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Winter (December to March) precipitation is the major source of rainfed agriculture, storage, and perennial water flow in the western river system of Pakistan. Hence, this study uses precipitation data and variables of land–ocean and atmosphere from the Pakistan Meteorological Department and European Centre for Medium-Range Weather Forecasts (ECMWF) and fifth-generation reanalysis data (ERA5), respectively, to investigate the changes in winter precipitation and its sensitivity to different land–ocean and atmosphere variables, which are rarely investigated in Pakistan. Non-parametric techniques, such as the modified Mann–Kendal, Sen slope, kernel density-based probability function (PDF), empirical orthogonal function (EOF), and correlation analysis, were used to assess the changes and modes of variability in winter precipitation. The overall seasonal precipitation showed a significant decreasing trend with a (−0.1 mm d−1 yr−1) in the seasonal mean and monthly precipitation, except in February which showed a significant increase (>0.11 mm d−1 yr−1). The highest decrease in daily precipitation (0.60) with the central Pacific and Indian Ocean’s basin-wide sea surface temperature, corroborating the influence of ENSO-induced meridional/zonal deviation of Hadley–Walker circulations. The Hadley and Walker cells affect the south-westerlies’ jet stream strength, impacting the water vapor transport and precipitation over Pakistan. These changes in the precipitation magnitude will affect rain-fed agriculture, especially the Rabi cropping pattern and perennial river flow.

Understanding the Tibetan Plateau (TP) thermal processes is of utmost significance in changing climate. This study investigates the effect of soil moisture in changing the TP thermal profile and consequently summer precipitation in South Asia (SA). Soil moisture from Special Sensor Microwave Imager (SSM/I) developed from the F-08, F-11, and F-13 fundamental climate data record and atmospheric reanalysis from ERA-Interim, MERRA-2, and NCEP/CFSR during 1988–2008 are used. A generalized linear method that assesses the reciprocal forcing between two connected fields, named the coupled manifold technique (CMT), is applied to TP soil moisture and SA summer precipitation. It is revealed that interannual variations of SA precipitation are significantly (confidence level = 99%) impacted by TP soil moisture and the explained ratio of variance in SA is 0.3–0.4. Composite analysis indicates that SA summer precipitation has positive anomalies in response to dry TP soil moisture in the previous spring and vice versa. For understanding the possible mechanism, thermal processes, relative humidity, wind components, and moisture flux anomalies were calculated for dry and wet TP soil moisture and summer precipitation. The results suggested that TP soil moisture is likely to regulate near-surface energy balance and diabatic heating profile over TP. As a result, the surrounding lower-level westerlies (easterlies) (at 850 hPa) converge (diverge), associated with divergence (convergence) at the upper troposphere (200 hPa). The westerlies (easterlies) are usually moisture-rich (moisture-deficient) and thus cause more (less) precipitation in western (eastern) SA. It is thus suggested that the spring soil moisture may affect the thermal profile of TP, affecting the summer precipitation in SA as a consequence.

The sharp rise in temperature has increased the frequency, intensity, duration, and timing of heat waves (HWs) over different regions of the world. Due to climate change, the China–Pakistan Economic Corridor (CPEC) is one of the highly vulnerable regions to HWs and needs comprehensive research studies to investigate the HW phenomenon in the region. This study analyzed the spatial and temporal changes in the daytime and nighttime HW characteristics based on multiple indices over the CPEC region. We used daily maximum and minimum temperatures (hereafter Tmax and Tmin) of 48 meteorological stations for the time period of 1980–2016. The non-parametric modified Mann–Kendall, Theil–Sen’s test, least square method, student t-test, and chi-square goodness-of-fit test techniques were used to analyze the long-term spatiotemporal changes in the daytime and nighttime HW characteristics. The results of the study show that the number of annual daytime/nighttime HW events, annual sum of participating daytime/nighttime HW days, the average length of annual daytime/nighttime HW events, duration of the longest annual daytime/nighttime HW event, the average magnitude of all annual daytime/nighttime HW events, amplitude of the hottest annual daytime/nighttime HW event, and the ending date of annual last daytime/nighttime HW event exhibited significant increasing trends at the rate of 0.78/1.43 events decade−1, 10/11.82, 2/1.74, 2.16/1.52 days decade−1, 0.40/0.59, 0.24/0.73 °C decade−1, and 12.29/10 days decade−1, respectively. Despite all, the onset date of the annual first daytime/nighttime HW event has shown a significant decreasing trend of − 5.71/− 5 days decade−1. The obvious positive trend of HW behaviors indicates that the country has experienced more frequent, stronger, more intense, and longer HWs during the study period. The spatial pattern of the trend indicates that the southern, central and eastern parts of Pakistan exhibited prominent and consistent HW activities, while the northwestern mountainous regions showed high spatial variability with some stations exhibited decreasing trends in HW indices. The findings of this study will be a base for the projection and mitigation of HWs in the region. Based on the study findings, we recommend that the mechanism of HW and its natural and anthropogenic drivers should be thoroughly investigated over the study region.

Seismic reservoir characterization is a renowned technique to obtain a better understandingand quantification of hydrocarbon bearing reservoirs by integration of seismic attributes, post stack inversion and wireline log analysis. In current case study, a methodology based on these techniques is proposed, and its applicability is tested for delineating the secondary reservoir potential of the Eocene carbonates (Habib Rahi and Sui Upper Limestone) in Qadirpur area, Lower Indus Basin, Pakistan. The application of post stack inversion provides a reasonable estimate of the acoustic impedance and enables the spatial distribution of important petrophysical properties (effective porosity and water saturation) available at sparse well locations. This distribution is facilitated by developing geostatistical relations between seismic and well derived reservoir properties in the range of seismic resolution. The results from all integrated techniques depict fluid saturated zones at Habib Rahi (gas at 907–922 m; water at 953–973 m) and Sui Upper Limestone (gas at 1192–1208 m) levels. The spatial distribution of the reservoir properties (effective porosity and water saturation) obtained via seismic data shows a very good calibration at the location of wells and reflects significant secondary reservoir potential for Eocene carbonates in the study area (effective porosity in the range of 7–26% and water saturation in the range of 35–60%). Furthermore, the methodology tested over here will be advantageous for the characterization of oil/gas reservoirs in various basins of Asia and other parts of world with similar geological settings.

The South Asian High (SAH) location and intensity are linked with the Tibetan Plateau (TP) and Yangtze River basin latent heating. The existing feedbacks of SAH variability is rarely linked with TP soil moisture regulated energy fluxes. In this study, remotely sensed soil moisture and global atmospheric reanalysis products are used to quantify the relationship between the TP spring (April, May, June) soil moisture with SAH and South Asian (SA) monsoon onset during 1988–2008. The diagnostic analysis infers that the SAH exhibits a significant correlation (R ≥ 0.90) with TP spring soil moisture and monsoon onset indices (R≥ -0.56−-0.61). During the early and late monsoon onset, a significant anomalous soil moisture regime influenced the surface energy fluxes, which affected the vertical diabatic heating profile. The diabatic heating profile affects the TP ascending motion and SAH intensity, which leads to regional monsoon circulation changes and onset. An asymmetric SAH movement in the upper troposphere appears before the early and late monsoon onset composites and drives the lower tropospheric westerlies/easterlies winds towards the continental SA. The wind shear and transition from prevailing easterlies into westerlies during the pre-onset, onset, and post-onset pentad results in strong/weak ascent in the Bay of Bengal and advances into continental regions. The onset- mechanism further suggested intensified/weaker westerlies/easterlies during early/late onset composites. The SAH intensity and movement are linked with TP soil moisture, which exhibits teleconnections with the regional circulation pattern. A detailed model experiment will be conducted to verify the influence of soil moisture as a driver of energy fluxes and SA monsoon onset.

Drought severity still remains a serious concern across sub-Saharan Africa (SSA) due to the destructive impact on multiple sectors of our society The interannual variability and trends in the changes of self-calibrated Palmer Drought Severity Index based on Penman–Monteith (scPDSIPM) and Thornthwaite (scPDSITH) methods for potential evapotranspiration (PET), precipitation (P) and normalized difference vegetation index (NDVI) anomalies, and sea surface temperature (SST) anomaly were investigated through statistical analysis of modelled and remote sensing data. It is shown that scPDSIPM and scPDSITH differed in the representation of drought characteristics over SSA. The scPDSI and remotely-sensed-based anomalies of P and NDVI showed wetting and drying trends over the period 1980-2012. The trend analysis showed increased drought events in the semi-arid and arid regions of SSA over the same period. A correlation analysis reveals a strong relationship between scPDSI variability and P, and NDVI anomalies for monsoon and pre-monsoon seasons. The correlation analysis of scPDSI variability with SST anomalies indicates significant positive and negative relationships, respectively. This study has demonstrated the applicability of multiple data sources for drought assessment and provides useful information for regional drought predictability and mitigation strategies.

In this study, an existing combination approach that maximizes temporal correlations is used to combine six passive microwave satellite soil moisture products from 1998 to 2015 to assess its added value in long-term applications. Five of the products used are included in existing merging schemes such as the European Space Agency’s essential climate variable soil moisture (ECV) program. These include the Special Sensor Microwave Imagers (SSM/I), the Tropical Rainfall Measuring Mission (TRMM/TMI), the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) sensor on the National Aeronautics and Space Administration’s (NASA) Aqua satellite, the WindSAT radiometer, onboard the Coriolis satellite and the soil moisture retrievals from the Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor onboard the Global Change Observation Mission on Water (GCOM-W). The sixth, the microwave radiometer imager (MWRI) onboard China’s Fengyun-3B (FY3B) satellite, is absent in the ECV scheme. Here, the normalized soil moisture products are merged based on their availability within the study period. Evaluation of the merged product demonstrated that the correlations and unbiased root mean square differences were improved over the whole period. Compared to ECV, the merged product from this scheme performed better over dense and sparsely vegetated regions. Additionally, the trends in the parent inputs are preserved in the merged data. Further analysis of FY3B’s contribution to the merging scheme showed that it is as dependable as the widely used AMSR2, as it contributed significantly to the improvements in the merged product.

The exploration and production of unconventional resources has increased significantly over the past few years around the globe to fulfill growing energy demands. Hydrocarbon potential of these unconventional petroleum systems depends on the presence of significant organic matter; their thermal maturity and the quality of present hydrocarbons i.e. gas or oil shale. In this work, we present a workflow for estimating Total Organic Content (TOC) from seismic reflection data. To achieve the objective of this study, we have chosen a classic potential candidate for exploration of unconventional reserves, the shale of the Sembar Formation, Lower Indus Basin, Pakistan. Our method includes the estimation of TOC from the well data using the Passey’s ΔlogR and Schwarzkofp’s methods. From seismic data, maps of Relative Acoustic Impedance (RAI) are extracted at maximum and minimum TOC zones within the Sembar Formation. A geostatistical trend with good correlation coefficient (R2) for cross-plots between TOC and RAI at well locations is used for estimation of seismic based TOC at the reservoir scale. Our results suggest a good calibration of TOC values from seismic at well locations. The estimated TOC values range from 1 to 4% showing that the shale of the Sembar Formation lies in the range of good to excellent unconventional oil/gas play within the context of TOC. This methodology of source rock evaluation provides a spatial distribution of TOC at the reservoir scale as compared to the conventional distribution generated from samples collected over sparse wells. The approach presented in this work has wider applications for source rock evaluation in other similar petroliferous basins worldwide.

Deviations in South Asian Summer Monsoon (SASM) precipitation affect the regional floods and drought patterns. In the current study, in-situ observations from Pakistan Meteorological Department (PMD), remotely sensed precipitation data from Climate Hazard Infrared Precipitation with Station data (CHIRPS), reanalysis data from ERA5, and National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) during 1981–2018 are used to explore the atmospheric circulation patterns during above and below-normal precipitation episodes. In a statistical sense, two methods, namely the Empirical Orthogonal Function (EOF) and Percent Normal (PN) indices are used to derive dominant spatial patterns and temporal evolution of extreme monsoon precipitation episodes. Results inferred 60% of the variance to the leading EOF mode depicting a similar spatial pattern of eigenvectors across the region. The leading principal component (PC) and PN index together depicted similar deviations, complementing the extreme flooding and drought years. From the composites, an anomalous increase (decrease) in seasonal precipitation magnitude was observed. The possible mechanism suggests an active control of atmospheric and sea-surface temperature (SST) forcing by altering the wind ascent (descent). The jet streams (200 hPa) intensification of Rossby waves high (low) pressure provides favorable frontal boundaries between polar cold and tropical warm air masses. The westerlies and easterlies are intensified (suppressed) during the above (below) normal precipitation composites, affecting the moisture transport. The enhanced (reduced) convective activities in the Indian Ocean as a primary source affected precipitation in the region during each composite.

This study was designed to evaluate the spatiotemporal performance of the Coupled Model Intercomparison Project Phase 5 (CMIP5) models in the historical simulation and future projections of minimum (Tmin), maximum (Tmax), and mean temperature (Tmean) over South Asia (SA) during global warming of 1.5 oC, 2 oC, and 3 oC targets under RCP4.5 and RCP8.5 scenarios. It is worth mentioning that the present study is the first of its kind to use such a large number of CMIP5 models to project future changes in Tmin, Tmax, and Tmean over SA using three different warming thresholds. The results show that CSIRO–MK3–6–0, MIROC–ESM–CHEM, CNRM–CM5, CCSM4, and MRI–CGCM3 models relatively performed better with a consistent and accurate spatiotemporal simulation of Tmin, Tmax, and Tmean over SA. In terms of projected changes, Tmin, Tmax, and Tmean show a dominating and consistent warming pattern over SA with stronger intensity in higher latitude than mid–low latitudes under 1.5 oC, 2 oC, and 3 oC warming thresholds. The northwestern (eastern) regions of SA will witness greater (least) warming in Tmin, Tmax, and Tmean under all warming thresholds in RCP4.5 and RCP8.5 scenarios. Furthermore, the central and southern parts of SA will experience a moderate increase in Tmin, Tmax, and Tmean under all warming targets. The uneven and intensified patterns of Tmin, Tmax, and Tmean may result in temperature extremes, which would pose potential risks to the local population. Therefore, more attention should be paid on the regional and local perspectives to estimate the adverse impacts of these extremes under different global warming targets. We further suggest to project future changes in climate extremes over SA under different warming levels, which will be helpful in climate change adaptation and mitigation over the study region.

Various state-of-the-art gridded satellite precipitation products (GPPs) have been derived from remote sensing and reanalysis data and are widely used in hydrological studies. An assessment of these GPPs against in-situ observations is necessary to determine their respective strengths and uncertainties. GPPs developed from satellite observations as a primary source were compared to in-situ observations, namely the Climate Hazard group Infrared Precipitation with Stations (CHIRPS), Multi-Source Weighted-Ensemble Precipitation (MSWEP), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA). These products were compared to in-situ data from 51 stations, spanning 1998–2016, across Pakistan on daily, monthly, annual and interannual time scales. Spatiotemporal climatology was well captured by all products, with more precipitation in the north eastern parts during the monsoon months and vice-versa. Daily precipitation with amount larger than 10 mm showed significant (95%, Kolmogorov-Smirnov test) agreement with the in-situ data, especially TMPA, followed by CHIRPS and MSWEP. At monthly scales, there were significant correlations (R) between the GPPs and in-situ records, suggesting similar dynamics; however, statistical metrics suggested that the performance of these products varies from north towards south. Temporal agreement on an interannual scale was higher in the central and southern parts which followed precipitation seasonality. TMPA performed the best, followed in order by CHIRPS, MSWEP and PERSIANN-CDR.