Michel Déqué’s research while affiliated with French National Centre for Scientific Research and other places

What is this page?


This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.

Publications (142)


Mean SLP difference between ARP-AMIP-AC (a) and ARP-AMIP (b) simulations minus ERA-I for the reference period 1981–2010 in winter (JJA, left) and summer (DJF, right). Value of the RMSE are given below the plots.
Mean sea-level pressure (SLP) map for the 20 best-matching units (BMUs) obtained after a self-organizing map analysis on daily SLP fields. SLP ranges from 1030 hPa (red) to 960 hPa (purple) with 10 hPa intervals.
Best-matching-unit (BMU) relative frequency (%) of ARP-AMIP (red), ARP-AMIP-AC (blue) and ERA-I (black) on daily SLP map over the 1981–2010 period. Root mean square errors and Pearson correlation coefficient with respect to ERA-I BMU frequencies are shown to the right of the legend.
(a) ARP-AMIP-AC minus ARP-AMIP T2m in winter (left) and summer (right). (b) Same as panel (a) but for ARP-AMIP-AC minus MAR-ERA-I. Circles represent mean bias for weather stations from the monthly READER database. Black contour lines represents where the difference is 1 standard deviation of MAR T2m. (c) Same as panel (b) but for ARP-AMIP-AC minus RACMO2-ERA-I.
Yearly mean total precipitation (mm w.e. yr-1) for ARP-AMIP-AC (a), ARP-AMIP (b), MAR-ERA-I (d) and RACMO2-ERA-I (g) for the reference period 1981–2010. Difference (mm w.e. yr-1) for ARP-AMIP-AC minus ARP-AMIP (c), ARP-AMIP-AC minus MAR-ERA-I (e), ARP-AMIP minus MAR-ERA-I (f), ARP-AMIP-AC minus RACMO2-ERA-I (h) and ARP-AMIP minus RACMO2-ERA-I (i). Blue (magenta) hatched contour lines represent areas where the positive (negative) difference is larger than 20 %. Mean error (ME) and RMSE statistics (mm w.e. yr-1) for the comparison with MAR and RACMO2 are shown below the panel.

+4

Significant additional Antarctic warming in atmospheric bias-corrected ARPEGE projections with respect to control run
  • Article
  • Full-text available

August 2021

·

50 Reads

·

2 Citations

·

Michel Déqué

·

·

[...]

·

In this study, we use run-time bias correction to correct for the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) atmospheric model systematic errors on large-scale atmospheric circulation. The bias-correction terms are built using the climatological mean of the adjustment terms on tendency errors in an ARPEGE simulation relaxed towards ERA-Interim reanalyses. The bias reduction with respect to the Atmospheric Model Intercomparison Project (AMIP)-style uncorrected control run for the general atmospheric circulation in the Southern Hemisphere is significant for mean state and daily variability. Comparisons for the Antarctic Ice Sheet with the polar-oriented regional atmospheric models MAR and RACMO2 and in situ observations also suggest substantial bias reduction for near-surface temperature and precipitation in coastal areas. Applying the method to climate projections for the late 21st century (2071–2100) leads to large differences in the projected changes of the atmospheric circulation in the southern high latitudes and of the Antarctic surface climate. The projected poleward shift and strengthening of the southern westerly winds are greatly reduced. These changes result in a significant 0.7 to 0.9 K additional warming and a 6 % to 9 % additional increase in precipitation over the grounded ice sheet. The sensitivity of precipitation increase to temperature increase (+7.7 % K-1 and +9 % K-1) found is also higher than previous estimates. The highest additional warming rates are found over East Antarctica in summer. In winter, there is a dipole of weaker warming and weaker precipitation increase over West Antarctica, contrasted by a stronger warming and a concomitant stronger precipitation increase from Victoria to Adélie Land, associated with a weaker intensification of the Amundsen Sea Low.

Download

Significant additional Antarctic warming in atmospheric bias-corrected ARPEGE projections

November 2020

·

78 Reads

In this study, we use run-time bias-correction to correct for ARPEGE atmospheric model systematic errors on large-scale atmospheric circulation. The bias correction terms are built using the climatological mean of the adjustment terms on tendency errors in an ARPEGE simulation relaxed towards ERA-Interim reanalyses. The improvements with respect to the AMIP-style uncorrected control run for the general atmospheric circulation in the Southern Hemisphere are significant for mean state and daily variability. Comparisons for the Antarctic Ice Sheet with the polar-oriented regional atmospheric models MAR and RACMO2 and in-situ observations also suggest substantial bias reduction for near-surface temperature and precipitation in coastal areas. Applying the method to climate projections for the late 21 st century (2071-2100) leads to large differences in the projected changes of the atmospheric circulation in the Southern high latitudes and of the Antarctic surface climate. The projected poleward shift and strengthening of the southern westerly winds are greatly reduced. These changes result in a significant 0.7 to 0.9 K additional warming and a 6 to 9% additional increase in precipitation over the grounded ice sheet. The sensitivity of precipitation increase to temperature increase (+7.7 and +9%.K −1 ) found is also higher than previous estimates. Highest additional warming rates are found over East Antarctica in summer. In winter, there is a dipole of weaker warming and weaker precipitation increase over West Antarctica, contrasted by a stronger warming and a concomitant stronger precipitation increase from Victoria to Adélie Land, associated with a weaker intensification of the Amundsen Sea Low.


Multimodel Forecasting of Precipitation at Subseasonal Timescales Over the Southwest Tropical Pacific

September 2020

·

127 Reads

·

17 Citations

Abstract Multimodel ensemble (MME) reforecasts of rainfall at subseasonal time scales in the southwest tropical Pacific are constructed using six models (BoM, CMA, ECCC, ECMWF, Météo‐France, and UKMO) from the Subseasonal‐to‐Seasonal (S2S) database by member pooling. These reforecasts are verified at each grid point of the 110°E to 200°E; 30°S to 0° domain for the 1996–2013 DJF period. The evaluation is based on correlation and on the ROC skill score of the upper quintile of precipitation for both weekly targets and Weeks 3–4 outlook. Confirming previous results at the seasonal time scales, the MME reaches the highest skill and also improves the reliability of probabilistic forecasts. However, an equivalent ensemble size comparison between the MME and the individual models shows that the better performance of the MME compared to the best individual models is significantly related to the larger ensemble size of the MME. Forecast skill is then explained in light of potential sources of predictability by evaluating the performance of the models depending on the initial ENSO and MJO state. While the role of ENSO on predictability is quite consistent with its related rainfall anomalies, the role of the MJO is more ambiguous and strongly depends on the location: An initialization in active MJO conditions does not necessarily imply better forecasts. This influence of ENSO and the MJO on predictability does not change when switching from individual models to the MME.


Teleconnection-based evaluation of seasonal forecast quality

September 2020

·

165 Reads

·

3 Citations

Climate Dynamics

In response to the high demand for more skillful climate forecasts at the seasonal timescale, innovative climate prediction systems are developed with improved physics and increased spatial resolution. Alongside the model development process, seasonal predictions need to be evaluated on past years to provide robust information on the forecast performance. This work presents the quality assessment of the Météo-France coupled climate prediction system, taking advantage of an experiment performed with 90 ensemble members over a 37-year re-forecast period from 1979 to 2015. We focus on the boreal winter season initialised in November. Beyond typical skill measures we evaluate the model capability in reproducing ENSO and NAO teleconnections on precipitation and near surface temperature respectively. Such an assessment is carried out first through a composite analysis, and shows that the model succeeds in reproducing the main patterns for near surface temperature and precipitation. A covariance method leads to consistent results. Finally we find that the teleconnection representation of the model is not affected by shortening the verification period and reducing the ensemble size and therefore can be used to evaluate operational seasonal forecast systems.


Extreme rainfall in Mediterranean France during the fall: added value of the CNRM-AROME Convection-Permitting Regional Climate Model

July 2020

·

505 Reads

·

92 Citations

Climate Dynamics

South-East France is a region often affected by heavy precipitating events the characteristics of which are likely to be significantly impacted in the future climate. In this study, cnrm-arome, a Convection-Permitting Regional Climate Model with a 2.5 km horizontal resolution is compared to its forcing model, the Regional Climate Model aladin-climate at a horizontal resolution of 12.5 km, self-driven by the era-interim reanalysis. An hourly observation dataset with a resolution of 1 km, comephore, is used in order to assess simulated surface precipitation from a seasonal to hourly scale. The representation of the spatial pattern of fall precipitation climatology is improved by cnrm-arome. It also shows a clear added value with respect to aladin-climate through the improvement of the localization and intensity of extreme rainfall on a daily and hourly time scale on both fine and coarse spatial scales (2.5, 12.5 and 50 km). cnrm-arome in particular is able to simulate intense rainfall on lowlands and makes sub-daily rainfall events more intense than aladin-climate. cnrm-arome still underestimates very extreme precipitation from above 30 mm/h or 230 mm/day.


Correction to: Extreme rainfall in Mediterranean France during the fall: added value of the CNRM‑AROME Convection‑Permitting Regional Climate Model

July 2020

·

91 Reads

·

2 Citations

Climate Dynamics

Unfortunately, the article “Extreme rainfall in Mediterranean France during the fall: added value of the CNRM‑AROME Convection‑Permitting Regional Climate Model”, written by Quentin Fumière was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 24 July 2019 without open access with incorrect copyright holder as “© Springer-Verlag GmbH Germany, part of Springer Nature 2019”.


Effect of prescribed sea surface conditions on the modern and future Antarctic surface climate simulated by the ARPEGE atmosphere general circulation model

November 2019

·

159 Reads

·

6 Citations

Owing to increase in snowfall, the Antarctic Ice Sheet surface mass balance is expected to increase by the end of the current century. Assuming no associated response of ice dynamics, this will be a negative contribution to sea-level rise. However, the assessment of these changes using dynamical downscaling of coupled climate model projections still bears considerable uncertainties due to poorly represented high-southern-latitude atmospheric circulation and sea surface conditions (SSCs), that is sea surface temperature and sea ice concentration. This study evaluates the Antarctic surface climate simulated using a global high-resolution atmospheric model and assesses the effects on the simulated Antarctic surface climate of two different SSC data sets obtained from two coupled climate model projections. The two coupled models from which SSCs are taken, MIROC-ESM and NorESM1-M, simulate future Antarctic sea ice trends at the opposite ends of the CMIP5 RCP8.5 projection range. The atmospheric model ARPEGE is used with a stretched grid configuration in order to achieve an average horizontal resolution of 35 km over Antarctica. Over the 1981–2010 period, ARPEGE is driven by the SSCs from MIROC-ESM, NorESM1-M and CMIP5 historical runs and by observed SSCs. These three simulations are evaluated against the ERA-Interim reanalyses for atmospheric general circulation as well as the MAR regional climate model and in situ observations for surface climate. For the late 21st century, SSCs from the same coupled climate models forced by the RCP8.5 emission scenario are used both directly and bias-corrected with an anomaly method which consists in adding the future climate anomaly from coupled model projections to the observed SSCs with taking into account the quantile distribution of these anomalies. We evaluate the effects of driving the atmospheric model by the bias-corrected instead of the original SSCs. For the simulation using SSCs from NorESM1-M, no significantly different climate change signals over Antarctica as a whole are found when bias-corrected SSCs are used. For the simulation driven by MIROC-ESM SSCs, a significant additional increase in precipitation and in winter temperatures for the Antarctic Ice Sheet is obtained when using bias-corrected SSCs. For the range of Antarctic warming found (+3 to +4 K), we confirm that snowfall increase will largely outweigh increases in melt and rainfall. Using the end members of sea ice trends from the CMIP5 RCP8.5 projections, the difference in warming obtained (∼ 1 K) is much smaller than the spread of the CMIP5 Antarctic warming projections. This confirms that the errors in representing the Southern Hemisphere atmospheric circulation in climate models are also determinant for the diversity of their projected late 21st century Antarctic climate change.


FIG. 7. Temporal correlation of the mean JJA 2-meter temperature over the period 1993-2014 between detrended CRUTS4 and the de-trended ensemble mean of (a) CTRL, (b) INIT and (c) PERT. Right-hand maps show the correlation difference (d) "INIT minus CTRL" and (e) "PERT minus CTRL". Stippling mark values significantly different from zero with a 95% confidence level based on a two-sided Student t-test for correlations, and on the Steiger (1980) test for correlation differences.
FIG. 8. Normalized yearly JJA 2-meter temperature anomalies (in K) over SGP for CRUTS4 (black dashed line) and the ensemble mean of CTRL (blue line), INIT (green line) and PERT (red line). The corresponding correlations with CRUTS4 are indicated at the upper left corner of the figure, with the same color code. The asterisk marks a significant correlation with a 95% confidence level based on a two-sided Student t-test.
On the Link between Summer Dry Bias over the U.S. Great Plains and Seasonal Temperature Prediction Skill in a Dynamical Forecast System

June 2019

·

37 Reads

·

7 Citations

Weather and Forecasting

Soil moisture anomalies are expected to be a driver of summer predictability for the U.S. Great Plains since this region is prone to intense and year-to-year varying water and energy exchange between the land and the atmosphere. However, dynamical seasonal forecast systems struggle to deliver skillful summer temperature forecasts over that region, otherwise subject to a consistent warm-season dry bias in many climate models. This study proposes two techniques to mitigate the impact of this precipitation deficit on the modeled soil water content in a forecast system based on the CNRM-CM6-1 model. Both techniques lead to increased evapotranspiration during summer and reduced temperature and precipitation bias. However, only the technique based on a correction of the precipitation feeding the land surface throughout the forecast integration enables skillful summer prediction. Although this result cannot be generalized for other parts of the globe, it confirms the link between bias and skill over the U.S. Great Plains and pleads for continued efforts of the modeling community to tackle the summer bias affecting that region.


Figure 2. Time evolution of the snow reliability index (including reanalysis annual values) for (a) groomed snow conditions and (b) groomed snow conditions with snowmaking, including independent estimates of annual ski-lift ticket sales. Time evolution of the frequency of snow seasons exhibiting fractional snow reliability values lower than the snow scarcity threshold Q20 for (c) groomed snow conditions and (d) groomed snow conditions with snowmaking. (e) Water demand associated to the production of snow, including independent estimates of the water volumes used for snowmaking 27 . All figures display the 15-yr average of the reanalysis and multi-model mean and standard deviation of 15-yr averages for historical and future climate scenarios.
Figure 3. Evolution of the snow reliability index (%) and water volume (Mm 3 ) for snowmaking of French Alps ski resorts for the reference period 1986-2005, near future (2030-2050) and end of century (2080-2100), depending on the RCP scenario and the snowmaking coverage (in % of total ski slopes surface area). Snow reliability values below the snow scarcity threshold (Q20) are highlighted in orange. Water volumes over three times the 95% percentile value (Q95) of the reference period are highlighted in blue. Note that years contributing to a given quantile for the snow reliability index do not necessarily contribute to the same quantile in terms of water volume for snowmaking.
Figure 4. Relationship to global warming level of (a) the snow reliability index, (b) the frequency of snow seasons below the snow scarcity threshold (Q20) and (c) water demand associated to the production of snow, accounting for grooming only (0% snowmaking coverage) and a 45% snowmaking coverage. The global surface air temperature change was computed with respect to the pre-industrial period (1851-1880). The mean value, standard deviation (error bars) and outliers are shown (see Methods). n is the number of GCM/RCM pairs within a given temperature bin.
Mean and standard deviation across multiple model estimates of 20-yr averages of the fractional snow reliability index for groomed snow conditions (top) and groomed snow conditions plus a 45% snowmaking coverage (bottom), for the reference period (1986–2005), the near future (2030–2050, RCP 8.5) and the end of century (2080–2100, RCP 8.5 and RCP 2.6, surrounded by red dashed lines) for the 23 massifs of the French Alps. Pie diagrams display the 20 year multi-model massif-scale snow reliability index, the diameter being proportional to the total ski-lift power within each massif. Background colors display the standard deviation around the mean. Situation of the 129 ski resorts covered in the present study and of the main cities in the French Alps (lower left).
Climate controls on snow reliability in French Alps ski resorts

May 2019

·

3,425 Reads

·

85 Citations

Ski tourism is a major sector of mountain regions economy, which is under the threat of long-term climate change. Snow management, and in particular grooming and artificial snowmaking, has become a routine component of ski resort operations, holding potential for counteracting the detrimental effect of natural snow decline. However, conventional snowmaking can only operate under specific meteorological conditions. Whether snowmaking is a relevant adaptation measure under future climate change is a widely debated issue in mountainous regions, with major implications on the supply side of this tourism industry. This often lacks comprehensive scientific studies for informing public and private decisions in this sector. Here we show how climate change influences the operating conditions of one of the main ski tourism markets worldwide, the French Alps. Our study addresses snow reliability in 129 ski resorts in the French Alps in the 21st century, using a dedicated snowpack model explicitly accounting for grooming and snowmaking driven by a large ensemble of adjusted and downscaled regional climate projections, and using a geospatial model of ski resorts organization. A 45% snowmaking fractional coverage, representative of the infrastructures in the early 2020s, is projected to improve snow reliability over grooming-only snow conditions, both during the reference period 1986–2005 and below 2 °C global warming since pre-industrial. Beyond 3 °C of global warming, with 45% snowmaking coverage, snow conditions would become frequently unreliable and induce higher water requirements.


Investigating the impact of soil moisture on European summer climate in ensemble numerical experiments

April 2019

·

269 Reads

·

13 Citations

Climate Dynamics

A better anticipation of high-impact heat and drought on human activity is the underlying motivation of many climate studies focused on the summer season. Although a large body of research has already highlighted the prominent impact of soil moisture anomalies on summer mid-latitudes climate variability and predictability, it still leaves room for a wide range of uncertainty and sometimes contradictions. The present work aims at revisiting soil moisture sensitivity studies by comparing an idealized ensemble model experiment in which soil moisture conditions are prescribed with a reference experiment in which soil moisture evolves freely. Two regional climate models centered over Europe contribute to these experiments and generate very similar results. Simulations with constrained soil moisture display significantly increased correlation between observed and simulated seasonal anomalies of maximum temperature, precipitation and surface solar radiation, as compared to the reference experiment. This widespread increase is not restricted to regions already known as hot-spots of land–atmosphere coupling such as southern Europe, where the evapotranspiration rate is mainly driven by soil moisture. In spite of a limited change in the ensemble spread, the sensitivity experiments show a substantially modified magnitude of temperature and precipitation variability. A focus on two case studies reveal contrasting results for the 2003 and 2010 heat waves. These results stress the prominent role of soil moisture as a boundary condition of the climate system in Europe, including regions that have not been highlighted by previous sensitivity works.


Citations (77)


... The method consists of bias-correcting the systematic errors in atmospheric general circulation using the statistics of a nudged simulation towards climate reanalysis. A substantial bias reduction in the general atmospheric circulation features and even in near-surface temperature and precipitation has been found (Beaumet et al., 2021;Krinner et al., 2019). This approach is attractive because it preserves a high degree of physical consistency across the representation of atmospheric processes, from large-scale circulation to subgrid parameterized processes, which is not possible with "a posteriori" bias correction methods. ...

Reference:

Towards an advanced representation of precipitation over Morocco in a global climate model with resolution enhancement and empirical run‐time bias corrections
Significant additional Antarctic warming in atmospheric bias-corrected ARPEGE projections with respect to control run

... The significant vulnerability of the Mediterranean region to future climate change has been emphasized since the early 2000s (Molinié et al. 2016;Brogli et al. 2019). Our results support the belief toward the end of 2100 that mean precipitation both in the study watershed and across important Mediterranean ecosystems is expected to decrease, coupled with increased temperatures. ...

Sub-chapter 1.3.1. Heavy precipitation in the Mediterranean basin

... Such studies (and Molteni et al., 2020) have also found that "freerunning" coupled model or SST-forced atmospheric model experiments do not, or only weakly, reproduce the ENSO teleconnection to the North Atlantic through the cold season, while initialized hindcasts perform better. Other studies have focused on the effects of the ENSO teleconnection on surface climate in Europe (precipitation, temperature, drought indices, e.g., Brönnimann et al., 2007;King et al., 2020;van Oldenborgh and Burgers, 2005), for which model performance is less well documented than for atmospheric circulation anomalies (but see, e.g., King et al., 2020;Volpi et al., 2020). Further research on surface climate impacts in models and prediction skills should consider the varying nature of the ENSO teleconnection through the cold season (discussion in King et al., 2018a). ...

Teleconnection-based evaluation of seasonal forecast quality

Climate Dynamics

... Ensemble techniques allow the combination of multiple models with different performances to produce more accurate forecasts (Weyn et al., 2021;Specq et al., 2020;Pakdaman et al., 2022). Studies have shown that using ensembles improves forecast quality (Gu et al., 2022;Kullahci and Altunkaynak, 2023;Kundu et al., 2023;Anggraeni et al., 2018), with the performance of each modelinfluencing its contribution to the ensemble. ...

Multimodel Forecasting of Precipitation at Subseasonal Timescales Over the Southwest Tropical Pacific

... An advantage of using the MOA = 0.7 threshold is that the effects of snow accumulation and liquid water availability (melt and rain, henceforth referred to as melt for readability), which are both expected to increase in Antarctica in a warming climate, can be separately quantified. This is relevant because model studies suggest that Antarctic-wide snow accumulation increases quasi-linearly with temperature, in first order following the Clausius-Clapeyron relationship 15,16 , but with large regional variations owing to changes in precipitation phase and large-scale circulation 14,17,18 . In contrast, surface melt is expected to increase more strongly than linear with temperature 19 because of several feedback mechanisms, such as the snowmelt-albedo feedback 20 , the wind-albedo interaction 21 and/or the poorly understood impacts of ice clouds and water clouds on rainfall 22 and surface melt 23 . ...

Effect of prescribed sea surface conditions on the modern and future Antarctic surface climate simulated by the ARPEGE atmosphere general circulation model

... We also use the high-resolution observed COmbinaison en vue de la Meilleure Estimation de la Précipitation HOraiRE (COMEPHORE) dataset, a precipitation blended product produced by Météo France using all available in situ and radar rainfall records (Champeaux et al 2009, Tabary et al 2012, Caillaud 2019, Fumière et al 2020. The COMEPHORE product covers the 1997-2022 period at hourly frequency and 1 km spatial resolution. ...

Extreme rainfall in Mediterranean France during the fall: added value of the CNRM-AROME Convection-Permitting Regional Climate Model

Climate Dynamics

... The water table depths were also compared to the global dataset of Fan et al. (2013) derived from a high-resolution groundwater model constrained with observations . The ISBA-CTRIP land surface system was then used in a number of studies dealing with global hydrology and/or climate change (Ardilouze et al. 2019;Giffard et al. 2019;Douville et al. 2020;Padrón et al. 2020;Pellet et al. 2020;Saint-Martin et al. 2021). ...

On the Link between Summer Dry Bias over the U.S. Great Plains and Seasonal Temperature Prediction Skill in a Dynamical Forecast System

Weather and Forecasting

... Both natural and artificial snow depend on the meteorological conditions, making the outdoor skiing industry climate sensitive 8 . The outdoor winter tourism sector, in particular the outdoor ski resorts, has been emphasized as one of the most vulnerable industries and have the increasing risks to climate change 1,[9][10][11][12][13][14] . ...

Climate controls on snow reliability in French Alps ski resorts

... A second approach, that we have chosen, consists in choosing one given global climate model and to run the so-called 'online biased-corrected simulations' which aims at removing systematic biases in ocean sea surface temperature and atmospheric circulation in the model. The method, proposed and established throughout a series of papers (e.g., Guldberg et al. (2005), Kharin and Scinocca (2012), Beaumet et al. (2019) and Krinner et al. (2019Krinner et al. ( , 2020) can be summarized as follows: Firstly, a present-day global simulation is set up with the wind components (U,V) nudged towards ERA5 reanalysis at each model time step as follows: ...

Assessing bias corrections of oceanic surface conditions for atmospheric models

... A posteriori" bias correction of the near-surface variables (mainly nearsurface air temperature and precipitation) cannot correct for atmospheric circulation biases (potentially leading to an implicit pinning of the atmospheric circulation features), yielding unphysical corrections that raise doubt about the credibility of the adjusted output (Maraun, 2016;Maraun et al., 2017). Following an approach first developed in the context of seasonal forecasting (Guldberg et al., 2005;Kharin & Scinocca, 2012), Krinner et al. (2019) proposed an empirical run-time bias correction approach for atmospheric variables, which they applied for Antarctic regional climate projections using the LMDZ Stretched-Grid GCM. The method consists of bias-correcting the systematic errors in atmospheric general circulation using the statistics of a nudged simulation towards climate reanalysis. ...

Empirical Run-Time Bias Correction for Antarctic Regional Climate Projections With a Stretched-Grid AGCM