scholarly journals Climate Zoning Under Climate Change Scenarios In The Basin Of Lake Urmia And Vicinity Basins

2022 ◽  
Author(s):  
Rasoul Jani ◽  
Rahman Khatibi ◽  
Sina Sadeghfam ◽  
Elnaz Zarrinbal
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Northern Region ◽  
Climate Change Scenarios ◽  
Climate Variables ◽  
Lake Urmia ◽  
The Caspian Sea ◽  
Time Periods ◽  
Using Data ◽  
Two Stages

Abstract A study of climate change scenarios is presented in this paper by projecting a set of recorded precipitation data into three future periods by statistical downscaling methods by employing LARS-WG using data from 7 synoptic stations. The study area covers the basin of Lake Urmia and its overlaps with two of its surrounding basins flowing to the Caspian Sea. The modelling is at two stages: Downscaling comprises: (i) use large-scale GCM models to provide climate variables (predictors); and (ii) downscale them to the local climatic variables for correlating with the observed timeseries (e.g. rainfall) for the period of T0: 1961-2001 - 40 years; Projecting comprises the derivation of precipitation values during the time periods of ; T1: 2011-2030), T2: 2046-2065 and T3: 2080-2099 at synoptic stations using three of standard scenarios: A1B, A2 and B1. These values are then used to map the climate zoning, which show: (i) climates at T1 are still similar to T0 and if any difference, precipitation increases; but changes are likely at T2 and T3 periods; (ii) the climate is moving toward a peakier regime at the northern region but drier towards the central region; and (iii) precipitation is likely to decrease in some of the zones. Thus, the results underpin the need for more responsive policymaking and should this not be realised in the next 5 to 10 years, the future seems bleak, as the loss of Lake Urmia and the depletion of aquifers are likely to be permanent, inflicting immigration from the region.

scholarly journals Simulating future precipitation extremes in a complex Alpine catchment

2013 ◽  
Vol 13 (2) ◽  
pp. 263-277 ◽  
Author(s):  
C. Dobler ◽  
G. Bürger ◽  
J. Stötter
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Precipitation Extremes ◽  
Climate Projections ◽  
Research Station ◽  
Climate Change Scenarios ◽  
Station Data

Abstract. The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.

scholarly journals Impact of future climate change on water supply and irrigation demand in a small mediterranean catchment. Case study: Nebhana dam system, Tunisia

2019 ◽  
Vol 11 (4) ◽  
pp. 1724-1747 ◽  
Author(s):  
M. Allani ◽  
R. Mezzi ◽  
A. Zouabi ◽  
R. Béji ◽  
F. Joumade-Mansouri ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Supply ◽  
General Circulation ◽  
General Circulation Models ◽  
Future Climate ◽  
Annual Rainfall ◽  
Future Climate Change ◽  
Cycle Duration ◽  
Climate Change Scenarios ◽  
Time Periods

Abstract This study evaluates the impacts of climate change on water supply and demand of the Nebhana dam system. Future climate change scenarios were obtained from five general circulation models (GCMs) of CMIP5 under RCP 4.5 and 8.5 emission scenarios for the time periods, 2021–2040, 2041–2060 and 2061–2080. Statistical downscaling was applied using LARS-WG. The GR2M hydrological model was calibrated, validated and used as input to the WEAP model to assess future water availability. Expected crop growth cycle lengths were estimated using a growing degree days model. By means of the WEAP-MABIA method, projected crop and irrigation water requirements were estimated. Results show an average increase in annual ETo of 6.1% and a decrease in annual rainfall of 11.4%, leading to a 24% decrease in inflow. Also, crops' growing cycles will decrease from 5.4% for wheat to 31% for citrus trees. The same tendency is observed for ETc. Concerning irrigation requirement, variations are more moderated depending on RCPs and time periods, and is explained by rainfall and crop cycle duration variations. As for demand and supply, results currently show that supply does not meet the system demand. Climate change could worsen the situation unless better planning of water surface use is done.

scholarly journals Tidal wetland resilience to sea level rise increases their carbon sequestration capacity in United States

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Faming Wang ◽  
Xiaoliang Lu ◽  
Christian J. Sanders ◽  
Jianwu Tang
Keyword(s):  
Climate Change ◽  
United States ◽  
Sea Level Rise ◽  
Sea Level ◽  
Large Scale ◽  
Accumulation Rate ◽  
C Sequestration ◽  
Tidal Wetlands ◽  
Tidal Wetland ◽  
Climate Change Scenarios

AbstractCoastal wetlands are large reservoirs of soil carbon (C). However, the annual C accumulation rates contributing to the C storage in these systems have yet to be spatially estimated on a large scale. We synthesized C accumulation rate (CAR) in tidal wetlands of the conterminous United States (US), upscaled the CAR to national scale, and predicted trends based on climate change scenarios. Here, we show that the mean CAR is 161.8 ± 6 g Cm−2 yr−1, and the conterminous US tidal wetlands sequestrate 4.2–5.0 Tg C yr−1. Relative sea level rise (RSLR) largely regulates the CAR. The tidal wetland CAR is projected to increase in this century and continue their C sequestration capacity in all climate change scenarios, suggesting a strong resilience to sea level rise. These results serve as a baseline assessment of C accumulation in tidal wetlands of US, and indicate a significant C sink throughout this century.

Drought modelling under climate change scenarios and its probabilistic characterization: A Review

2021 ◽  
pp. 403-417
Author(s):  
Amit Dubey ◽  
Deepak Swami ◽  
Nitin Joshi
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Time Window ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Indices ◽  
Climate Change Scenarios ◽  
Drought Forecasting ◽  
Copula Models

ncrease in the water scarcity and the related rise in demand of water coupled with the threating events of climate change, ultimately witnessed drought in the recent years to occur frequently. Therefore, Drought hydrology is drawing most of the attention. Drought which is a natural hazard can be best characterized by various hydrological and climatological parameters. In order to model drought, researchers have applied various concepts starting from simplistic model to the complex ones. The suitability of different modelling approaches and their negative and positive traits are very essential to comprehend. This paper is an attempt to review various methodologies utilized in modelling of drought such as forecasting of drought, drought modelling based on probability, Global Climate Models (GCM) under climate change scenarios. It is obtained from the present study that the past three decades have witnessed a very significant improvement in the drought modelling studies. For the larger time window of drought forecasting, hybrid models which incorporates large scale climate indices are promisingly suitable. Drought characterization based on copula models for multivariate drought characterization seems to have an edge over the others. At the end some conclusive remarks are made as far as the future drought modelling and research is concerned.

scholarly journals Large-scale winds in the southern North Sea region: the wind part of the KNMI’14 climate change scenarios

2015 ◽  
Vol 10 (3) ◽  
pp. 035004 ◽  
Author(s):  
Andreas Sterl ◽  
Alexander M R Bakker ◽  
Henk W van den Brink ◽  
Rein Haarsma ◽  
Andrew Stepek ◽  
...  
Keyword(s):  
Climate Change ◽  
North Sea ◽  
Large Scale ◽  
Climate Change Scenarios ◽  
Southern North Sea

Future changes of circulation types associated with extremes over Sweden

2020 ◽  
Author(s):  
Felicitas Hansen ◽  
Danijel Belusic ◽  
Klaus Wyser
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Radiative Forcing ◽  
Large Scale ◽  
Extreme Values ◽  
Global Climate Model ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Circulation Types ◽  
Precipitation And Temperature

<p>The large-scale atmospheric circulation is one of the most important factors influencing weather and climate conditions on different timescales. Its short- and long-term changes considerably determine both mean and extreme values of surface parameters like temperature or precipitation rates. Future changes of circulation patterns are of particular interest as these may significantly alter or amplify the expected thermodynamic changes due to changing concentrations of greenhouse gases, albedo and land use. We analyse both historical as well as future climate simulations of the SMHI large ensemble (S-LENS) performed with the EC-Earth3 global climate model to examine large-scale circulation situations and their association to extremes in precipitation and temperature over Sweden. Various methods exist to classify mostly sea level pressure or geopotential height fields into characteristic circulation types, and we compare several of these methods for their applicability to represent precipitation and temperature variability over our region of interest. S-LENS consists of a 50-member ensemble for a historical period (1970-2014) and four 50-member climate change scenario ensembles covering the 21st century differing in terms of assumptions made for future radiative forcing development. We study the efficiency of circulation types in the historical period to give rise to extremes, and examine further the frequency and within-type changes of those circulation types associated with extremes by the middle and the end of the 21st century under the different climate change scenarios. S-LENS with its comparatively large number of both multi-decadal scenarios and realizations for each scenario serves as a perfect testbed to study potential changes in events of low frequency within the environment of a single model.</p>

Chaos in Estimates of Climate Change Impacts

2020 ◽  
Author(s):  
Emanuele Massetti ◽  
Emanuele Di Lorenzo
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Initial Conditions ◽  
Climate Change Impacts ◽  
Internal Variability ◽  
Future Climate ◽  
Climate System ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Exogenous Forcing

<p>Estimates of physical, social and economic impacts of climate change are less accurate than usually thought because the impacts literature has largely neglected the internal variability of the climate system. Climate change scenarios are highly sensitive to the initial conditions of the climate system due the chaotic dynamics of weather. As the initial conditions of the climate system are unknown with a sufficiently high level of precision, each future climate scenario – for any given model parameterization and level of exogenous forcing – is only one of the many possible future realizations of climate. The impacts literature usually relies on only one realization randomly taken out of the full distribution of future climates. Here we use one of the few available large scale ensembles produced to study internal variability and an econometric model of climate change impacts on United States (US) agricultural productivity to show that the range of impacts is much larger than previously thought. Different ensemble members lead to significantly different impacts. Significant sign reversals are frequent. Relying only on one ensemble member leads to incorrect conclusions on the effect of climate change on agriculture in most of the US counties. Impacts studies should start using large scale ensembles of future climate change to predict damages. Climatologists should ramp-up efforts to run large ensembles for all GCMs, for at least the most frequently used scenarios of exogenous forcing.</p>

Verification of GCM-Generated Regional Seasonal Precipitation for Current Climate and of Statistical Downscaling Estimates under Changing Climate Conditions

1999 ◽  
Vol 12 (1) ◽  
pp. 258-272 ◽  
Author(s):  
Aristita Busuioc ◽  
Hans von Storch ◽  
Reiner Schnur
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Climate Models ◽  
Regional Scale ◽  
The Other ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Seasonal Precipitation ◽  
Empirical Downscaling

Abstract Empirical downscaling procedures relate large-scale atmospheric features with local features such as station rainfall in order to facilitate local scenarios of climate change. The purpose of the present paper is twofold: first, a downscaling technique is used as a diagnostic tool to verify the performance of climate models on the regional scale; second, a technique is proposed for verifying the validity of empirical downscaling procedures in climate change applications. The case considered is regional seasonal precipitation in Romania. The downscaling model is a regression based on canonical correlation analysis between observed station precipitation and European-scale sea level pressure (SLP). The climate models considered here are the T21 and T42 versions of the Hamburg ECHAM3 atmospheric GCM run in “time-slice” mode. The climate change scenario refers to the expected time of doubled carbon dioxide concentrations around the year 2050. The downscaling model is skillful for all seasons except spring. The general features of the large-scale SLP variability are reproduced fairly well by both GCMs in all seasons. The climate models reproduce the empirically determined precipitation–SLP link in winter, whereas the observed link is only partially captured for the other seasons. Thus, these models may be considered skillful with respect to regional precipitation during winter, and partially during the other seasons. Generally, applications of statistical downscaling to climate change scenarios have been based on the assumption that the empirical link between the large-scale and regional parameters remains valid under a changed climate. In this study, a rationale is proposed for this assumption by showing the consistency of the 2 × CO2 GCM scenarios in winter, derived directly from the gridpoint data, with the regional scenarios obtained through empirical downscaling. Since the skill of the GCMs in regional terms is already established, it is concluded that the downscaling technique is adequate for describing climatically changing regional and local conditions, at least for precipitation in Romania during winter.

scholarly journals Application of LARS - WG downscaling model for building climate change scenarios in the Srepok watershed

2014 ◽  
Vol 17 (2) ◽  
pp. 108-122
Author(s):  
Khoi Nguyen Dao ◽  
Nhung Thi Hong Nguyen ◽  
Canh Thanh Truong
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Emission Scenario ◽  
Circulation Model ◽  
Climate Change Scenarios ◽  
Climate Variables ◽  
Climate Data ◽  
Policy Makers ◽  
Rain Gauges ◽  
Temperature And Precipitation

There are statistical downscaling methods such as: SDSM, LARS-WG, WGEN…, used to convert information on climate variables from the simulation results of General Circulation Model (GCM) to build climate change scenarios for local region. In this study, we used the LARS-WG model and HadCM3 GCM for two emission scenarios: B1 (low emission scenario) and A1B (medium emission scenario) to generate future scenarios for temperature and precipitation at meteorological stations and rain gauges in the Srepok watershed. The LARS-WG model was calibrated and validated against observed climate data for the period 1980-2009, and the calibrated LARS-WG was then used to generate future climate variables for the 2020s (2011-2030), 2055s (2046-2065), and 2090s (2080-2099). The climate change scenarios suggested that the climate in the study area will become warmer and drier in the future. The results obtained in this study could be useful for policy makers in planning climate change adaptation strategies for the study area.

Sign in / Sign up

Export Citation Format

Share Document