Evaluation of three model estimations of solar radiation at 24 UK stations

Rivington, Mike; Bellocchi, Gianni; Matthews, Keith; Buchan, K.

doi:10.1016/j.agrformet.2005.07.013

Cited by 102 publications

(44 citation statements)

References 43 publications

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“…e performance of these methods, however, can vary according to the region and the season of the year, as reported by Rivington et al [54]. In this study, it was found that the best Q g estimates were found in Southern and Southeastern Brazil, where it seems to be a better correlation between nebulosity and daily thermal amplitude.…”

Section: Solar Radiation Modelssupporting

confidence: 58%

Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

Bender

Sentelhas

2018

Advances in Meteorology

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e quantification of climate change impacts on several human activities depends on reliable weather data series, without gaps and long enough to build up future climate. Based on that, this study aimed to evaluate the performance of temperature-based models for estimating global solar radiation and gridded databases (AgCFSR, AgMERRA, NASA/POWER, and XAVIER) as alternative ways for filling gaps in historical weather series in Brazil and to project climate change scenarios based on measured and gridded weather data. Projections for mid-and end-of-century periods (2040-2069 and 2070-2099), using seven global climate models from CMIP5 under intermediate (RCP4.5) and high (RCP8.5) emission scenarios, were performed. e Bristow-Campbell model was the one that best estimated solar radiation, whereas the XAVIER gridded database was the closest to observed weather data. Future climate projections, under RCP4.5 and RCP8.5 scenarios, as expected, showed warmer conditions for all scenarios over Brazil. On the contrary, rainfall projections are more uncertain. Despite that, the rainfall amounts will be reduced in the North-Northeast region and increased in Southern Brazil. No significant differences between projections using the observed and XAVIER gridded database were observed; therefore, such a database showed to be reliable for both to fill gaps and to generate climate change scenarios.

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Section: Solar Radiation Modelssupporting

confidence: 58%

Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

Bender

Sentelhas

2018

Advances in Meteorology

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“…Os modelos de Angström (Angström, 1924) e de Johnson-Woodward (Rivington et al, 2005;Miller et al, 2008) utilizam a insolação (horas de brilho solar fornecida pelo heliógrafo) para estimar a radiação solar incidente. A temperatura do ar, a umidade relativa do ar, a evaporação da água e a precipitação pluvial têm sido igualmente utilizadas (Hargreaves & Samani, 1982;Thornton & Running, 1999;Weiss & Hays, 2004).…”

Section: Introductionunclassified

Avaliação de modelos de estimativa da radiação solar incidente em Cruz das Almas, Bahia

Borges¹,

Oliveira

Filho

et al. 2010

Rev. bras. eng. agríc. ambient.

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RESUMOEm estudos agroambientais a radiação solar incidente (R s ) é uma das mais importantes variáveis meteorológicas. Na ausência de dados observados de R s é possível estimá-los mediante modelos. O objetivo deste estudo foi avaliar modelos baseados na temperatura do ar para estimativa diária de R s nas condições do Recôncavo Sul da Bahia. Utilizaram-se dados de R s do período de 2004 a 2006, medidos por uma estação meteorológica automática pertencente ao INMET, instalada em Cruz das Almas, Bahia. Como etapa preliminar, verificou-se a qualidade dos dados de R s tomando-se como referência curvas de radiação esperada em dias claros. Os seguintes modelos foram avaliados: Hargreaves-Samani para regiões interiores e regiões costeiras, Thornton-Running e o de Weiss. O desempenho de cada método foi avaliado através dos seguintes indicadores: coeficiente de determinção (R 2 ), razão média (RM), erro absoluto médio (EAM), raiz quadrada do quadrado médio do erro (RQME) e índice de concordância de Wilmott Evaluating models for estimation of incoming solar radiation in Cruz das Almas, Bahia, Brazil ABSTRACT Solar radiation at the earth's surface (R s ) is one of the essential weather variables for several agro-environmental studies. In the absence of measured R s , it's possible to simulate them by models. Using three years of daily R s data (2004)(2005)(2006) collected by an INMET (Brazilian Meteorological Service) automatic weather station installed in the municipality of Cruz das Almas, BA, three air temperature-based R s simulation models were evaluated. As a preliminary step, data quality was investigated and, when needed, adjustments were made based on clear sky solar radiation envelopes. The following models were evaluated: Hargreaves-Samani for both interior and coastal regions, Thornton-Running, and the Weiss model. Linear regression R 2 , mean ratio (MR), mean absolute error (MAE), root mean square error (RMSE), and the index of agreement of Willmott (d W ) were used for model performance evaluation against measured R s . The results recommended the coastal-region Hargreaves-Samani for prediction of R s in the Reconcavo of Bahia, Brazil, since it presented the MR value closest to 1.00 (1.01), the lowest MAE (2.54 MJ m -2 d -1 ), the lowest RMSE (3.13 MJ m -2 d -1 ), and the highest d W (0.90).

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“…Solar radiation (S o ) data was not available. However, S o is a key input into crop models and can be a major source of error in yield estimates (Rivington et al 2005). So as to avoid the risk of introducing additional uncertainty between scenarios in estimating S o , we used functions within the CropSyst crop model, based on air temperature for each scenario, to make estimates.…”

mentioning

confidence: 99%

Effects of climate change on crop production in Cameroon

Tingem¹,

Rivington²,

Bellocchi³

et al. 2008

Clim. Res.

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This study involves an assessment of the potential effects of greenhouse gas climate change, as well as the direct fertilization effect of CO 2 on crop yields in Cameroon. The methodology involves coupling the transient diagnostics of 2 atmosphere-ocean general circulation models, namely NASA/Goddard Institute GISS and the Hadley Centre's HadCM3, to the CropSyst crop model to simulate current and future (2020, 2080) crop yields (bambara nut, groundnut, maize, sorghum and soybean) in 8 agricultural regions of Cameroon. For the future we estimate substantial yield increases for bambara groundnut, soybean and groundnut, and little or no change and even decreases of maize and sorghum yields, varying according to the climate scenario and the agricultural region. Maize and sorghum (both C4 crops) yields are expected to decrease by 14.6 and 39.9%, respectively, across the whole country under GISS 2080 scenarios. The results also show that the effect of temperature patterns on climate change is much more important than that of precipitation. Findings call for monitoring of climate change/variability and dissemination of information to farmers, to encourage adaptation to climate change.KEY WORDS: Cameroon · Climate change · CO 2 · Crop yields · Adaptation · CropSyst Resale or republication not permitted without written consent of the publisherClim Res 36: [65][66][67][68][69][70][71][72][73][74][75][76][77] 2008 Though a few studies have been conducted to assess the impact of climate change on agriculture in developing countries (Seo et al. 2005, Adejuwon, 2006, Thornton et al. 2006, Kabubo-Mariara & Karanja 2007, there is a dearth of literature on this impact in Cameroon; thus the adaptation and mitigation measures that are available to policy makers are severely limited.The present study aims to partially address this research gap. It uses the coupled climate scenariocrop model method, in which coupled atmosphereocean general circulation models (A-OGCMs), used to generate future climate scenarios, are integrated into crop models in order to simulate future crop yields (Tubiello et al. 2000, Brassard & Singh 2007. The use of this method allows us to gain an insight not only into how future crop yields may change, but also into the nature of the factors responsible for yield changes, and how they may affect crop production. Understanding the impacts of long-term climate change on agriculture is crucial for future agricultural policies and interventions in Cameroon, as well as aiding practical steps to mitigate potentially adverse impacts of climate change, which is likely to have important implications for future food security.The general objective of this study is to examine the effects of long-term climate change on Cameroon crop agriculture and identify the adaptation options of agroecological systems using a simulation analysis. The specific objectives are to simulate and highlight the expected effects of various long-term climate change scenarios on future agricultural productivity and discuss policy ...

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Evaluation of three model estimations of solar radiation at 24 UK stations

Cited by 102 publications

References 43 publications

Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

Avaliação de modelos de estimativa da radiação solar incidente em Cruz das Almas, Bahia

Effects of climate change on crop production in Cameroon

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