AgMIP Climate Data and Scenarios for Integrated Assessment

Ruane, Alexander C.; Winter, Jonathan M.; McDermid, Sonali P.; Hudson, Nicholas I.

doi:10.1142/9781783265640_0003

Cited by 45 publications

(46 citation statements)

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“…A weakness of the climate data used was the assumption of no changes in the number of rain-days per month, solar radiation and relative humidity in future scenarios -variables that are important in determining crop water status and irrigation requirements. Future assessments are therefore advised to explore the use of AgMIP's mean-and-variability scenario approaches, which adjust the number of rain-days and the distribution of extreme temperatures in addition to mean changes (Ruane et al, 2015).…”

Section: Methodology Issuesmentioning

confidence: 99%

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Simulated impacts of climate change on water use and yield of irrigated sugarcane in South Africa

Jones

Singels

Ruane

2015

Agricultural Systems

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Reliable predictions of climate change impacts on water use, irrigation requirements and yields of irrigated sugarcane in South Africa (a water-scarce country) are necessary to plan adaptation strategies. Although previous work has been done in this regard, methodologies and results vary considerably. The objectives were (1) to estimate likely impacts of climate change on sugarcane yields, water use and irrigation demand at three irrigated sugarcane production sites in South Africa (Malelane, Pongola and La Mercy) for current and future (2070-2100) climate scenarios, using an approach based on the Agricultural Model Intercomparison and Improvement Project (AgMIP) protocols; and (2) to assess the suitability of this methodology for investigating climate change impacts on sugarcane production. 2Future climate datasets were generated using the Delta downscaling method and three Global Circulation Models (GCMs) assuming atmospheric CO 2 concentration [CO 2 ] of 734 ppm (A2 emissions scenario). Yield and water use were simulated using the DSSAT-Canegro v4.5 model.Irrigated cane yields are expected to increase at all three sites (between 11 and 14%), primarily due to increased interception of radiation as a result of accelerated canopy development. Evapotranspiration and irrigation requirements increased by 11% due to increased canopy cover and evaporative demand. Sucrose yields are expected to decline because of increased consumption of photo-assimilate for structural growth and maintenance respiration. Crop responses in canopy development and yield formation differed markedly between the crop cycles investigated.Possible agronomic implications of these results include reduced weed control costs due to shortened periods of partial canopy, a need for improved efficiency of irrigation to counter increased demands, and adjustments to ripening and harvest practices to counter decreased cane quality and optimise productivity.Although the Delta climate data downscaling method is considered robust, accurate and easily-understood, it does not change the future number of rain-days per month. The impacts of this and other climate data simplifications ought to be explored in future work.Shortcomings of the DSSAT-Canegro model include the simulated responses of phenological development, photosynthesis and respiration processes to high temperatures, and the disconnect between simulated biomass accumulation and expansive growth. Proposed methodology refinements should improve the reliability of predicted climate change impacts on sugarcane yield.

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Section: Methodology Issuesmentioning

confidence: 99%

“…It is also a relatively simple, easily understood method compared to more complicated approaches (for example the bias-corrected spatially disaggregated approach) for which the value added is not always clear. (Ruane et al, 2015) The average of all GCMs is also shown for each site.…”

Section: Downscaling Of Future Climate Datamentioning

confidence: 99%

Simulated impacts of climate change on water use and yield of irrigated sugarcane in South Africa

Jones

Singels

Ruane

2015

Agricultural Systems

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“…When averaging GCM projections of seasonal precipitation changes over multiple months, historical climate information over the "current" period is needed to recognize that percentage changes in wet months impact total season precipitation more than changes in dry months. To demonstrate similar characteristics of GCM projections, we create simple climate scenarios by imposing the temperature changes (an additive factor) and precipitation changes (a multiplicative factor) upon historical observations as is done in the "Delta" approach among many other statistical methods (Wilby et al 2004;Ruane et al 2015b). Future time periods are defined as Near-term (2010Near-term ( -2039, Mid-Century (2040-2069, and "End-of-Century" (2070-2099) as in Ruane et al (2015b).…”

Section: Future Climate Projectionsmentioning

confidence: 99%

“…AgMERRA provides a global, daily, 0.25°× 0.25°gridded climate dataset spanning 1980-2010 containing maximum and minimum temperatures, precipitation, solar radiation, wind speed, and relative humidity at the maximum temperature time of day. AgMERRA has been used in numerous AgMIP activities (Elliott et al 2015;Ruane et al 2015b). Climate sensitivities represent an equilibrium global mean surface temperature increase resulting from a doubling of pre-industrial CO 2 concentrations (from Table 9.5 of Flato et al 2013; n.a.…”

Section: Historical Climate Datamentioning

confidence: 99%

“…The ramifications of choosing this subset, based in part upon which GCMs available at the time, continues to be explored (McSweeney and Jones 2016). Early AgMIP regional integrated assessments also used 5 GCMs selected according to prominence in publications, length of participation in CMIP, spatial resolution, and historical monsoon patterns (Ruane et al 2015b).…”

Section: Introductionmentioning

confidence: 99%

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Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment

2017

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We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

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Integrated Assessment of Climate Change Impacts and Adaptation in Agriculture: The Case Study of the Wami River Sub-basin, Tanzania

Tumbo¹,

Mutabazi²,

Mourice³

et al. 2020

Sustainable Development Goals Series

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AgMIP Climate Data and Scenarios for Integrated Assessment

Cited by 45 publications

References 0 publications

Simulated impacts of climate change on water use and yield of irrigated sugarcane in South Africa

Simulated impacts of climate change on water use and yield of irrigated sugarcane in South Africa

Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment

Integrated Assessment of Climate Change Impacts and Adaptation in Agriculture: The Case Study of the Wami River Sub-basin, Tanzania

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