scholarly journals Does increasing the spatial resolution in dynamical downscaling impact climate change projection of Indian summer monsoon, population and GDP?

2021 ◽  
Author(s):  
C. B. Jayasankar ◽  
K. Rajendran ◽  
Surendran Sajani
Keyword(s):  
Climate Change ◽  
Spatial Resolution ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Dynamical Downscaling ◽  
Climate Change Projection

scholarly journals Does increasing the spatial resolution in dynamical downscaling impact climate change projection of Indian summer monsoon, population and GDP?

2021 ◽  
Author(s):  
Jayasankar C B ◽  
Rajendran K ◽  
Sajani Surendran
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Urban Areas ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Climate Change Projection ◽  
Future Population

Abstract High-resolution regional climate model (RCM) simulations are found to be very useful in deriving realistic climate change projection information. This study uses high-resolution dynamical downscaling framework (CCSM4-WRF) for India. To delineate the advantage of high resolution, we compared the results of 9-km resolution CCSM4-WRF simulations against the 50-km resolution RCM simulations under Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) programme. Quantitative estimations show that majority of CORDEX-SA models exhibit large dry bias (<-4mm/day) and low pattern correlation coefficient (PCC) over the Western Ghats (WG). Mean climatology of Indian summer monsoon (ISM) rainfall simulated by high-resolution CCSM4-WRF outperforms the CORDEX-SA RCMs with low negative biases (~ 1mm/day) and high PCC (≥ 0.755). This skill of CCSM4-WRF provides better confidence in its future projection at local scale. CCSM4-WRF projects future intensification of monsoon rainfall over most parts of India and reduction over southern WG, which is consistent with recent observed trends, but none of the CORDEX-SA RCMs could simulate this rainfall reduction. For all-India rainfall, ensemble mean of CORDEX-SA models projects an increase by 1.3 ± 0.9mm/day and CCSM4-WRF projects 0.67mm/day. Projected changes in socioeconomic variables such as population and gross domestic product (GDP) exhibit future enhancement over most parts of India but with spatial heterogeneity. Shared Socioeconomic Pathways scenarios show pronounced future population growth over Indian coastal areas, and large enhancement in productivity over urban areas. Therefore, climate change projection information of ISM rainfall, together with enhanced future population and GDP, is useful for taking necessary steps for adaptation and mitigation in a sustainable manner.

scholarly journals Climate change projection of snowfall in the Colorado River Basin using dynamical downscaling

2012 ◽  
Vol 48 (5) ◽  
Author(s):  
Sungwook Wi ◽  
Francina Dominguez ◽  
Matej Durcik ◽  
Juan Valdes ◽  
Henry F. Diaz ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Colorado River ◽  
Dynamical Downscaling ◽  
Colorado River Basin ◽  
Climate Change Projection

scholarly journals How extreme could the near term evolution of the Indian Summer Monsoon rainfall be?

2021 ◽  
Author(s):  
Shipra Jain ◽  
Adam A. Scaife
Keyword(s):  
Climate Change ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Monsoon Rainfall ◽  
Indian Summer Monsoon Rainfall ◽  
Internal Variability ◽  
Summer Monsoon Rainfall ◽  
Climate Change Signal ◽  
Worst Case ◽  
Rainfall Trends

Abstract We provide a methodology to estimate possible extreme changes in seasonal rainfall for the coming decades. We demonstrate this methodology using Indian summer monsoon rainfall as an example however it can be extended to other climate variables, regions and timescale conditional to the model forecasts being a good representative of the observations in current climate. We use an ensemble of ~1600 initialized climate simulations from selected seasonal prediction systems to estimate internal variability and how it can exacerbate or alleviate forced climate change. Our estimates show that for the next decade there is a ~60% chance of wetting trends whereas the chance of drying is ~40%. Wetting trends are systematically more favoured than drying with increasing length of the period. This provides a quantitative explanation for the varying trends in the past observational record of rainfall over India. We also quantify the likelihood of extreme trends and show that there is at least a 1% chance that monsoon rainfall could increase or decrease by one fifth over the next decade and that more extreme trends, though unlikely, are possible. We find that monsoon rainfall trends are influenced by trends in sea-surface temperatures over the Niño3.4 region and tropical Indian Ocean, and ~1.5° cooling or warming of these regions can approximately double or negate the influence of climate change on rainfall over the next two decades. We also investigate the time-of-emergence of climate change signals in rainfall trends and find that it is unlikely for a climate change signal to emerge by the year 2050 due to the large internal variability of monsoon rainfall. The estimates of extreme rainfall change provided here could be useful for governments to prepare for worst-case scenarios and therefore aid disaster preparedness and decision-making.

scholarly journals Selecting Ensemble Members to Provide Regional Climate Change Information

2012 ◽  
Vol 25 (20) ◽  
pp. 7100-7121 ◽  
Author(s):  
Carol F. McSweeney ◽  
Richard G. Jones ◽  
Ben B. B. Booth
Keyword(s):  
Climate Change ◽  
Summer Monsoon ◽  
Dynamical Downscaling ◽  
Asian Summer Monsoon ◽  
Regional Climate ◽  
Full Range ◽  
Regional Climate Change ◽  
Climate Projections ◽  
Similar Data ◽  
Asian Summer

Abstract Climate model ensembles, such as the Coupled Model Intercomparison Project, phase 3 (CMIP3), are used to characterize broadscale ranges of projected regional climate change and their impacts. The 17-member Hadley Centre perturbed physics GCM ensemble [Quantifying Uncertainty in Model Predictions (“QUMP”)] extends this capability by including data enabling dynamical downscaling of these ranges, and similar data are now being made available from the CMIP phase 5 (CMIP5) GCMs. These raise new opportunities to provide and apply high-resolution regional climate projections. This study highlights the importance of employing a well-considered sampling strategy from available ensembles to provide scientifically credible information on regional climate change while minimizing the computational complexity of ensemble downscaling. A subset of the QUMP ensemble is selected for a downscaling program in Vietnam using the Providing Regional Climates for Impacts Studies (PRECIS) regional climate modeling system. Multiannual mean fields from each GCM are assessed with a focus on the Asian summer monsoon, given its importance to proposed applications of the projections. First, the study examines whether any model should be eliminated because significant deficiencies in its simulation may render its future climate projections unrealistic. No evidence is found to eliminate any of the 17 GCMs on these grounds. Second, the range of their future projections is explored and five models that best represent the full range of future climates are identified. The subset characterizes the range of both global and regional responses, and patterns of rainfall response, the wettest and driest projections for Vietnam, and different projected Asian summer monsoon changes. How these ranges of responses compare with those in the CMIP3 ensemble are also assessed, finding differences in both the signal and the spread of results in Southeast Asia.

scholarly journals Evaluating the timing and structure of the 4.2 ka event in the Indian summer monsoon domain from an annually resolved speleothem record from Northeast India

2018 ◽  
Vol 14 (12) ◽  
pp. 1869-1879 ◽  
Author(s):  
Gayatri Kathayat ◽  
Hai Cheng ◽  
Ashish Sinha ◽  
Max Berkelhammer ◽  
Haiwei Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Oxygen Isotope ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Northeast India ◽  
Large Array ◽  
Long Period ◽  
Proxy Records ◽  
Proxy Reconstructions

Abstract. A large array of proxy records suggests that the “4.2 ka event” marks an approximately 300-year long period (∼3.9 to 4.2 ka) of major climate change across the globe. However, the climatic manifestation of this event, including its onset, duration, and termination, remains less clear in the Indian summer monsoon (ISM) domain. Here, we present new oxygen isotope (δ18O) data from a pair of speleothems (ML.1 and ML.2) from Mawmluh Cave, Meghalaya, India, that provide a high-resolution record of ISM variability during a period (∼3.78 and 4.44 ka) that fully encompasses the 4.2 ka event. The sub-annually to annually resolved ML.1 δ18O record is constrained by 18 230Th dates with an average dating error of ±13 years (2σ) and a resolution of ∼40 years, which allows us to characterize the ISM variability with unprecedented detail. The inferred pattern of ISM variability during the period contemporaneous with the 4.2 ka event shares broad similarities and key differences with the previous reconstructions of ISM from the Mawmluh Cave and other proxy records from the region. Our data suggest that the ISM intensity, in the context of the length of our record, abruptly decreased at ∼4.0 ka (∼±13 years), marking the onset of a multi-centennial period of relatively reduced ISM, which was punctuated by at least two multi-decadal droughts between ∼3.9 and 4.0 ka. The latter stands out in contrast with some previous proxy reconstructions of the ISM, in which the 4.2 ka event has been depicted as a singular multi-centennial drought.

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