scholarly journals Here be dragons: important spatial uncertainty driven by climate data in forecasted distribution of an endangered insular reptile

2021 ◽  
Author(s):  
Nicolas Dubos ◽  
Stephane Augros ◽  
Gregory Deso ◽  
Jean-Michel Probst ◽  
Jean-Cyrille Notter ◽  
...  
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Future Climate ◽  
Climate Data ◽  
Spatial Overlap ◽  
Global Circulation ◽  
Sample Bias ◽  
Environmental Suitability ◽  
Global Circulation Models ◽  
Baseline Climate

The effect of future climate change is poorly documented in the tropics, especially in mountainous areas. Yet, species living in these environments are predicted to be strongly affected. Newly available high-resolution environmental data and statistical methods enable the development of forecasting models. Nevertheless, the uncertainty related to climate models can be strong, which can lead to ineffective conservation actions. Predicted studies aimed at providing conservation guidelines often account for a range of future climate predictions (climate scenarios and global circulation models). However, very few studies considered potential differences related to baseline climate data and/or did not account for spatial information (overlap) in uncertainty assessments. We modelled the environmental suitability for Phelsuma borbonica, an endangered reptile native to Reunion Island. Using two metrics of species range change (difference in overall suitability and spatial overlap), we quantified the uncertainty related to the modelling technique (n = 10), sample bias correction, climate change scenario, global circulation models (GCM) and baseline climate (CHELSA versus Worldclim). Uncertainty was mainly driven by GCMs when considering overall suitability, while for spatial overlap the uncertainty related to baseline climate became more important than that of GCMs. The uncertainty driven by sample bias correction and variable selection was much higher when assessed based on spatial overlap. The modelling technique was a strong driver of uncertainty in both cases. We eventually provide a consensus ensemble prediction map of the environmental suitability of P. borbonica to identify the areas predicted to be the most suitable in the future with the highest certainty. Predictive studies aimed at identifying priority areas for conservation in the face of climate change need to account for a wide panel of modelling techniques, GCMs and baseline climate data. We recommend the use of multiple approaches, including spatial overlap, when assessing uncertainty in species distribution models.

scholarly journals Projecting Future Climate Change Scenarios Using Three Bias-Correction Methods

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Donghyuk Kum ◽  
Kyoung Jae Lim ◽  
Chun Hwa Jang ◽  
Jichul Ryu ◽  
Jae E. Yang ◽  
...  
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Interdisciplinary Studies ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Quantile Mapping ◽  
Global Circulation ◽  
Global Circulation Models ◽  
The Individual

We performed bias correction in future climate change scenarios to provide better accuracy of models through adaptation to future climate change. The proposed combination of the change factor (CF) and quantile mapping (QM) methods combines the individual advantages of both methods for adjusting the bias in global circulation models (GCMs) and regional circulation models (RCMs). We selected a study site in Songwol-dong, Seoul, Republic of Korea, to test and assess our proposed method. Our results show that the combined CF + QM method delivers better performance in terms of correcting the bias in GCMs/RCMs than when both methods are applied individually. In particular, our proposed method considerably improved the bias-corrected precipitation by capturing both the high peaks and amounts of precipitation as compared to that from the CF-only and QM-only methods. Thus, our proposed method can provide high-accuracy bias-corrected precipitation data, which could prove to be highly useful in interdisciplinary studies across the world.

scholarly journals Effect of Climate Change on a Monolithic Desulphurized Tailings Cover

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2645
Author(s):  
Rashid Bashir ◽  
Fiaz Ahmad ◽  
Ryley Beddoe
Keyword(s):  
Climate Change ◽  
Soil Cover ◽  
Water Saturation ◽  
Future Climate ◽  
Oxygen Flux ◽  
Climate Data ◽  
Maximum Increase ◽  
Soil Covers ◽  
Global Circulation Models ◽  
The Future

A soil cover system can be viewed as a thin interface placed between the atmosphere and the underlying waste. Climate is a primary design variable in soil cover design; therefore, climate change poses a number of challenges to design, operation and long-term performance of covers. In this research climate change effects on the hydraulic behavior of soil covers at a Northern Ontario, Canada site were assessed. Covers were analyzed using historical and future climate datasets. Historical climate data were compiled from an Environment Canada weather station near the site. The future climate datasets were sourced for different Global Circulation Models (GCM) for various representative concentration pathways (RCP). The covers at the site were constructed with a single layer of desulphurized tailings. Soil covers were meant to limit oxygen ingress to the underlying reactive tailings by maintaining high water saturation in the covers. Oxygen flux through soil covers for current and future climates were predicted using variably saturated water flow and oxygen transport modeling using the finite element method. The results of this research indicate that the effect of climate change on soil cover depends on the hydraulic properties of the soil cover materials and that of the underlying tailings. The results of this study suggest that the effect of climate change on the coarse tailing covers could be marginal resulting in a maximum increase of 5% in oxygen flux at the cover surface for the future climates in comparison to the base climate. However, in the case of fine tailings covers, increases of up to 65% can be expected.

Bias correction of extreme values of high resolution climate simulations for risk analysis.

2021 ◽  
Author(s):  
luis Augusto sanabria ◽  
Xuerong Qin ◽  
Jin Li ◽  
Robert Peter Cechet
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Extreme Values ◽  
The Body ◽  
Future Climate ◽  
Return Periods ◽  
Climate Conditions ◽  
Mitigation And Adaptation ◽  
Climate Simulations ◽  
The Impact

Abstract Most climatic models show that climate change affects natural perils' frequency and severity. Quantifying the impact of future climate conditions on natural hazard is essential for mitigation and adaptation planning. One crucial factor to consider when using climate simulations projections is the inherent systematic differences (bias) of the modelled data compared with observations. This bias can originate from the modelling process, the techniques used for downscaling of results, and the ensembles' intrinsic variability. Analysis of climate simulations has shown that the biases associated with these data types can be significant. Hence, it is often necessary to correct the bias before the data can be reliably used for further analysis. Natural perils are often associated with extreme climatic conditions. Analysing trends in the tail end of distributions are already complicated because noise is much more prominent than that in the mean climate. The bias of the simulations can introduce significant errors in practical applications. In this paper, we present a methodology for bias correction of climate simulated data. The technique corrects the bias in both the body and the tail of the distribution (extreme values). As an illustration, maps of the 50 and 100-year Return Period of climate simulated Forest Fire Danger Index (FFDI) in Australia are presented and compared against the corresponding observation-based maps. The results show that the algorithm can substantially improve the calculation of simulation-based Return Periods. Forthcoming work will focus on the impact of climate change on these Return Periods considering future climate conditions.

scholarly journals Potential Impact of Climate Change on Schistosomiasis: A Global Assessment Attempt

2018 ◽  
Vol 3 (4) ◽  
pp. 117 ◽  
Author(s):  
Guo-Jing Yang ◽  
Robert Bergquist
Keyword(s):  
Climate Change ◽  
Coupled Model ◽  
Maximum Temperature ◽  
Intergovernmental Panel ◽  
Meteorological Model ◽  
Ambient Temperatures ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Parasite Stage ◽  
Near Future

Based on an ensemble of global circulation models (GCMs), four representative concentration pathways (RCPs) and several ongoing and planned Coupled Model Intercomparison Projects (CMIPs), the Intergovernmental Panel on Climate Change (IPCC) predicts that global, average temperatures will increase by at least 1.5 °C in the near future and more by the end of the century if greenhouse gases (GHGs) emissions are not genuinely tempered. While the RCPs are indicative of various amounts of GHGs in the atmosphere the CMIPs are designed to improve the workings of the GCMs. We chose RCP4.5 which represented a medium GHG emission increase and CMIP5, the most recently completed CMIP phase. Combining this meteorological model with a biological counterpart model accounted for replication and survival of the snail intermediate host as well as maturation of the parasite stage inside the snail at different ambient temperatures. The potential geographical distribution of the three main schistosome species: Schistosoma japonicum, S. mansoni and S. haematobium was investigated with reference to their different transmission capabilities at the monthly mean temperature, the maximum temperature of the warmest month(s) and the minimum temperature of the coldest month(s). The set of six maps representing the predicted situations in 2021–2050 and 2071–2100 for each species mainly showed increased transmission areas for all three species but they also left room for potential shrinkages in certain areas.

scholarly journals STUDY ON BIAS CORRECTION METHODS OF CENTRAL ATMOSPHERIC PRESSURE OF TYPHOON IN A FUTURE CLIMATE DATA SET

2017 ◽  
Vol 73 (2) ◽  
pp. I_1417-I_1422
Author(s):  
Yoshihiko IDE ◽  
Yuji ISSHIKI ◽  
Mitsuyoshi KODAMA ◽  
Noriaki HASHIMOTO ◽  
Masaru YAMASHIRO
Keyword(s):  
Bias Correction ◽  
Atmospheric Pressure ◽  
Future Climate ◽  
Climate Data ◽  
Data Set

scholarly journals Simulation of future climate scenarios and the impact on the water availability in southern Brazil

2021 ◽  
Vol 43 ◽  
pp. e56026
Author(s):  
Gabriela Leite Neves ◽  
Jorim Sousa das Virgens Filho ◽  
Maysa de Lima Leite ◽  
Frederico Fabio Mauad
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Water Availability ◽  
Meteorological Data ◽  
Future Climate ◽  
Climate Scenarios ◽  
Southern Brazil ◽  
Climate Data ◽  
Intergovernmental Panel ◽  
The Impact

Water is an essential natural resource that is being impacted by climate change. Thus, knowledge of future water availability conditions around the globe becomes necessary. Based on that, this study aimed to simulate future climate scenarios and evaluate the impact on water balance in southern Brazil. Daily data of rainfall and air temperature (maximum and minimum) were used. The meteorological data were collected in 28 locations over 30 years (1980-2009). For the data simulation, we used the climate data stochastic generator PGECLIMA_R. It was considered two scenarios of the fifth report of the Intergovernmental Panel on Climate Change (IPCC) and a scenario with the historical data trend. The water balance estimates were performed for the current data and the simulated data, through the methodology of Thornthwaite and Mather (1955). The moisture indexes were spatialized by the kriging method. These indexes were chosen as the parameters to represent the water conditions in different situations. The region assessed presented a high variability in water availability among locations; however, it did not present high water deficiency values, even with climate change. Overall, it was observed a reduction of moisture index in most sites and in all scenarios assessed, especially in the northern region when compared to the other regions. The second scenario of the IPCC (the worst situation) promoting higher reductions and dry conditions for the 2099 year. The impacts of climate change on water availability, identified in this study, can affect the general society, therefore, they must be considered in the planning and management of water resources, especially in the regional context

scholarly journals Effects of climate change on agriculture water demand in lower Pak Phanang river basin, southern part of Thailand

2018 ◽  
Vol 192 ◽  
pp. 03043
Author(s):  
Natapon Kaewthong ◽  
Pakorn Ditthakit
Keyword(s):  
Climate Change ◽  
Land Use ◽  
River Basin ◽  
Water Demand ◽  
Land Development ◽  
Circulation Model ◽  
Climate Data ◽  
Global Circulation Model ◽  
Baseline Climate ◽  
Agriculture Water

The aim of the research is to analyse the effects on agricultural water demand in the Lower Pak Phanang River Basin area due to climate change. The climate data used in the analysis were rainfall, maximum, minimum, and average temperatures. The climate datasets were obtained from statistical downscaling of global circulation model under the CMIP5 project by means of bias correction with Optimizing Quantile Mapping implemented by the Hydro and Agro Informatics Institute. To determine agriculture water demand, reference evapotranspiration (ETo) based on Hargreaves method was calculated for both baseline climate data (1987-2015) and forecasted climate data in 2038. For agriculture water demand in the Pak Phanang river basin, we considered paddy field, palm oil, rubber, grapefruit, orchard, vegetable, ruzy and biennial crop, based on land use data of the Land Development Department of Thailand in 2012. The results showed that forecasted agriculture water demand in 2038 with existing land use data in 2012 will be increased with the average of 18.9% or 61.78 MCM as compared to baseline climate condition. Both water demand and supply management measures would be suitably prepared before facing unexpected situation.

scholarly journals Choice of baseline climate data impacts projected species' responses to climate change

2016 ◽  
Vol 22 (7) ◽  
pp. 2392-2404 ◽  
Author(s):  
David J. Baker ◽  
Andrew J. Hartley ◽  
Stuart H. M. Butchart ◽  
Stephen G. Willis
Keyword(s):  
Climate Change ◽  
Climate Data ◽  
Species Responses ◽  
Baseline Climate

Projecting future vegetation change for northeast China using CMIP6

2020 ◽  
Author(s):  
Wei Yuan ◽  
Shuang-ye Wu ◽  
Shugui Hou
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Management Strategies ◽  
Future Climate ◽  
Future Climate Change ◽  
Vegetation Changes ◽  
Emission Scenarios ◽  
Climate Data ◽  
Climate Conditions ◽  
Temperature And Precipitation

<p>This study aims to establish future vegetation changes in the east and central of northern China (ECNC), an ecologically sensitive region in the transition zonal from humid monsoonal to arid continental climate. The region has experienced significant greening in the past several decades. However, few studies exist on how vegetation will change with future climate change, and great uncertainties exist due to complex, and often spatially non-stationary, relationships between vegetation and climate. In this study, we first used historical NDVI and climate data to model this spatially variable relationship with Geographically Weighted Logit Regression. We found that temperature and precipitation could explain, on average, 43% of NDVI variance, and they could be used to model NDVI fairly well. We then establish future climate change using the output of 11 CMIP6 models for the medium (SSP245) and high (SSP585) emission scenarios for the mid-century (2041-2070) and late-century (2071-2100). The results show that for this region, both temperature and precipitation will increase under both scenarios. By late-century under SSP585, precipitation is projected to increase by 25.12% and temperature is projected to increase 5.87<sup>o</sup>C in ECNC. Finally, we used future climate conditions as input for the regression models to project future vegetation (indicated by NDVI). We found that NDVI will increase under climate change. By mid-century, the average NDVI in ECNC will increase by 0.024 and 0.021 under SSP245 and SSP585. By late-century, it will increase by 0.016 and 0.006 under SSP245 and SSP585 respectively. Although NDVI is projected to increase, the magnitude of increase is likely to diminish with higher emission scenarios, possibly due to the benefit of precipitation increase being gradually encroached by the detrimental effects of temperature increase. Moreover, despite the overall NDVI increase, the area likely to suffer vegetation degradation will also expands, particularly in the western part of ECNC. With higher emissions and later into the century, region with low NDVI is likely to shift and/or expand north-forward. Our results could provide important information on possible vegetation changes, which could help to develop effective management strategies to ensure ecological and economic sustainability in the future.</p>

scholarly journals Reservoir yield intercomparison of large dams in Jaguaribe Basin-CE in climate change scenarios

RBRH ◽  
2017 ◽  
Vol 22 (0) ◽  
Author(s):  
Renato de Oliveira Fernandes ◽  
Cleiton da Silva Silveira ◽  
Ticiana Marinho de Carvalho Studart ◽  
Francisco de Assis de Souza Filho
Keyword(s):  
Climate Change ◽  
Climate Changes ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Great Divergence ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Reservoir Yield

ABSTRACT Climate changes can have different impacts on water resources. Strategies to adapt to climate changes depend on impact studies. In this context, this study aimed to estimate the impact that changes in precipitation, projected by Global Circulation Models (GCMs) in the fifth report by the Intergovernmental Panel on Climate Change (IPCC-AR5) may cause on reservoir yield (Q90) of large reservoirs (Castanhão and Banabuiú), located in the Jaguaribe River Basin, Ceará. The rainfall data are from 20 GCMs using two greenhouse gas scenarios (RCP4.5 and RCP8.5). The precipitation projections were used as input data for the rainfall-runoff model (SMAP) and, after the reservoirs’ inflow generation, the reservoir yields were simulated in the AcquaNet model, for the time periods of 2040-2069 and 2070-2099. The results were analyzed and presented a great divergence, in sign (increase or decrease) and in the magnitude of change of Q90. However, most Q90 projections indicated reduction in both reservoirs, for the two periods, especially at the end of the 21th century.

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