Ranking the AR4 climate models over the Murray-Darling Basin using simulated maximum temperature, minimum temperature and precipitation

2008 ◽  
Vol 28 (8) ◽  
pp. 1097-1112 ◽  
Author(s):  
C. C. Maxino ◽  
B. J. McAvaney ◽  
A. J. Pitman ◽  
S. E. Perkins
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.


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.


2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.


Author(s):  
S.S. Mote ◽  
D.S. Chauhan* and Nilotpal Ghosh1

The study was undertaken to evaluate the effect of different macro climatic variables on lactation milk yield and lactation length of Holdeo (Holstein Friesian x Deoni) crossbred cattle. Milk data of 145 Holdeo crossbred cows with 619 lactation records and the meteorological data over a period of 15 years (1995-2009) were obtained from Cattle Cross Breeding Project, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani and University Meteorological Observatory, respectively. It was observed that maximum temperature has significant correlation with lactation milk yield; whereas maximum temperature, minimum temperature, sunshine hours and wind speed have significant correlation with lactation length. Regression analysis indicated that all the climatic variables except minimum temperature exhibited significant regression results with lactation milk yield, and maximum temperature, minimum temperature and maximum humidity have significant regression results with lactation length. All the climatic variables considered in the study accounted for 75 % and 65 % direct variation on lactation milk yield and lactation length, respectively, as verified by the value of coefficient of determination (R2). It was observed that lactation milk yield (1136.56 + 21.04 kg.) and lactation length (295.29 + 5.51 days) were highest among the cows calved during winter season as compared to rainy and summer season. All the climatic variables considered in the study accounted for 57% , 56 % and 48 % direct variation on milk yield and 68% , 53 % and 46 % direct variation on lactation length in rainy, winter and summer season, respectively, as verified by the value of coefficient of determination (R2). This research indicated that crossbred cows were sensitive to seasonal changes on their lactation performance. The optimum ranges of temperature; humidity and THI for better performance of crossbred in subtropical region of India were found to be 19-26 oC, 52-66 % and 65-68 %, respectively.


2016 ◽  
Vol 29 (23) ◽  
pp. 8285-8299 ◽  
Author(s):  
Andrea J. Dittus ◽  
David J. Karoly ◽  
Sophie C. Lewis ◽  
Lisa V. Alexander ◽  
Markus G. Donat

Abstract The skill of eight climate models in simulating the variability and trends in the observed areal extent of daily temperature and precipitation extremes is evaluated across five large-scale regions, using the climate extremes index (CEI) framework. Focusing on Europe, North America, Asia, Australia, and the Northern Hemisphere, results show that overall the models are generally able to simulate the decadal variability and trends of the observed temperature and precipitation components over the period 1951–2005. Climate models are able to reproduce observed increasing trends in the area experiencing warm maximum and minimum temperature extremes, as well as, to a lesser extent, increasing trends in the areas experiencing an extreme contribution of heavy precipitation to total annual precipitation for the Northern Hemisphere regions. Using simulations performed under different radiative forcing scenarios, the causes of simulated and observed trends are investigated. A clear anthropogenic signal is found in the trends in the maximum and minimum temperature components for all regions. In North America, a strong anthropogenically forced trend in the maximum temperature component is simulated despite no significant trend in the gridded observations, although a trend is detected in a reanalysis product. A distinct anthropogenic influence is also found for trends in the area affected by a much-above-average contribution of heavy precipitation to annual precipitation totals for Europe in a majority of models and to varying degrees in other Northern Hemisphere regions. However, observed trends in the area experiencing extreme total annual precipitation and extreme number of wet and dry days are not reproduced by climate models under any forcing scenario.


2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Miyuru B. Gunathilake ◽  
Yasasna V. Amaratunga ◽  
Anushka Perera ◽  
Imiya M. Chathuranika ◽  
Anura S. Gunathilake ◽  
...  

Water resources in Northern Thailand have been less explored with regard to the impact on hydrology that the future climate would have. For this study, three regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) of Coupled Model Intercomparison Project 5 (CMIP5) were used to project future climate of the upper Nan River basin. Future climate data of ACCESS_CCAM, MPI_ESM_CCAM, and CNRM_CCAM under Representation Concentration Pathways RCP4.5 and RCP8.5 were bias-corrected by the linear scaling method and subsequently drove the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) to simulate future streamflow. This study compared baseline (1988–2005) climate and streamflow values with future time scales during 2020–2039 (2030s), 2040–2069 (2050s), and 2070–2099 (2080s). The upper Nan River basin will become warmer in future with highest increases in the maximum temperature of 3.8°C/year for MPI_ESM and minimum temperature of 3.6°C/year for ACCESS_CCAM under RCP8.5 during 2080s. The magnitude of changes and directions in mean monthly precipitation varies, with the highest increase of 109 mm for ACESSS_CCAM under RCP 4.5 in September and highest decrease of 77 mm in July for CNRM, during 2080s. Average of RCM combinations shows that decreases will be in ranges of −5.5 to −48.9% for annual flows, −31 to −47% for rainy season flows, and −47 to −67% for winter season flows. Increases in summer seasonal flows will be between 14 and 58%. Projection of future temperature levels indicates that higher increases will be during the latter part of the 20th century, and in general, the increases in the minimum temperature will be higher than those in the maximum temperature. The results of this study will be useful for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset negative impacts of future changes in climate. In addition, the results will also be valuable for agriculturists and hydropower planners.


Author(s):  
S. S. Mote ◽  
D. S. Chauhan ◽  
Nilotpal Ghosh

The study was undertaken to evaluate the effect of different macro climatic variables on lactation milk yield and lactation length of Holdeo (Holstein Friesian x Deoni) crossbred cattle. Milk data of 145 Holdeo crossbred cows with 619 lactation records and the meteorological data over a period of 15 years (1995-2009) were obtained from Cattle Cross Breeding Project, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani and University Meteorological Observatory, respectively. It was observed that maximum temperature has significant correlation with lactation milk yield; whereas maximum temperature, minimum temperature, sunshine hours and wind speed have significant correlation with lactation length. Regression analysis indicated that all the climatic variables except minimum temperature exhibited significant regression results with lactation milk yield, and maximum temperature, minimum temperature and maximum humidity have significant regression results with lactation length. All the climatic variables considered in the study accounted for 75 % and 65 % direct variation on lactation milk yield and lactation length, respectively, as verified by the value of coefficient of determination (R2). It was observed that lactation milk yield (1136.56 + 21.04 kg.) and lactation length (295.29 + 5.51 days) were highest among the cows calved during winter season as compared to rainy and summer season. All the climatic variables considered in the study accounted for 57% , 56 % and 48 % direct variation on milk yield and 68% , 53 % and 46 % direct variation on lactation length in rainy, winter and summer season, respectively, as verified by the value of coefficient of determination (R2). This research indicated that crossbred cows were sensitive to seasonal changes on their lactation performance. The optimum ranges of temperature; humidity and THI for better performance of crossbred in subtropical region of India were found to be 19-26 oC, 52-66 % and 65-68 %, respectively.


2015 ◽  
Vol 17 (1) ◽  
pp. 175-185

<div> <p>The present study analyses future climate uncertainty for the 21st century over Tamilnadu state for six weather parameters: solar radiation, maximum temperature, minimum temperature, relative humidity, wind speed and rainfall. The climate projection data was dynamically downscaled using high resolution regional climate models, PRECIS and RegCM4 at 0.22&deg;x0.22&deg; resolution. PRECIS RCM was driven by HadCM3Q ensembles (HQ0, HQ1, HQ3, HQ16) lateral boundary conditions (LBCs) and RegCM4 driven by ECHAM5 LBCs for 130 years (1971-2100). The deviations in weather variables between 2091-2100 decade and the base years (1971-2000) were calculated for all grids of Tamilnadu for ascertaining the uncertainty. These deviations indicated that all model members projected no appreciable difference in relative humidity, wind speed and solar radiation. The temperature (maximum and minimum) however showed a definite increasing trend with 1.8 to 4.0&deg;C and 2.0 to 4.8&deg;C, respectively. The model members for rainfall exhibited a high uncertainty as they projected high negative and positive deviations (-379 to 854 mm). The spatial representation of maximum and minimum temperature indicated a definite rhythm of increment from coastal area to inland. However, variability in projected rainfall was noticed.</p> </div> <p>&nbsp;</p>


Sign in / Sign up

Export Citation Format

Share Document