Published January 24, 2019 | Version v1
Journal article

Low fidelity of CORDEX and their driving experiments indicates future climatic uncertainty over Himalayan watersheds of Indus basin

  • 1. University of Hamburg, Centre for Earth System Research and Sustainability (CEN), Institute of Geography (Germany)
  • 2. Asian Disaster Preparedness Center, SERVIR-Mekong (Thailand)

Description

Assessment of future water availability from the Himalayan watersheds of Indus Basin (Jhelum, Kabul and upper Indus basin—UIB) is a growing concern for safeguarding the sustainable socioeconomic wellbeing downstream. This requires, before all, robust climate change information from the present-day state-of-the-art climate models. However, the robustness of climate change projections highly depends upon the fidelity of climate modeling experiments. Hence, this study assesses the fidelity of seven dynamically refined (0.44) experiments, performed under the framework of the coordinated regional climate downscaling experiment for South Asia (CX-SA), and additionally, their six coarse-resolution driving datasets participating in the coupled model intercomparison project phase 5 (CMIP5). We assess fidelity in terms of reproducibility of the observed climatology of temperature and precipitation, and the seasonality of the latter for the historical period (1971–2005). Based on the model fidelity results, we further assess the robustness or uncertainty of the far future climate (2061–2095), as projected under the extreme-end warming scenario of the representative concentration pathway (RCP) 8.5. Our results show that the CX-SA and their driving CMIP5 experiments consistently feature low fidelity in terms of the chosen skill metrics, suggesting substantial cold (6–10 C) and wet (up to 80%) biases and underestimation of observed precipitation seasonality. Surprisingly, the CX-SA are unable to outperform their driving datasets. Further, the biases of CX-SA and of their driving CMIP5 datasets are higher in magnitude than their projected changes under RCP8.5—and hence under less extreme RCPs—by the end of 21st century, indicating uncertain future climates for the Indus Basin watersheds. Higher inter-dataset disagreements of both CMIP5 and CX-SA for their simulated historical precipitation and for its projected changes reinforce uncertain future wet/dry conditions whereas the CMIP5 projected warming is less robust owing to higher historical period uncertainty. Interestingly, a better agreement among those CX-SA experiments that have been obtained through downscaling different CMIP5 experiments with the same regional climate model (RCM) indicates the RCMs' ability of modulating the influence of lateral boundary conditions over a large domain. These findings, instead of suggesting the usual skill-based identification of 'reasonable' global or regional low fidelity experiments, rather emphasize on a paradigm shift towards improving their fidelity by exploiting the potential of meso-to-local scale climate models—preferably of those that can solely resolve global-to-local scale climatic processes—in terms of microphysics, resolution and explicitly resolved convections. Additionally, an extensive monitoring of the nival regime within the Himalayan watersheds will reduce the observational uncertainty, allowing for a more robust fidelity assessment of the climate modeling experiments.

Additional details

Identifiers

Publishing Information

Journal Title
Climate Dynamics
Journal Volume
52
Journal Issue
1-2
Journal Page Range
p. 777-798
ISSN
0930-7575
CODEN
CLDYEM

INIS

Country of Publication
Germany
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52000670
Subject category
S54: ENVIRONMENTAL SCIENCES;
Descriptors DEI
AFGHANISTAN; ATMOSPHERIC PRECIPITATIONS; CLIMATE MODELS; COMPUTERIZED SIMULATION; FORECASTING; GREENHOUSE EFFECT; HIMALAYAS; HUMIDITY; INDIA; METEOROLOGY; PAKISTAN; REGRESSION ANALYSIS; WATERSHEDS
Descriptors DEC
ASIA; CLIMATIC CHANGE; DEVELOPING COUNTRIES; MATHEMATICAL MODELS; MATHEMATICS; MOISTURE; MOUNTAINS; SIMULATION; STATISTICS

Optional Information

Copyright
Copyright (c) 2018 The Author(s)