Advancing the climate data driven crop-modeling studies in the dry areas of Northern Syria and Lebanon: An important first step for assessing impact of future climate

2015 ◽  
Vol 511 ◽  
pp. 562-575 ◽  
Author(s):  
Prakash N. Dixit ◽  
Roberto Telleria
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ruth Kerry ◽  
Ben Ingram ◽  
Esther Garcia-Cela ◽  
Naresh Magan ◽  
Brenda V. Ortiz ◽  
...  

AbstractAflatoxins (AFs) are produced by fungi in crops and can cause liver cancer. Permitted levels are legislated and batches of grain are rejected based on average concentrations. Corn grown in Southern Georgia (GA), USA, which experiences drought during the mid-silk growth period in June, is particularly susceptible to infection by Aspergillus section Flavi species which produce AFs. Previous studies showed strong association between AFs and June weather. Risk factors were developed: June maximum temperatures > 33 °C and June rainfall < 50 mm, the 30-year normals for the region. Future climate data were estimated for each year (2000–2100) and county in southern GA using the RCP 4.5 and RCP 8.5 emissions scenarios. The number of counties with June maximum temperatures > 33 °C and rainfall < 50 mm increased and then plateaued for both emissions scenarios. The percentage of years thresholds were exceeded was greater for RCP 8.5 than RCP 4.5. The spatial distribution of high-risk counties changed over time. Results suggest corn growth distribution should be changed or adaptation strategies employed like planting resistant varieties, irrigating and planting earlier. There were significantly more counties exceeding thresholds in 2010–2040 compared to 2000–2030 suggesting that adaptation strategies should be employed as soon as possible.


2017 ◽  
Vol 73 (2) ◽  
pp. I_1417-I_1422
Author(s):  
Yoshihiko IDE ◽  
Yuji ISSHIKI ◽  
Mitsuyoshi KODAMA ◽  
Noriaki HASHIMOTO ◽  
Masaru YAMASHIRO

2021 ◽  
Vol 43 ◽  
pp. e56026
Author(s):  
Gabriela Leite Neves ◽  
Jorim Sousa das Virgens Filho ◽  
Maysa de Lima Leite ◽  
Frederico Fabio Mauad

Water is an essential natural resource that is being impacted by climate change. Thus, knowledge of future water availability conditions around the globe becomes necessary. Based on that, this study aimed to simulate future climate scenarios and evaluate the impact on water balance in southern Brazil. Daily data of rainfall and air temperature (maximum and minimum) were used. The meteorological data were collected in 28 locations over 30 years (1980-2009). For the data simulation, we used the climate data stochastic generator PGECLIMA_R. It was considered two scenarios of the fifth report of the Intergovernmental Panel on Climate Change (IPCC) and a scenario with the historical data trend. The water balance estimates were performed for the current data and the simulated data, through the methodology of Thornthwaite and Mather (1955). The moisture indexes were spatialized by the kriging method. These indexes were chosen as the parameters to represent the water conditions in different situations. The region assessed presented a high variability in water availability among locations; however, it did not present high water deficiency values, even with climate change. Overall, it was observed a reduction of moisture index in most sites and in all scenarios assessed, especially in the northern region when compared to the other regions. The second scenario of the IPCC (the worst situation) promoting higher reductions and dry conditions for the 2099 year. The impacts of climate change on water availability, identified in this study, can affect the general society, therefore, they must be considered in the planning and management of water resources, especially in the regional context


2013 ◽  
Vol 6 (2) ◽  
pp. 3349-3380 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
P. H. Garthwaite ◽  
K. Fraedrich ◽  
F. Lunkeit ◽  
...  

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS. Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, and the validation of the results against empirical data and higher-complexity models. We also demonstrate the application to estimates of sea-level rise and associated uncertainty.


2019 ◽  
Vol 7 (2) ◽  
pp. 11
Author(s):  
Ebrima Sonko ◽  
Sampson K. Agodzo ◽  
Philip Antwi-Agyei

Climate change and variability impact on staple food crops present a daunting challenge in the 21st century. The study assesses future climate variability on maize and rice yield over a 30-year period by comparing the outcomes under two GCM models, namely, CSIRO_RCP4.5 and NOAA_RCP4.5 of Australia’s Commonwealth Scientific and National Oceanic and Atmospheric Administration respectively. Historical climate data and yield data were used to establish correlations and then subsequently used to project future yields between 2021 and 2050. Using the average yield data for the period 1987-2016 as baseline yield data, future yield predictions for 2021-2030, 2031-2040 and 2041-2050 were then compared with the baseline data. The results showed that the future maize and rice yield would be vulnerable to climate variability with CSIRO_RCP4.5 showing increase in maize yield whilst CSIRO_RCP4.5 gives a better projection for rice yield. Furthermore, the results estimated the percentage mean yield gain for maize under CSIRO_RCP4.5 and NOAA_ RCP4.5 by about 17 %, 31 % and 48 % for the period 2021-2030, 2031-2040 and 2041-2050 respectively. Mean rice yield lossess of -23 %, -19 % and -23 % were expected for the same period respectively. The study recommended the use of improved rice and maize cultivars to offset the negative effects of climate variability in future.


2020 ◽  
Vol 172 ◽  
pp. 11003
Author(s):  
Zhe Xiao ◽  
Michael A. Lacasse ◽  
A. Gaur ◽  
Elena Dragomirescu

In North America, and abroad, there currently exist standard test protocols for assessing the watertightness of wall assemblies and fenestration components although most of these methods are not directly related to expectations of in-field conditions as might be experienced by a wall assembly over its intended service life. How useful might such test protocols be to help determine the longevity of wall assemblies to future climate loads? Existing walls may, depending on their geographic location, be vulnerable to future climate loads and thus risk premature deterioration. For the design of new wall assemblies consideration ought to given to the non-stationarity of the climate and implications on the moisture loads on walls and the expected performance over the long-term. To permit assessing the resilience of wall assemblies to the effects of a changing climate as may occur in the future, and indeed, perhaps heightened moisture loads, one requires sufficient information on the watertightness of the assembly in relation to specified wind-driven rain loads and wall air-leakage conditions from which wall moisture retention functions could readily be developed. Such moisture functions are the basis of input of moisture loads to hygrothermal models and from which the expected long-term wall moisture performance can subsequently be derived. In this paper, a description is provided of the strategies used to analyze the WDR load for generating experimental input for a watertightness test protocol under development to assess resilience of wall assemblies to moisture loads arising from the effects of wind-driven rain in consideration of both historical climate loads and those as may arise from a changing climate.


2012 ◽  
Vol 47 (3-4) ◽  
pp. 389-405 ◽  
Author(s):  
N. R. Samal ◽  
D. C. Pierson ◽  
E. Schneiderman ◽  
Y. Huang ◽  
J. S. Read ◽  
...  

Global Circulation Model values of mean daily air temperature, wind speed and solar radiation for the 2081–2100 period are used to produce change factors that are applied to a 39 year record of local meteorological data to produce future climate scenarios. These climate scenarios are used to drive two separate, but coupled models: the Generalized Watershed Loading Functions-Variable Source Area model in order to simulate reservoir tributary inflows, and a one-dimensional reservoir hydrothermal model used to evaluate changes in reservoir thermal structure in response to changes in meteorological forcing and changes in simulated inflow. Comparisons between simulations based on present-day climate data (baseline conditions) and future simulations (change-factor adjusted baseline conditions) are used to evaluate the development and breakdown of thermal stratification, as well as a number of metrics that describe reservoir thermal structure, stability and mixing. Both epilimnion and hypolimnion water temperatures are projected to increase. Indices of mixing and stability show changes that are consistent with the simulated changes in reservoir thermal structure. Simulations suggest that stratification will begin earlier and the reservoir will exhibit longer and more stable periods of thermal stratification under future climate conditions.


2020 ◽  
Author(s):  
Wei Yuan ◽  
Shuang-ye Wu ◽  
Shugui Hou

&lt;p&gt;This study aims to establish future vegetation changes in the east and central of northern China (ECNC), an ecologically sensitive region in the transition zonal from humid monsoonal to arid continental climate. The region has experienced significant greening in the past several decades. However, few studies exist on how vegetation will change with future climate change, and great uncertainties exist due to complex, and often spatially non-stationary, relationships between vegetation and climate. In this study, we first used historical NDVI and climate data to model this spatially variable relationship with Geographically Weighted Logit Regression. We found that temperature and precipitation could explain, on average, 43% of NDVI variance, and they could be used to&amp;#160;model NDVI fairly well. We then establish future climate change using the output of 11 CMIP6 models for the medium (SSP245) and high (SSP585) emission scenarios for the mid-century (2041-2070) and late-century (2071-2100). The results show that for this region, both temperature and precipitation will increase under both scenarios. By late-century under SSP585, precipitation is projected to increase by 25.12% and temperature is projected to increase 5.87&lt;sup&gt;o&lt;/sup&gt;C in ECNC. Finally, we used future climate conditions as input for the regression models to project future vegetation (indicated by NDVI). We found that NDVI will increase under climate change. By mid-century, the average NDVI in ECNC will increase by 0.024 and 0.021 under SSP245 and SSP585. By late-century, it will increase by 0.016 and 0.006 under SSP245 and SSP585&amp;#160;respectively. Although NDVI is projected to increase, the magnitude of increase is likely to diminish with higher emission scenarios, possibly due to the benefit of precipitation increase being gradually encroached by the detrimental effects of temperature increase. Moreover, despite the overall NDVI increase, the area likely to suffer vegetation degradation will also expands, particularly in the western part of ECNC. With higher emissions and later into the century, region with low NDVI is likely to shift and/or expand north-forward. Our results could provide important information on possible&amp;#160;vegetation changes, which could help to develop effective management strategies to ensure ecological and economic sustainability&amp;#160;in the future.&lt;/p&gt;


2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yingzhi Lin ◽  
Anping Liu ◽  
Enjun Ma ◽  
Fan Zhang

An agroecological zone (AEZ) is a land resource mapping unit, defined in terms of climate, landform, and soils, and has a specific range of potentials and constraints for cropping (FAO, 1996). The shifting patterns of AEZs in China driven by future climatic changes were assessed by applying the agroecological zoning methodology proposed by International Institute for Applied Systems Analysis (IIASA) and Food and Agriculture Organization of the United Nations (FAO) in this study. A data processing scheme was proposed in this study to reduce systematic errors in projected climate data using observed data from meteorological stations. AEZs in China of each of the four periods: 2011–2020, 2021–2030, 2031–2040, and 2041–2050 were drawn. It is found that the future climate change will lead to significant local changes of AEZs in China and the overall pattern of AEZs in China is stable. The shifting patterns of AEZs will be characterized by northward expansion of humid AEZs to subhumid AEZs in south China, eastward expansion of arid AEZs to dry and moist semiarid AEZs in north China, and southward expansion of dry semiarid AEZs to arid AEZs in southwest China.


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