scholarly journals Dengue fever epidemic potential as projected by general circulation models of global climate change.

1998 ◽  
Vol 106 (3) ◽  
pp. 147-153 ◽  
Author(s):  
J A Patz ◽  
W J Martens ◽  
D A Focks ◽  
T H Jetten
Keyword(s):  
Climate Change ◽  
Dengue Fever ◽  
Global Climate Change ◽  
General Circulation ◽  
Global Climate ◽  
General Circulation Models

scholarly journals Evaluation of data-driven models to downscale rainfall parameters from global climate models outputs: the case study of Latyan watershed

2018 ◽  
Vol 11 (1) ◽  
pp. 200-216 ◽  
Author(s):  
Reza Haji Hosseini ◽  
Saeed Golian ◽  
Jafar Yazdi
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Fuzzy Inference ◽  
Global Climate ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Data Driven ◽  
Observation Data ◽  
Inference System

Abstract Assessment of climate change in future periods is considered necessary, especially with regard to probable changes to water resources. One of the methods for estimating climate change is the use of the simulation outputs of general circulation models (GCMs). However, due to the low resolution of these models, they are not applicable to regional and local studies and downscaling methods should be applied. The purpose of the present study was to use GCM models' outputs for downscaling precipitation measurements at Amameh station in Latyan dam basin. For this purpose, the observation data from the Amameh station during the 1980–2005 period, 26 output variables from two GCM models, namely, HadCM3 and CanESM2 were used. Downscaling was performed by three data-driven methods, namely, artificial neural network (ANN), nonparametric K-nearest neighborhood (KNN) method, and adaptive network-based fuzzy inference system method (ANFIS). Comparison of the monthly results showed the superiority of KNN compared to the other two methods in simulating precipitation. However, all three, ANN, KNN, and ANFIS methods, showed satisfactory results for both HadDCM3 and CanESM2 GCM models in downscaling precipitation in the study area.

scholarly journals Impacts of Projected Climate Change over the Lake Champlain Basin in Vermont

2014 ◽  
Vol 53 (8) ◽  
pp. 1861-1875 ◽  
Author(s):  
Justin Guilbert ◽  
Brian Beckage ◽  
Jonathan M. Winter ◽  
Radley M. Horton ◽  
Timothy Perkins ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Global Climate ◽  
Coupled Model ◽  
General Circulation Models ◽  
First Century ◽  
Lake Champlain ◽  
Maple Syrup ◽  
Twenty First Century ◽  
Precipitation And Temperature

AbstractThe Lake Champlain basin is a critical ecological and socioeconomic resource of the northeastern United States and southern Quebec, Canada. While general circulation models (GCMs) provide an overview of climate change in the region, they lack the spatial and temporal resolution necessary to fully anticipate the effects of rising global temperatures associated with increasing greenhouse gas concentrations. Observed trends in precipitation and temperature were assessed across the Lake Champlain basin to bridge the gap between global climate change and local impacts. Future shifts in precipitation and temperature were evaluated as well as derived indices, including maple syrup production, days above 32.2°C (90°F), and snowfall, relevant to managing the natural and human environments in the region. Four statistically downscaled, bias-corrected GCM simulations were evaluated from the Coupled Model Intercomparison Project phase 5 (CMIP5) forced by two representative concentration pathways (RCPs) to sample the uncertainty in future climate simulations. Precipitation is projected to increase by between 9.1 and 12.8 mm yr−1 decade−1 during the twenty-first century while daily temperatures are projected to increase between 0.43° and 0.49°C decade−1. Annual snowfall at six major ski resorts in the region is projected to decrease between 46.9% and 52.4% by the late twenty-first century. In the month of July, the number of days above 32.2°C in Burlington, Vermont, is projected to increase by over 10 days during the twenty-first century.

scholarly journals Modeling the Impacts of Climate Change on Groundwater Resources: A Review

2020 ◽  
pp. 61-76
Author(s):  
Syed Rouhullah Ali ◽  
Junaid N. Khan ◽  
Yogesh Pandey ◽  
Mehraj U. Din Dar ◽  
Mudasir Shafi ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Water Resource Management ◽  
Climate Models ◽  
Global Climate ◽  
Groundwater Resources ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Basin Scale ◽  
The Face

Global atmospheric general circulation models (GCMs) were developed to simulate the current climate and are used to predict climate change. Several Global Climate Models (GCM’s) are available for understanding and projecting climate change. GCM requires to be downscale on a basin-scale and combined with applicable hydrological models considering all components of the hydrologic process. The performance of such coupling models, such as groundwater recharge quantification, should help to make correct adaptation strategies. Climate change has the ability to affect both the quality and quantity of available groundwater, mainly through impact on recharge, evapotranspiration, pump-age and abstraction. As a consequence, groundwater is a significant contributor to the streamflow in areas with fairly shallow water resources, knowing how climate change could impact groundwater supplies is crucial for long-term water resource management. The effect of climate change on groundwater systems is very difficult to predict. Part of the uncertainty of climate predictions is embedded of possibilities. Better insights, a more profound knowledge of mechanisms and modeling skills are required to determine this critical resource’s potential in the face of predicted climate change.

scholarly journals The impact of climate change on hydrological patterns in Czech headwater catchments

2010 ◽  
Vol 7 (1) ◽  
pp. 1245-1278 ◽  
Author(s):  
A. Benčoková ◽  
P. Krám ◽  
J. Hruška
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
General Circulation Models ◽  
Annual Runoff ◽  
Mean Flow ◽  
Forested Catchments ◽  
The Impact

Abstract. The aim of this study was to estimate the impacts of anticipated global climate change on runoff and evapotranspiration in small-forested catchments. The investigated Lysina and Pluhův Bor catchments are situated in the Slavkov Forest in the western part of the Czech Republic. To forecast hydrological patterns for the period 2071–2100, outputs from two general circulation models, HadAM3H and ECHAM4/OPYC3, were downscaled by an RCAO (regional climate model) which ran the SRES emission scenarios A2 and B2 for each model. Bias-corrected RCAO daily outputs were used in combination with the hydrological model Brook90. Annual runoff is predicted to decline by 6–45%, and impacts on the distribution of monthly flow are predicted to be significant, with summer-autumn decreases of 29–96%, and winter increases of up to ~48% compared to mean flow from 1967–1990. Mean daily flows are estimated to decrease by 63–94% from August to November. These changes would have serious ecological consequences, since streams could regularly dry-up for short periods of time.

Uncertainty of climate change and its impact on reference evapotranspiration in Rasht City, Iran

2011 ◽  
Vol 2 (1) ◽  
pp. 72-83 ◽  
Author(s):  
Heerbod Jahanbani ◽  
Lee Teang Shui ◽  
Alireza Massah Bavani ◽  
Abdul Halim Ghazali
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Model ◽  
Reference Evapotranspiration ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
General Circulation Models ◽  
Model Version ◽  
The Impact

There are many factors of uncertainty regarding the impact of climate change on reference evapotranspiration (ETo). The accuracy of the results is strictly related to these factors and ignoring any one of them reduces the precision of the results, and reduces their applicability for decision makers. In this study, the uncertainty related to two ETo models, the Hargreaves-Samani (HGS) and Artificial Neural Network (ANN), and two Atmosphere-Ocean General Circulation Models (AOGCMs), Hadley Centre Coupled Model, version 3 (HadCM3) climatic model and the Canadian Global Climate Model, version 3 (CGCM3) climatic model under climate change, was evaluated. The models predicted average temperature increases by 2010 to 2039 of 0.95 °C by the HadCM3 model and 1.13°C by the CGCM3 model under the A2 scenario relative to observed temperature. Accordingly, the models predicted average ETo would increase of 0.48, 0.60, 0.50 and 0.60 (mm/day) by 2010 to 2039 projected by four methods (by introducing the temperature of the HadCM3-A2 model and the CGCM3-A2 to ANN and HGS) relative to ETo of the observed period. The results showed that uncertainty of the AOGCMs is more than that of the ETo models applied in this study.

scholarly journals The impact of the climate change on discharge of Suir River Catchment (Ireland) under different climate scenarios

2006 ◽  
Vol 6 (3) ◽  
pp. 387-395 ◽  
Author(s):  
S. Wang ◽  
R. McGrath ◽  
T. Semmler ◽  
C. Sweeney ◽  
P. Nolan
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Hydrological Model ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
General Circulation Models ◽  
Climate Data ◽  
River Catchment ◽  
The Impact

Abstract. The impact of climate change on local discharge variability is investigated in the Suir River Catchment which is located in the south-east of Ireland. In this paper, the Rossby Centre Regional Atmospheric Model (RCA) is driven by different global climate data sets. For the past climate (1961–2000), the model is driven by ECMWF reanalysis (ERA-40) data as well as by the output of the general circulation models (GCM's) ECHAM4 and ECHAM5. For the future simulation (2021–2060), the model is driven by two GCM scenarios: ECHAM4_B2 and ECHAM5_A2. To investigate the influence of changed future climate on local discharge, the precipitation of the model output is used as input for the HBV hydrological model. The calibration and validation results of our ERA-40 driven present day simulation shows that the HBV model can reproduce the discharge fairly well, except the extreme discharge is systematically underestimated by about 15–20%. Altogether the application of a high resolution regional climate model in connection with a conceptual hydrological model is capable of capturing the local variability of river discharge for present-day climate using boundary values assimilated with observations such as ERA-40 data. However, using GCM data to drive RCA and HBV suggests, that there is still large uncertainty connected with the GCM formulation: For present day climate the validation of the ECHAM4 and ECHAM5 driven simulations indicates stronger discharge compared to the observations due to overprediction of precipitation, especially for the ECHAM5 driven simulation in the summer season. Whereas according to the ECHAM4_B2 scenario the discharge generally increases – most pronounced in the wet winter time, there are only slight increases in winter and considerable decreases in summer according to the ECHAM5_A2 scenario. This also leads to a different behaviour in the evolution of return levels of extreme discharge events: Strong increases according to the ECHAM4_B2 scenario and slight decreases according to the ECHAM5_A2 scenario.

scholarly journals Assessing the Impact of Climate Change on Future Water Demand using Weather Data

2021 ◽  
Author(s):  
Diana Fiorillo ◽  
Zoran Kapelan ◽  
Maria Xenochristou ◽  
Francesco De Paola ◽  
Maurizio Giugni
Keyword(s):  
Climate Change ◽  
Water Demand ◽  
General Circulation ◽  
Global Climate ◽  
General Circulation Models ◽  
Social Characteristics ◽  
Weather Data ◽  
Climate Change Scenarios ◽  
Impact Of Climate Change ◽  
The Impact

AbstractAssessing the impact of climate change on water demand is a challenging task. This paper proposes a novel methodology that quantifies this impact by establishing a link between water demand and weather based on climate change scenarios, via Coupled General Circulation Models. These models simulate the response of the global climate system to increasing greenhouse gas concentrations by reproducing atmospheric and ocean processes. In order to establish the link between water demand and weather, Random Forest models based on weather variables were used. This methodology was applied to a district metered area in Naples (Italy). Results demonstrate that the total district water demand may increase by 9–10% during the weeks with the highest temperatures. Furthermore, results show that the increase in water demand changes depending on the social characteristics of the users. The water demand of employed users with high education may increase by 13–15% when the highest temperatures occur. These increases can seriously affect the capacity and operation of existing water systems.

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