Variability, trends, and teleconnections of observed precipitation over Pakistan

et al. 2020

Water

Assessing the long-term precipitation changes is of utmost importance for understanding the impact of climate change. This study investigated the variability of extreme precipitation events over Pakistan on the basis of daily precipitation data from 51 weather stations from 1980-2016. The non-parametric Mann–Kendall, Sen’s slope estimator, least squares method, and two-tailed simple t-test methods were used to assess the trend in eight precipitation extreme indices. These indices were wet days (R1 ≥1 mm), heavy precipitation days (R10 ≥ 10 mm), very heavy precipitation days (R20 ≥ 20 mm), severe precipitation (R50 ≥ 50 mm), very wet days (R95p) defining daily precipitation ≥ 95 percentile, extremely wet days (R99p) defining daily precipitation ≥ 99 percentile, annual total precipitation in wet days (PRCPTOT), and mean precipitation amount on wet days as simple daily intensity index (SDII). The study is unique in terms of using high stations’ density, extended temporal coverage, advanced statistical techniques, and additional extreme indices. Furthermore, this study is the first of its kind to detect abrupt changes in the temporal trend of precipitation extremes over Pakistan. The results showed that the spatial distribution of trends in different precipitation extreme indices over the study region increased as a whole; however, the monsoon and westerlies humid regions experienced a decreasing trend of extreme precipitation indices during the study period. The results of the sequential Mann–Kendall (SqMK) test showed that all precipitation extremes exhibited abrupt dynamic changes in temporal trend during the study period; however, the most frequent mutation points with increasing tendency were observed during 2011 and onward. The results further illustrated that the linear trend of all extreme indices showed an increasing tendency from 1980- 2016. Similarly, for elevation, most of the precipitation extremes showed an inverse relationship, suggesting a decrease of precipitation along the latitudinal extent of the country. The spatiotemporal variations in precipitation extremes give a possible indication of the ongoing phenomena of climate change and variability that modified the precipitation regime of Pakistan. On the basis of the current findings, the study recommends that future studies focus on underlying physical and natural drivers of precipitation variability over the study region.

Section: The Trend In Extreme Precipitation Indicesmentioning

confidence: 99%

Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan

Bhatti

Wang

et al. 2020

Water

“…However, the impacts of temperature extremes on hydrological balance and river flow at high altitude remain poorly understood because of high meteorological variability, physical inaccessibility, and the complex interaction between climate, cryosphere, and hydrological processes (Ragettli et al, 2016). The region receives heavy snow in winter season due to mid-latitude western disturbance (Iqbal and Athar, 2017;Hunt et al, 2018), while intense precipitation in summer season due to South Asian monsoon systems (Wang et al, 2011;Priya et al, 2017;Wang et al, 2017). Recent studies reported that the spatiotemporal variability of temperature and precipitation in northern Pakistan has significant effects on water availability of the Indus River network (Hartmann and Buchanan, 2014;Ahmad et al, 2015).…”

Section: Elevation-dependent Warmingmentioning

confidence: 99%

Observed changes in temperature extremes over China–Pakistan Economic Corridor during 1980–2016

You

Intl Journal of Climatology

et al. 2018

This study uses the daily maximum and minimum temperature data sets of 48 meteorological stations to assess the observed changes in temperature extremes over China–Pakistan Economic Corridor (CPEC) during 1980–2016. The nonparametric Mann–Kendall, Sen's slope estimator, least squares method, and two‐tailed simple t‐test methods were used to assess the trend in nine temperature extreme indices. The results of the study indicated that the trends in annual mean anomalies of cold nights, cold days, and frost days significantly decreased at the rates of −1.09, −1.58, and −1.05 day/decade, respectively. The number of warm nights, warm days, and summer days exhibited significant positive trends at the rates of 1.49, 1.04, and 4.32 day/decade, respectively. In addition, the trends of the warmest day and coldest day also increased significantly at the rates of 0.45 and 0.51 °C/decade, respectively. The trend of diurnal temperature range decreased significantly with −0.35 °C/decade. The spatial distribution of temperature extreme indices indicated that the number of cold nights, cold days, and diurnal temperature range have been decreased, while the trends of warm nights, warm days, summer days, warmest day, and coldest day have been increased over the whole country. Large‐scale atmospheric circulation changes derived from ERA‐Interim reanalysis show that a weak (strong) wind pressure, increasing (decreasing) geopotential height, and rapid warming (cooling) over the northern (southern) region have contributed to the changes in temperature extremes in Pakistan to some extent. With respect to elevation‐dependent warming (EDW), the trends of cold nights, warm days, summer days, warmest day, and diurnal temperature range showed significant positive correlations with increasing elevation. However, the trends of cold days, warm nights, frost days, and coldest day showed significant negative relationships with increasing elevation. The findings of this study will be helpful in the adaptation of climate change and mitigation of climatological disasters in the region. The study recommends that future studies should investigate the natural and anthropogenic drivers of temperature extremes and the possible mechanism of EDW in the CPEC region.

Intl Journal of Climatology

“…As discussed earlier, negative DTR years are mainly associated with higher precipitation as compared to positive DTR years. It has been observed that precipitation variability in the region is mainly explained by ENSO variation (see, e.g., Iqbal and Athar, ). The strong impact of ENSO on regional DTR in negative DTR years may be attributed to precipitation variability of the region.…”

Section: Discussionmentioning

confidence: 99%

“…In order to assess the influence of the large-scale atmospheric circulation on the regional DTR, El Niño-Southern Oscillation (ENSO) index is used in this study (see, e.g., Iqbal and Athar, 2017). Furthermore, European Centre for Medium-Range Weather Forecasts (ECMWF) based monthly ERA-Interim reanalysis data for specific humidity, u wind and v wind with 0.125 × 0.125 spatial grid resolution at 1,000, 925 and 850 hPa are used in this study (Dee et al, 2011).…”

Section: Observed and Reanalysis Datamentioning

confidence: 99%

Observed diurnal temperature range variations and its association with observed cloud cover in northern Pakistan

Ahmad

Athar

2018

Self Cite

Spatio‐temporal variability in the observed diurnal temperature range (DTR) for the recent 30‐year period (1986–2015) is examined from a total of 18 weather stations in Hindukush Karakoram Himalaya region of northern Pakistan (HKNP). The daily maximum and minimum temperature data are used to compute the regional DTR, whereas observed total cloud cover (TCC) is used to assess its possible relationship with regional DTR, both on seasonal and annual basis. The regional mean DTR is 13.27 °C on annual basis, with a maximum in autumn (14.63 °C) and minimum in winter (11.81 °C). On annual basis, the regional DTR has increased significantly at a rate of .34 °C/decade, during the 30‐year study period at p ≤ .05, based on Mann–Kendall test. On seasonal basis, the DTR displays an increasing trend in all four seasons with largest significant increase in the winter season at a rate of .32 °C/decade. The DTR is positively correlated with maximum temperature of the region on seasonal and annual basis. Strong negative correlation is found between the DTR and observed TCC in all seasons, indicating that variability in TCC has an impact on the variation of DTR in this region. The statistically significant increasing DTR trend along with statistically significant decreasing trend of TCC in spring season suggests an early melt of snow and ice covers in the region, consequently changing the hydrological cycle of the region that demands a better water resource management in the HKNP.