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Adnan M.,Global Change Impact Studies Center | Rehman N.,Global Change Impact Studies Center | Ali S.,Global Change Impact Studies Center | Mehmood S.,Global Change Impact Studies Center | And 3 more authors.
Weather | Year: 2017

Agriculture contributes around a quarter to Pakistan's economy and is closely linked with the variability of monsoon rainfall. The prediction of monsoon rains with sufficient lead time has immense importance for the planning and management of water resources and agriculture. In this study, Multiple Linear Regression (MLR) and Principal Component Regression (PCR) methods are employed to predict monsoon rainfall, and their performances are compared for June–September (JJAS) for the period 1961–2014 over the monsoon region of Pakistan. Rainfall data of Meteorological stations are used as the predictand. In the MLR method, predictors are carried out from sea level pressure (SLP) and sea surface temperature (SST) of the National Centers for Environmental Prediction (NCEP) reanalysis datasets. The PCR method first calculates principal components (PCs) from SLP and SST data, and these PCs are then combined with the regression technique and used as predictors. The performance of both models is tested using statistical measures such as root mean square error (RMSE), mean absolute error (MAE), bias and the correlation coefficient to evaluate the skill of the forecast. The agreement between actual and predicted rainfall data provides evidence for reasonably accurate predictions from both methods. The MLR and PCR models explained 84.6 and 92.2% of the variation of data, and the multiple correlation coefficients are 0.92 and 0.96 respectively. The correlation coefficient for the verification period (2005–2014) is 0.73 for MLR and 0.89 for PCR. The values of mean bias, MAE and RMSE are −5.5, 20.0 and 25.1mm for MLR, and −0.42, 16.2 and 16.6mm for PCR, respectively. The results indicate that the PCR model forecast is slightly better than that of the MLR model. © 2017 Royal Meteorological Society


Dogar M.M.,King Abdullah University of Science and Technology | Dogar M.M.,Global Change Impact Studies Center | Kucharski F.,Abdus Salam International Center For Theoretical Physics | Azharuddin S.,University of Lucknow
Journal of Earth System Science | Year: 2017

ENSO is considered as a strong atmospheric teleconnection that has pronounced global and regional circulation effects. It modifies global monsoon system, especially, Asian and African monsoons. Previous studies suggest that both the frequency and magnitude of ENSO events have increased over the last few decades resulting in a need to study climatic impacts of ENSO magnitude both at global and regional scales. Hence, to better understand the impact of ENSO amplitude over the tropical and extratropical regions focussing on the Asian and African domains, ENSO sensitivity experiments are conducted using ICTPAGCM (‘SPEEDY’). It is anticipated that the tropical Pacific SST forcing will be enough to produce ENSO-induced teleconnection patterns; therefore, the model is forced using NINO3.4 regressed SST anomalies over the tropical Pacific only. SPEEDY reproduces the impact of ENSO over the Pacific, North and South America and African regions very well. However, it underestimates ENSO teleconnection patterns and associated changes over South Asia, particularly in the Indian region, which suggests that the tropical Pacific SST forcing is not sufficient to represent ENSO-induced teleconnection patterns over South Asia. Therefore, SST forcing over the tropical Indian Ocean together with air–sea coupling is also required for better representation of ENSO-induced changes in these regions. Moreover, results obtained by this pacemaker experiment show that ENSO impacts are relatively stronger over the Inter-Tropical Convergence Zone (ITCZ) compared to extratropics and high latitude regions. The positive phase of ENSO causes weakening in rainfall activity over African tropical rain belt, parts of South and Southeast Asia, whereas, the La Niña phase produces more rain over these regions during the summer season. Model results further reveal that ENSO magnitude has a stronger impact over African Sahel and South Asia, especially over the Indian region because of its significant impact over the tropical Atlantic and the Indian Ocean through Walker circulation. ENSO-induced negative (positive) NAO-like response and associated changes over Southern Europe and North Africa get significantly strong following increased intensity of El Niño (La Niña) in the northern (southern) hemisphere in the boreal winter (summer) season. We further find that ENSO magnitude significantly impacts Hadley and Walker circulations. The positive phase of ENSO (El Niño) overall strengthens Hadley cell and a reverse is true for the La Niña phase. ENSO-induced strengthening and weakening of Hadley cell induces significant impact over South Asian and African ITCZ convective regions through modification of ITCZ/monsoon circulation system. © Indian Academy of Sciences.


Sheikh M.M.,Global Change Impact Studies Center | Manzoor N.,Global Change Impact Studies Center | Ashraf J.,Global Change Impact Studies Center | Adnan M.,Global Change Impact Studies Center | And 9 more authors.
International Journal of Climatology | Year: 2015

Over the last few decades, weather and climate extremes have become a major focus of researchers, the media and general public due to their damaging effects on human society and infrastructure. Trends in indices of climate extremes are studied for the South Asian region using high-quality records of daily temperature and precipitation observations. Data records from 210 (265) temperature (precipitation) observation stations are analysed over the period 1971-2000 (1961-2000). Spatial maps of station trends, time series of regional averages and frequency distribution analysis form the basis of this study. Due to the highly diverse geography of the South Asian region, the results are also described for some specific regions, such as the island of Sri Lanka; the tropical region (excluding Sri Lanka); the Greater Himalayas above 35°N, the Eastern Himalayas (Nepal) and the Thar Desert. Generally, changes in the frequency of temperature extremes over South Asia are what one would expect in a warming world; warm extremes have become more common and cold extremes less common. The warming influence is greater in the Eastern Himalayas compared with that in the Greater Himalayas. The Thar Desert also shows enhanced warming, but increases are mostly less than in the Eastern Himalayas. Changes in the indices of extreme precipitation are more mixed than those of temperature, with spatially coherent changes evident only at relatively small scales. Nevertheless, most extreme precipitation indices show increases in the South Asia average, consistent with globally averaged results. The indices trends are further studied in the context of Atmospheric Brown Clouds (ABCs) over the region. Countries falling within the ABC hotspot namely Indo-Gangetic Plain (IGP) have shown a different behaviour on the trends of extreme indices compared with the parts outside this hotspot. IGP has increased temperature and decreased rainfall and tally closely with the actual trends. © 2014 Royal Meteorological Society.


Saeed S.,Global Change Impact Studies Center | Saeed S.,Max Planck Institute for Meteorology | Liu Y.,Beijing Climate Center
Theoretical and Applied Climatology | Year: 2011

Multiyear (1983-2006) hindcast simulation of summer monsoon over South Asia has been carried out using the regional climate model of the Beijing Climate Centre (BCC_RegCM1. 0). The regional climate model (hereafter BCC RCM) is nested into the global climate model of the Beijing Climate Centre BCC_CGCM1. 0 (here after CGCM). The regional climate model is initialized on 01 May and integrated up to the end of the September for 24 years. Compared to the driving CGCM the BCC RCM reproduces reasonably well the intensity and magnitude of the large-scale features associated with the South Asia summer monsoon such as the upper level anticyclone at 200 hPa, the mid-tropospheric warming over the Tibetan plateau, the surface heat low and the 850 hPa moisture transport from ocean to the land. Both models, i.e., BCC RCM and the driving CGCM overestimates (underestimates) the 850 hPa southwesterly flow over the northern (southern) Arabian Sea. Moreover, both models overestimate the seasonal mean precipitation over much of the South Asia region compared to the observations. However, the precipitation biases are significantly reduced in the BCC RCM simulations. Furthermore, both models simulate reasonably the interannual variability of the summer monsoon over India. The precipitation index simulated by BCC RCM shows significant correlation (0.62) with the observed one. The BCC RCM simulates reasonably well the spatial and temporal variation of the precipitation and surface air temperature compared to the driving CGCM. Further, the temperature biases are significantly reduced (1-4°C) in the BCC RCM simulations. The simulated vertical structure of the atmosphere show biases above the four sub-regions, however, these biases are significantly reduced in the BCC RCM simulations compared to the driving CGCM. Compared to the driving CGCM, the evolution processes of the onset of summer monsoon, e.g., the meridional temperature gradient and the vertical wind shear are well simulated by the BCC RCM. The 24-year simulations also show that with a little exception the BCC RCM is capable to reproduce the monsoon active and break phases and the intraseasonal precipitation variation over the Indian subcontinent. © 2010 Springer-Verlag.


Mir K.A.,National University of Singapore | Mir K.A.,Global Change Impact Studies Center | Purohit P.,International Institute For Applied Systems Analysis | Goldstein G.A.,DecisionWare Group LLC | Balasubramanian R.,National University of Singapore
Environmental Science and Pollution Research | Year: 2016

This study aims to assess the current and future air pollution and associated health impacts in Pakistan. In this study, the Pakistan Integrated Energy Model (Pak-IEM) is used to assess current and future energy consumption in Pakistan. To assess air pollution levels and associated health impacts, we used the Greenhouse gas and Air pollution INteractions and Synergies (GAINS) model. A linkage has been established between both the models to feed the energy outputs from Pak-IEM into GAINS for exploring different scenarios. Mainly, the emissions of three air pollutants (SO2, NOx, and PM2.5) as well as the associated health impacts of increased emissions are assessed. Baseline emission scenario (BES) shows a growth in emissions of SO2, NOx, and PM2.5 by a factor of 2.4, 2.2, and 2.5 between 2007 and 2030. In terms of health impacts, by 2030, annual mean concentrations of fine particles (PM2.5) would increase to more than 150 μg/m3 in some parts of Punjab region of Pakistan, for which loss in statistical life expectancy is calculated to increase from 30 to 60 months in 2007 up to 60–100 months in 2030 on average. © 2016 Springer-Verlag Berlin Heidelberg


Yadav R.K.,Indian Institute of Tropical Meteorology | Yoo J.H.,Abdus Salam International Center For Theoretical Physics | Kucharski F.,Abdus Salam International Center For Theoretical Physics | Abid M.A.,Global Change Impact Studies Center
Journal of Climate | Year: 2010

This study examines decadal changes of the El Niño-Southern Oscillation (ENSO) influence on the interannual variability of northwest India winter precipitation (NWIWP). The analysis is based on correlations and regressions performed using India Meteorological Department (IMD) records based on station data and reanalysis fields from 1950 to 2008. The authors find that the interannual variability of NWIWP is influenced by the ENSO phenomenon in the recent decades. This conclusion is supported by a consistency across the different observational datasets employed in this study and confirmed by numerical modeling. A physical mechanism for such an influence is proposed, by which western disturbances (WDs) are intensified over northwest India because of a baroclinic response due to Sverdrup balance related to large-scale sinking motion over the western Pacific during the warm phase of ENSO. This response causes an upper-level cyclonic circulation anomaly north of India and a low-level anticyclonic anomaly over southern and central India. The cyclonic circulation anomaly intensifies the WDs passing over northwest India. © 2010 American Meteorological Society.


Zhu T.,International Food Policy Research Institute | Ringler C.,International Food Policy Research Institute | Iqbal M.M.,Global Change Impact Studies Center | Sulser T.B.,Food and Agriculture Organization of the United Nations | Goheer M.A.,Global Change Impact Studies Center
Water International | Year: 2013

Climate change is expected to considerably affect the water resources in the Indus River basin in Pakistan and thus agricultural production in the country. This article reports an analysis of the impacts of various climate scenarios on both water resources and food production out to 2050. While changes in water availability range from -12% to +24%, depending on the scenario, crop yield and production impacts are negative across all scenarios, and net food imports increase. We suggest a combination of accelerated investment in agricultural research and increased water-use efficiency in agriculture to reduce the adverse impacts of climate change on water and food. © 2013 International Water Resources Association.


Ali S.,CAS Institute of Atmospheric Physics | Ali S.,University of Chinese Academy of Sciences | Ali S.,Global Change Impact Studies Center | Dan L.,CAS Institute of Atmospheric Physics | And 2 more authors.
Advances in Atmospheric Sciences | Year: 2015

This study discusses the sensitivity of convective parameterization schemes (CPSs) in the Regional Climate Model (version 4.3) (RegCM4.3) over East/South Asia. The simulations using different CPSs in RegCM are compared to discover a suitable scheme for this region, as the performance of different schemes is greatly influenced by region and seasonality. Over Southeast China and the Bay of Bengal, the Grell scheme exhibits the lowest RMSEs of summer precipitation compared to observed data. Moreover, the Emanuel over land and Grell over ocean (ELGO) scheme enhances the simulation, in comparison with any single CPS (Grell/Emanuel) over Western Ghats, Sri Lanka, and Southeast India. Over the Huang-Huai-Hai Plain (3H) and Tibetan Plateau (TP) regions of China, the Tiedtke scheme simulates the more reasonable summer precipitation with high correlation coefficient and comparable amplitude. Especially, it reproduces a minimum convective precipitation bias of 8 mm d−1 and the lowest RMSEs throughout the year over East/South Asia. Furthermore, for seasonal variation of precipitation, the Tiedtke scheme results are closer to the observed data over the 3H and TP regions. However, none of the CPSs is able to simulate the seasonal variation over North Pakistan (NP). In comparison with previous research, the results of this study support the Grell scheme over South Asia. However, the Tiedtke scheme shows superiority for the 3H, TP and NP regions. The thicker PBL, less surface latent heat flux, the unique ability of deep convection and the entrainment process in the Tiedtke scheme are responsible for reducing the wet bias. © 2015, Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg.


Ali S.,Chinese Academy of Sciences | Ali S.,Global Change Impact Studies Center | Li D.,Chinese Academy of Sciences | Congbin F.,Chinese Academy of Sciences | Khan F.,Klagenfurt University
Environmental Research Letters | Year: 2015

This study is based on both the recent and the predicted twenty first century climatic and hydrological changes over the mountainous Upper Indus Basin (UIB), which are influenced by snow and glacier melting. Conformal-Cubic Atmospheric Model (CCAM) data for the periods 1976-2005, 2006-2035, 2041-2070, and 2071-2100 with RCP4.5 and RCP8.5; and Regional Climate Model (RegCM) data for the periods of 2041-2050 and 2071-2080 with RCP8.5 are used for climatic projection and, after bias correction, the same data are used as an input to the University of British Columbia (UBC) hydrological model for river flow projections. The projections of all of the future periods were compared with the results of 1976-2005 and with each other. Projections of future changes show a consistent increase in air temperature and precipitation. However, temperature and precipitation increase is relatively slow during 2071-2100 in contrast with 2041-2070. Northern parts are more likely to experience an increase in precipitation and temperature in comparison to the southern parts. A higher increase in temperature is projected during spring and winter over southern parts and during summer over northern parts. Moreover, the increase in minimum temperature is larger in both scenarios for all future periods. Future river flow is projected by both models to increase in the twenty first century (CCAM and RegCM) in both scenarios. However, the rate of increase is larger during the first half while it is relatively small in the second half of the twenty first century in RCP4.5. The possible reason for high river flow during the first half of the twenty first century is the large increase in temperature, which may cause faster melting of snow, while in the last half of the century there is a decreasing trend in river flow, precipitation, and temperature (2071-2100) in comparison to 2041-2070 for RCP4.5. Generally, for all future periods, the percentage of increased river flow is larger in winter than in summer, while quantitatively large river flow was projected, particularly during the summer monsoon. Due to high river flow and increase in precipitation in UIB, water availability is likely to be increased in the twenty first century and this may sustain water demands. © 2015 IOP Publishing Ltd.


Amjad M.,Global Change Impact Studies Center | Zafar Q.,Global Change Impact Studies Center | Khan F.,Global Change Impact Studies Center | Sheikh M.M.,Global Change Impact Studies Center
International Journal of Climatology | Year: 2015

Weather research and forecasting (WRF) model is the state-of-the-art mesoscale model that could be used as a guideline to effectively assess the wind resource of Gharo wind station lying in the coastal belt of Pakistan. The anemometer heights of 10 and 30 m for the year 2005 have been used to study the wind profile of the region for summer (June, July, August, September) and winter (December, January, February, March). The study uses an innovative approach for model comparisons, i.e. an eta-half level is added in the model on 60 m height and is interpolated to 30 m height by using well known power law. This is done by studying the diurnal variation of wind shear for the whole year of 2005 in order to reduce maximum possible interpolation error. For both seasons, the error measures of mean bias error (MBE), mean absolute error (MAE) and root mean square error (RMSE) of 30 m interpolated data were found lower than 10 m height data with increased correlation (r). A bias correction methodology (best easy systematic estimator) was further applied over the model output showing a significant improvement toward MBE, MAE and RMSE reduction, i.e. up to 99%, 73% and 68% on 10 m height and 99%, 51% and 46% on 30 m height. Errors were reduced more for summer than winter. The selected bias correction methodology was thus found to be highly applicable for both model heights. The wind energy assessment of Gharo wind station from the corrected model simulation showed summer having more potential for wind energy than winter with an estimated energy of up to 1000 MWh. © 2015 Royal Meteorological Society.

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