scholarly journals Case study on the use of dynamically downscaled climate model data for assessing water security in the Lower Hunter region of the eastern seaboard of Australia

2016 ◽  
Vol 66 (2) ◽  
pp. 177
Author(s):  
Natalie Lockart ◽  
Garry Willgoose ◽  
George Kuczera ◽  
Anthony S. Kiem ◽  
AFM Kamal Chowdhury ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Potential Evapotranspiration ◽  
Circulation Model ◽  
Water Security ◽  
Climate Modelling ◽  
Security Assessment ◽  
Large Role ◽  
Eastern Seaboard

A key aim of the Eastern Seaboard Climate Change Initiative (ESCCI) is under-standing the effect of climate change on the eastern seaboard of Australia, and the implications for climate change adaptation in this area. The New South Wales (NSW) / Australian Capital Territory (ACT) Regional Climate Modelling project (NARCliM) has produced three dynamically downscaled reanalysis climate datasets along with 12 downscaled general circulation model (GCM) projections of current (1990–2009) and future climate. It is expected that the NARCliM dataset will be used for many climate change impact studies including water security assessment. Therefore, in this study we perform a case study investigation into the usefulness and limitations of using NARCliM data for water security assessment, using the Lower Hunter urban water supply system managed by Hunter Water Corporation. We compare streamflow and reservoir levels simulated using NARCliM rainfall and a gridded historical rainfall dataset (AWAP) and focus our analysis on the differences in the simulated streamflow and reservoir levels. We show that when raw (i.e. not bias-corrected) NARCliM rainfall and potential evapotranspiration (PET) data is used to simulate streamflow and reservoir storage levels, some of the NARCliM datasets produce unrealistic results when compared with the simulations using AWAP; for example, some NARCliM datasets simulate reservoirs at or near empty while the AWAP reservoir simulations rarely drop below 60%. The bias-corrected NARCliM rainfall (corrected to AWAP) produces estimates of streamflow and reservoir levels that have a closer, but still inconsistent, match with the streamflow and reservoir levels simulated using AWAP directly. The inconsistency between the simulations using bias-corrected rainfall and historical AWAP rainfall is potentially because while bias-correction reduces systematic deviations it does not fix temporal rainfall sequencing issues. Additionally, the NARCliM PET is not bias-corrected and using bias-corrected rainfall with uncorrected PET in hydrological models results in physical inconsistencies in the rainfall-PET relationship and simulated streamflow. We demonstrate that rainfall plays a large role in the streamflow simulations, while PET seems to play a large role in the reasonableness of the simulated reservoir dynamics by determining the evaporation losses from the reservoirs. The downscaled GCM datasets that simulate the greatest average PET for 1990–2009 show reservoirs often (unrealistically) near empty. This study highlights the need to assess the validity of all climate data for the applications required, with a focus on long-term statistics for reservoir modelling and ensuring realism and coherence across all projected variables.

scholarly journals Evaluation of Climate Change Impacts on Cotton Yield using Cropsyst and Regression Models

2018 ◽  
Vol 8 ◽  
pp. 1433-1451 ◽  
Author(s):  
Pantazis Georgiou ◽  
Panagiota Koukouli
Keyword(s):  
Climate Change ◽  
Regression Models ◽  
General Circulation ◽  
Management Practices ◽  
Potential Evapotranspiration ◽  
Circulation Model ◽  
Planting Date ◽  
Climate Variables ◽  
Cotton Yield ◽  
Cotton Production

The regional as well as the international crop production is expected to be influenced by climate change. This study describes an assessment of simulated potential cotton yield using CropSyst, a cropping systems simulation model, in Northern Greece. CropSyst was used under the General Circulation Model CGCM3.1/T63 of the climate change scenario SRES B1 for time periods of climate change 2020-2050 and 2070-2100 for two planting dates. Additionally, an appraisal of the relationship between climate variables, potential evapotranspiration and cotton yield was done based on regression models. Multiple linear regression models based on climate variables and potential evapotranspiration could be used as a simple tool for the prediction of crop yield changes in response to climate change in the future. The CropSyst simulation under SRES B1, resulted in an increase by 6% for the period 2020-2050 and a decrease by about 15% in cotton yield for 2070-2100. For the earlier planting date a higher increase and a slighter reduction was observed in cotton yield for 2020-2050 and 2070-2100, respectively. The results indicate that alteration of crop management practices, such as changing the planting date could be used as potential adaptation measures to address the impacts of climate change on cotton production.

scholarly journals Assessment of hydrological response in Subarnarekha river basin under anticipated climate change scenarios

2020 ◽  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
General Circulation ◽  
Circulation Model ◽  
Climate Modelling ◽  
Climate Change Scenarios ◽  
Hydrological Response ◽  
Study Region ◽  
Subarnarekha River ◽  
Subarnarekha River Basin

<p>Two hydrological climate modelling techniques, general circulation model (GCM) and hypothetical climate change scenarios, were used to analyse the hydrological response to the anticipated climate change scenarios in the Subarnarekha river basin in Eastern India. Both models verified individually for the same river basin and a comparative performance of the models was evaluated to relate the two models for the near (2014-2040) period climate. The hydrological response under the anticipated climate change in the Subarnarekha river basin is well assessed by GCM under the RCP 8.5 scenarios compared to the RCPs 4.5. Results indicate GCM best suited over the hypothetical climate change scenarios as GCM has demonstrated their potential in accurately reproducing the past observed climatic changes. The strong performance of the hypothetical climate change scenarios model, particularly for warming climate scenarios, suggests that it may have distinct advantages for the analysis of water balance components in the river basin. The monthly streamflows of Subarnarekha river basin was simulated using a total of 14 years (2000-2013) daily observed streamflow data in the ArcSWAT model integrated with model calibration and uncertainty analysis by means of SUFI-2 algorithm. The results indicate during the calibration the coefficient of determination (R2) and Nash-Sutcliff Efficiency (NSE) were reported as 0.98 and 0.97, respectively, while during the validation the R2 and NSE were obtained as 0.94 and 0.94, respectively, confirms the hydrological model performance was very good both in calibration and validation. The obtained climate change water impact index (ICCWI) values reveal the Subarnarekha river basin is more responsive to climate change. The reduction in precipitation along with the significant warming under the projected future climate is likely to reduce availability of water substantially in the study region. This work would be useful for the effective management of water resources for sustainable agriculture and in mitigating natural hazards such as droughts and floods in the study region.</p>

scholarly journals Potential evapotranspiration method influence on climate change impacts on river flow: a mid-latitude case study

2016 ◽  
Vol 47 (5) ◽  
pp. 951-963 ◽  
Author(s):  
L. P. Koedyk ◽  
D. G. Kingston
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
River Flow ◽  
Potential Evapotranspiration ◽  
Climate Change Impacts ◽  
High Sensitivity ◽  
General Circulation Models ◽  
Global Mean Temperature ◽  
Projected Changes

Projected changes in 21st century climate are likely to impact water resources substantially, although much uncertainty remains as to the nature of such impacts. A relatively under-explored source of uncertainty is the method by which current and scenario evapotranspiration (ET) are estimated. Using the Waikaia River (New Zealand) as a case study, the influence of a potential ET (PET) method is investigated for a scenario of a 2°C increase in global mean temperature (the presumed threshold of ‘dangerous’ climate change). Six PET methods are investigated, with five general circulation models (GCMs) used to provide an indication of GCM uncertainty. The HBV-Light hydrological model is used to simulate river runoff. Uncertainty in scenario PET between methods is generally greater than between GCMs, but the reverse is found for runoff. The cause of the reduction in uncertainty from PET to runoff is unclear: the catchment is not water-limited during the summer half-year, indicating that it is not because of actual ET failing to reach the potential rate. Irrespective of the cause, these results stand in contrast to previous estimations of relatively high sensitivity of runoff projections to PET methods, indicating that further work is required to understand the controls on this source of uncertainty.

Impact of climate change on the future quality of surface waters: case study of the Ardak River, northeast of Iran

2019 ◽  
Vol 11 (3) ◽  
pp. 685-702 ◽  
Author(s):  
Morteza Nikakhtar ◽  
Seyedeh Hoda Rahmati ◽  
Ali Reza Massah Bavani
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
General Circulation ◽  
Oxygen Demand ◽  
Circulation Model ◽  
Quality Parameters ◽  
Quality Of Water ◽  
Monthly Streamflow

Abstract In recent decades, climate change has influenced the quantity and quality of water resources, affecting water supply for various demands. In this case study, the effects of climate change on the quality of the Ardak River in the northeast of Iran are discussed. The Qual2kW model was used to simulate water quality parameters, by sampling dissolved oxygen (DO), pH, chemical oxygen demand (COD), and NO3. The rainfall-streamflow model IHACRES was used for simulating monthly streamflow. Monthly general circulation model (GCM) temperature and rainfall data from representative concentration pathways (RCP) RCP2.6 and RCP8.5 were downloaded for 1986 to 2005 and 2020 to 2039. The previously verified model LARS-WG was used to predict future temperatures and rainfall. By importing this data into IHACRES, stream flows were simulated, enabling Qual2kW to predict future effects on water quality. Although changes in temperature of 0.5 to 1.2 °C were predicted, maximum changes in temperature and rainfall will occur in winter and summer in series. Therefore, water quality was predicted to decrease only on the Abghad branch, due to increased temperature and lower flow rates. The highest percentage variations in DO and NO3 are −12.19 and 31.25 in RCP8.5 and in COD and PH, −35.4 and 0.29 in RCP2.6.

scholarly journals Modeled climate change effects on distributions of Canadian butterfly species

2004 ◽  
Vol 82 (6) ◽  
pp. 851-858 ◽  
Author(s):  
A Townsend Peterson ◽  
Enrique Martínez-Meyer ◽  
Constantino González-Salazar ◽  
Peter W Hall
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Ecological Niche Modeling ◽  
Circulation Model ◽  
Species Distributions ◽  
Butterfly Species ◽  
Climate Modelling ◽  
Emission Scenarios ◽  
Climate Change Effects ◽  
Hadley Centre

Climate change effects on biodiversity are being documented now frequently in the form of changes in phenology and distributional shifts. However, the form that these effects will take over a longer timespan is unclear; for this understanding, a quantitative, validated, predictive approach is key. Here, we use ecological niche modeling and general circulation model outputs to estimate future potential geographic distributions of 111 Canadian butterfly species. We develop future estimates under two emission scenarios from each of two climate change modeling centers; future projections for biodiversity are not only scenario dependent (more severe emission scenarios produce more severe effects on species' distributions) but also model dependent (the Canadian Centre for Climate Modelling and Analysis results were more severe than the Hadley Centre results). One interesting feature is the appearance of disjunctions in species' distributions, hence creating "vicariant events" over very short time periods. In general, however, a cost of 1%–3% additional loss of species' distributions is associated with more severe scenarios of emissions and climate change, suggesting that subtle biodiversity consequences are associated with the different climate futures debated in political circles.

Case study on the use of dynamically downscaled climate model data for assessing water security in the Lower Hunter region of the eastern seaboard of Australia

2016 ◽  
Vol 66 (2) ◽  
pp. 177-202 ◽  
Author(s):  
Natalie Lockart ◽  
Garry Willgoose ◽  
George Kuczera ◽  
Anthony Kiem ◽  
AFM Kamal Chowdhury ◽  
...  
Keyword(s):  
Climate Model ◽  
Water Security ◽  
Model Data ◽  
Hunter Region ◽  
Eastern Seaboard

“Modes of Variability” and Climate Change

2009 ◽  
Vol 22 (10) ◽  
pp. 2639-2658 ◽  
Author(s):  
Grant Branstator ◽  
Frank Selten
Keyword(s):  
Climate Change ◽  
Stochastic Model ◽  
General Circulation ◽  
Climate Changes ◽  
Circulation Model ◽  
Meridional Wind ◽  
Model Atmosphere ◽  
Linear Pattern ◽  
Modes Of Variability ◽  
Mean State

Abstract A 62-member ensemble of coupled general circulation model (GCM) simulations of the years 1940–2080, including the effects of projected greenhouse gas increases, is examined. The focus is on the interplay between the trend in the Northern Hemisphere December–February (DJF) mean state and the intrinsic modes of variability of the model atmosphere as given by the upper-tropospheric meridional wind. The structure of the leading modes and the trend are similar. Two commonly proposed explanations for this similarity are considered. Several results suggest that this similarity in most respects is consistent with an explanation involving patterns that result from the model dynamics being well approximated by a linear system. Specifically, the leading intrinsic modes are similar to the leading modes of a stochastic model linearized about the mean state of the GCM atmosphere, trends in GCM tropical precipitation appear to excite the leading linear pattern, and the probability density functions (PDFs) of prominent circulation patterns are quasi-Gaussian. There are, on the other hand, some subtle indications that an explanation for the similarity involving preferred states (which necessarily result from nonlinear influences) has some relevance. For example, though unimodal, PDFs of prominent patterns have departures from Gaussianity that are suggestive of a mixture of two Gaussian components. And there is some evidence of a shift in probability between the two components as the climate changes. Interestingly, contrary to the most prominent theory of the influence of nonlinearly produced preferred states on climate change, the centroids of the components also change as the climate changes. This modification of the system’s preferred states corresponds to a change in the structure of its dominant patterns. The change in pattern structure is reproduced by the linear stochastic model when its basic state is modified to correspond to the trend in the general circulation model’s mean atmospheric state. Thus, there is a two-way interaction between the trend and the modes of variability.

scholarly journals Meteorological modes of variability for fine particulate matter (PM2.5) air quality in the United States: implications for PM2.5 sensitivity to climate change

2012 ◽  
Vol 12 (6) ◽  
pp. 3131-3145 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Transport Model ◽  
Circulation Model ◽  
Multiple Linear Regression Model ◽  
The United States ◽  
Chemical Transport Model ◽  
Modes Of Variability ◽  
The Us ◽  
Cyclone Frequency

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.

scholarly journals Impact of climate change on sediment yield in the Mekong River basin: a case study of the Nam Ou basin, Lao PDR

2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  
Keyword(s):  
Climate Change ◽  
Sediment Yield ◽  
General Circulation ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Circulation Model ◽  
Sediment Flux ◽  
Seasonal Temperature ◽  
Impact Of Climate Change ◽  
The Impact

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.

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