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

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 Regional climate model data used within the SWURVE project – 2: addressing uncertainty in regional climate model data for five European case study areas

2007 ◽  
Vol 11 (3) ◽  
pp. 1085-1096 ◽  
Author(s):  
M. Ekström ◽  
B. Hingray ◽  
A. Mezghani ◽  
P. D. Jones
Keyword(s):  
Probability Distribution ◽  
Climate Model ◽  
Regional Climate ◽  
Model Data ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
Regional Temperature ◽  
Scaling Variables ◽  
Annual Average Temperature

Abstract. To aid assessments of the impact of climate change on water related activities in the case study regions (CSRs) of the EC-funded project SWURVE, estimates of uncertainty in climate model data need to be developed. This paper compares two methods for estimating uncertainty in annual surface temperature and precipitation for the period 2070–2099. Both combine probability distribution functions for global temperature increase and for scaling variables (i.e. the change in regional temperature/precipitation per degree of global annual average temperature change) to produce a probability distribution for regional temperature and precipitation. The methods differ in terms of the distribution used for the respective probability distribution function. For scaling variables, the first method assumes a uniform distribution, whilst the second method assumes a normal distribution. For the probability distribution function of global annual average temperature change, the first method uses a uniform distribution and the second uses a log-normal approximation to a distribution derived from Wigley and Raper, 2001. Although the methods give somewhat different ranges of change, they agree on how temperature and precipitation in each of the CSRs are likely to change relative to each other. For annual surface temperature, both methods predict increases in all CSRs, although somewhat less so for NW England (5th and 95th percentiles vary between 1.1–1.9°C to 3.8–5.7°C) and about 1.7–3.1°C to 5.3–8.6°C for the others. For precipitation, most probability distributions (except for NW England) show predominantly decreasing precipitation, particularly so for the Iberian CSR (5th and 95th percentiles vary from –29.3 to –44% to –9.6 to –4%).

scholarly journals Projected increases in surface melt and ice loss for the Northern and Southern Patagonian Icefields

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Claudio Bravo ◽  
Deniz Bozkurt ◽  
Andrew N. Ross ◽  
Duncan J. Quincey
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Historical Period ◽  
Emission Scenarios ◽  
Recent Past ◽  
Model Data ◽  
Surface Mass ◽  
The Mean ◽  
Surface Melt ◽  
Frontal Ablation

AbstractThe Northern Patagonian Icefield (NPI) and the Southern Patagonian Icefield (SPI) have increased their ice mass loss in recent decades. In view of the impacts of glacier shrinkage in Patagonia, an assessment of the potential future surface mass balance (SMB) of the icefields is critical. We seek to provide this assessment by modelling the SMB between 1976 and 2050 for both icefields, using regional climate model data (RegCM4.6) and a range of emission scenarios. For the NPI, reductions between 1.5 m w.e. (RCP2.6) and 1.9 m w.e. (RCP8.5) were estimated in the mean SMB during the period 2005–2050 compared to the historical period (1976–2005). For the SPI, the estimated reductions were between 1.1 m w.e. (RCP2.6) and 1.5 m w.e. (RCP8.5). Recently frontal ablation estimates suggest that mean SMB in the SPI is positively biased by 1.5 m w.e., probably due to accumulation overestimation. If it is assumed that frontal ablation rates of the recent past will continue, ice loss and sea-level rise contribution will increase. The trend towards lower SMB is mostly explained by an increase in surface melt. Positive ice loss feedbacks linked to increasing in meltwater availability are expected for calving glaciers.

scholarly journals Water security in the Canadian Prairies: science and management challenges

2013 ◽  
Vol 371 (2002) ◽  
pp. 20120409 ◽  
Author(s):  
Howard Wheater ◽  
Patricia Gober
Keyword(s):  
Social Sciences ◽  
Large Scale ◽  
Water Security ◽  
Western Canada ◽  
Deep Uncertainty ◽  
Canadian Prairies ◽  
Multiple Dimensions ◽  
Security Challenges ◽  
Water Problems

In this paper, we discuss the multiple dimensions of water security and define a set of thematic challenges for science, policy and governance, based around cross-scale dynamics, complexity and uncertainty. A case study of the Saskatchewan River basin (SRB) in western Canada is presented, which encompasses many of the water-security challenges faced worldwide. A science agenda is defined based on the development of the SRB as a large-scale observatory to develop the underpinning science and social science needed to improve our understanding of water futures under societal and environmental change. We argue that non-stationarity poses profound challenges for existing science and that new integration of the natural sciences, engineering and social sciences is needed to address decision making under deep uncertainty. We suggest that vulnerability analysis can be combined with scenario-based modelling to address issues of water security and that knowledge translation should be coupled with place-based modelling, adaptive governance and social learning to address the complexity uncertainty and scale dynamics of contemporary water problems.

Simulation of an extreme rainfall event over Mumbai using a regional climate model: a case study

2021 ◽  
Vol 134 (1) ◽  
Author(s):  
Manas Pant ◽  
Soumik Ghosh ◽  
Shruti Verma ◽  
Palash Sinha ◽  
R. K. Mall ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Extreme Rainfall Event

scholarly journals Local government's response to the recovery of the tourism sector after the COVID-19 pandemic (case study in Singkawang City, Indonesia)

2021 ◽  
Vol 5 (3) ◽  
pp. 176-183
Author(s):  
Martoyo Martoyo ◽  
Herlan Herlan ◽  
Nahot Tua Parlindungan Sihaloho ◽  
Deni Darmawan
Keyword(s):  
City Government ◽  
Model Data ◽  
Mitigation Policy ◽  
Analysis Techniques ◽  
Impact Mitigation ◽  
Alternative Tourism ◽  
Tourism Sector ◽  
Tourism Resources ◽  
Local Levels

This study aims to analyze the strategy of the Singkawang City Government in restoring the private sector during the COVID-19 pandemic. The research method is descriptive and qualitative, specifically related to the COVID-19 impact mitigation strategy and Singkawang tourism policies. Then analyze the strategic elements of a policy according to the implementation of the O.Jones model. Data was collected by using interviews, observation, and documentation techniques. The data is then analyzed using domain data analysis techniques as a researcher's effort to get a general and comprehensive (holistic) picture of the object under study. The findings in this study are 1) a connected tourism COVID-19 impact mitigation policy strategy from the national to local levels in Singkawang in the form of directives, regulations, COVID-19 mitigation programs, and stimulus for economic recovery in the tourism sector; and 2) there are no visible creative efforts based on health protocols in organizing tourism resources, methods, and unit synergies to restore tourism, interpretation of social media-based policies regarding tourist visits has not been measured, and strategies have not been implemented to meet the opportunities for pandemic trend tourism types with models alternative tourism according to health protocols.

scholarly journals Tracking Scheme Dependence of Simulated Tropical Cyclone Response to Idealized Climate Simulations

2014 ◽  
Vol 27 (24) ◽  
pp. 9197-9213 ◽  
Author(s):  
Michael Horn ◽  
Kevin Walsh ◽  
Ming Zhao ◽  
Suzana J. Camargo ◽  
Enrico Scoccimarro ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
General Circulation Models ◽  
Tropical Cyclone Activity ◽  
Model Data ◽  
Cyclone Activity ◽  
Sensitivity Testing

Abstract Future tropical cyclone activity is a topic of great scientific and societal interest. In the absence of a climate theory of tropical cyclogenesis, general circulation models are the primary tool available for investigating the issue. However, the identification of tropical cyclones in model data at moderate resolution is complex, and numerous schemes have been developed for their detection. The influence of different tracking schemes on detected tropical cyclone activity and responses in the Hurricane Working Group experiments is examined herein. These are idealized atmospheric general circulation model experiments aimed at determining and distinguishing the effects of increased sea surface temperature and other increased CO2 effects on tropical cyclone activity. Two tracking schemes are applied to these data and the tracks provided by each modeling group are analyzed. The results herein indicate moderate agreement between the different tracking methods, with some models and experiments showing better agreement across schemes than others. When comparing responses between experiments, it is found that much of the disagreement between schemes is due to differences in duration, wind speed, and formation-latitude thresholds. After homogenization in these thresholds, agreement between different tracking methods is improved. However, much disagreement remains, accountable for by more fundamental differences between the tracking schemes. The results indicate that sensitivity testing and selection of objective thresholds are the key factors in obtaining meaningful, reproducible results when tracking tropical cyclones in climate model data at these resolutions, but that more fundamental differences between tracking methods can also have a significant impact on the responses in activity detected.

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