scholarly journals Evaluation of Long-Term SOC and Crop Productivity within Conservation Systems Using GFDL CM2.1 and EPIC

2018 ◽  
Vol 10 (8) ◽  
pp. 2665 ◽  
Author(s):  
Kieu N. Le ◽  
Manoj K. Jha ◽  
Jaehak Jeong ◽  
Philip W. Gassman ◽  
Manuel R. Reyes ◽  
...  
Keyword(s):  
Climate Change ◽  
Management Practices ◽  
Climate Model ◽  
Crop Yields ◽  
Upland Rice ◽  
Cropping Systems ◽  
Global Climate Model ◽  
Crop Productivity ◽  
Climate Projections ◽  
Epic Model

Will soil organic carbon (SOC) and yields increase for conservation management systems in tropical zones in response to the next 100 years? To answer the question, the Environmental Policy Integrated Climate (EPIC) model was used to study the effects of climate change, cropping systems, conservation agriculture (CA) and conservation tillage management practices on SOC and crop productivity in Kampong Cham, Cambodia. The EPIC model was successfully calibrated and validated for crop yields, biomass, SOC and nitrogen based on field data from a five-year field experiment. Historical weather (1994–2013) was used for baseline assessment versus mid-century (2046–2064) and late-century (2081–2100) climate projections generated by the Geophysical Fluids Dynamics Laboratory (GFDL) CM2.1 global climate model. The simulated results showed that upland rice yield would increase the most under the B1 scenario in mid-century for all treatments, followed by soybean and maize. Cassava yield only increased under CA treatment when cultivated as a continuous primary crop. Carbon sequestration was more sensitive to cropping systems and crop rotation than climate change. The results indicated that the rotated CA primary crop (maize) systems should be prioritized for SOC sequestration as well as for increasing crop productivity. In addition, rice systems may increase SOC compared to soybean and cassava.

Future global crop production increases by adapting crop phenology to local climate change

2021 ◽  
Author(s):  
Sara Minoli ◽  
Jonas Jägermeyr ◽  
Senthold Asseng ◽  
Christoph Müller
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Management Practices ◽  
Crop Yields ◽  
Crop Productivity ◽  
Global Scale ◽  
Adaptation Strategies ◽  
Systematic Evaluation ◽  
Management Scenarios ◽  
Crop Phenology

<p>Broad evidence is pointing at possible adverse impacts of climate change on crop yields. Due to scarce information about farming management practices, most global-scale studies, however, do not consider adaptation strategies.</p><p>Here we integrate models of farmers' decision making with crop biophysical modeling at the global scale to investigate how accounting for adaptation of crop phenology affects projections of future crop productivity under climate change. Farmers in each simulation unit are assumed to adapt crop growing periods by continuously selecting sowing dates and cultivars that match climatic conditions best. We compare counterfactual management scenarios, assuming crop calendars and cultivars to be either the same as in the reference climate – as often assumed in previous climate impact assessments – or adapted to future climate.</p><p>Based on crop model simulations, we find that the implementation of adapted growing periods can substantially increase (+15%) total crop production in 2080-2099 (RCP6.0). In general, summer crops are responsive to both sowing and harvest date adjustments, which result in overall longer growing periods and improved yields, compared to production systems without adaptation of growing periods. Winter wheat presents challenges in adapting to a warming climate and requires region-specific adjustments to pre and post winter conditions. We present a systematic evaluation of how local and climate-scenario specific adaptation strategies can enhance global crop productivity on current cropland. Our findings highlight the importance of further research on the readiness of required crop varieties.</p>

scholarly journals Flood risk assessment methodology for planning under climate change scenarios and the corresponding change in land cover

2019 ◽  
Vol 11 (4) ◽  
pp. 1370-1382 ◽  
Author(s):  
Asma Hanif ◽  
Ashwin Dhanasekar ◽  
Anthony Keene ◽  
Huishu Li ◽  
Kenneth Carlson
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate Model ◽  
The United States ◽  
Army Corps ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Rcp Scenarios ◽  
Daily Precipitation Data ◽  
Time Frames

Abstract Projected climate change impacts on the hydrological regime and corresponding flood risks were examined for the years 2030 (near-term) and 2050 (long-term), under representative concentration pathways (RCP) 4.5 (moderate) and 8.5 (high) emission scenarios. The United States Army Corps of Engineers' (USACE) Hydrologic Engineering Center's Hydrologic Modeling System was used to simulate the complete hydrologic processes of the various dendritic watershed systems and USACEs' Hydrologic Engineering Center's River Analysis System hydraulic model was used for the two-dimensional unsteady flow flood calculations. Climate projections are based on recent global climate model simulations developed for the International Panel on Climate Change, Coupled Model Inter-comparison Project Phase 5. Hydrographs for frequent (high-recurrence interval) storms were derived from 30-year historical daily precipitation data and decadal projections for both time frames and RCP scenarios. Since the climate projections for each scenario only represented ten years of data, 100-year or 500-year storms cannot be derived. Hence, this novel approach of identifying frequent storms is used as an indicator to compare across the various time frames and climate scenarios. Hydrographs were used to generate inundation maps and results are used to identify vulnerabilities and formulate adaptation strategies to flooding at 43 locations worldwide.

scholarly journals Do Convection-Permitting Regional Climate Models Improve Projections of Future Precipitation Change?

2017 ◽  
Vol 98 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Elizabeth J. Kendon ◽  
Nikolina Ban ◽  
Nigel M. Roberts ◽  
Hayley J. Fowler ◽  
Malcolm J. Roberts ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Convective Storms ◽  
Wide Range

Abstract Regional climate projections are used in a wide range of impact studies, from assessing future flood risk to climate change impacts on food and energy production. These model projections are typically at 12–50-km resolution, providing valuable regional detail but with inherent limitations, in part because of the need to parameterize convection. The first climate change experiments at convection-permitting resolution (kilometer-scale grid spacing) are now available for the United Kingdom; the Alps; Germany; Sydney, Australia; and the western United States. These models give a more realistic representation of convection and are better able to simulate hourly precipitation characteristics that are poorly represented in coarser-resolution climate models. Here we examine these new experiments to determine whether future midlatitude precipitation projections are robust from coarse to higher resolutions, with implications also for the tropics. We find that the explicit representation of the convective storms themselves, only possible in convection-permitting models, is necessary for capturing changes in the intensity and duration of summertime rain on daily and shorter time scales. Other aspects of rainfall change, including changes in seasonal mean precipitation and event occurrence, appear robust across resolutions, and therefore coarse-resolution regional climate models are likely to provide reliable future projections, provided that large-scale changes from the global climate model are reliable. The improved representation of convective storms also has implications for projections of wind, hail, fog, and lightning. We identify a number of impact areas, especially flooding, but also transport and wind energy, for which very high-resolution models may be needed for reliable future assessments.

Climate change impact on legumes' water production function in the northeast of Iran

2014 ◽  
Vol 6 (2) ◽  
pp. 374-385 ◽  
Author(s):  
N. Sayari ◽  
M. Bannayan ◽  
A. Alizadeh ◽  
A. Farid ◽  
M. R. Hessami Kermani ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Climate Model ◽  
Crop Yields ◽  
Global Climate Model ◽  
Mitigation Strategies ◽  
Stochastic Weather Generator ◽  
Time Periods ◽  
Northeast Iran ◽  
Far Future

Enhanced understanding of the climate impact on crops' production is necessary to cope with expected climate variability and change. This study was conducted to find any robust association between crop yield and evapotranspiration using historical data (1986–2005) and subsequently employ the acquired relationship to project crop yield under future climate conditions for two agricultural centers in northeast Iran. Three legume crops of chickpea, lentil, and bean were selected in this study. The future precipitation and temperature data were projected by downscaling outputs of global climate model HadCM3 (A2 scenario) by LARS-WG stochastic weather generator. The data were downscaled for the baseline (1961–1990) and two time periods (2011–2030 and 2080–2099) as near and far future conditions. Projected temperature under A2 scenario showed increasing trend changed from 4 to 26% during the legumes' growth period compared to baseline. In addition, projected annual precipitation change was between −14 and 10% range under different time periods in contrast to baseline. There was a nonlinear relationship between crop yields and the seasonal values of crop evapotranspiration for all crops. The results showed that seasonal evapotranspiration would increase under climate change conditions across study locations. Crop yield would also increase for chickpea but not for lentil and bean for the far future in Sabzevar location compared to baseline. In conclusion, increasing the temperature and decreasing the precipitation may have a negative effect on legumes' yield in northeast Iran, especially for far future conditions. Therefore, planning effective adaptation and mitigation strategies would be necessary for northeast Iran.

scholarly journals Projection of Global Wave Climate Change toward the End of the Twenty-First Century

2012 ◽  
Vol 26 (21) ◽  
pp. 8269-8288 ◽  
Author(s):  
Alvaro Semedo ◽  
Ralf Weisse ◽  
Arno Behrens ◽  
Andreas Sterl ◽  
Lennart Bengtsson ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate Model ◽  
Wave Climate ◽  
Ocean Model ◽  
First Century ◽  
Climate Projections ◽  
Moderate Increase ◽  
Intergovernmental Panel ◽  
Twenty First Century

Abstract Wind-generated waves at the sea surface are of outstanding importance for both their practical relevance in many aspects, such as coastal erosion, protection, or safety of navigation, and for their scientific relevance in modifying fluxes at the air–sea interface. So far, long-term changes in ocean wave climate have been studied mostly from a regional perspective with global dynamical studies emerging only recently. Here a global wave climate study is presented, in which a global wave model [Wave Ocean Model (WAM)] is driven by atmospheric forcing from a global climate model (ECHAM5) for present-day and potential future climate conditions represented by the Intergovernmental Panel for Climate Change (IPCC) A1B emission scenario. It is found that changes in mean and extreme wave climate toward the end of the twenty-first century are small to moderate, with the largest signals being a poleward shift in the annual mean and extreme significant wave heights in the midlatitudes of both hemispheres, more pronounced in the Southern Hemisphere and most likely associated with a corresponding shift in midlatitude storm tracks. These changes are broadly consistent with results from the few studies available so far. The projected changes in the mean wave periods, associated with the changes in the wave climate in the middle to high latitudes, are also shown, revealing a moderate increase in the equatorial eastern side of the ocean basins. This study presents a step forward toward a larger ensemble of global wave climate projections required to better assess robustness and uncertainty of potential future wave climate change.

scholarly journals Impact of Climate Change on Some Agricultural Crops Distribution and Productivity in Georgia

2021 ◽  
Vol 24 (s1) ◽  
pp. 20-26
Author(s):  
Lia Megrelidze ◽  
Nato Kutaladze ◽  
Gizo Gogichaishvili ◽  
Marina Shvangiradze
Keyword(s):  
Climate Change ◽  
Management Practices ◽  
Climate Model ◽  
Crop Yields ◽  
Regional Climate ◽  
Regional Scale ◽  
Circulation Model ◽  
Global Circulation Model ◽  
Adaptation Measures ◽  
Aquacrop Model

Abstract Under the increase of the concern for food security in the world, mainly caused by water resources shortages, the forecast and determination of crop yield at regional scale has been considered as a strategic topic. This study has been conducted to assess the possible impacts of the climate change on cereal crops productivity and irrigation requirement for two main producing regions of Georgia, according to the current crop pattern, and for the 2050s periods. With this aim, water-driven FAO-AquaCrop model has been used. Furthermore, ongoing and forecasted changes, up to the end of the century, in agro-climatic zones relevant for cereals production have been assessed. The climate change data was generated for RCP4.5 scenario through the global circulation model ECHAM4.1, dynamically downscaled on the region via regional climate model (RegCM4.1). Results show overall increase in cereal crop yields, but also enhancement in water shortages even considering optimum management practices under rainfed conditions. Based on the results obtained, recommendations have been developed for adaptation measures to the climate change for the Georgia Agriculture sector.

The hidden signature of temperature-moisture couplings in the heat sensitivity of global crops

2021 ◽  
Author(s):  
Corey Lesk ◽  
Ethan Coffel ◽  
Jonathan Winter ◽  
Deepak Ray ◽  
Jakob Zscheischler ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Climate Model ◽  
Crop Yields ◽  
Cropping Systems ◽  
Critical Role ◽  
Heat Sensitivity ◽  
Local Strength ◽  
Dry Conditions ◽  
The Impact

<p><strong>Rising air temperatures are a leading risk to global crop production and food security under climate change</strong><strong>. Recent research has emphasized the critical role of moisture availability in regulating crop responses to heat</strong><strong> and the importance of temperature-moisture couplings in the genesis of concurrent hot and dry conditions</strong><strong>. Here, we demonstrate that the heat sensitivity of key global crops is dependent on the local strength of couplings between temperature and moisture in the climate system (namely, the interannual correlations of growing season temperature with evapotransipration and precipitation). Over 1970-2013, maize and soy yields declined more during hotter growing seasons where decreased precipitation and evapotranspiration more strongly accompanied higher temperatures. Based on this historical pattern and a suite of CMIP6 climate model projections, we show that changes in temperature-moisture couplings in response to warming could enhance the heat sensitivity of these crops as temperatures rise, worsening the impact of warming by ~5% on global average. However, these changes will benefit crops in some areas where couplings weaken, and are highly uncertain in others. Our results demonstrate that climate change will impact crops not only through warming, but also through changes in temperature-moisture couplings, which may alter the sensitivity of crop yields to heat as warming proceeds. Robust adaptation of cropping systems will need to consider this underappreciated risk to food production from climate change.</strong></p>

scholarly journals Modeling Climate Change Projections for Ferozpur Sub-catchment of Jhelum Sub-basin of Kashmir Valley

2018 ◽  
pp. 39-52
Author(s):  
Syed Rouhullah Ali ◽  
Junaid N. Khan ◽  
Mehraj U. Din Dar ◽  
Shakeel Ahmad Bhat ◽  
Syed Midhat Fazil ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate Model ◽  
Climate Projections ◽  
Mean Annual Temperature ◽  
Kashmir Valley ◽  
Climate Change Projections ◽  
Intergovernmental Panel ◽  
Temperature And Precipitation

Aims: The study aimed at modeling the climate change projections for Ferozpur subcatchment of Jhelum sub-basin of Kashmir Valley using the SDSM model. Study Design: The study was carried out in three different time slices viz Baseline (1985-2015), Mid-century (2030-2059) and End-century (2070-2099). Place and Duration of Study: Division of Agricultural Engineering, SKUAST-K, Shalimar between August 2015 and July 2016. Methodology: Statistical downscaling model (SDSM) was applied in downscaling weather files (Tmax, Tminand precipitation). The study includes the calibration of the SDSM model by using Observed daily climate data (Tmax, Tmin and precipitation) of thirty one years and large scale atmospheric variables encompassing National Centers for Environmental Prediction (NCEP) reanalysis data, the validation of the model, and the outputs of downscaled scenario A2 of the Global Climate Model (GCM) data of Hadley Centre Coupled Model, Version 3 (HadCM3) model for the future. Daily Climate (Tmax, Tmin and precipitation) scenarios were generated from 1961 to 2099 under A2 defined by Intergovernmental Panel on Climate Change (IPCC). Results: The results showed that temperature and precipitation would increase by 0.29°C, 255.38 mm (30.97%) in MC (Mid-century) (2030-2059); and 0.67oC and 233.28 mm (28.29%) during EC (End-century) (2070-2099), respectively. Conclusion: The climate projections for 21st century under A2 scenario indicated that both mean annual temperature and precipitation are showing an increasing trend.

scholarly journals Simulating Hydrological Impacts under Climate Change: Implications from Methodological Differences of a Pan European Assessment

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1331 ◽  
Author(s):  
Aristeidis Koutroulis ◽  
Lamprini Papadimitriou ◽  
Manolis Grillakis ◽  
Ioannis Tsanis ◽  
Klaus Wyser ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Surface Model ◽  
Climate Projections ◽  
European Continent ◽  
Hydrological Changes ◽  
Hydrological Impacts

The simulation of hydrological impacts in a changing climate remains one of the main challenges of the earth system sciences. Impact assessments can be, in many cases, laborious processes leading to inevitable methodological compromises that drastically affect the robustness of the conclusions. In this study we examine the implications of different CMIP5-based regional and global climate model ensembles for projections of the hydrological impacts of climate change. We compare results from three different assessments of hydrological impacts under high-end climate change (RCP8.5) across Europe, and we focus on how methodological differences affect the projections. We assess, as systematically as possible, the differences in runoff projections as simulated by a land surface model driven by three different sets of climate projections over the European continent at global warming of 1.5 °C, 2 °C and 4 °C relative to pre-industrial levels, according to the RCP8.5 concentration scenario. We find that these methodological differences lead to considerably different outputs for a number of indicators used to express different aspects of runoff. We further use a number of new global climate model experiments, with an emphasis on high resolution, to test the assumption that many of the uncertainties in regional climate and hydrological changes are driven predominantly by the prescribed sea surface temperatures (SSTs) and sea-ice concentrations (SICs) and we find that results are more sensitive to the choice of the atmosphere model compared to the driving SSTs. Finally, we combine all sources of information to identify robust patterns of hydrological changes across the European continent.

scholarly journals Statistical Downscaling in the Tropics Can Be Sensitive to Reanalysis Choice: A Case Study for Precipitation in the Philippines

2015 ◽  
Vol 28 (10) ◽  
pp. 4171-4184 ◽  
Author(s):  
R. Manzanas ◽  
S. Brands ◽  
D. San-Martín ◽  
A. Lucero ◽  
C. Limbo ◽  
...  
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Climate Model ◽  
Global Climate Model ◽  
The Philippines ◽  
Local Scale ◽  
Specific Humidity ◽  
Climate Change Signal ◽  
Climate Projections ◽  
Climate Change Projections

Abstract This work shows that local-scale climate projections obtained by means of statistical downscaling are sensitive to the choice of reanalysis used for calibration. To this aim, a generalized linear model (GLM) approach is applied to downscale daily precipitation in the Philippines. First, the GLMs are trained and tested separately with two distinct reanalyses (ERA-Interim and JRA-25) using a cross-validation scheme over the period 1981–2000. When the observed and downscaled time series are compared, the attained performance is found to be sensitive to the reanalysis considered if climate change signal–bearing variables (temperature and/or specific humidity) are included in the predictor field. Moreover, performance differences are shown to be in correspondence with the disagreement found between the raw predictors from the two reanalyses. Second, the regression coefficients calibrated either with ERA-Interim or JRA-25 are subsequently applied to the output of a global climate model (MPI-ECHAM5) in order to assess the sensitivity of local-scale climate change projections (up to 2100) to reanalysis choice. In this case, the differences detected in present climate conditions are considerably amplified, leading to “delta-change” estimates differing by up to 35% (on average for the entire country) depending on the reanalysis used for calibration. Therefore, reanalysis choice is an important contributor to the uncertainty of local-scale climate change projections and, consequently, should be treated with as much care as other better-known sources of uncertainty (e.g., the choice of the GCM and/or downscaling method). Implications of the results for the entire tropics, as well as for the model output statistics downscaling approach are also briefly discussed.

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