Non-Linearity in Climate Change Impact Assessments

Semenov, M. A.; Iacr, John R. Porter

doi:10.2307/2845960

Cited by 17 publications

(6 citation statements)

References 17 publications

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“…Granovetter (1978Granovetter ( , p. 1422 argues that different people will make different decisions in response to stimuli and that a ''threshold is simply that point where the perceived benefits to an individual of doing the thing in question exceed the perceived costs.'' The concept has also been widely applied in relation to natural systems (Semenov and Porter 1995;Arnell 2000) and in fact climate change itself, with a climatic tipping point reached when ''the climate system is forced to cross some threshold and it subsequently changes dramatically beyond that which would be caused by the initial forcing'' (Kniveton et al 2008, p. 24). Here, we use threshold in a slightly different manner to either of these definitions to identify a situation where a significant change in collective social behaviour results.…”

Section: Framing Climate Change Migrationmentioning

confidence: 98%

Migration and climate change: examining thresholds of change to guide effective adaptation decision-making

2010

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The implications of environmental change for migration are little understood. Migration as a response to climate change could be seen as a failure of in situ adaptation methods, or migration could be alternatively perceived as a rational component of creative adaptation to environmental risk. This paper frames migration as part of an adaptation response to climate change impacts to natural resource condition and environmental hazards. Thresholds will be reached by communities after which migration will become a vital component of an effective adaptation response. Such changes to migration patterns have the potential to undermine migration policy unless appropriate preparations are undertaken. This paper describes an approach to assist researchers to frame how climate change will influence migration by critically analysing how thresholds of fundamental change to migration patterns could be identified, primarily in relation to two case studies in Nepal and Thailand. Future policy for internal and international migration could be guided by the analysis of such thresholds of non-linear migration and resourced effectively to ensure that socio-economic and humanitarian outcomes are maximised.

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Section: Framing Climate Change Migrationmentioning

confidence: 98%

Migration and climate change: examining thresholds of change to guide effective adaptation decision-making

2010

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“…Another main driver for the uncertainty in model outputs are climate, soil and management input data (Bouman 1994; Nonhebel 1994; Pachepsky & Acock 1998; Soltani et al 2004; Masutomi et al 2009). In addition, crop models are sensitive to the variability and spatial scale of the weather data inputs (Semenov & Porter 1995; Mearns et al 1997; Tatsumi et al 2011).…”

Section: Introductionmentioning

confidence: 99%

The performance of Metop Advanced SCATterometer soil moisture data as a complementary source for the estimation of crop-soil water balance in Central Europe

et al. 2018

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Simulation of the water balance in cropping systems is an essential tool, not only to monitor water status and determine drought but also to find ways in which soil water and irrigation water can be used more efficiently. However, besides the requirement that models are physically correct, the spatial representativeness of input data and, in particular, accurate precipitation data remain a challenge. In recent years, satellite-based soil moisture products have become an important data source for soil wetness information at various spatial-temporal scales. Four different study areas in the Czech Republic and Austria were selected representing Central European soil and climatic conditions. The performance of soil water content outputs from two different crop-water balance models and the Metop Advanced SCATterometer (ASCAT) soil moisture product was tested with field measurements from 2007 to 2011. The model output for soil water content shows that the crop model Decision Support System for Agrotechnology Transfer performs well during dry periods (<30% plant available soil moisture (ASM), whereas the soil water-balance model SoilClim presents the best results in humid months (>60% ASM). Moreover, the model performance is best in the early growing season and decreases later in the season due to biases in simulated crop-related above-ground biomass compared with the relatively stable grass canopy of the measurement sites. The Metop ASCAT soil moisture product, which presents a spatial average of soil surface moisture, shows the best performance under medium soil wetness conditions (30–50% ASM), which is related to low variation in precipitation frequency and under conditions of low-surface biomass (early vegetation season).

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“…Furthermore the choice of predictor combinations and domain spaces can be critical to the results of downscaling (Liu et al, 2011). King,Irwin,Sarwar,McLeod,and Simonovic 255 LARS-WG is another popular and user-friendly downscaling tool developed for agricultural impact assessments (Racsko et al, 1991;Semenov and Porter, 1995;Semenov and Barrow, 1997). Downscaling is achieved by applying AOGCM change-factors to the observed weather series to develop AOGCMmodified daily inputs to the weather generator.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Climate Change on Extreme Precipitation Events in the Upper Thames River Basin: A Comparison of Downscaling Approaches

King

Irwin

Sarwar

et al. 2012

Canadian Water Resources Journal / Revue canadienne des ressour

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Future changes in climatic conditions from increasing greenhouse gas concentrations will have a major impact on the hydrologic cycle. It is important to understand and predict future changes in temperature and precipitation in order to effectively manage water resources. Atmosphere-Ocean coupled Global Climate Models (AOGCMs) are used widely to predict the effects of greenhouse-gas forcing on global climate conditions. However, their spatial and temporal resolutions are quite large so their outputs must be modified to represent local climate conditions. This process is called downscaling, and there are a variety of tools available to achieve this goal. This study compares three downscaling approaches, namely the Statistical DownScaling Model (SDSM), Long Ashton Research Station Weather Generator (LARS-WG), and the K-NN Weather Generator with Principal Component Analysis (WG-PCA). Each weather generator is used to simulate the historical climate for the Upper Thames River Basin in Ontario, Canada for use in a comparison of downscaling tools. Future climate conditions are simulated by LARS-WG and WG-PCA from six different AOGCMs, each with two to three emissions scenarios, for a total of 15 different models. In simulation of historical climate variability, the models generally perform better in terms of mean daily precipitation and total monthly precipitation. LARS-WG simulates precipitation events well but cannot reproduce means and variances in the daily temperature series. SDSM adequately simulates both temperatures and precipitation events. WG-PCA reproduces daily temperatures very well but overestimates the occurrence of some extreme precipitation events. Results are variable for the downscaling of AOGCMs; however, the downscaling tools generally predict a rise in winter, spring and fall precipitation totals, as well as an overall increase in mean annual precipitation in future decades.

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Non-Linearity in Climate Change Impact Assessments

Cited by 17 publications

References 17 publications

Migration and climate change: examining thresholds of change to guide effective adaptation decision-making

Migration and climate change: examining thresholds of change to guide effective adaptation decision-making

The performance of Metop Advanced SCATterometer soil moisture data as a complementary source for the estimation of crop-soil water balance in Central Europe

The Effects of Climate Change on Extreme Precipitation Events in the Upper Thames River Basin: A Comparison of Downscaling Approaches

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