Water scarcity and water quality degradation are exacerbated by climate change in all countries, including Pakistan. The use of water in agriculture is one of the most predominant resources, so reducing consumption and improving resource management is of utmost importance. In the past few decades, excessive irrigation has led to severe water scarcity and reduced water quality. This study determined the irrigation requirements for cotton, rice, and wheat, using the CROPWAT model in Southern Punjab (Multan District). In the study area, evapotranspiration ranged from 1.8 to 10.24 mm/day, while effective rainfall ranged from 2 to 31.3 mm. Rice, cotton, and wheat each required 996.4, 623.3, and 209.5 mm of irrigation, respectively. Among rice, cotton, and wheat, the total net irrigation was 72.4, 67.8, and 44.1 mm, respectively, while the total gross irrigation was 103.5, 99.8, and 63 mm. The CROPWAT model showed a moderately useful result for identifying irrigation needs in Southern Punjab. The study emphasizes the need for groundwater harvesting and water management technologies to implement a water management system that reduces water shortages.

Middle East surface air temperature (ME-SAT), during boreal summer (June to August: JJA), shows robust multidecadal variations for the period 1948−2016. Here, using observational and reanalysis datasets, as well as coupled atmosphere–ocean model simulations, we linked the observed summer ME-SAT variability to the multidecadal variability of sea surface temperature (SST) in the North Atlantic Ocean (AMV). This Atlantic−ME connection during summer involves ocean–atmosphere interactions through multiple ocean basins, with an influence from the Indian Ocean and the Arabian Sea. The downstream response to Atlantic SST is a weakening of the subtropical westerly jet stream that impacts summer ME-SAT variability through a wave-like pattern in the upper tropospheric levels. The Atlantic SST response is further characterized by positive geopotential height anomalies in the upper levels over the Eurasian region and a dipole-like pressure distribution over the ME in lower levels. For positive Atlantic SST anomalies this pressure gradient initiates anomalous low-level southerly flow, which transports moisture from the neighboring water bodies toward the extremely hot and dry ME landmass. The increase in atmospheric moisture reduces the longwave radiation damping of the SAT anomaly, increasing further ME-SAT. A suite of Atlantic Pacemaker experiments skillfully reproduces the North Atlantic–ME teleconnection. Our findings reveal that in observations and models the Atlantic Ocean acts as a critical pacemaker for summer ME-SAT multidecadal variability and that a positive AMV can lead to enhanced summer warming over the Middle East.

This paper provides an updated assessment of the “International Research Institute for Climate and Society’s (IRI) El Niño Southern Oscillation (ENSO) Predictions Plume”. We evaluate 253 real-time forecasts of the Niño 3.4 index issued from February 2002 to February 2023 and examine multimodal means of dynamical (DYN) and statistical (STAT) models separately. Forecast skill diminishes as lead time increases in both DYN and STAT forecasts, with peak accuracy occurring post-northern hemisphere spring predictability barrier and preceding seasons. The DYN forecasts outperform STAT forecasts with a pronounced advantage in forecasts initiated from late boreal winter through spring. The analysis uncovers an asymmetry in predicting the onset of cold and warm ENSO episodes, with warm episode onsets being better forecasted than cold onsets in both DYN and STAT models. The DYN forecasts are found to be valuable for predicting warm and cold ENSO episode onsets at least several months in advance, while STAT forecasts are less informative about ENSO phase transitions. The results indicate that predicting ENSO onset is challenging and that the ability to do so is both model- and event-dependent.

In South Asia (SA), the boreal summer monsoon (June to September; JJAS) and the El Niño-Southern Oscillation (ENSO) are connected, though different areas in SA respond differently to ENSO. In this paper, a new 41-year (1981 to 2021) high-resolution gridded rainfall dataset (ENACTS-BMD; Enhancing National Climate Services for Bangladesh Meteorological Department) is used to investigate the linkage between the Bangladesh Summer Monsoon Rainfall (BSMR) and ENSO. Observed BSMR shows a weak positive correlation (r = + 0.21, not statistically significant at the 5% level) with sea surface temperatures (SST) in the central-eastern (Niño3.4) Pacific region. Among the eight El Niño events, seven of them corresponded to above-normal BSMR. However, during the 11 La Niña events, the relationship was more varied, with above-normal BSMR occurring in seven instances. These findings highlight an asymmetric relationship between BSMR and ENSO. Furthermore, BSMR is negatively correlated (r = − 0.47 statistically significant at the 5% level) with Indian Summer Monsoon Rainfall (ISMR: 75°–85^oE, 18°–30^oN). The potential physical mechanism can be outlined as follows: during El Niño, the Walker circulation tends to be weakened, resulting in a weakening of the summer monsoon circulation, which in turn reduces the intensity of easterly winds along the Bangladesh Himalayan foothills. Subsequently, a lower-level anomalous cyclonic circulation is established, facilitating the convergence of moisture within the boundary layer. This, in turn, leads to intensified rainfall over Bangladesh and the surrounding regions during El Niño. Seasonal forecast models do not adequately capture BSMR and ENSO, BSMR and circulation, and BSMR and ISMR inverse correlations. While the observed BSMR-ENSO relationship is complex and teleconnections are weak, awareness of the inverse relationship with ISMR and the incorrect model behavior could be useful in the context of seasonal BSMR predictions.