ECONOMIC IMPACTS OF CLIMATE CHANGE IN SYRIA

2013 ◽  
Vol 04 (01) ◽  
pp. 1350002 ◽  
Author(s):  
CLEMENS BREISINGER ◽  
TINGJU ZHU ◽  
PERRIHAN AL RIFFAI ◽  
GERALD NELSON ◽  
RICHARD ROBERTSON ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
National Level ◽  
Economic Modeling ◽  
Food Prices ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Impacts Of Climate Change

There is broad consensus among scientists that climate change is altering weather patterns around the world. However, economists are only beginning to develop comprehensive tools that allow for the quantification of such weather changes on countries' economies and people. This paper presents a modeling suite that links the downscaling of global climate models, crop modeling, global economic modeling, and sub-national-level dynamic computable equilibrium modeling. Important to note is that this approach allows for decomposing the potential global and local economic effects on countries, including various economic sectors and different household groups. We apply this modeling suite to Syria, a relevant case study given the country's location in a region that is consistently projected to be among those hit hardest by climate change. We find that, despite a certain degree of endogenous adaptation, local impacts of climate change (through declining yields) are likely to affect Syria beyond the agricultural sector and farmers and also reduce economy-wide growth and incomes of urban households in the long term. The overall effects of global climate change (through higher food prices) are also negative, but some farmers may reap the benefit of higher prices. Combining local and global climate change scenarios shows welfare losses across all rural and urban household groups, whereas the poorest household groups are the hardest hit.

scholarly journals Strategy for generation of climate change projections feeding Spanish impact community

2018 ◽  
Vol 15 ◽  
pp. 217-230
Author(s):  
María Pilar Amblar-Francés ◽  
María Asunción Pastor-Saavedra ◽  
María Jesús Casado-Calle ◽  
Petra Ramos-Calzado ◽  
Ernesto Rodríguez-Camino
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Model ◽  
National Level ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Climate Change Projections

Abstract. Over the past decades, the successive Coupled Model Intercomparison Projects (CMIPs) have produced a huge amount of global climate model simulations. Along these years, the climate models have advanced and can thus provide credible evolution of climate at least at continental or global scales since they are better representing physical processes and feedbacks in the climate system. Nevertheless, due to the coarse horizontal resolution of global climate models, it is necessary to downscale these results for their use to assess possible future impacts of climate change in climate sensitive ecosystems and sectors and to adopt adaptation strategies at local and national level. In this vein, the Spanish State Meteorological Agency (AEMET) has been producing since 2006 a set of reference downscaled climate change projections over Spain either applying statistical downscaling techniques to the outputs of the Global Climate Models (GCMs) or making use of the information generated by dynamical downscaling techniques through European projects or international initiatives such as PRUDENCE, ENSEMBLES and EURO-CORDEX. The AEMET strategy aims at exploiting all the available sources of information on climate change projections. The generalized use of statistical and dynamical downscaling approaches allow us to encompass a great number of global models and therefore to provide a better estimation of uncertainty. Most impact climate change studies over Spain make use of this reference downscaled projections emphasizing the estimation of uncertainties. Additionally to the rationale and history behind the AEMET generation of climate change scenarios, we focus on some preliminary analysis of the dependency of estimated uncertainties on the different sources of data.

scholarly journals Projecting heat-related excess mortality under climate change scenarios in China

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jun Yang ◽  
Maigeng Zhou ◽  
Zhoupeng Ren ◽  
Mengmeng Li ◽  
Boguang Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Excess Mortality ◽  
Climate Models ◽  
Global Climate ◽  
Specific Effect ◽  
Northern China ◽  
The Elderly ◽  
Population Ageing ◽  
Global Climate Models ◽  
Climate Change Scenarios

AbstractRecent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.

The challenge of combining initialised and uninitialised decadal projections

2020 ◽  
Author(s):  
James Murphy
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Internal Climate Variability ◽  
Climate Risks ◽  
Early Results ◽  
Ensemble Mean ◽  
Decadal Climate

<p>The challenge of combining initialised and uninitialised decadal projections</p><p>James Murphy, Robin Clark, Nick Dunstone, Glen Harris, Leon Hermanson and Doug Smith</p><p>During the past 10 years or so, exploratory work in initialised decadal climate prediction, using global climate models started from recent analyses of observations, has grown into a coordinated international programme that contributes to IPCC assessments. At the same time, countries have continued to develop and update their national climate change scenarios.  These typically cover the full 21<sup>st</sup> century, including the initial decade that overlaps with the latest initialised forecasts. To date, however, national scenarios continue to be based exclusively on long-term (uninitialised) climate change simulations, with initialised information regarded as a separate stream of information.</p><p>We will use early results from the latest UK national scenarios (UKCP), and the latest CMIP6 initialised predictions, to illustrate the potential and challenges associated with the notion of combining both streams of information. This involves assessing the effects of initialisation on predictability and uncertainty (as indicated, for example, by the skill of ensemble-mean forecasts and the spread amongst constituent ensemble members). Here, a particular challenge involves interpretation of the “signal-to-noise” problem, in which ensemble-mean skill can sometimes be found which is larger than would be expected on the basis of the ensemble spread. In addition to initialisation, we will also emphasise the importance of understanding how the assessment of climate risks depends on other features of prediction system design, including the sampling of model uncertainties and the simulation of internal climate variability.</p>

scholarly journals Impact of Climate Change on the Hydrology of the Forested Watershed That Drains to Lake Erken in Sweden: An Analysis Using SWAT+ and CMIP6 Scenarios

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1803
Author(s):  
Inmaculada C. Jiménez-Navarro ◽  
Patricia Jimeno-Sáez ◽  
Adrián López-Ballesteros ◽  
Julio Pérez-Sánchez ◽  
Javier Senent-Aparicio
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Water Discharge ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Case Scenario ◽  
Worst Case

Precipitation and temperature around the world are expected to be altered by climate change. This will cause regional alterations to the hydrological cycle. For proper water management, anticipating these changes is necessary. In this study, the basin of Lake Erken (Sweden) was simulated with the recently released software SWAT+ to study such alterations in a short (2026–2050), medium (2051–2075) and long (2076–2100) period, under two different climate change scenarios (SSP2-45 and SSP5-85). Seven global climate models from the latest projections of future climates that are available (CIMP 6) were compared and ensembled. A bias-correction of the models’ data was performed with five different methods to select the most appropriate one. Results showed that the temperature is expected to increase in the future from 2 to 4 °C, and precipitation from 6% to 20%, depending on the scenario. As a result, water discharge would also increase by about 18% in the best-case scenario and by 50% in the worst-case scenario, and the surface runoff would increase between 5% and 30%. The floods and torrential precipitations would also increase in the basin. This trend could lead to soil impoverishment and reduced water availability in the basin, which could damage the watershed’s forests. In addition, rising temperatures would result in a 65% reduction in the snow water equivalent at best and 92% at worst.

Seasonal and Long-Term Changes to Pavement Life Caused by Rising Temperatures from Climate Change

2019 ◽  
Vol 2673 (6) ◽  
pp. 267-278 ◽  
Author(s):  
Jayne F. Knott ◽  
Jo E. Sias ◽  
Eshan V. Dave ◽  
Jennifer M. Jacobs
Keyword(s):  
Climate Change ◽  
Temperature Rise ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Top Down ◽  
Bottom Up ◽  
Pavement Damage ◽  
The Impact

Pavements are vulnerable to reduced life with climate-change-induced temperature rise. Greenhouse gas emissions have caused an increase in global temperatures since the mid-20th century and the warming is projected to accelerate. Many studies have characterized this risk with a top-down approach in which climate-change scenarios are chosen and applied to predict pavement-life reduction. This approach is useful in identifying possible pavement futures but may miss short-term or seasonal pavement-response trends that are essential for adaptation planning. A bottom-up approach focuses on a pavement’s response to incremental temperature change resulting in a more complete understanding of temperature-induced pavement damage. In this study, a hybrid bottom-up/top-down approach was used to quantify the impact of changing pavement seasons and temperatures on pavement life with incremental temperature rise from 0 to 5°C at a site in coastal New Hampshire. Changes in season length, seasonal average temperatures, and temperature-dependent resilient modulus were used in layered-elastic analysis to simulate the pavement’s response to temperature rise. Projected temperature rise from downscaled global climate models was then superimposed on the results to determine the timing of the effects. The winter pavement season is projected to end by mid-century, replaced by a lengthening fall season. Seasonal pavement damage, currently dominated by the late spring and summer seasons, is projected to be distributed more evenly throughout the year as temperatures rise. A 7% to 32% increase in the asphalt-layer thickness is recommended to protect the base and subgrade with rising temperatures from early century to late-mid-century.

Decomposing the uncertainties in global drought projection

2021 ◽  
Author(s):  
Yusuke Satoh ◽  
Hideo Shiogama ◽  
Naota Hanasaki ◽  
Yadu Pokhrel ◽  
Julien Boulange ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Dominant Factor ◽  
Climate Change Scenarios ◽  
Relative Importance ◽  
Main Factors ◽  
Global Water ◽  
Uncertainty Source

<p>Droughts are anticipated to intensify or become more frequent in many parts of the world due to climate change. However, the issue of drought definition, namely the diversity of drought definition, makes it difficult to compare drought projections and hampers overviewing future changes in drought. This issue is widely known and underscored in recent reports of the Intergovernmental Panel on Climate Change, but the relative importance of the issue and its spatial distribution have never been quantitatively evaluated compared to other sources of uncertainty.</p><p>Here, using a multi-scenario and multi-model dataset with combinations of three climate change scenarios, four global climate models and seven global water models, we evaluated changes in the frequency of three categories of drought (meteorological, agricultural, and hydrological droughts) by a consistent standardized approach with four different temporal scales of accumulation periods to show how differences among the drought definitions could result in critical uncertainties. For simplicity, this study focuses on one drought index per drought category. Firstly we investigated the disagreement in the sign of changes between definitions, and then we decomposed the overall uncertainty to estimate the relative importance of each source of uncertainty. By a multifactorial ANOVA, uncertainty was decomposed into four main factors, namely drought definitions, climate change scenarios, global climate models and global water impact models, and their interactions.</p><p>Our results highlight specific regions where the sign of change disagrees between drought definitions. Importantly, changes in drought frequency in such regions tended to be statistically insignificant with low ensemble member agreement. Drought definition attributed to18% of the main factor uncertainty at the global scale, and the definition was the dominant uncertainty source over 11% of the global land area. The contribution of difference in the drought category showed a higher contribution to overall uncertainty than the difference in scales. The contribution of scenario uncertainty was the least among the main factors in general, though it is a dominant factor in the far-future in a couple of hotspot regions such as the Mediterranean region. Overall, model uncertainties were the primary source of uncertainty, and the definition issue was less important over large areas. However, definition uncertainty was the primal uncertainty source with significant changes in particular regions, such as parts of high-latitude areas in the northern hemisphere. One needs to pay attention to these regions in overviewing future drought change. Nonetheless, what this study quantified is the relative importance of uncertainty stemming from drought definition that should be avoidable or reducible if one treats drought specifically. Our results indicate that we can reduce uncertainty in drought projections to some extent and get a clearer picture by clarifying hydrological processes or sectors of interest.</p>

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 Assessing the Impact of Projected Climate Change on Zoo Visitation in Toronto (Canada)

2016 ◽  
Vol 8 (2) ◽  
pp. 30 ◽  
Author(s):  
Micah J. Hewer ◽  
William A. Gough
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Positive Impact ◽  
Global Climate ◽  
Global Climate Models ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Local Climate ◽  
The Impact

Weather and climate have been widely recognised as having an important influence on tourism and recreational activities. However, the nature of these relationships varies depending on the type, timing and location of these activities. Climate change is expected to have considerable and diverse impacts on recreation and tourism. Nonetheless, the potential impact of climate change on zoo visitation has yet to be assessed in a scientific manner. This case study begins by establishing the baseline conditions and statistical relationship between weather and zoo visitation in Toronto, Canada. Regression analysis, relying on historical weather and visitation data, measured at the daily time scale, formed the basis for this analysis. Climate change projections relied on output produced by Global Climate Models (GCMs) for the Intergovernmental Panel on Climate Change’s 2013 Fifth Assessment Report, ranked and selected using the herein defined Selective Ensemble Approach. This seasonal GCM output was then used to inform daily, local, climate change scenarios, generated using Statistical Down-Scaling Model Version 5.2. A series of seasonal models were then used to assess the impact of projected climate change on zoo visitation. While accounting for the negative effects of precipitation and extreme heat, the models suggested that annual visitation to the zoo will likely increase over the course of the 21st century due to projected climate change: from +8% in the 2020s to +18% by the 2080s, for the least change scenario; and from +8% in the 2020s to +34% in the 2080s, for the greatest change scenario. The majority of the positive impact of projected climate change on zoo visitation in Toronto will likely occur in the shoulder season (spring and fall); with only moderate increases in the off season (winter) and potentially negative impacts associated with the peak season (summer), especially if warming exceeds 3.5 °C.

Sign in / Sign up

Export Citation Format

Share Document