3-Step dynamical downscaling with empirical correction of sea-surface conditions: application to a CORDEX Africa simulation

Hernández-Díaz, Leticia; Laprise, René; Nikiéma, Oumarou; Winger, Katja

doi:10.1007/s00382-016-3201-9

Cited by 24 publications

(33 citation statements)

References 48 publications

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“…The significantly improved results of CRCM5 historical simulations over CORDEX-Africa domain using this strategy (Hernández-Díaz et al 2016) motivated us to perform such method over Arctic domain. The outputs of CGCM (MPI-ESM-MR in our case) are always biased, resulting in part from their coarse resolution.…”

Section: Discussionmentioning

confidence: 99%

“…The importance of the intermediate AGCM simulation is to make a compatible combination of lower and lateral boundary conditions (keep the physical coherence between the atmosphere and the correct SST). Note however that unlike in Hernández-Díaz et al (2016), no correction has been applied to sea-ice concentration (SIC). Whenever the corrected SST was found to be incoherent with the CGCM-simulated SIC, it was adjusted to be coherent with SIC.…”

Section: Discussionmentioning

confidence: 99%

“…Richter 2015). Given the sensitivity of RCMs simulations to the biases of the driving data, several attempts have been made to develop bias-correction methods, such as the studies of Christensen and Christensen (2007), Katzfey et al (2009), Bruyère et al (2014, Yu andHernández-Díaz et al (2016;hereinafter HD16), to cite but a few.…”

Section: Introductionmentioning

confidence: 99%

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Dynamical downscaling with the fifth-generation Canadian regional climate model (CRCM5) over the CORDEX Arctic domain: effect of large-scale spectral nudging and of empirical correction of sea-surface temperature

et al. 2017

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most notable positive effect over the Arctic is a reduction of the T2m bias over the North Pacific Ocean and the North Atlantic Ocean in all seasons. Future projections using this method are compared with the results obtained with the traditional 2-step dynamical downscaling (CGCM-RCM) to assess the impact of correcting systematic biases of SST upon future-climate projections. The future projections are mostly similar for the two methods, except for precipitation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Dynamical downscaling with the fifth-generation Canadian regional climate model (CRCM5) over the CORDEX Arctic domain: effect of large-scale spectral nudging and of empirical correction of sea-surface temperature

et al. 2017

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“…Therefore the empirical bias correction of future SIC from coupled models scenarios is a much more complex issue to deal with than the bias correction of SSTs. The absence of satisfying solution proposals for this issue in the literature has led to incorrect bias-correction of future SIC in a recent study (Hernández-Díaz et al, 2017). Yet, the 5 proposal of convenient solutions for the bias correction of sea-ice for future scenarios is crucial for the community interested in the downscaling of future climate scenarios for polar regions.…”

Section: Sea-ice Concentrationmentioning

confidence: 99%

“…However, skills of atmospheric GCM are generally better when forced by observed oceanic boundary conditions (Krinner et al, 2008;Ashfaq et al, 2011;Hernández-Díaz et al, 2017).…”

Section: General Considerations On Bias Correction Of Oceanic Forcingsmentioning

confidence: 99%

Assessing bias-corrections of oceanic surface conditions for atmospheric models

Beaumet¹,

Krinner²,

Déqué³

et al. 2017

Preprint

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Abstract. Future sea-surface temperature and sea-ice concentration from coupled ocean-atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcing for the downscaling of future climate experiment.Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly and a quantile-quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea-ice concentration (SIC) are presented. For SIC, we also propose a new 5 analog method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiment and some real-case applications using observations. With respect to other previously existing methods for SIC, the analog method is a substantial improvement for the bias correction of future sea-ice concentrations.

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Potential influence of sea surface temperature representation in climate model simulations over CORDEX‐SEA domain

Magnaye

Narisma

Cruz

et al. 2021

Intl Journal of Climatology

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Regional climate simulations from the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment – Southeast Asia (SEA) indicated model biases in temperature and rainfall over SEA. Given the influence of sea surface temperature (SST) variability on SEA climate, this study examines SST representation in climate models to investigate its potential contribution to the resulting model biases over the Philippines. Observed SST over SEA is first characterized by its spatial patterns and temporal variability. An analysis of the SST representation over SEA and its potential influence on modelled climate over the Philippines in Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCMs) is then conducted, followed by an assessment of the potential influence of SST representation in CMIP5 GCMs on downscaled regional climate output. Our results show that GCMs with well represented SSTs (i.e., low bias, well captured variability, and pattern) can produce climate simulations well over the Philippines. Whether or not the GCMs with poor SST representation can perform well is inconclusive. During boreal winter (summer), climate variables with high (low) spatial correlation with model SST get poor (better) spatial correlation with observed climate. Over west of the Philippines, where model SST seasonal variability is captured well, models also adequately simulate climate variables. Results suggest that the negative temperature biases, and positive precipitation and wind speed biases, in both GCMs and downscaled simulations, are associated with negative model SST biases. These findings give a better understanding on how SST potentially influences modelled climatology over the Philippines.

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3-Step dynamical downscaling with empirical correction of sea-surface conditions: application to a CORDEX Africa simulation

Cited by 24 publications

References 48 publications

Dynamical downscaling with the fifth-generation Canadian regional climate model (CRCM5) over the CORDEX Arctic domain: effect of large-scale spectral nudging and of empirical correction of sea-surface temperature

Dynamical downscaling with the fifth-generation Canadian regional climate model (CRCM5) over the CORDEX Arctic domain: effect of large-scale spectral nudging and of empirical correction of sea-surface temperature

Assessing bias-corrections of oceanic surface conditions for atmospheric models

Potential influence of sea surface temperature representation in climate model simulations over CORDEX‐SEA domain

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