A toolkit for climate change analysis and pattern recognition for extreme weather conditions – Case study: California-Baja California Peninsula

Vaghefi, Saeid Ashraf; Abbaspour, Nazanin; Kamali, Bahareh; Abbaspour, Karim C.

doi:10.1016/j.envsoft.2017.06.033

Cited by 72 publications

(26 citation statements)

References 55 publications

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“…This study used the climate research unit (CRU) daily prcp, Tmax and Tmin datasets between the historic years of 1980 to 2005 over the Niger Delta part of Nigeria due to the scarcity of reliable long records of hydroclimatological station observations in the area. The CRU datasets are observation-based gridded prcp, Tmin and Tmax datasets, which are widely used because of their extensive spatial and temporal coverage extracted from the CRU version 4.01 global climate dataset [46][47][48]. They were found to be the best-fit datasets that replicated the distribution patterns, spatial, and temporal variability of the Niger Delta's observed datasets [49].…”

Section: Gridded Datasetmentioning

confidence: 99%

“…As the GCMs are available in different resolutions, all CMIP5 data were extracted and downscaled uniformly to the same spatial scale (0.5 • × 0.5 • ) to reduce biases introduced by different resolutions for a fair comparison. This technique uses nearby areas to generate point output from each GCM at each grid point, thus providing a smooth interpolation that is widely used for the re-gridding of GCMs [48]. Table 1 gives an overview of the GCMs.…”

Section: Coupled Model Inter-comparison Project Phase 5 (Cmip5) Gcm Dmentioning

confidence: 99%

“…Bias correction was carried out to correct the projected raw GCM output using the differences in the mean and variability between GCM and observed datasets. In this study, the biases in the daily time series of the variables (i.e., prcp, Tmin, and Tmax) from the four top-ranked GCM output were corrected using the easiest and the most common methods, which were the additive method for temperature and multiplicative method for prcp [48,58,59]. For temperature, the additive correction factor for each month was used, and the adjusted formula for modified daily temperature (Tmax and Tmin) is expressed in Equation (6).…”

Section: Bias Correctionmentioning

confidence: 99%

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Selection of CMIP5 GCM Ensemble for the Projection of Spatio-Temporal Changes in Precipitation and Temperature over the Niger Delta, Nigeria

Hassan

Kalin

White

et al. 2020

Water

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Selection of a suitable general circulation model (GCM) ensemble is crucial for effective water resource management and reliable climate studies in developing countries with constraint in human and computational resources. A careful selection of a GCM subset by excluding those with limited similarity to the observed climate from the existing pool of GCMs developed by different modeling centers at various resolutions can ease the task and minimize uncertainties. In this study, a feature selection method known as symmetrical uncertainty (SU) was employed to assess the performance of 26 Coupled Model Intercomparison Project Phase 5 (CMIP5) GCM outputs under Representative Concentration Pathway (RCP) 4.5 and 8.5. The selection was made according to their capability to simulate observed daily precipitation (prcp), maximum and minimum temperature (Tmax and Tmin) over the historical period 1980-2005 in the Niger Delta region, which is highly vulnerable to extreme climate events. The ensemble of the four top-ranked GCMs, namely ACCESS1.3, MIROC-ESM, MIROC-ESM-CHM, and NorESM1-M, were selected for the spatio-temporal projection of prcp, Tmax, and Tmin over the study area. Results from the chosen ensemble predicted an increase in the mean annual prcp between the range of 0.26% to 3.57% under RCP4.5, and 0.7% to 4.94% under RCP 8.5 by the end of the century when compared to the base period. The study also revealed an increase in Tmax in the range of 0 to 0.4 • C under RCP4.5 and 1.25-1.79 • C under RCP8.5 during the periods 2070-2099. Tmin also revealed a significant increase of 0 to 0.52 • C under RCP4.5 and between 1.38-2.02 • C under RCP8.5, which shows that extreme events might threaten the Niger Delta due to climate change. Water resource managers in the region can use these findings for effective water resource planning, management, and adaptation measures.

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Section: Gridded Datasetmentioning

confidence: 99%

Section: Coupled Model Inter-comparison Project Phase 5 (Cmip5) Gcm Dmentioning

confidence: 99%

Section: Bias Correctionmentioning

confidence: 99%

See 1 more Smart Citation

Selection of CMIP5 GCM Ensemble for the Projection of Spatio-Temporal Changes in Precipitation and Temperature over the Niger Delta, Nigeria

Hassan

Kalin

White

et al. 2020

Water

View full text Add to dashboard Cite

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“…In this study, the software Climate Change Toolkit (CCT) (described by Vaghefi et al [23]) had been used to prepare the data for the climate change scenarios. CCT is a platform which allows the user to extract and prepare data needed in a climate change study for application to hydrology.…”

Section: Data Sourcesmentioning

confidence: 99%

Impact of Climate Change on Water Balance Components and Droughts in the Guajoyo River Basin (El Salvador)

Blanco-Gómez

Jimeno‐Sáez

Senent‐Aparicio

et al. 2019

Water

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This study assessed how changes in terms of temperature and precipitation might translate into changes in water availability and droughts in an area in a developing country with environmental interest. The hydrological model Soil and Water Assessment Tool (SWAT) was applied to analyze the impacts of climate change on water resources of the Guajoyo River Basin in El Salvador. El Salvador is in one of the most vulnerable regions in Latin America to the effects of climate change. The predicted future climate change by two climate change scenarios (RCP 4.5 and RCP 8.5) and five general circulation models (GCMs) were considered. A statistical analysis was performed to identify which GCM was better in terms of goodness of fit to variation in means and standard deviations of the historical series. A significant decreasing trend in precipitation and a significant increase in annual average temperatures were projected by the middle and the end of the twenty–first century. The results indicated a decreasing trend of the amount of water available and more severe droughts for future climate scenarios with respect to the base period (1975–2004). These findings will provide local water management authorities useful information in the face of climate change to help decision making.

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“…The datasets used in this study are daily rainfall time series datasets obtained from the Climate Research Unit (CRU) for the historical periods of 1980 to 2005 over the Niger Delta part of Nigeria due to the scarcity of reliable long time records of hydroclimatological stations in the area. The CRU datasets are observation-based gridded rainfall and temperature datasets, which are widely used globally because of their extensive spatial and temporal coverage [31][32][33]. A study by [34] found the CRU datasets to be the best-fit datasets that replicate the distribution patterns, spatial, and temporal variability of the Niger Delta's observed hydroclimatological datasets.…”

Section: Meteorological Datasetsmentioning

confidence: 99%

Potential Impacts of Climate Change on Extreme Weather Events in the Niger Delta Part of Nigeria

et al. 2020

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The Niger Delta is the most climate-vulnerable region in Nigeria. Flooding events are recorded annually in settlements along the River Niger and its tributaries, inundating many towns and displacing people from their homes. In this study, climate change impacts from extreme meteorological events over the period 2010–2099 are predicted and analyzed. Four coupled model intercomparison project phase 5 (CMIP5) global climate models (GCMs) under respectively concentration pathways (RCP4.5 and RCP8.5) emission scenarios were used for climate change predictions. Standardized precipitation indices (SPI) of 1-month and 12-month time steps were used for extreme event assessment. Results from the climate change scenarios predict an increase in rainfall across all future periods and under both emission scenarios, with the highest projected increase during the last three decades of the century. Under the RCP8.5 emission scenario, the rainfall at Port Harcourt and Yenagoa Stations is predicted to increase by about 2.47% and 2.62% while the rainfall at Warri Station is predicted to increase by about 1.39% toward the end of the century. The 12-month SPI under RCP4.5 and RCP8.5 emission scenarios predict an exceedance in the extreme wet threshold (i.e., SPI > 2) during all future periods and across all study locations. These findings suggest an increasing risk of flooding within the projected periods. The finding can be useful to policymakers for the formulation and planning of flood mitigation and adaptation measures.

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A toolkit for climate change analysis and pattern recognition for extreme weather conditions – Case study: California-Baja California Peninsula

Cited by 72 publications

References 55 publications

Selection of CMIP5 GCM Ensemble for the Projection of Spatio-Temporal Changes in Precipitation and Temperature over the Niger Delta, Nigeria

Selection of CMIP5 GCM Ensemble for the Projection of Spatio-Temporal Changes in Precipitation and Temperature over the Niger Delta, Nigeria

Impact of Climate Change on Water Balance Components and Droughts in the Guajoyo River Basin (El Salvador)

Potential Impacts of Climate Change on Extreme Weather Events in the Niger Delta Part of Nigeria

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