Circumglobal wave train and the summer monsoon over northwestern India and Pakistan: the explicit role of the surface heat low

This study examines the influence of the mid-latitude circulation on the surface heat low (HL) and associated monsoon rainfall over northwestern India and Pakistan using the ERA40 data and high resolution (T106L31) climate model ECHAM5 simulation. Special emphasis is given to the surface HL which forms over Pakistan and adjoining areas of India, Iran and Afghanistan during the summer season. A heat low index (HLI) is defined to depict the surface HL. The HLI displays significant correlations with the upper level mid-latitude circulation over western central Asia and low level monsoon circulation over Arabian Sea and acts as a bridge connecting the mid-latitude wave train to the Indian summer monsoon. A time-lagged singular value decomposition analysis reveals that the eastward propagation of the mid-latitude circumglobal wave train (CGT) influences the surface pressure anomalies over the Indian domain. The largest low (negative) pressure anomalies over the western parts of the HL region (i.e., Iran and Afghanistan) occur in conjunction with the upper level anomalous high that develops over western-central Asia during the positive phase of the CGT. The composite analysis also reveals a significant increase in the low pressure anomalies over Iran and Afghanistan during the positive phase of CGT. The westward increasing low pressure anomalies with its north?Csouth orientation provokes enormous north?Csouth pressure gradient (lower pressure over land than over sea). This in turn enables the moist southerly flow from the Arabian Sea to penetrate farther northward over northwestern India and Pakistan. A monsoon trough like conditions develops over northwestern India and Pakistan where the moist southwesterly flow from the Arabian Sea and the Persian Gulf converge. The convergence in association with the orographic uplifting expedites convection and associated precipitation over northwestern India and Pakistan. The high resolution climate model ECHAM5 simulation also underlines the proposed findings and mechanism.     

Multiyear hindcast simulations of summer monsoon over South Asia using a nested regional climate model��BCC_RegCM1.0

Multiyear (1983?C2006) 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?C4°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.     

Intensification of future heat waves in Pakistan: a study using CORDEX regional climate models ensemble

Future trends in the occurrence of heat waves (HW) over Pakistan have been presented using three regional climate models (RCMs), forced by three different global climate models (GCMs) runs under RCP8.5 scenarios. The results of RCMs are obtained from CORDEX (Coordinated Regional climate Downscaling EXperiment) database. Two different approaches for the assessment of HWs are defined, namely Fixed and Relative approaches. Fixed approach is defined for a life-threatening extreme event in which the temperature can reach more than 45 °C for a continuous stretch of several days; however, Relative approach events may not be directly life-threatening, but may cause snow/ice melt flooding and impact on food security of the country in summer and winter seasons, respectively. The results indicate a consistent increase in the occurrence of HWs for both approaches. For the Fixed approach, the increase is evident in the eastern areas of Pakistan, particularly plains of Punjab and Sindh provinces which host many big cities of the country. It is argued that the effect of HWs may also be exacerbated in future due to urban heat island effect. Moreover, summer time HWs for Relative approach is most likely to increase over northern areas of the country which hosts reservoirs of snow and glacier, which may result in events like glacial lake outburst flood and snow/ice melt flooding. Furthermore, the increase in winter time HWs for Relative approach may affect negatively on the wheat production, which in turn can distress the overall food productivity and livelihoods of the country. It is concluded that this study may be a useful document for future planning in order to better adapt to these threats due to climate change.     

Prediction of the Shear Wave Velocity from Compressional Wave Velocity for Gachsaran Formation

Shear and compressional wave velocities, coupled with other petrophysical data, are very important for hydrocarbon reservoir characterization. In situ shear wave velocity (Vs) is measured by some sonic logging tools. Shear velocity coupled with compressional velocity is vitally important in determining geomechanical parameters, identifying the lithology, mud weight design, hydraulic fracturing, geophysical studies such as VSP, etc. In this paper, a correlation between compressional and shear wave velocity is obtained for Gachsaran formation in Maroon oil field. Real data were used to examine the accuracy of the prediction equation. Moreover, the genetic algorithm was used to obtain the optimal value for constants of the suggested equation. Furthermore, artificial neural network was used to inspect the reliability of this method. These investigations verify the notion that the suggested equation could be considered as an efficient, fast, and cost-effective method for predicting Vs from Vp.     

Hydrodynamic study of karstic and intergranular aquifers using isotope geochemistry in Basara basin, Sulaimani, North-Eastern Iraq

The study area is located in the border of the high and low folded zone having a semi-arid climate area. This study initiated in 2009–2010, deals essentially with the investigation of the stable isotope (¹⁸O and deuterium ²H) as well as radioactive isotope represented by tritium ³H in rain, carbonate springs, intergranular aquifer, and surface water in order to investigate the source and relative ages of the groundwater and to show the influence of the altitude variations of the isotope composition. In this study and for the first time in the area, a local meteoric water line have been drawn with an empirical formula δ ²H?=?7.7δ ¹⁸O?+?14.4. The δ ¹⁸O–altitude effect was determined using isotopic data for several samples taken from groundwater and surface water; it was approximated at ?0.79?‰/100 m for the entire area of the study. The output of the tritium concentrations in the springs and water well samples revealed to the conclusion that the values closely resembles to the present time tritium concentration in precipitation.     

Estimation of soil hydraulic properties and their uncertainty through the Beerkan infiltration experiment

The Beerkan method based on in situ single‐ring water infiltration experiments along with the relevant specific Beerkan estimation of soil transfer parameters (BEST) algorithm is attractive for simple soil hydraulic characterization. However, the BEST algorithm may lead to erroneous or null values for the saturated hydraulic conductivity and sorptivity especially when there are only few infiltration data points under the transient flow state, either for sandy soil or soils in wet conditions. This study developed an alternative algorithm for analysis of the Beerkan infiltration experiment referred to as BEST‐generalized likelihood uncertainty estimation (GLUE). The proposed method estimates the scale parameters of van Genuchten water retention and Brooks–Corey hydraulic conductivity functions through the GLUE methodology. The GLUE method is a Bayesian Monte Carlo parameter estimation technique that makes use of a likelihood function to measure the goodness‐of‐fit between modelled and observed data. The results showed that using a combination of three different likelihood measurements based on observed transient flow, steady‐state flow and experimental steady‐state infiltration rate made the BEST‐GLUE procedure capable of performing an efficient inverse analysis of Beerkan infiltration experiments. Therefore, it is more applicable for a wider range of soils with contrasting texture, structure, and initial and saturated water content. Copyright © 2015 John Wiley & Sons, Ltd.     

Classification of rocks radionuclide data using machine learning techniques

The aim of this study is to assess the performance of linear discriminate analysis, support vector machines (SVMs) with linear and radial basis, classification and regression trees and random forest (RF) in the classification of radionuclide data obtained from three different types of rocks. Radionuclide data were obtained for metamorphic, sedimentary and igneous rocks using gamma spectroscopic method. A P-type high-purity germanium detector was used for the radiometric study. For analysis purpose, we have determined activity concentrations of ²³²Th, ²²⁶Ra and ⁴⁰K radionuclides, published elsewhere (Rafique et al. in Russ Geol Geophys 55:1073–1082, 2014), in different rock samples and built the classification model after pre-processing the data using three times tenfold cross-validation. Using this model, we have classified the new samples into known categories of sedimentary, igneous and metamorphic. The statistics depicts that RF and SVM with radial kernel outperform as compared to other classification methods in terms of error rate, area under the curve and with respect to other performance measures.     

Determinants of farmers’ choice of coping and adaptation measures to the drought hazard in northwest Balochistan,Pakistan

This study identifies the coping and adaptation behavior of the farm households and also examines the factors that influence farmers’ choice for drought-induced adaptation strategies. The study employs a multivariate probit model on 215 farm households’ survey data from northwest Balochistan, Pakistan. The findings reveal that the farmers have shown considerable fortitude in coping with the impacts of drought on their agro-based practices and employed several adaptation initiatives both at on-farm and off-farm levels. These include crop management, water management, adjustment in agricultural inputs, income diversification, economization of expenditure and consumption smoothing, migrating to other places to seek alternative sources of income, assets depletion, and borrowing. Empirically, it is depicted that landholding, annual income, livestock ownership, credit access, farmer-to-farmer extension, GOs/NGOs support increase the probability of farmers’ decision to cope and adapt better with drought hazard. This study implies for specific policy and practice-oriented solutions in order to cope with and adapt in drought situation.