. Precipitation exhibits an increasing trend of 2.74 mm/decade annually, while, increasing in winter, summer and autumn at rates of 1.18, 2.06 and 0.62 mm/decade respectively. The warming in Tmax and an increase in precipitation have been more distinct since the mid-1990s, while the cooling in Tmin is observed in the UIB since the mid-1980s. Warming in the middle and higher altitude (1500–2800 m and >2800 m) are much stronger, and the increase is more obvious in regions with elevation >2800 m. The wavelet analysis illustrated sporadic inter-annual covariance of seasonal Tmax, Tmin and precipitation with ENSO, NAO, IOD and PDO in the UIB. The periodicities were usually constant over short timescales and discontinuous over longer timescales. This study offers a better understanding of the local climate characteristics and provides a scientific basis for government policymakers.


Author(s):  
Sohail Abbas ◽  
Safdar Ali Shirazi ◽  
Nausheen Mazhar ◽  
Kashif Mahmood ◽  
Ashfak Ahmad Khan

Identifying the temperature change at a regional level is one of the essential parameters to determine the intensity of climate change. The current investigation provides an examination of changing trends of temperature in the Punjab province from 1970 to 2019. Sen's slope estimator method is applied to monthly data of mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) to calculate the rate of temperature change. Statistical methods were used to find out the level of significance in terms of negative or positive trends to examine the variability among various weather observatories. Moreover, predicted values have also been observed for a detailed analysis of temperature variability and trends. Significant and pronounced changes in the mean temperature (T mean) are distinguished all over the Punjab regions with an increasing trend from North to South Punjab. In the case of maximum temperature (Tmax), a faster rate of rising in temperature is observed over the Southern and Western regions of Punjab. In contrast, the minimum temperature (Tmin) shows an increasing trend in Central Punjab. The findings provide detailed insight to policymakers for the planning of mitigating efforts and adaptation strategies in response to climate change.


2021 ◽  
Author(s):  
Atiqur Chowdhury

Abstract In this study, we analyzed publicly available agricultural data on rice production in Bangladesh between 2008 to 2017 to address the relationship between climate changes and rice production in Bangladesh by estimating predictor variables, i.e., average rainfall and maximum temperature, minimum temperature, and humidity. A generalized linear regression model sets up for each rice (Aush, Aman, Boro) with the climate variables (average rainfall, maximum temperature, minimum temperature, and humidity). We used Markov-Chain-Monte-Carlo's (MCMC)'s Gibbs sampling on the collected data to approximate marginal posterior distribution from the prior distribution to see the profound relationship between those predictor variables and the predicted variables (Aush, Aman, Boro). We also saw whether any storm's impact could modify the relationship between climate change variables and rice production in Bangladesh.


Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 67
Author(s):  
Helen Teshome ◽  
Kindie Tesfaye ◽  
Nigussie Dechassa ◽  
Tamado Tana ◽  
Matthew Huber

Smallholder farmers in East and West Hararghe zones, Ethiopia frequently face problems of climate extremes. Knowledge of past and projected climate change and variability at local and regional scales can help develop adaptation measures. A study was therefore conducted to investigate the spatio-temporal dynamics of rainfall and temperature in the past (1988–2017) and projected periods of 2030 and 2050 under two Representative Concentration Pathways (RCP4.5 and RCP8.5) at selected stations in East and West Hararghe zones, Ethiopia. To detect the trends and magnitude of change Mann–Kendall test and Sen’s slope estimator were employed, respectively. The result of the study indicated that for the last three decades annual and seasonal and monthly rainfall showed high variability but the changes are not statistically significant. On the other hand, the minimum temperature of the ‘Belg’ season showed a significant (p < 0.05) increment. The mean annual minimum temperature is projected to increase by 0.34 °C and 2.52 °C for 2030, and 0.41 °C and 4.15 °C for 2050 under RCP4.5 and RCP8.5, respectively. Additionally, the mean maximum temperature is projected to change by −0.02 °C and 1.14 °C for 2030, and 0.54 °C and 1.87 °C for 2050 under RCP4.5 and RCP 8.5, respectively. Annual rainfall amount is also projected to increase by 2.5% and 29% for 2030, and 12% and 32% for 2050 under RCP4.5 and RCP 8.5, respectively. Hence, it is concluded that there was an increasing trend in the Belg season minimum temperature. A significant increasing trend in rainfall and temperature are projected compared to the baseline period for most of the districts studied. This implies a need to design climate-smart crop and livestock production strategies, as well as an early warning system to counter the drastic effects of climate change and variability on agricultural production and farmers’ livelihood in the region.


2021 ◽  
Author(s):  
S. Sheraz Mahdi ◽  
Bhagyashree Shankarao Dhekale ◽  
Ashaq Hussain ◽  
Intikhab Aalum Jehangir ◽  
Rukhsana Jan ◽  
...  

Abstract Analysis of climatic variables is important for detection and attribution of climate change trends and has received a considerable attention from researchers across the globe including India. Kashmir valley of newly formed Union Territory Jammu & Kashmir situated in north western part of India is having a rich repository of glaciers, a small change in the precipitation and temperature management could introduce about environmental, agricultural and economic penalties. To this end, current study aims to analyse changing patterns in precipitation and temperature variables over the various elevation zones of the Kashmir Valley using long term precipitation and temperature data obtained from National Data Centre, Indian Meteorological Department (IMD), Pune for the period of 40 years (1980–2019). The results revealed that average mean minimum and maximum temperature of the Kashmir valley has increased substantially at a rate of 0.02oC/year. Warming trends has been observed in all seasons, however, winter and spring season temperatures have shown statistically significant increasing trends. In addition, mean maximum and minimum temperature in plain and mountain areas have reported higher rates of increase in comparison to Karewah’s and foothill areas of Kashmir. Study of annual precipitation results for the same period indicates a diminishing pattern with a rate of -5.01 mm/year. Seasonal precipitation was also found decreasing at rate of -4.95, -0.30, -0.28 and − 0.06 mm/year for the spring, winter, autumn and summer seasons respectively and at different elevation zones, higher rates of precipitation decline have been observed in the mountainous area, which can be very detrimental to the agricultural crops of the Kashmir valley through water supply, climate regulation and ground water recharge. Further, the above statistical test results of increase in temperature and decrease in precipitation over different topographical zones of Kashmir were corroborated with the information attained from interview and involvement of the small farmer holders of 06 different locations representing the whole Kashmir and has been discussed in this paper to get a clearer understanding of climate change related instability and patterns in weather variables in the Kashmir Valley.


MAUSAM ◽  
2021 ◽  
Vol 68 (4) ◽  
pp. 589-596
Author(s):  
JAYANTA SARKAR ◽  
J. R. CHICHOLIKAR

Climate change is considered to be the greatest challenge faced by mankind in the twenty first century which can lead to severe impacts on different major sectors of the world such as water resources, agriculture, energy and tourism and are likely to alter trends and timing of precipitation and other weather drivers. Analyses and prediction of change in critical climatic variables like rainfall and temperature are, therefore, extremely important. Keeping this in mind, this study aims to verify the skills of LARS-WG (Long Ashton Research - Weather Generator), a statistical downscaling model, in simulating weather data in hot semi-arid climate of Saurashtra and analyze the future changes of temperature (maximum and minimum) and precipitation downscaled by LARS-WG based on IPCC SRA2 scenario generated by seven GCMs' projections for the near (2011-2030), medium (2046-2065) and far (2080-2099) future periods. Rajkot (22.3° N, 70.78° E) observatory of IMD, representing hot semi-arid climate of Saurashtra, Gujarat state was chosen for this purpose. Daily rainfall, maximum and minimum temperature data for the period of 1969-2013 have been utilized.             LARS-WG is found to show reasonably good skill in downscaling daily rainfall and excellent skill in downscaling maximum and minimum temperature. The downscaled rainfall indicated no coherent change trends among various GCMs’ projections of rainfall during near, medium and far future periods. Contrary to rainfall projections, simulations from the seven GCMs have coherent results for both the maximum and minimum temperatures. Based on the ensemble mean of seven GCMs, projected rainfall at Rajkot in monsoon season (JJAS) showed an increase in near future, i.e., 2011-2030, medium future (2046-2065) and far future (2080-2099) periods to the tune of 2, 11 and 14% respectively compared to the baseline value. Model studies indicating tropospheric warming leading to enhancement of atmospheric moisture content could be the reason for this increasing trend. Further, at the study site summer (MAM) maximum temperature is projected to increase by 0.5, 1.7 and 3.3°C during 2011-2030, 2046-2065 and 2080-2099 respectively and winter (DJF) minimum temperature is projected to increase by 0.8, 2.2 and 4.5 °C during 2011-2030, 2046-2065 and 2080-2099 respectively.  


Sign in / Sign up

Export Citation Format

Share Document