Precipitation assessment of Indian summer monsoon based on CMIP5 climate simulations

Babar, Zaheer Ahmad; Zhi, Xiefei; Ge, Fei

doi:10.1007/s12517-014-1518-4

Cited by 24 publications

(11 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Most of these models show their skill mainly for the Ganges basin, followed by the Brahmaputra, Mekong and Indus basins, respectively. Our results of better representation of seasonal cycle of monsoonal P for MIROC and CSIRO-Mk3-6-0 models (5 out of 12 metrics) are in agreement with Babar et al (2014).…”

Section: Summary Discussion and Conclusionsupporting

confidence: 88%

Seasonal cycle of precipitation over major river basins in South and Southeast Asia: A review of the CMIP5 climate models data for present climate and future climate projections

Hasson

Pascale²,

Lucarini

et al. 2016

Atmospheric Research

133

View full text Add to dashboard Cite

We review the skill of thirty coupled climate models participating in the Coupled Model Intercomparison Project 5 (CMIP5) in terms of reproducing properties of the seasonal cycle of precipitation over the major river basins of South and Southeast Asia (Indus, Ganges, Brahmaputra and Mekong) for the historical period . We also present projected changes by these models by the end of century (2061-2100) under the extreme scenario RCP8.5. First, we assess their ability to reproduce observed timings of the monsoon onset and the rate of rapid fractional accumulation (RFA slope) -a measure of seasonality within the active monsoon period. Secondly, we apply a threshold-independent seasonality index (SI) -a multiplicative measure of precipitation (P) and extent of its concentration relative to the uniform distribution (relative entropy -RE). We apply SI distinctly for the whole monsoonal precipitation regime (MPR), westerly precipitation regime (WPR) and annual precipitation regime. For the present climate, neither any single model nor the multi-model mean performs best in all chosen metrics. Models show overall a modest skill in suggesting right timings of the monsoon onset while the RFA slope is generally underestimated. One third of the models fail to capture the monsoon signal over the Indus basin. Mostly, SI estimates for WPR are simulated higher than observed for all basins, while for MPR, it is simulated higher (lower) for the Ganges and Brahmaputra (Indus and Mekong) basins, following the pattern of overestimation (underestimation) of precipitation. However, models are biased positive (negative) for RE estimates over the Indus and Ganges (Brahmaputra and Mekong) basins, implying the extent of precipitation concentration for MPR and number of dry days within WPR higher (lower) than observed for these basins. Under the RCP8.5 scenario, most of the models project a slightly delayed monsoon onset, and a general increase in the RFA slope, precipitation and extent of its concentration (RE), all suggesting a higher seasonality of the future MPR for all basins. Similarly, a modest inter-model agreement suggests a less intermittent WPR associated with a general decrease in number of wet days and a decrease (increase) in precipitation over the Indus and Ganges (Brahmaputra and Mekong) basins. Based on SI, multi-model mean suggests an extension of the monsoonal domain westward over northwest India and Pakistan and northward over China. These findings have serious implications for the food and water security of the region in the future.

show abstract

Section: Summary Discussion and Conclusionsupporting

confidence: 88%

Seasonal cycle of precipitation over major river basins in South and Southeast Asia: A review of the CMIP5 climate models data for present climate and future climate projections

Hasson

Pascale²,

Lucarini

et al. 2016

Atmospheric Research

133

View full text Add to dashboard Cite

show abstract

“…Overall ranks of GCMs for mean annual, monsoon and winter precipitation based on rating metric values.The better performance of NorESM1-M, CESM1-CAM5 and HadGEM2-AO in simulating precipitation over Indo-Pak subcontinent has also been reported in several past studies Babar et al (2014). assessed 13 CMIP5 GCMs for simulating Indian summer monsoon precipitation and found that NorESM1-M can capture the seasonal cycle of precipitation Anand et al (2018).…”

supporting

confidence: 63%

Selection of multi-model ensemble of GCMs for the simulation of precipitation based on spatial assessment metrics

Ahmed

Sachindra

Shahid

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. The climate modelling community has trialled a large number metrics to evaluate the temporal performance of the Global Circulation Models (GCMs) for the selection of GCMs, while very little attention has been given to spatial performance of GCMs which is equally important. This study evaluated the performance of 20 Coupled Model Intercomparison Project 5 (CMIP5) GCMs pertaining to their skills in simulating mean annual, monsoon and winter precipitation over Pakistan using state-of-the-art spatial metrics; SPAtial EFficiency, Goodman–Kruskal's lambda, Fractions Skill Score, Cramer’s V, Mapcurves, and Kling-Gupta efficiency for the period 1961–2005. The multi-model ensemble (MME) precipitation was generated through intelligent merging of simulated precipitation of selected GCMs employing Random Forest (RF) regression and Simple Mean (SM). The results indicated some differences in the ranks of GCMs for different metrics. The overall ranks indicated NorESM1-M, CESM1-CAM5, GFDL-CM3 and GFDL-ESM2G as the best GCMs in simulating the spatial patterns of mean annual, monsoon and winter precipitation over Pakistan. MME precipitation generated based on the best performing GCMs showed more similarities with observed precipitation compared to precipitation simulated by individual GCMs. The MME developed using RF displayed better performance than the MME-based on SM. Multiple spatial metrics have been used for the first time for selecting GCMs based on their capability to mimic the spatial patterns of annual and seasonal precipitation. The approach suggested in the present study can be extended to any number of GCMs and climate variables and applicable to any region for the suitable selection of an ensemble of GCMs to reduce uncertainties in climate projections.

show abstract

“…RCP4.5 and RCP8.5 correspond to the Special Report on Emissions Scenarios (SRES) B1 and A1F1 in terms of temperature anomaly. Three GCM (i.e., MIROC5, BCC-CSM1.1, and CanESM2) were selected from the literature review based on their performance and have been used widely in climate change studies in South Asia [29][30][31]. Table A1 provides the detail description (development countries, spatial resolution, and time) of all the GCMs used in this study.…”

Section: Representative Concentration Pathway (Rcps) Scenariosmentioning

confidence: 99%

Simulating the Impact of Climate Change on the Hydrological Regimes of a Sparsely Gauged Mountainous Basin, Northern Pakistan

Saddique

Usman

Bernhofer

2019

Water

View full text Add to dashboard Cite

Projected climate changes for the 21st century may cause great uncertainties on the hydrology of a river basin. This study explored the impacts of climate change on the water balance and hydrological regime of the Jhelum River Basin using the Soil and Water Assessment Tool (SWAT). Two downscaling methods (SDSM, Statistical Downscaling Model and LARS-WG, Long Ashton Research Station Weather Generator), three Global Circulation Models (GCMs), and two representative concentration pathways (RCP4.5 and RCP8.5) for three future periods (2030s, 2050s, and 2090s) were used to assess the climate change impacts on flow regimes. The results exhibited that both downscaling methods suggested an increase in annual streamflow over the river basin. There is generally an increasing trend of winter and autumn discharge, whereas it is complicated for summer and spring to conclude if the trend is increasing or decreasing depending on the downscaling methods. Therefore, the uncertainty associated with the downscaling of climate simulation needs to consider, for the best estimate, the impact of climate change, with its uncertainty, on a particular basin. The study also resulted that water yield and evapotranspiration in the eastern part of the basin (sub-basins at high elevation) would be most affected by climate change. The outcomes of this study would be useful for providing guidance in water management and planning for the river basin under climate change.

show abstract

Precipitation assessment of Indian summer monsoon based on CMIP5 climate simulations

Cited by 24 publications

References 34 publications

Seasonal cycle of precipitation over major river basins in South and Southeast Asia: A review of the CMIP5 climate models data for present climate and future climate projections

Seasonal cycle of precipitation over major river basins in South and Southeast Asia: A review of the CMIP5 climate models data for present climate and future climate projections

Selection of multi-model ensemble of GCMs for the simulation of precipitation based on spatial assessment metrics

Simulating the Impact of Climate Change on the Hydrological Regimes of a Sparsely Gauged Mountainous Basin, Northern Pakistan

Contact Info

Product

Resources

About