scholarly journals The impact of climate change in wheat and barley yields in the Iberian Peninsula

2021 ◽  
Author(s):  
Virgílio A. Bento ◽  
Andreia F.S. Ribeiro ◽  
Ana Russo ◽  
Célia M. Gouveia ◽  
Rita M. Cardoso ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Iberian Peninsula ◽  
Climate Models ◽  
Crop Yields ◽  
Greenhouse Gas Emission ◽  
Hot Spot ◽  
Historical Period ◽  
Temperature And Precipitation ◽  
The Impact

<p>World food and drink production largely depends on wheat and barley crops, which are the basis of nutrition for both humans and animals. The Iberian Peninsula (IP), and particularly Spain, is responsible for a large percentage of farming areas dedicated to these two crops. Furthermore, the IP is known as a prominent climate change hot spot, with expected rising temperatures and a decrease in mean precipitation (with more extreme events). Thus, it is vital to understand the effects of climate change in wheat and barley yields in the IP.</p><p>Multiple linear regression (MLR) models were developed based on the relation between temperature and precipitation and both crop yields, with the aim of projecting these into the future. Three main objectives were pursued: (1) to establish the existence of a relationship between wheat and barley yields and temperature and precipitation, taking advantage of data from the EURO-CORDEX regional climate models (RCMs) forced with ERA-Interim; (2) to calibrate and validate MLR models using a selection of predictors from the same EURO-CORDEX RCMs; and (3) to apply these MLR models to EURO-CORDEX RCMs forced with global climate models (GCMs) for an historical period (1971-2000) and two future periods (2041-2070 and 2071-2100) according to two greenhouse gas emission scenarios (RCP4.5 and RCP8.5). Results show a dichotomic behaviour of wheat and barley future yields depending on the crop’s production region. Projections for the southern cluster of the IP show severe yield losses for both cereals, which may be a consequence of the increase in maximum temperatures in spring, particularly for RCP8.5 at the end of the 21st century. Conversely, projections for the northern cluster of the IP show an increase in yield output, which may be a result of the projected warming taking place within the early winter months.</p><p>This study reinforces the worth to implementing changes in the society to mitigate losses and to assess production gains/losses due to climate change. These may be implemented locally (different cultivar species), countrywide (implementing sustainable policies), or even globally (alleviate greenhouse gas emissions). This work was supported by project IMPECAF (PTDC/CTA-CLI/28902/2017), LEADING (PTDC/CTA-MET/28914/2017) and by IDL (UIDB/50019/2020).</p>

scholarly journals The impact of climate change in wheat and barley yields in the Iberian Peninsula

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Virgílio A. Bento ◽  
Andreia F. S. Ribeiro ◽  
Ana Russo ◽  
Célia M. Gouveia ◽  
Rita M. Cardoso ◽  
...  
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Model ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Historical Period ◽  
Early Winter ◽  
Impact Of Climate Change ◽  
The Impact ◽  
Spring Maximum

AbstractThe impact of climate change on wheat and barley yields in two regions of the Iberian Peninsula is here examined. Regression models are developed by using EURO-CORDEX regional climate model (RCM) simulations, forced by ERA-Interim, with monthly maximum and minimum air temperatures and monthly accumulated precipitation as predictors. Additionally, RCM simulations forced by different global climate models for the historical period (1972–2000) and mid-of-century (2042–2070; under the two emission scenarios RCP4.5 and RCP8.5) are analysed. Results point to different regional responses of wheat and barley. In the southernmost regions, results indicate that the main yield driver is spring maximum temperature, while further north a larger dependence on spring precipitation and early winter maximum temperature is observed. Climate change seems to induce severe yield losses in the southern region, mainly due to an increase in spring maximum temperature. On the contrary, a yield increase is projected in the northern regions, with the main driver being early winter warming that stimulates earlier growth. These results warn on the need to implement sustainable agriculture policies, and on the necessity of regional adaptation strategies.

Structural safety and design under climate change

2019 ◽  
Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Structural Reliability ◽  
Greenhouse Gas Emission ◽  
Extreme Value ◽  
Structural Safety ◽  
Climate Projections ◽  
Climate Conditions ◽  
Impact Of Climate Change ◽  
The Impact

<p>The impact of climate change on climatic actions could significantly affect, in the mid-term future, the design of new structures as well as the reliability of existing ones designed in accordance to the provisions of present and past codes. Indeed, current climatic loads are defined under the assumption of stationary climate conditions but climate is not stationary and the current accelerated rate of changes imposes to consider its effects.</p><p>Increase of greenhouse gas emissions generally induces a global increase of the average temperature, but at local scale, the consequences of this phenomenon could be much more complex and even apparently not coherent with the global trend of main climatic parameters, like for example, temperature, rainfalls, snowfalls and wind velocity.</p><p>In the paper, a general methodology is presented, aiming to evaluate the impact of climate change on structural design, as the result of variations of characteristic values of the most relevant climatic actions over time. The proposed procedure is based on the analysis of an ensemble of climate projections provided according a medium and a high greenhouse gas emission scenario. Factor of change for extreme value distribution’s parameters and return values are thus estimated in subsequent time windows providing guidance for adaptation of the current definition of structural loads.</p><p>The methodology is illustrated together with the outcomes obtained for snow, wind and thermal actions in Italy. Finally, starting from the estimated changes in extreme value parameters, the influence on the long-term structural reliability can be investigated comparing the resulting time dependent reliability with the reference reliability levels adopted in modern Structural codes.</p>

scholarly journals Impact of climate change on sediment yield in the Mekong River basin: a case study of the Nam Ou basin, Lao PDR

2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  
Keyword(s):  
Climate Change ◽  
Sediment Yield ◽  
General Circulation ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Circulation Model ◽  
Sediment Flux ◽  
Seasonal Temperature ◽  
Impact Of Climate Change ◽  
The Impact

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.

scholarly journals Perceptions of Food Retailers Regarding Climate Change and Greenhouse Gas Emissions

2021 ◽  
Vol 5 (4) ◽  
pp. 26-35
Author(s):  
Ayanda Pamella Deliwe ◽  
Shelley Beryl Beck ◽  
Elroy Eugene Smith
Keyword(s):  
Climate Change ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Greenhouse Gas Emission ◽  
Harmful Effect ◽  
Retail Sector ◽  
Food Retail ◽  
Gas Emissions ◽  
Food Retailers ◽  
The Impact

Objective – This paper sets out to assess perceptions of food retailers regarding climate change, greenhouse gas emission and sustainability in the Nelson Mandela Bay region of South Africa. The primary objective of this study is to investigate the food retailers’ greenhouse gas emissions strategies. Climate change catastrophic potential and the harmful effect that it has had on the community and businesses has led to it being given attention from social media and in literature. Methodology/Technique – This paper covered a literature review that provided the theoretical framework. The empirical study that was carried out included self-administered questionnaires which were distributed to 120 food retailers who were selected from the population using convenience sampling. Findings - The results revealed that most of the respondents were neutral towards the impact of operational factors regarding GHG emission in the food retail sector. Novelty - There is limited research that has been conducted among food retailers from the designated population. The study provided guidelines that will be of assistance to food retailers when dealing with climate change and greenhouse gas emissions impact in the food retail sector. Type of Paper: Empirical. JEL Classification: L66, Q54, Q59. Keywords: Climate Change; Food Retailers; Greenhouse Gas Emissions; Perceptions; Strategies; Sustainability Reference to this paper should be made as follows: Deliwe, A.P; Beck, S.B; Smith, E.E. (2021). Perceptions of Food Retailers Regarding Climate Change and Greenhouse Gas Emissions, Journal of Business and Economics Review, 5(4) 26–35. https://doi.org/10.35609/jber.2021.5.4(3)

scholarly journals Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

Climate ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 139
Author(s):  
Manashi Paul ◽  
Sijal Dangol ◽  
Vitaly Kholodovsky ◽  
Amy R. Sapkota ◽  
Masoud Negahban-Azar ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
River Watershed ◽  
Temperature And Precipitation ◽  
The Impact

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.

PESTICIDE AND GREENHOUSE GAS EXTERNALITIES FROM US AGRICULTURE — THE IMPACT OF THEIR INTERNALIZATION AND CLIMATE CHANGE

2013 ◽  
Vol 04 (03) ◽  
pp. 1350008 ◽  
Author(s):  
NIKOLINKA SHAKHRAMANYAN ◽  
UWE A. SCHNEIDER ◽  
BRUCE A. McCARL
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Agricultural Sector ◽  
Greenhouse Gas Emission ◽  
Production Costs ◽  
Net Income ◽  
Gas Emission ◽  
Emission Mitigation ◽  
The Us ◽  
The Impact

Climate change may affect the use of pesticides and their associated environmental and human health impacts. This study employs and modifies a partial equilibrium model of the US agricultural sector to examine the effects of alternative regulations of the pesticide and greenhouse gas emission externality. Simulation results indicate that without pesticide externality regulations and low greenhouse gas emission mitigation strategy, climate change benefits from increased agricultural production in the US are more than offset by increased environmental costs. Although the combined regulation of pesticide and greenhouse gas emission externalities increases farmers' production costs, their net income effects are positive because of price adjustments and associated welfare shifts from consumers to producers. The results also show heterogeneous impacts on preferred pest management intensities across major crops. While pesticide externality regulations lead to substantial increases in total water use, climate policies induce the opposite effect.

scholarly journals Effects of Climate Change on the Distribution of Akebia quinata

2021 ◽  
Vol 9 ◽  
Author(s):  
Jun-Ming Zhang ◽  
Min-Li Song ◽  
Zhen-Jian Li ◽  
Xiang-Yong Peng ◽  
Shang Su ◽  
...  
Keyword(s):  
Climate Change ◽  
East Asia ◽  
Distribution Pattern ◽  
Greenhouse Gas ◽  
Greenhouse Gas Emission ◽  
Climate Factors ◽  
Gas Emission ◽  
Tropical Zone ◽  
Geometric Center ◽  
The Impact

Akebia quinata, also known as chocolate vine, is a creeping woody vine which is used as Chinese herbal medicine, and found widely distributed in East Asia. At present, its wild resources are being constantly destroyed. This study aims to provide a theoretical basis for the resource protection of this plant species by analyzing the possible changes in its geographic distribution pattern and its response to climate factors. It is the first time maximum entropy modeling (MaxEnt) and ArcGIS software have been used to predict the distribution of A. quinata in the past, the present, and the future (four greenhouse gas emission scenarios, namely, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Through the prediction results, the impact of climate change on the distribution of A. quinata and the response of A. quinata to climate factors were analyzed. The results showed that the most significant climatic factor affecting the distribution pattern of A. quinata was the annual precipitation. At present, the suitable distribution regions of A. quinata are mainly in the temperate zone, and a few suitable distribution regions are in the tropical zone. The medium and high suitable regions are mainly located in East Asia, accounting for 51.1 and 81.7% of the worldwide medium and high suitable regions, respectively. The migration of the geometric center of the distribution regions of A. quinata in East Asia is mainly affected by the change of distribution regions in China, and the average migration rate of the geometric center in each climate scenario is positively correlated with the level of greenhouse gas emission scenario.

scholarly journals An Investigation of Parameter Sensitivity of Minimum Complexity Earth Simulator

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 95
Author(s):  
Jiewei Chen ◽  
Huijuan Cui ◽  
Yangyang Xu ◽  
Quansheng Ge
Keyword(s):  
Climate Change ◽  
Sensitivity Analysis ◽  
Climate Models ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Parameter Sensitivity ◽  
Parameter Sensitivity Analysis ◽  
Output Measurement ◽  
Sensitivity Analysis Method ◽  
The Impact

Climate change, induced by human greenhouse gas emission, has already influenced the environment and society. To quantify the impact of human activity on climate change, scientists have developed numerical climate models to simulate the evolution of the climate system, which often contains many parameters. The choice of parameters is of great importance to the reliability of the simulation. Therefore, parameter sensitivity analysis is needed to optimize the parameters for the model so that the physical process of nature can be reasonably simulated. In this study, we analyzed the parameter sensitivity of a simple carbon-cycle energy balance climate model, called the Minimum Complexity Earth Simulator (MiCES), in different periods using a multi-parameter sensitivity analysis method and output measurement method. The results show that the seven parameters related to heat and carbon transferred are most sensitive among all 37 parameters. Then uncertainties of the above key parameters are further analyzed by changing the input emission and temperature, providing reference bounds of parameters with 95% confidence intervals. Furthermore, we found that ocean heat capacity will be more sensitive if the simulation time becomes longer, indicating that ocean influence on climate is stronger in the future.

Exploring the role of observational uncertainty and resolution mismatch in the application of bias adjustment methods

2020 ◽  
Author(s):  
Ana Casanueva ◽  
Sixto Herrera ◽  
Maialen Iturbide ◽  
Stefan Lange ◽  
Martin Jury ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Change Signal ◽  
Climate Indices ◽  
Bias Adjustment ◽  
Temperature And Precipitation ◽  
Observational Uncertainty ◽  
Distribution Mapping ◽  
Systematic Biases ◽  
The Impact

&lt;p&gt;Systematic biases in climate models hamper their direct use in impact studies and, as a consequence, many bias adjustment methods, which merely correct for deficiencies in the distribution, have been developed. Despite adjusting the desired features under historical simulations, their application in a climate change context is subject to additional uncertainties and modifications of the change signals, especially for climate indices which have not been tackled by the methods. In this sense, some of the commonly-used bias adjustment methods allow changes of the signals, which appear by construction in case of intensity-dependent biases; some others ensure the trends in some statistics of the original, raw models. Two relevant sources of uncertainty, often overlooked, which bring further uncertainties are the sensitivity to the observational reference used to calibrate the method and the effect of the resolution mismatch between model and observations (downscaling effect).&lt;/p&gt;&lt;p&gt;In the present work, we assess the impact of these factors on the climate change signal of a set of climate indices of temperature and precipitation considering marginal, temporal and extreme aspects. We use eight standard and state-of-the-art bias adjustment methods (spanning a variety of methods regarding their nature -empirical or parametric-, fitted parameters and preservation of the signals) for a case study in the Iberian Peninsula. The quantile trend-preserving methods (namely quantile delta mapping -QDM-, scaled distribution mapping -SDM- and the method from the third phase of ISIMIP -ISIMIP3) preserve better the raw signals for the different indices and variables (not all preserved by construction). However they rely largely on the reference dataset used for calibration, thus present a larger sensitivity to the observations, especially for precipitation intensity, spells and extreme indices. Thus, high-quality observational datasets are essential for comprehensive analyses in larger (continental) domains. Similar conclusions hold for experiments carried out at high (approximately 20km) and low (approximately 120km) spatial resolutions.&lt;/p&gt;

scholarly journals Climate change and U.S. agriculture: Accounting for multidimensional slope heterogeneity in panel data

2020 ◽  
Vol 11 (4) ◽  
pp. 1391-1429 ◽  
Author(s):  
Michael Keane ◽  
Timothy Neal
Keyword(s):  
Climate Change ◽  
Panel Data ◽  
Climate Models ◽  
Crop Yields ◽  
Greenhouse Gas Emission ◽  
Weather Conditions ◽  
Weather Data ◽  
Future Climate Change ◽  
Spatial And Temporal Variation ◽  
Local Climate

We study potential impacts of future climate change on U.S. agricultural productivity using county‐level yield and weather data from 1950 to 2015. To account for adaptation of production to different weather conditions, it is crucial to allow for both spatial and temporal variation in the production process mapping weather to crop yields. We present a new panel data estimation technique, called mean observation OLS (MO‐OLS) that allows for spatial and temporal heterogeneity in all regression parameters (intercepts and slopes). Both forms of heterogeneity are important: We find strong evidence that production function parameters adapt to local climate, and also that sensitivity of yield to high temperature declined from 1950–89. We use our estimates to project corn yields to 2100 using 19 climate models and three greenhouse gas emission scenarios. We predict unmitigated climate change will greatly reduce yield. Our mean prediction (over climate models) is that adaptation alone can mitigate 36% of the damage, while emissions reductions consistent with the Paris targets would mitigate 76%.

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