The Implications and Importance of Non-Linear Responses in Modelling the Growth and Development of Wheat

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

doi:10.1007/978-94-011-0962-8_14

Cited by 13 publications

(7 citation statements)

References 18 publications

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“…Stochastic weather generators are widely used by many researchers world-wide (Racsko et al, 1991;Semenov and Porter, 1994;Qian et al, 2004, Semenov, 2007. Stochastic weather generators may be site-specific, i.e.…”

Section: Methodsmentioning

confidence: 99%

Impact of climate change on rainfall in Northwestern Bangladesh using multi‐GCM ensembles

Kumar¹,

Arya

Murumkar³

et al. 2013

Intl Journal of Climatology

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Teesta River basin, located in the northwest of Bangladesh, is more vulnerable to floods if compared to other parts of the country. In this context, daily rainfall data of ten raingauge stations located in the catchment of the Jamuneswari River, part of the Teesta River basin, were analysed to study the impact of climate change on rainfall. Length of wet and dry series and mean monthly rainfalls along with their variances were used for validating Long Ashton Research Station Weather Generator (LARS‐WG). The analysis was carried out for A1B, A2 and B1 emission scenarios using 15 Global Climate Models GCMs simulations for the periods 2011–2030 centred at 2020, 2046–2065 centred at 2055 and 2080–2099 centred at 2090. The analysis of the data shows that the uncertainty in the prediction increases with the timescale. It was also found that the variability in the predictions is smaller in annual values followed by seasonal. Ensemble of seasonal analysis shows that most of the GCM are in agreement for changes in monsoon season. The LARS‐WG has reasonable skill to downscale the point rainfall data and the results obtained so are useful to analyse the impact of climate change on the hydrology of the basin.

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Section: Methodsmentioning

confidence: 99%

Impact of climate change on rainfall in Northwestern Bangladesh using multi‐GCM ensembles

Kumar¹,

Arya

Murumkar³

et al. 2013

Intl Journal of Climatology

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“…Values of n and R a for Yorkshire are provided in Table II. LARS-WG has been applied in impacts studies by Semenev andPorter (1994), andSemenev andBarrow (1997). Faulkner et al (1997) compared its performance with a first and second-order Markov chain model at three UK sites.…”

Section: Applying the Scenariosmentioning

confidence: 99%

Monte Carlo Assessment of Sampling Uncertainty of Climate Change Impacts on Water Resources Yield in Yorkshire, England

Nawaz

Adeloye

2006

Climatic Change

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Despite much effort over the last decade, there still remain many uncertainties in the assessed impacts of climate change on water resources. This study has carried out Monte Carlo Simulations to characterise the sampling uncertainties in assessed water resources impacts. The investigation employed data from catchments in northeast England, which incorporate water supply reservoirs. The impacts assessment used scenarios from three GCM experiments: (i) the Canadian first generation coupled model (CGCM1), (ii) the Australian first generation coupled model (CSIROmk2b) and (iii) the British third generation model (HadCM3). The results showed that yield impacts are subject to wide variability, irrespective of the GCM experiment, which calls for caution when using mean impacts obtained from single data record analysis for decision making.

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“…Other studies stressed that changes in climate variability, as can be expected in a warmer climate, may have a more profound effect on yield than changes in mean climate (Semenov andPorter 1994, 1995;Mearns et al 1996;Southworth et al 2000;Porter and Semenov 2005). As such, policy analysis should not rely on scenarios of future climate involving only changes in means (Katz and Brown 1992;Semenov and Barrow 1997).…”

Section: Introductionmentioning

confidence: 95%

Climate change impact assessment: the role of climate extremes in crop yield simulation

2010

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This work was aimed at assessing the role of climate extremes in climate change impact assessment of typical winter and summer Mediterranean crops by using Regional Circulation Model (RCM) outputs as drivers of a modified version of the CropSyst model. More specifically, climate change effects were investigated on sunflower (Helianthus annuus L.) and winter wheat (Triticum aestivum L.) development and yield under the A2 and B2 scenarios of the IPCC Special Report on Emissions Scenarios (SRES). The direct impact of extreme climate events (i.e. heat stress at anthesis stage) was also included. The increase in both mean temperatures and temperature extremes under A2 and B2 scenarios (2071-2100) resulted in: a general advancement of the main phenological stages, shortening of the growing season and an increase in the frequency of heat stress during anthesis with respect to the baseline . The potential impact of these changes on crop yields was evaluated. It was found that winter and summer crops may possess a different fitting capacity to climate change. Sunflower, cultivated in the southern regions of the Mediterranean countries, was more prone to the direct effect of heat stress at anthesis and drought during its growing cycle. These factors resulted in severe yield reduction. In contrast, the lower frequency of heat stress and drought allowed the winter wheat M. Moriondo (B) CNR-IBIMET,

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The Implications and Importance of Non-Linear Responses in Modelling the Growth and Development of Wheat

Cited by 13 publications

References 18 publications

Impact of climate change on rainfall in Northwestern Bangladesh using multi‐GCM ensembles

Impact of climate change on rainfall in Northwestern Bangladesh using multi‐GCM ensembles

Monte Carlo Assessment of Sampling Uncertainty of Climate Change Impacts on Water Resources Yield in Yorkshire, England

Climate change impact assessment: the role of climate extremes in crop yield simulation

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