A Norwegian Approach to Downscaling

Benestad, Rasmus E.

doi:10.5194/gmd-2021-176

Cited by 6 publications

(3 citation statements)

References 65 publications

(96 reference statements)

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“…Additionally, it should be noticed that all ESD methods here evaluated operate at a daily scale (“downscaling weather”), but “downscaling climate” appears to be a promising approach, as parameters of the distributions are usually easier to predict than daily states and transferability issues might be palliated (Erlandsen et al ., 2020; Benestad, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…Erlandsen et al . (2020) evaluated an ESD method based on “downscaling climate” instead of “downscaling weather,” which consists in estimating parameters of the distributions instead of daily data (Benestad, 2021). They combined this approach with the use of common EOFs (Benestad, 2001; 2021) using a convective permitting RCM over the emissive scenario RCP8.5 (see IPCC, 2013) and found a significant sensitivity to the predictors choice and to the calibration period.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of statistical downscaling methods for climate change projections over Spain: Future conditions with pseudo reality (transferability experiment)

Hernanz

García‐Valero

Domínguez

et al. 2021

Intl Journal of Climatology

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The Spanish Meteorological Agency (AEMET) is responsible for the elaboration of downscaled climate projections over Spain to feed the Second National Plan of Adaptation to Climate Change (PNACC-2) and this is the last of three papers aimed to evaluate and intercompare five empirical/statistical downscaling (ESD) methods developed at AEMET: (a) Analog, (b) Regression, (c) Artificial Neural Networks, (d) Support Vector Machines and (e) Kernel Ridge Regression, in order to decide which methods and under what configurations are more suitable for that purpose. Following the framework established by the EU COST Action VALUE, in this experiment we test the transferability of these methods to future climate conditions with the use of regional climate models (RCMs) as pseudo observations. We evaluate the marginal aspects of the distributions of daily maximum/minimum temperatures and daily accumulated precipitation, over mainland Spain and the Balearic Islands, analysed by season. For maximum/minimum temperatures all methods display certain transferability issues, being remarkable for Support Vector Machines and Kernel Ridge Regression. For precipitation all methods appear to suffer from transferability difficulties as well, although conclusions are not as clear as for temperature, probably due to the fact that precipitation does not present such a marked signal of change. This study has revealed how an analysis over a historical period is not enough to fully evaluate ESD methods, so we propose that some type of analysis of transferability should be added in a standard procedure of a complete evaluation.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of statistical downscaling methods for climate change projections over Spain: Future conditions with pseudo reality (transferability experiment)

Hernanz

García‐Valero

Domínguez

et al. 2021

Intl Journal of Climatology

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“…As such, employing a small number of global climate models for projecting regional or local future climate is prone to result in misleading outlooks. It is possible to account for such regional internal model variability by using large ensembles of global climate model simulations (Benestad, 2021). Proper consideration of climate uncertainty and variability might be done when output from large (e.g., 30–100 member) ensembles of global climate models are downscaled to regional climate projections that are all propagated into a distribution of plausible risks that comprehensively represent the combined uncertainty and variability of future climate conditions, chemical exposures, and environmental effects (Moe et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Incorporating climate projections in the environmental risk assessment of pesticides in aquatic ecosystems

Oldenkamp,

Benestad,

Hader

et al. 2023

Integr Envir Assess & Manag

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Global climate change will significantly impact the biodiversity of freshwater ecosystems, both directly and indirectly via the exacerbation of impacts from other stressors. Pesticides form a prime example of chemical stressors that are expected to synergise with climate change. Aquatic exposures to pesticides might change in magnitude due to increased runoff from agricultural fields, and in composition as application patterns will change due to changes in pest pressures and crop types. Any prospective chemical risk assessment that aims to capture the influence of climate change should properly and comprehensively account for the variabilities and uncertainties that are inherent to projections of future climate. This is only feasible if they probabilistically propagate extensive ensembles of climate model projections. However, current prospective risk assessments typically make use of process‐based models of chemical fate that do not typically allow for such high‐throughput application. Here we describe a Bayesian network model that does. It incorporates a two‐step univariate regression model based on a thirty‐day antecedent precipitation index, circumventing the need for computationally laborious mechanistic models. We show its feasibility and application potential in a case study with two pesticides in a Norwegian stream: the fungicide trifloxystrobin and herbicide clopyralid. Our analysis showed that variations in pesticide application rates as well as precipitation intensity lead to variations in in‐stream exposures. When relating to aquatic risks, the influence of these processes reduces and distributions of risk are dominated by effect‐related parameters. Predicted risks for clopyralid were negligible, but the probability of unacceptable future environmental risks due to exposure to trifloxystrobin (i.e., a risk quotient > 1) was 8‐12%. This percentage further increases to 30‐35% when a more conservative precautionary factor of 100 instead of 30 was used.

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Trends and Effects of Climate Change on Reindeer Husbandry in the Republic of Sakha (Yakutia)

et al. 2022

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The Republic of Sakha (Yakutia), like other Arctic regions, faces severe climatic and environmental changes and hazards such as temperature increase, permafrost thaw, intense forest fires, earlier melting, and flooding. Significant climate and environmental changes over the past decades pose risks to the preservation of the traditional way of life of Indigenous peoples, including reindeer husbandry. Understanding trends and effects of climate change in the Republic of Sakha is needed to project and manage the future of reindeer husbandry, the resilience of Indigenous communities, and plan their economic adaptation. In this article, we analyze meteorological data from four weather stations located in different reindeer herding areas of Yakutia focusing on snow cover formation, permafrost conditions, and forest fires; provide the results of in-depth interviews with local people on the impact of climate change on reindeer herding. The financing of resilience development in the Republic is discussed. In conclusion, suggest necessary measures that can be taken for adaptation and overcoming emerging threats and challenges for further development of reindeer husbandry which is the central basis of the identity of the Indigenous peoples of the North.

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A Norwegian Approach to Downscaling

Cited by 6 publications

References 65 publications

Evaluation of statistical downscaling methods for climate change projections over Spain: Future conditions with pseudo reality (transferability experiment)

Evaluation of statistical downscaling methods for climate change projections over Spain: Future conditions with pseudo reality (transferability experiment)

Incorporating climate projections in the environmental risk assessment of pesticides in aquatic ecosystems

Trends and Effects of Climate Change on Reindeer Husbandry in the Republic of Sakha (Yakutia)

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