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Temperature Projections over the Indus River Basin of Pakistan Using Statistical Downscaling

1
Faculty of Medicine, Chair of Regional Climate Change and Health, Augsburg University, Alter Postweg 118, 86159 Augsburg, Germany
2
Climate, Energy and Water Research Institute, Pakistan Agricultural Research Council (PARC), Islamabad 44000, Pakistan
*
Author to whom correspondence should be addressed.
Academic Editor: Graziano Coppa
Atmosphere 2021, 12(2), 195; https://doi.org/10.3390/atmos12020195
Received: 3 November 2020 / Revised: 21 January 2021 / Accepted: 25 January 2021 / Published: 31 January 2021
(This article belongs to the Section Climatology)
We assessed maximum (Tmax) and minimum (Tmin) temperatures over Pakistan’s Indus basin during the 21st century using statistical downscaling. A particular focus was given to spatiotemporal heterogeneity, reference and General Circulation Model (GCM) uncertainties, and statistical skills of regression models using an observational profile that could significantly be improved by recent high-altitude observatories. First, we characterized the basin into homogeneous climate regions using K-means clustering. Predictors from ERA-Interim reanalysis were then used to model observed temperatures skillfully and quantify reference and GCM uncertainties. Thermodynamical (dynamical) variables mainly governed reference (GCM) uncertainties. The GCM predictors under RCP4.5 and RCP8.5 scenarios were used as “new” predictors in statistical models to project ensemble temperature changes. Our analysis projected non-uniform warming but could not validate elevation-dependent warming (EDW) at the basin scale. We obtained more significant warming during the westerly-dominated seasons, with maximum heating during the winter season through Tmin changes. The most striking feature is a low-warming monsoon (with the possibility of no change to slight cooling) over the Upper Indus Basin (UIB). Therefore, the likelihood of continuing the anomalous UIB behavior during the primary melt season may not entirely be ruled out at the end of the 21st century under RCP8.5. View Full-Text
Keywords: statistical downscaling; multiple linear regression; predictor uncertainty; model weighting; elevation-dependent warming statistical downscaling; multiple linear regression; predictor uncertainty; model weighting; elevation-dependent warming
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MDPI and ACS Style

Pomee, M.S.; Hertig, E. Temperature Projections over the Indus River Basin of Pakistan Using Statistical Downscaling. Atmosphere 2021, 12, 195. https://doi.org/10.3390/atmos12020195

AMA Style

Pomee MS, Hertig E. Temperature Projections over the Indus River Basin of Pakistan Using Statistical Downscaling. Atmosphere. 2021; 12(2):195. https://doi.org/10.3390/atmos12020195

Chicago/Turabian Style

Pomee, Muhammad S., and Elke Hertig. 2021. "Temperature Projections over the Indus River Basin of Pakistan Using Statistical Downscaling" Atmosphere 12, no. 2: 195. https://doi.org/10.3390/atmos12020195

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