scholarly journals Selection of CMIP5 general circulation model outputs of precipitation for peninsular Malaysia

2020 ◽  
Vol 51 (4) ◽  
pp. 781-798 ◽  
Author(s):  
Saleem A. Salman ◽  
Mohamed Salem Nashwan ◽  
Tarmizi Ismail ◽  
Shamsuddin Shahid

Abstract Reduction of uncertainty in climate change projections is a major challenge in impact assessment and adaptation planning. General circulation models (GCMs) along with projection scenarios are the major sources of uncertainty in climate change projections. Therefore, the selection of appropriate GCMs for a region can significantly reduce uncertainty in climate projections. In this study, 20 GCMs were statistically evaluated in replicating the spatial pattern of monsoon propagation towards Peninsular Malaysia at annual and seasonal time frames against the 20th Century Reanalysis dataset. The performance evaluation metrics of the GCMs for different time frames were compromised using a state-of-art multi-criteria decision-making approach, compromise programming, for the selection of GCMs. Finally, the selected GCMs were interpolated to 0.25° × 0.25° spatial resolution and bias-corrected using the Asian Precipitation – Highly-Resolved Observational Integration Towards Evaluation (APHRODITE) rainfall as reference data. The results revealed the better performance of BCC-CSM1-1 and HadGEM2-ES in replicating the historical rainfall in Peninsular Malaysia. The bias-corrected projections of selected GCMs revealed a large variation of the mean, standard deviation and 95% percentile of daily rainfall in the study area for two futures, 2020–2059 and 2060–2099 compared to base climate.

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Vimal Mishra ◽  
Udit Bhatia ◽  
Amar Deep Tiwari

Abstract Climate change is likely to pose enormous challenges for agriculture, water resources, infrastructure, and livelihood of millions of people living in South Asia. Here, we develop daily bias-corrected data of precipitation, maximum and minimum temperatures at 0.25° spatial resolution for South Asia (India, Pakistan, Bangladesh, Nepal, Bhutan, and Sri Lanka) and 18 river basins located in the Indian sub-continent. The bias-corrected dataset is developed using Empirical Quantile Mapping (EQM) for the historic (1951–2014) and projected (2015–2100) climate for the four scenarios (SSP126, SSP245, SSP370, SSP585) using output from 13 General Circulation Models (GCMs) from Coupled Model Intercomparison Project-6 (CMIP6). The bias-corrected dataset was evaluated against the observations for both mean and extremes of precipitation, maximum and minimum temperatures. Bias corrected projections from 13 CMIP6-GCMs project a warmer (3–5°C) and wetter (13–30%) climate in South Asia in the 21st century. The bias-corrected projections from CMIP6-GCMs can be used for climate change impact assessment in South Asia and hydrologic impact assessment in the sub-continental river basins.


Author(s):  
H. M. S. M. Herath ◽  
P. R. Sarukkalige ◽  
V. T. V. Nguyen

Abstract. Downscaling of climate projections is the most adopted method to assess the impacts of climate change at regional and local scale. In the last decade, downscaling techniques which provide reasonable improvement to resolution of General Circulation Models' (GCMs) output are developed in notable manner. Most of these techniques are limited to spatial downscaling of GCMs' output and still there is a high demand to develop temporal downscaling approaches. As the main objective of this study, combined approach of spatial and temporal downscaling is developed to improve the resolution of rainfall predicted by GCMs. Canberra airport region is subjected to this study and the applicability of proposed downscaling approach is evaluated for Sydney, Melbourne, Brisbane, Adelaide, Perth and Darwin regions. Statistical Downscaling Model (SDSM) is used to spatial downscaling and numerical model based on scaling invariant concept is used to temporal downscaling of rainfalls. National Centre of Environmental Prediction (NCEP) data is used in SDSM model calibration and validation. Regression based bias correction function is used to improve the accuracy of downscaled annual maximum rainfalls using HadCM3-A2. By analysing the non-central moments of observed rainfalls, single time regime (from 30 min to 24 h) is identified which exist scaling behaviour and it is used to estimate the sub daily extreme rainfall depths from daily downscaled rainfalls. Finally, as the major output of this study, Intensity Duration Frequency (IDF) relations are developed for the future periods of 2020s, 2050s and 2080s in the context of climate change.


MAUSAM ◽  
2021 ◽  
Vol 52 (1) ◽  
pp. 229-244
Author(s):  
K. RUPA KUMAR ◽  
R. G. ASHRIT

The regional climatic impacts associated with global climatic change and their assessment are very important since agriculture, water resources, ecology etc., are all vulnerable to climatic changes on regional scale. Coupled Atmosphere-Ocean general circulation model (AOGCM) simulations provide a range of scenarios, which can be used, for the assessment of impacts and development of adaptive or mitigative strategies. Validation of the models against the observations and establishing the sensitivity to climate change forcing are essential before the model projections are used for assessment of possible impacts. Moreover model simulated climate projections are often of coarse resolution while the models used for impact assessment, (e.g. crop simulation models, or river runoff models etc.) operate on a higher spatial resolution. This spatial mismatch can be overcome by adopting an appropriate strategy of downscaling the GCM output.   This study examines two AOGCM (ECHAM4/OPYC3 and HadCM2) climate change simulations for their performance in the simulation of monsoon climate over India and the sensitivity of the simulated monsoon climate to transient changes in the atmospheric concentrations of greenhouse gases and sulfate aerosols. The results show that the two models simulate the gross features of climate over India reasonably well. However the inter-model differences in simulation of mean characteristics, sensitivity to forcing and in the simulation of climate change suggest need for caution. Further an empirical downscaling approach in used to assess the possibility of using GCM projections for preparation of regional climate change scenario for India.


2016 ◽  
Vol 29 (10) ◽  
pp. 3831-3840 ◽  
Author(s):  
M. Matsueda ◽  
A. Weisheimer ◽  
T. N. Palmer

Abstract In earlier work, it was proposed that the reliability of climate change projections, particularly of regional rainfall, could be improved if such projections were calibrated using quantitative measures of reliability obtained by running the same model in seasonal forecast mode. This proposal is tested for fast atmospheric processes (such as clouds and convection) by considering output from versions of the same atmospheric general circulation model run at two different resolutions and forced with prescribed sea surface temperatures and sea ice. Here output from the high-resolution version of the model is treated as a proxy for truth. The reason for using this approach is simply that the twenty-first-century climate change signal is not yet known and, hence, no climate change projections can be verified using observations. Quantitative assessments of reliability of the low-resolution model, run in seasonal hindcast mode, are used to calibrate climate change time-slice projections made with the same low-resolution model. Results show that the calibrated climate change probabilities are closer to the proxy truth than the uncalibrated probabilities. Given that seasonal forecasts are performed operationally already at several centers around the world, in a seamless forecast system they provide a resource that can be used without cost to help calibrate climate change projections and make them more reliable for users.


2011 ◽  
Vol 3 (4) ◽  
pp. 281-292 ◽  
Author(s):  
Scott Greene ◽  
Laurence S. Kalkstein ◽  
David M. Mills ◽  
Jason Samenow

Abstract This study examines the impact of a changing climate on heat-related mortality in 40 large cities in the United States. A synoptic climatological procedure, the spatial synoptic classification, is used to evaluate present climate–mortality relationships and project how potential climate changes might affect these values. Specifically, the synoptic classification is combined with downscaled future climate projections for the decadal periods of 2020–29, 2045–55, and 2090–99 from a coupled atmospheric–oceanic general circulation model. The results show an increase in excessive heat event (EHE) days and increased heat-attributable mortality across the study cities with the most pronounced increases projected to occur in the Southeast and Northeast. This increase becomes more dramatic toward the end of the twenty-first century as the anticipated impact of climate change intensifies. The health impact associated with different emissions scenarios is also examined. These results suggest that a “business as usual” approach to greenhouse gas emissions mitigation could result in twice as many heat-related deaths by the end of the century than a lower emissions scenario. Finally, a comparison of future estimates of heat-related mortality during EHEs is presented using algorithms developed during two different, although overlapping, time periods, one that includes some recent large-scale significant EHE intervention strategies (1975–2004), and one without (1975–95). The results suggest these public health responses can significantly decrease heat-related mortality.


2016 ◽  
Author(s):  
Younggu Her ◽  
Seung-Hwan Yoo ◽  
Chounghyun Seong ◽  
Jaehak Jeong ◽  
Jaepil Cho ◽  
...  

Abstract. Quantification of uncertainty in ensemble based predictions of climate change and the corresponding hydrologic impact is necessary for the development of robust climate change adaptation plans. Although the equifinality of hydrological modeling has been discussed for a long time, its impact on the hydrologic analysis of climate change has not been studied enough to provide clear ideas that represent the relative contributions of uncertainty contained in both multi-GCM (general circulation model) and multi-parameter ensembles toward the projections of hydrologic components. This study demonstrated that the uncertainty in multi-GCM (or multi-model) ensembles could be an order of magnitude larger than that of multi-parameter ensembles for predictions of direct runoff, suggesting that the selection of appropriate GCMs should be much more emphasized than the selection of a parameter set among behavioral ones when projecting direct runoff. When simulating soil moisture and groundwater, on the other hand, equifinality in hydrologic modeling was more influential than uncertainty in the multi-GCM ensemble. Also, uncertainty in a hydrologic simulation of climate change impact was much more closely associated with uncertainty in ensemble projections of precipitation than that in projected temperature, indicating a need to pay closer attention to the precipitation data for improvement of the reliability of hydrologic predictions. From among 35 GCMs incorporated, this study identified GCMs that contributed the most and least to uncertainty in an assessment of climate change impacts on the hydrology of 61 Ohio River watersheds, thereby exhibiting a framework to quantify contributions of individual GCMs to the overall uncertainty in climate change modeling.


2021 ◽  
Author(s):  
Richard Fewster ◽  
Paul Morris ◽  
Ruza Ivanovic ◽  
Graeme Swindles ◽  
Anna Peregon ◽  
...  

<p>Northern permafrost peatlands represent one of Earth’s largest terrestrial carbon stores and are highly sensitive to climate change. Whilst frozen, peatland carbon fluxes are restricted by cold temperatures, but once permafrost thaws and saturated surficial conditions develop, emissions of carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) substantially increase. This positive feedback mechanism threatens to accelerate future climate change globally. Whilst future permafrost distributions in mineral soils have been modelled extensively, the insulating properties of organic soils mean that peatland permafrost responses are highly uncertain. Peatland permafrost is commonly evidenced by frost mounds, termed palsas/peat plateaus, or by polygonal patterning in more northerly regions. Although the distribution of palsas in northern Fennoscandia is well-studied, the extent of palsas/peat plateaus and polygon mires elsewhere remains poorly constrained, which currently restricts predictions of their future persistence under climate change.  </p><p>Here, we present the first pan-Arctic analyses of the modern climate envelopes and future distributions of permafrost peatland landforms in North America, Fennoscandia, and Western Siberia. We relate a novel hemispheric-scale catalogue of palsas/peat plateaus and polygon mires (>2,100<strong> </strong>individual sites) to modern climate data using one-vs-all (OVA) binary logistic regression. We predict future distributions of permafrost peatland landforms across the northern hemisphere under four Shared Socioeconomic Pathway (SSP) scenarios, using future climate projections from an ensemble of 12 general circulation models included in the Coupled Model Intercomparison Project 6 (CMIP6). We then combine our simulations with recent soil organic carbon maps to estimate how northern peatland carbon stocks may be affected by future permafrost redistribution. These novel analyses will improve our understanding of future peatland trajectories across the northern hemisphere and assist predictions of climate feedbacks resulting from peatland permafrost thaw. </p>


2011 ◽  
Vol 15 (27) ◽  
pp. 1-23 ◽  
Author(s):  
Kathryn M. Koczot ◽  
Steven L. Markstrom ◽  
Lauren E. Hay

AbstractChanges in temperature and precipitation projected from five general circulation models, using one late-twentieth-century and three twenty-first-century emission scenarios, were downscaled to three different baseline conditions. Baseline conditions are periods of measured temperature and precipitation data selected to represent twentieth-century climate. The hydrologic effects of the climate projections are evaluated using the Precipitation-Runoff Modeling System (PRMS), which is a watershed hydrology simulation model. The Almanor Catchment in the North Fork of the Feather River basin, California, is used as a case study.Differences and similarities between PRMS simulations of hydrologic components (i.e., snowpack formation and melt, evapotranspiration, and streamflow) are examined, and results indicate that the selection of a specific time period used for baseline conditions has a substantial effect on some, but not all, hydrologic variables. This effect seems to be amplified in hydrologic variables, which accumulate over time, such as soil-moisture content. Results also indicate that uncertainty related to the selection of baseline conditions should be evaluated using a range of different baseline conditions. This is particularly important for studies in basins with highly variable climate, such as the Almanor Catchment.


Water Policy ◽  
2013 ◽  
Vol 15 (S1) ◽  
pp. 26-50 ◽  
Author(s):  
Marc Jeuland ◽  
Nagaraja Harshadeep ◽  
Jorge Escurra ◽  
Don Blackmore ◽  
Claudia Sadoff

This paper presents the first basin-wide assessment of the potential impact of climate change on the hydrology and production of the Ganges system, undertaken as part of the World Bank's Ganges Strategic Basin Assessment. A series of modeling efforts – downscaling of climate projections, water balance calculations, hydrological simulation and economic optimization – inform the assessment. We find that projections of precipitation across the basin, obtained from 16 Intergovernmental Panel on Climate Change-recognized General Circulation Models are highly variable, and lead to considerable differences in predictions of mean flows in the main stem of the Ganges and its tributaries. Despite uncertainties in predicted future flows, they are not, however, outside the range of natural variability in this basin, except perhaps at the tributary or sub-catchment levels. We also find that the hydropower potential associated with a set of 23 large dams in Nepal remains high across climate models, largely because annual flow in the tributary rivers greatly exceeds the storage capacities of these projects even in dry scenarios. The additional storage and smoothing of flows provided by these infrastructures translates into enhanced water availability in the dry season, but the relative value of this water for the purposes of irrigation in the Gangetic plain, and for low flow augmentation to Bangladesh under climate change, is unclear.


2019 ◽  
Vol 11 (4) ◽  
pp. 1067-1083 ◽  
Author(s):  
Mohammed Sanusi Shiru ◽  
Shamsuddin Shahid ◽  
Suleiman Shiru ◽  
Eun Sung Chung ◽  
Noraliani Alias ◽  
...  

Abstract This study assesses the water resources and environmental challenges of Lagos mega city, Nigeria, in the context of climate change. Being a commercial hub, the Lagos population has grown rapidly causing an insurmountable water and environmental crisis. In this study, a combined field observation, sample analysis, and interviews were used to assess water challenges. Observed climate, general circulation model (GCM) projections and groundwater data were used to assess water challenges due to climate change. The study revealed that unavailability of sufficient water supply provision in Lagos has overwhelmingly compelled the population to depend on groundwater, which has eventually caused groundwater overdraft. Salt water intrusion and subsidence has occurred due to groundwater overexploitation. High concentrations of heavy metals were observed in wells around a landfill. Climate projections showed a decrease in rainfall of up to 140 mm and an increase in temperature of up to 8 °C. Groundwater storage is projected to decrease after the mid-century due to climate change. Sea level rise will continue until the end of the century. As the water and environmental challenges of Lagos are broad and the changing characteristics of the climate are expected to intensify these as projected, tackling these challenges requires a holistic approach from an integrated water resources management perspective.


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