Spatiotemporal Precipitation Trends and Associated Large-Scale Teleconnections in Northern Pakistan

Abstract

The effects of climate change are unparalleled in magnitude, ranging from changing weather patterns that endanger food production to increasing sea levels that increase the likelihood of catastrophic flooding. Therefore, determining the extent of such variations on regional and local scales is imperative. We used monthly precipitation data from 25 meteorological stations in northern Pakistan (NP) to document the observed changes in seasonal and annual precipitation. The station density in the NP is small and unevenly distributed; therefore, ERA-5 reanalysis data were used to supplement the observed dataset to assess the spatial trends in NP. The non-parametric Mann–Kendall (MK), Sen’s Slope estimator (SSE), and Sequential Mann–Kendall (SQMK) tests were performed to assess the trends. In addition, the wavelet analysis technique was used to determine the association of precipitation with various oceanic indices from 1960 to 2016. Results indicate that maximum precipitation was shown in the annual and summer seasons. In NP, annual, winter, spring, and summer precipitation declined, while an increase in autumn was observed at a rate of 0.43 mm/decade between 1989 and 2016. The spatial trends for observed and ERA-5 reanalysis datasets were almost similar in winter, spring, and autumn; however, some disagreement was observed in both datasets in the summer and annual precipitation trends in NP during 1960–2016. Between 1989 and 2016, summer and annual precipitation increased significantly in Region III. However, seasonal and annual precipitation decreased in NP between 1960 and 2016. Moreover, there were no prominent trends in annual precipitation until the mid-1980s, but an apparent increase from 1985 onwards. Annual precipitation increased in all elevations except at the 500–1000 m zone. The ENSO (El Niño–Southern Oscillation) shared notable interannual coherences among all indices above 16–64 months. Inter-decadal coherence with the ENSO, AO (Arctic Oscillation), and PDO (Pacific Decadal Oscillation) in NP for 128 months and above. Generally, AO, AMO (Atlantic Multidecadal Oscillation), and NAO (North Atlantic Oscillation) exhibited less coherence with precipitation in NP. The regression of seasonal and annual precipitation revealed that winter and spring precipitation levels had higher linear regression with the AO and ENSO, respectively, while both the AO and ENSO also dominated at the annual scale. Similarly, the IOD and PDO indices had a higher influence in summer precipitation. The findings may help water resource managers and climate researchers develop a contingency plan for better water resource management policies in the face of changing climate change in Pakistan, particularly in NP.

Augmented human thermal discomfort in urban centers of the Arabian Peninsula

“…The same is evident for the ENSO4.0 but the dipole pattern shows a regionally varying effect. The mechanism of the dipole pattern for the eastern Pacific and UTCI min could be related to the ENSO-driven monsoon circulation that affects the South Asian monsoon through controlling the zonal easterlies and hence a negative relationship with the eastern parts of AP and positive relationship with the western AP 72 , 73 , 94 , 95 . The eastern Pacific on the other hand appeared to have widespread global effects and thus its positive mode could affect the Indian Ocean basin-wide forcing and the overall thermal stress regime of the AP region 96 – 99 .…”

“…We preferred these non-parametric tests over other statistical tests as they are simple and robust against outliers and missing values in a time series 70 , 71 . Furthermore, these tests are less sensitive to abrupt breaks in a time series and do not require data normalization 72 , 73 . More details about SSE and m-MK tests can be found in recent studies 74 , 75 .…”

Ocean–atmosphere circulation coherences associated with temperature increase in Pakistan

“…El Niño, the warm phase of ENSO, is associated with enhanced precipitation over South Asia, whereas La Niña, the cold phase, is associated with suppressed precipitation and drought (Barlow et al 2021). For instance, Rebi et al (2023) and Nawaz et al (2023) observed dominant interannual precipitation coherences in northern Pakistan. The population in southern Pakistan is highly dependent on agriculture to meet basic livelihood needs.…”

“…Like, the stations were selected based on data length, completeness, and quality (i.e. consistency and homogeneity), and deviations attributed to climatic and non-climatic factors were checked (Kidd et al 2017, Ullah et al 2021, Hussain et al 2022a, 2022c, Rebi et al 2023. As, it is important to guarantee that observed temperature trends must represent natural variability instead of non-climatic factors, such as heat islands (El Kenawy et al 2012, Hussain et al 2023b.…”

A novel approach for evaluation of CMIP6 GCMs in simulating temperature and precipitation extremes of Pakistan

“…The ERA5 dataset, which has a horizontal spatial resolution of 30 km, combines extensive past climate observations into global‐scale approximations using advanced modelling techniques and data integration methods (Ali et al, 2022; Mistry et al, 2022). Due to the lack of long‐term observational data from various weather stations across Pakistan, the ERA5 dataset was chosen for this region due to its higher resolution and availability over an extended period (Rebi et al, 2023; Waseem et al, 2022; Zittis et al, 2016). Compared to other products, this ERA5 reanalysis product performed well in reproducing climate variables such as precipitation and temperature in the region (Ali et al, 2022; Waseem et al, 2022).…”