|
|
Kyle, P., Müller, C., Calvin, K., & Thomson, A. (2014). Meeting the radiative forcing targets of the representative concentration pathways in a world with agricultural climate impacts. Earth’s Future, 2, 83–98.
Abstract: This study assesses how climate impacts on agriculture may change the evolution of the agricultural and energy systems in meeting the end-of-century radiative forcing targets of the representative concentration pathways (RCPs). We build on the recently completed Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) exercise that has produced global gridded estimates of future crop yields for major agricultural crops using climate model projections of the RCPs from the Coupled Model Intercomparison Project Phase 5 (CMIP5). For this study we use the bias-corrected outputs of the HadGEM2-ES climate model as inputs to the LPJmL crop growth model, and the outputs of LPJmL to modify inputs to the GCAM integrated assessment model. Our results indicate that agricultural climate impacts generally lead to an increase in global cropland, as compared with corresponding emissions scenarios that do not consider climate impacts on agricultural productivity. This is driven mostly by negative impacts on wheat, rice, other grains, and oil crops. Still, including agricultural climate impacts does not significantly increase the costs or change the technological strategies of global, whole-system emissions mitigation. In fact, to meet the most aggressive climate change mitigation target (2.6W/m(2) in 2100), the net mitigation costs are slightly lower when agricultural climate impacts are considered. Key contributing factors to these results are (a) low levels of climate change in the low-forcing scenarios, (b) adaptation to climate impacts simulated in GCAM through inter-regional shifting in the production of agricultural goods, and (c) positive average climate impacts on bioenergy crop yields.
|
|
|
|
Fan, F., Henriksen, C. B., & Porter, J. (2018). Long-term effects of conversion to organic farming on ecosystem services – a model simulation case study and on-farm case study in Denmark. Agroecology and Sustainable Food Systems, 42(5), 504–529.
Abstract: Organic agriculture aims to produce food while establishing an ecological balance to augment ecosystem services (ES) and has been rapidly expanding in the world since the 1980s. Recently, however, in several European countries, including Denmark, organic farmers have converted back to conventional farming. Hence, understanding how agricultural ES are affected by the number of years since conversion to organic farming is imperative for policy makers to guide future agricultural policy. In order to investigate the long-term effects of conversion to organic farming on ES we performed i) a model simulation case study by applying the Daisy model to simulate 14 different conversion scenarios for a Danish farm during a 65 year period with increasing number of years under organic farming, and ii) an on-farm case study in Denmark with one conventional farm, one organic farm under conversion, and three organic farms converted 10, 15 and 58 years ago, respectively. Both the model simulation case study and the on-farm case study showed that non-marketable ES values increased with increasing number of years under organic farming. Trade-offs between marketable and non-marketable ES were not evident, since also marketable ES values generally showed an increasing trend, except when the price difference between organic and conventional products in the model simulation study was the smallest, and when an alfalfa pre-crop in the on-farm case study resulted in a significantly higher level of plant available nitrogen, which boosted the yield and the associated marketable ES of the subsequent winter rye crop. These results indicate a possible benefit of preserving long-term organic farms and could be used to argue for agricultural policy interventions to offset further reduction in the number of organic farms or the land area under organic farming.
|
|
|
|
Özkan, Ş., Ahmadi, B. V., Bonesmo, H., Østerås, O., Stott, A., & Harstad, O. M. (2015). Impact of animal health on greenhouse gas emissions. Advances in Animal Biosciences, 6(01), 24–25.
|
|
|
|
Heinke, J., Ostberg, S., Schaphoff, S., Frieler, K., Müller, C., Gerten, D., et al. (2013). A new climate dataset for systematic assessments of climate change impacts as a function of global warming. Geosci. Model Dev., 6(5), 1689–1703.
Abstract: In the ongoing political debate on climate change, global mean temperature change (Delta T-glob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of Delta T-glob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of Delta T-glob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere-Ocean General Circulation Models (AOGCMs). The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs’ climate change properties, even though they, necessarily, utilise a simplified relationships between Delta T-glob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.
|
|
|
|
Park, S. K., Sungmin, O., & Cassardo, C. (2017). Soil temperature response in Korea to a changing climate using a land surface model. Asia-Pacific Journal of Atmospheric Sciences, 53(4), 457–470.
Abstract: The land surface processes play an important role in weather and climate systems through its regulation of radiation, heat, water and momentum fluxes. Soil temperature (ST) is one of the most important parameters in the land surface processes; however, there are few extensive measurements of ST with a long time series in the world. According to the CLImatology of Parameters at the Surface (CLIPS) methodology, the output of a trusted Soil-Vegetation- Atmosphere Transfer (SVAT) scheme can be utilized instead of observations to investigate the regional climate of interest. In this study, ST in South Korea is estimated in a view of future climate using the output from a trusted SVAT scheme – the University of TOrino model of land Process Interaction with Atmosphere (UTOPIA), which is driven by a regional climate model. Here characteristic changes in ST are analyzed under the IPCC A2 future climate for 2046-2055 and 2091-2100, and are compared with those under the reference climate for 1996-2005. The UTOPIA results were validated using the observed ST in the reference climate, and the model proved to produce reasonable ST in South Korea. The UTOPIA simulations indicate that ST increases due to environmental change, especially in air temperature (AT), in the future climate. The increment of ST is proportional to that of AT except for winter. In wintertime, the ST variations are different from region to region mainly due to variations in snow cover, which keeps ST from significant changes by the climate change.
|
|
