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.

scholarly journals A new climate dataset for systematic assessments of climate change impacts as a function of global warming

2013 ◽  
Vol 6 (5) ◽  
pp. 1689-1703 ◽  
Author(s):  
J. Heinke ◽  
S. Ostberg ◽  
S. Schaphoff ◽  
K. Frieler ◽  
C. Müller ◽  
...  
Keyword(s):  
Climate Change ◽  
Temperature Change ◽  
General Circulation ◽  
Climate Model ◽  
Climate Change Impacts ◽  
General Circulation Models ◽  
Climate Change Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract. In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere–Ocean General Circulation Models (AOGCMs). The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilise a simplified relationships between ΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

scholarly journals Climate change impact on meteorological droughts in watershed scale (case study: southwestern Iran)

2014 ◽  
Vol 4 (1) ◽  
pp. 1 ◽  
Author(s):  
Alireza Nikbakht Shahbazi
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Meteorological Data ◽  
Climate Change Impacts ◽  
General Circulation Models ◽  
Future Climate Change ◽  
Monthly Precipitation ◽  
Spring Precipitation ◽  
Data Simulation ◽  
Intergovernmental Panel

Drought is one of the major natural disasters in the world which has a lot of social and economic impacts. There are various factors that affect climate changes; the investigation of this incident is also sensitive. Climate scenarios of future climate change studies and investigation of efficient methods for investigating these events on drought should be assumed. This study intends to investigate climate change impacts on drought in Karoon3 watershed in the future. For this purpose, the atmospheric general circulation models (GCM) data under Intergovernmental Panel on Climate Change (IPCC) scenarios should be investigated. In this study, watershed drought under climate change impacts will be simulated in future periods (2011 to 2099). In this research standard precipitation index (SPI) was calculated using mean monthly precipitation data in Karoon3 watershed. SPI was calculated in 6, 12 and 24 months periods. Statistical analysis on daily precipitation and minimum and maximum daily temperature was performed. To determine the feasibility of future periods meteorological data production of LRAS-WG5 model, calibration and verification was performed for the base year (1980-2007). Meteorological data simulation for future periods under General Circulation Models and climate change IPCC scenarios was performed and then the drought status using SPI under climate change effects analyzed. Results showed that differences between monthly maximum and minimum temperature will decrease under climate change and spring precipitation shall increase while summer and autumn rainfall shall decrease. The most increase of precipitation will take place in winter and in December. Normal and wet SPI category is more frequent in B1 and A2 emissions scenarios than A1B. Wet years increases in the study area during 2011-2030 period and the more continuous drought years gradually increases during 2046-2065 period, the more severe and frequent drought will occur during the 2080-2099 period.

Integrated Assessment of Climate Change Impacts on Corn Yield in the U.S. Using a Crop Model

2017 ◽  
Vol 60 (6) ◽  
pp. 2123-2136
Author(s):  
Kenichi Tatsumi
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Change Impacts ◽  
General Circulation Models ◽  
Crop Model ◽  
Corn Yield ◽  
Negative Impacts ◽  
Growing Conditions ◽  
Almost All ◽  
The U.S

Abstract. A detailed analysis was conducted of the effects of climate change and increased carbon dioxide (CO2) concentrations on corn yield in the U.S. with a crop model using outputs from multiple general circulation models (multi-GCMs). Corn yield was simulated for 1999-2010, for the 2050s (average for 2041-2060), and for the 2070s (average for 2061-2080) under the representative concentration pathway 8.5 (RCP8.5) climate scenario. Results indicated a shortening of the growing period (GP), decreased water use efficiency (WUE) in almost all regions, and increased evapotranspiration (ET) during GP in almost all regions except for the southern U.S. Using multi-GCMs, the simulations under the RCP8.5 scenario resulted in negative effects of climate change on yield in almost all regions during both future periods. Especially strong negative impacts were reported south of latitude 40° N due to less optimal growing conditions. On the other hand, there were relatively smaller negative impacts in high-latitude regions (approximately north of latitude 40° N) due to more optimal growing conditions because of larger temperature changes compared to low-latitude and mid-latitude regions. Higher CO2 concentrations have the potential to increase corn yield. CO2 effects resulted in an approximately 0.04% to 0.05% increase in yield per 1 ppm increase in CO2 concentration under the RCP8.5 scenario, but the negative impacts of increased temperatures fully outweighed the CO2-fertilization effects. Keywords: Climate change impacts, CO2 effects, Corn yield, Multiple GCMs, Uncertainty.

scholarly journals Using Geospatial Analysis and Hydrologic Modeling to Estimate Climate Change Impacts on Nitrogen Export: Case Study for a Forest and Pasture Dominated Watershed in North Carolina

2018 ◽  
Vol 7 (7) ◽  
pp. 280 ◽  
Author(s):  
Md Alam ◽  
Mehmet Ercan ◽  
Faria Zahura ◽  
Jonathan Goodall
Keyword(s):  
Climate Change ◽  
North Carolina ◽  
General Circulation ◽  
Assessment Tool ◽  
Inorganic Nitrogen ◽  
Swat Model ◽  
Climate Change Impacts ◽  
General Circulation Models ◽  
Nitrogen Loading ◽  
Nitrogen Export

Many watersheds are currently experiencing streamflow and water quality related problems that are caused by excess nitrogen. Given that weather is a major driver of nitrogen transport through watersheds, the objective of this study was to predict climate change impacts on streamflow and nitrogen export. A forest and pasture dominated watershed in North Carolina Piedmont region was used as the study area. A physically-based Soil and Water Assessment Tool (SWAT) model parameterized using geospatial data layers and spatially downscaled temperature and precipitation estimates from eight different General Circulation Models (GCMs) were used for this study. While temperature change predictions are fairly consistent across the GCMs for the study watershed, there is significant variability in precipitation change predictions across the GCMs, and this leads to uncertainty in the future conditions within the watershed. However, when the downscaled GCM projections were taken as a model ensemble, the results suggest that both high and low emission scenarios would result in an average increase in streamflow of 14.1% and 12.5%, respectively, and a decrease in the inorganic nitrogen export by 12.1% and 8.5%, respectively, by the end of the century. The results also show clear seasonal patterns with streamflow and nitrogen loading both increasing in fall and winter months by 97.8% and 50.8%, respectively, and decreasing by 20.2% and 35.5%, respectively, in spring and summer months by the end of the century.

Evaluation of climate change impacts on streamflow to a multiple reservoir system using a data-based mechanistic model

2014 ◽  
Vol 5 (4) ◽  
pp. 610-624 ◽  
Author(s):  
Sara Nazif ◽  
Mohammad Karamouz
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Mechanistic Model ◽  
Moving Average ◽  
Daily Rainfall ◽  
Circulation Model ◽  
Climate Change Impacts ◽  
Climate Change Scenarios ◽  
Daily Streamflow ◽  
Global Mean Temperature

Recent investigations have demonstrated scientists' consensus on the increase in global mean temperature and climate variability. These changes alter the hydro-climatic condition of regions. Investigation of surface water changes is an important issue in water resources planning as well as for the operation of reservoirs. In this study a data-based mechanistic (DBM) model has been used for daily streamflow simulation. This model is a data-driven statistical base simulation model that can take advantage of additional climate variables with time variable configurations. The model has been developed for simulation of streamflow to three reservoirs, located in central Iran, using the daily rainfall, temperature and streamflow data. Comparison of the DBM results with the autoregressive integrated moving average model, as an alternative model, shows its higher performance. To include climate change impacts in study, an artificial neural network-based statistical downscaling model is developed for rainfall and temperature downscaling. The downscaled temperature and rainfall data under climate change scenarios based on HadCM3 general circulation model outputs are used to evaluate the climate change impacts on streamflow for the 2000–2050 time horizon. The results demonstrate the considerable impact of climate change on streamflow variability with significantly different behaviour in the three adjacent basins.

An Improved Daily Weather Generator for the Assessment of Regional Climate Change Impacts

2021 ◽  
Author(s):  
Mohammad Reza Khazaei ◽  
Mehraveh Hasirchian ◽  
Bagher Zahabiyoun
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Regional Climate ◽  
Low Frequency ◽  
Climate Change Impacts ◽  
Regional Climate Change ◽  
General Circulation Models ◽  
Weather Generator ◽  
Weather Data ◽  
Monthly Precipitation

Abstract Weather Generators (WGs) are one of the major downscaling tools for assessing regional climate change impacts. However, some deficiencies in the performance of WGs have limited their usage. This paper presents a method for correcting the low-frequency variability (LFV) of precipitation in the Improved Weather Generator (IWG) model. The method is based on bias correction in the monthly precipitation distribution of the generated daily series. The performance of the modified model was tested directly by comparing the statistics of generated and observed weather data for 14 stations, and also indirectly by comparing the characteristics of simulated stream-flows of a basin from the simulations run based on generated and observed weather data. The results showed that the method not only corrected the LFV of precipitation but also improved the reproduction of many other statistics. The provided IWG2 model can serve as a useful tool for the downscaling of General Circulation Models (GCMs) scenarios to assess regional climate change impacts, especially hydrological effects.

Simulating present and future climates of southern Africa using general circulation models

1997 ◽  
Vol 21 (1) ◽  
pp. 51-78 ◽  
Author(s):  
A.M. Joubert ◽  
B.C. Hewitson
Keyword(s):  
Climate Change ◽  
Southern Africa ◽  
General Circulation ◽  
Regional Climate ◽  
Daily Rainfall ◽  
Regional Climate Change ◽  
Summer Rainfall ◽  
General Circulation Models ◽  
Empirical Downscaling ◽  
Projected Changes

The current state of regional climate and climate change modelling using GCMs is reviewed for southern Africa, and several approaches to regional climate change prediction which have been applied to southern Africa are assessed. Confidence in projected regional changes is based on the ability of a range of models to simulate present regional climate, and is greatest where intermodel consensus in terms of the nature of projected changes is highest. Both equil ibrium and transient climate change projections for southern Africa are considered. Warming projected over southern Africa is within the range of globally averaged estimates. Uncertainties associated with the parameterization of convection ensure that projected changes in rainfall at GCM grid scales remain unreliable. However, empirical downscaling approaches produce rainfall changes consistent with synoptic-scale circulation. Both downscaling and grid-scale approaches indicate a 10-15% decrease in summer rainfall over the central interior which may have important implications for surface hydrology. Climate change may be manifested as a change in variability, and not in mean climate. Over southern Africa, increases in the variability and intensity of daily rainfall events are indicated.

scholarly journals Assessment of the Impact of Climate Change on Snow Distribution and River Flows in a Snow-Dominated Mountainous Watershed in the Western Hindukush–Himalaya, Afghanistan

Hydrology ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 74
Author(s):  
Abdul Haseeb Azizi ◽  
Yoshihiro Asaoka
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
21St Century ◽  
General Circulation ◽  
River Flow ◽  
General Circulation Models ◽  
Snow Cover Area ◽  
River Flows ◽  
Late 21St Century ◽  
The Impact

Projected snow cover and river flows are important for planning and managing water resources in snow-dominated basins of the Himalayas. To quantify the impacts of climate change in the data scarce Panjshir River basin of Afghanistan, this study simulated present and future snow cover area (SCA) distributions with the snow model (SM), and river flows with the snowmelt runoff model (SRM). The SRM used the degree-day factor and precipitation gradient optimized by the SM to simulate river flows. Temperature and precipitation data from eight kinds of general circulation models (GCMs) were used for bias correction. The SM and SRM were first calibrated and validated using 2009–2015 data, and then bias-corrected future climate data were input to the models to simulate future SCA and river flows. Under both the representative concentration pathways (RCP) 4.5 and 8.5, the annual average SCA and river flow were projected to decrease in the mid and late 21st century, although seasonal increases were simulated in some instances. Uncertainty ranges in projected SCA and river flow under RCP 8.5 were small in the mid 21st century and large in the late 21st century. Therefore, climate change is projected to alter high-altitude stream sources in the Hindukush mountains and reduce the amount of water reaching downstream areas.

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