Parametric model of the Earth’s radiation budget

Summary Proposition of the Earths radiation budget, based on properties of the absorption, reflection and scattering coefficients, is presented. In the model, the final fluxes of radiation are expressed directly by absorption properties of the atmospheres components. Consequently, total (i.e., with all feedback) greenhouse effect, forced by any component of the atmosphere, can be determined. Presented model is averaged and one dimensional, but it can be developed if it meets with acceptance.     

Does the model regional bias affect the projected regional climate change? An analysis of global model projections

An analysis is presented of the dependence of the regional temperature and precipitation change signal on systematic regional biases in global climate change projections. The CMIP3 multi-model ensemble is analyzed over 26 land regions and for the A1B greenhouse gas emission scenario. For temperature, the model regional bias has a negligible effect on the projected regional change. For precipitation, a significant correlation between change and bias is found in about 30% of the seasonal/regional cases analyzed, covering a wide range of different climate regimes. For these cases, a performance-based selection of models in producing climate change scenarios can affect the resulting change estimate, and it is noted that a minimum of four to five models is needed to obtain robust precipitation change estimates. In a number of cases, models with largely different precipitation biases can still produce changes of consistent sign. Overall, it is assessed that in the present generation of models the regional bias does not appear to be a dominant factor in determining the simulated regional change in the majority of cases.     

Simulation of the Indian monsoon using the RegCM3–ROMS regional coupled model

A regional coupled atmosphere–ocean model was developed to study the role of air–sea interactions in the simulation of the Indian summer monsoon. The coupled model includes the regional climate model (RegCM3) as atmospheric component and the regional ocean modeling system (ROMS) as oceanic component. The two-way coupled model system exchanges sea surface temperature (SST) from the ocean to the atmospheric model and surface wind stress and energy fluxes from the atmosphere to the ocean model. The coupled model is run for four years 1997, 1998, 2002 and 2003 and the results are compared with observations and atmosphere-only model runs employing Reynolds SSTs as lower boundary condition. It is found that the coupled model captures the main features of the Indian monsoon and simulates a substantially more realistic spatial and temporal distribution of monsoon rainfall compared to the uncoupled atmosphere-only model. The intraseasonal oscillations are also better simulated in the coupled model compared to the atmosphere-only model. These improvements are due to a better representation of the feedbacks between the SST and convection and highlight the importance of air–sea coupling in the simulation of the Indian monsoon.     

Does the integration of the dynamic nitrogen cycle in a terrestrial biosphere model improve the long-term trend of the leaf area index?

The carbon cycle strongly interacts with the nitrogen cycle. Several observations show that the effects of global change on primary production and carbon storage in plant biomass and soils are partially controlled by N availability. Nevertheless, only a small number of terrestrial biosphere models represent explicitly the nitrogen cycle, despite its importance on the carbon cycle and on climate. These models are difficult to evaluate at large spatiotemporal scales because of the scarcity of data at the global scale over a long time period. In this study, we benchmark the capacity of the O–CN global terrestrial biosphere model to reproduce temporal changes in leaf area index (LAI) at the global scale observed by NOAA_AVHRR satellites over the period 1982–2002. Using a satellite LAI product based on the normalized difference vegetation index of global inventory monitoring and modelling studies dataset, we estimate the long-term trend of LAI and we compare it with the results from the terrestrial biosphere models, either with (O–CN) or without (O–C) a dynamic nitrogen cycle coupled to the carbon–water-energy cycles. In boreal and temperate regions, including a dynamic N cycle (O–CN) improved the fit between observed and modeled temporal changes in LAI. In contrast, in the tropics, simulated LAI from the model without the dynamic N cycle (O–C) better matched observed changes in LAI over time. Despite differential regional trends, the satellite estimate suggests an increase in the global average LAI during 1982–2002 by 0.0020 m² m^?2 y^?1. Both versions of the model substantially overestimated the rate of change in LAI over time (0.0065 m² m^?2 y^?1 for O–C and 0.0057 m² m^?2 y^?1 for O–CN), suggesting that some additional limitation mechanisms are missing in the model. We also estimated the relative importance of climate, CO₂ and N deposition as potential drivers of the temporal changes in LAI. We found that recent climate change better explained temporal changes in LAI when the dynamic N cycle was included in the model (higher ranked fit for O–CN vs. O–C). Using the O–C configuration to estimate the direct effect of climate on LAI, we quantified the importance of climate-N cycle feedbacks in explaining the LAI response. We found that the warming-induced release of N from soil organic matter decomposition explains 17.5 % of the global trend in LAI over time, however, reaching up to 40.9 % explained variance in the boreal zone, which is a more important contribution than increasing anthropogenic nitrogen deposition. Our analysis supports a strong connection between warming, N cycling, and vegetation productivity. These findings underscore the importance of including N cycling in global-scale models of vegetation response to environmental change.     

Impact of initialization procedures on the predictive skill of a coupled ocean–atmosphere model

The sensitivity of the predictive skill of a decadal climate prediction system is investigated with respect to details of the initialization procedure. For this purpose, the coupled ocean–atmosphere UCLA/MITgcm climate model is initialized using the following three different initialization approaches: full state initialization (FSI), anomaly initialization (AI) and FSI employing heat flux and freshwater flux corrections (FC). The ocean initial conditions are provided by the German contribution to Estimating the Circulation and Climate of the Ocean state estimate (GECCO project), from which ensembles of decadal hindcasts are initialized every 5 years from 1961 to 2001. The predictive skill for sea surface temperature (SST), sea surface height (SSH) and the Atlantic meridional overturning circulation (AMOC) is assessed against the GECCO synthesis. In regions with a deep mixed layer the predictive skill for SST anomalies remains significant for up to a decade in the FC experiment. By contrast, FSI shows less persistent skill in the North Atlantic and AI does not show high skill in the extratropical Southern Hemisphere, but appears to be more skillful in the tropics. In the extratropics, the improved skill is related to the ability of the FC initialization method to better represent the mixed layer depth, and the highest skill occurs during wintertime. The correlation skill for the spatially averaged North Atlantic SSH hindcasts remains significant up to a decade only for FC. The North Atlantic MOC initialized hindcasts show high correlation values in the first pentad while correlation remains significant in the following pentad too for FSI and FC. Overall, for the current setup, the FC approach appears to lead to the best results, followed by the FSI and AI procedures.     

Impacts of landscape fragmentation on simulated precipitation fields in the Amazonian sub-basin of Ji-Paraná using the Eta model

Numerical studies on impacts of landscape fragmentation due to land use and land cover change (LUCC) on precipitation fields over the Ji-Paraná basin in the Amazon region are carried out using atmospheric Eta model. Experiments consider historical data about LUCC over the basin from 1978 to 2000 and compare simulations under LUCC conditions with simulations under pristine conditions. In agreement with previous observational studies, model results do not show statistically significant impacts on precipitation in the region. Results indicate that variability in precipitation in this region is mainly controlled by large-scale atmospheric characteristics and soil moisture conditions. However, some limitations are identified in the model simulations, mainly associated to the diurnal cycle of precipitation.     

Assimilation of satellite altimeter data in a primitive-equation model of the Azores–Madeira region

The aim of this study is to implement satellite altimetric assimilation into a high-resolution primitive-equation ocean model and check the validity and sensitivity of the results. Beyond this paper, the remote objective is to get a dynamical tool capable of simulating the surface ocean processes linked to the air–sea interactions as well as to perform mesoscale ocean forecasting. For computational cost and practical reasons, this study takes place in a 1000 by 1000 sq km open domain of the Canary basin. The assimilation experiments are carried out with the combined TOPEX/POSEIDON and ERS-1 data sets between June 1993 and December 1993. The space–time domain overlaps with in situ data collected during the SEMAPHORE experiment and thus enables an objective validation of the results. A special boundary treatment is applied to the model by creating a surrounding recirculating area separated from the interior by a buffer zone. The altimetric assimilation is done by implementing a reduced-order optimal interpolation algorithm with a special vertical projection of the surface model/data misfits. We perform a first experiment with a vertical projection onto an isopycnal EOF representing the Azores Current vertical variability. An objective validation of the model's velocities with Lagrangian float data shows good results (the correlation is 0.715 at 150 dbar). The question of the sensitivity to the vertical projection is addressed by performing similar experiments using a method for lifting/lowering of the water column, and using an EOF in Z-coordinates. Some comparisons with in situ temperature data do not show any significant difference between the three projections, after five months of assimilation. However, in order to preserve the large-scale water characteristics, we felt that the isopycnal projection was a more physically consistent choice. Then, the complementary character of the two satellites is assessed with two additional experiments which use each altimeter data sets separately. There is an evidence of the benefit of combining the two data sets. Otherwise, an experiment assimilating long-wavelength bias-corrected CLS altimetric maps every 10 days exhibits the best correlation scores and emphasizes the importance of reducing the orbit error and biases in the altimetric data sets. The surface layers of the model are forced using realistic daily wind stress values computed from ECMWF analyses. Although we resolve small space and time scales, in our limited domain the wind stress does not significantly influence the quality of the results obtained with the altimetric assimilation. Finally, the relative effects of the data selection procedure and of the integration times (cycle lengths) is explored by performing data window experiments. A value of 10 days seems to be the most satisfactory cycle length.     

SPOM: A regional model of the sub‐polar north Atlantic

Abstract

A regional model of the sub‐polar North Atlantic has been developed for use in process and variability studies of this important high‐latitude area. Open boundary conditions handle connections with the rest of the Atlantic Ocean at 38°N, while buffer zones are used in the northern boundary regions. Extensive testing and experimentation has led to a model which can reproduce major elements of the hydrography and circulation in the region, although limitations exist. A key model feature is the inclusion of a finite volume partial cell topographic representation that significantly improves the structure of the underlying bottom topography. Improvements include a tighter and sharper gyre structure, increased transports, sub‐polar mode water formation sites linked to the topographic slope along the outside of the gyre and a more reasonable representation of Labrador Sea water properties and dispersal pathways. The choice of inflow conditions for the open southern boundary affects the deep western boundary current, as well as the representation of Mediterranean Water, which has a significant effect on Labrador Sea water in the eastern basin.     

Initialisation and predictability of the AMOC over the last 50 years in a climate model

The mechanisms involved in Atlantic meridional overturning circulation (AMOC) decadal variability and predictability over the last 50 years are analysed in the IPSL–CM5A–LR model using historical and initialised simulations. The initialisation procedure only uses nudging towards sea surface temperature anomalies with a physically based restoring coefficient. When compared to two independent AMOC reconstructions, both the historical and nudged ensemble simulations exhibit skill at reproducing AMOC variations from 1977 onwards, and in particular two maxima occurring respectively around 1978 and 1997. We argue that one source of skill is related to the large Mount Agung volcanic eruption starting in 1963, which reset an internal 20-year variability cycle in the North Atlantic in the model. This cycle involves the East Greenland Current intensity, and advection of active tracers along the subpolar gyre, which leads to an AMOC maximum around 15 years after the Mount Agung eruption. The 1997 maximum occurs approximately 20 years after the former one. The nudged simulations better reproduce this second maximum than the historical simulations. This is due to the initialisation of a cooling of the convection sites in the 1980s under the effect of a persistent North Atlantic oscillation (NAO) positive phase, a feature not captured in the historical simulations. Hence we argue that the 20-year cycle excited by the 1963 Mount Agung eruption together with the NAO forcing both contributed to the 1990s AMOC maximum. These results support the existence of a 20-year cycle in the North Atlantic in the observations. Hindcasts following the CMIP5 protocol are launched from a nudged simulation every 5 years for the 1960–2005 period. They exhibit significant correlation skill score as compared to an independent reconstruction of the AMOC from 4-year lead-time average. This encouraging result is accompanied by increased correlation skills in reproducing the observed 2-m air temperature in the bordering regions of the North Atlantic as compared to non-initialized simulations. To a lesser extent, predicted precipitation tends to correlate with the nudged simulation in the tropical Atlantic. We argue that this skill is due to the initialisation and predictability of the AMOC in the present prediction system. The mechanisms evidenced here support the idea of volcanic eruptions as a pacemaker for internal variability of the AMOC. Together with the existence of a 20-year cycle in the North Atlantic they propose a novel and complementary explanation for the AMOC variations over the last 50 years.     

Does increasing the spatial resolution of a regional climate model improve the simulated daily precipitation?

Three different resolution (50, 12, and 1.5 km) regional climate model simulations are compared in terms of their ability to simulate moderate and high daily precipitation events over the southern United Kingdom. The convection-permitting 1.5-km simulation is carried out without convective parametrisation. As in previous studies, increasing resolution (especially from 50 to 12 km) is found to improve the representation of orographic precipitation. The 50-km simulation underestimates mean precipitation over the mountainous region of Wales, and event intensity tends to be too weak; this bias is reduced in both the 12- and 1.5-km simulations for both summer and winter. In south–east England lowlands where summer extremes are mostly convective, increasing resolution does not necessary lead to an improvement in the simulation. For the 12-km simulation, simulated daily extreme events are overly intense. Even though the average intensity of summer daily extremes is improved in the 1.5-km simulation, this simulation has a poorer mean bias with too many events exceeding high thresholds. Spatial density and clustering of summer extremes in south–east England are poorly simulated in both the 12- and 1.5-km simulations. In general, we have not found any clear evidence to show that the 1.5-km simulation is superior to the 12-km simulation, or vice versa at the daily level.     

The economics of decarbonizing the energy system—results and insights from the RECIPE model intercomparison

This paper synthesizes the results from the model intercomparison exercise among regionalized global energy-economy models conducted in the context of the RECIPE project. The economic adjustment effects of long-term climate policy are investigated based on the cross-comparison of the intertemporal optimization models ReMIND-R and WITCH as well as the recursive dynamic computable general equilibrium model IMACLIM-R. A number of robust findings emerge. If the international community takes immediate action to mitigate climate change, the costs of stabilizing atmospheric CO₂ concentrations at 450?ppm (roughly 530?C550?ppm-e) discounted at 3% are estimated to be 1.4% or lower of global consumption over the twenty-first century. Second best settings with either a delay in climate policy or restrictions to the deployment of low-carbon technologies can result in substantial increases of mitigation costs. A delay of global climate policy until 2030 would render the 450?ppm target unachievable. Renewables and CCS are found to be the most critical mitigation technologies, and all models project a rapid switch of investments away from freely emitting energy conversion technologies towards renewables, CCS and nuclear. Concerning end use sectors, the models consistently show an almost full scale decarbonization of the electricity sector by the middle of the twenty-first century, while the decarbonization of non-electric energy demand, in particular in the transport sector remains incomplete in all mitigation scenarios. The results suggest that assumptions about low-carbon alternatives for non-electric energy demand are of key importance for the costs and achievability of very low stabilization scenarios.     

Statistical downscaling of sea-surface wind over the Peru�CChile upwelling region: diagnosing the impact of climate change from the IPSL-CM4 model

The key aspect of the ocean circulation off Peru?CChile is the wind-driven upwelling of deep, cold, nutrient-rich waters that promote a rich marine ecosystem. It has been suggested that global warming may be associated with an intensification of upwelling-favorable winds. However, the lack of high-resolution long-term observations has been a limitation for a quantitative analysis of this process. In this study, we use a statistical downscaling method to assess the regional impact of climate change on the sea-surface wind over the Peru?CChile upwelling region as simulated by the global coupled general circulation model IPSL-CM4. Taking advantage of the high-resolution QuikSCAT wind product and of the NCEP reanalysis data, a statistical model based on multiple linear regressions is built for the daily mean meridional and zonal wind at 10?m for the period 2000?C2008. The large-scale 10?m wind components and sea level pressure are used as regional circulation predictors. The skill of the downscaling method is assessed by comparing with the surface wind derived from the ERS satellite measurements, with in situ wind observations collected by ICOADS and through cross-validation. It is then applied to the outputs of the IPSL-CM4 model over stabilized periods of the pre-industrial, 2?×?CO₂ and 4?×?CO₂ IPCC climate scenarios. The results indicate that surface along-shore winds off central Chile (off central Peru) experience a significant intensification (weakening) during Austral winter (summer) in warmer climates. This is associated with a general decrease in intra-seasonal variability.     

Predictability of the subtropical dipole modes in a coupled ocean–atmosphere model

Predictability of the subtropical dipole modes is assessed using the SINTEX-F coupled model. Despite the known difficulty in predicting subtropical climate due to large internal variability of the atmosphere and weak ocean–atmosphere coupling, it is shown for the first time that the coupled model can successfully predict the South Atlantic Subtropical Dipole (SASD) 1 season ahead, and the prediction skill is better than the persistence in all the 1–12 month lead hindcast experiments. There is a prediction barrier in austral winter due to the seasonal phase locking of the SASD to austral summer. The prediction skill is lower for the Indian Ocean Subtropical Dipole (IOSD) than for the SASD, and only slightly better than the persistence till 6-month lead because of the low predictability of the sea surface temperature anomaly in its southwestern pole. However, for some strong IOSD events in the last three decades, the model can predict them 1 season ahead. The co-occurrence of the negative SASD and IOSD in 1997/1998 austral summer can be predicted from July 1st of 1997. This is because the negative sea level pressure anomalies over the South Atlantic and the southern Indian Ocean in September–October (November–December) that trigger the occurrence of the negative SASD and IOSD are related to the well predicted tropical Indian Ocean Dipole (El Niño/Southern Oscillation). Owing to the overall good performances of the SINTEX-F model in predicting the SASD, some strong IOSD, and El Niño/Southern Oscillation, the prediction skill of the southern African summer precipitation is high in the SINTEX-F model.     

Intraseasonal variability in the far-east pacific: investigation of the role of air�Csea coupling in a regional coupled model

Intraseasonal variability in the eastern Pacific warm pool in summer is studied, using a regional ocean?Catmosphere model, a linear baroclinic model (LBM), and satellite observations. The atmospheric component of the model is forced by lateral boundary conditions from reanalysis data. The aim is to quantify the importance to atmospheric deep convection of local air?Csea coupling. In particular, the effect of sea surface temperature (SST) anomalies on surface heat fluxes is examined. Intraseasonal (20?C90?day) east Pacific warm-pool zonal wind and outgoing longwave radiation (OLR) variability in the regional coupled model are correlated at 0.8 and 0.6 with observations, respectively, significant at the 99% confidence level. The strength of the intraseasonal variability in the coupled model, as measured by the variance of outgoing longwave radiation, is close in magnitude to that observed, but with a maximum located about 10° further west. East Pacific warm pool intraseasonal convection and winds agree in phase with those from observations, suggesting that remote forcing at the boundaries associated with the Madden?CJulian oscillation determines the phase of intraseasonal convection in the east Pacific warm pool. When the ocean model component is replaced by weekly reanalysis SST in an atmosphere-only experiment, there is a slight improvement in the location of the highest OLR variance. Further sensitivity experiments with the regional atmosphere-only model in which intraseasonal SST variability is removed indicate that convective variability has only a weak dependence on the SST variability, but a stronger dependence on the climatological mean SST distribution. A scaling analysis confirms that wind speed anomalies give a much larger contribution to the intraseasonal evaporation signal than SST anomalies, in both model and observations. A LBM is used to show that local feedbacks would serve to amplify intraseasonal convection and the large-scale circulation. Further, Hovm?ller diagrams reveal that whereas a significant dynamic intraseasonal signal enters the model domain from the west, the strong deep convection mostly arises within the domain. Taken together, the regional and linear model results suggest that in this region remote forcing and local convection?Ccirculation feedbacks are both important to the intraseasonal variability, but ocean?Catmosphere coupling has only a small effect. Possible mechanisms of remote forcing are discussed.     

A coupled model on land-atmosphere interactions — Simulating the characteristics of the PBL over a heterogeneous surface

An attempt is made to construct a model, coupling land surface and atmospheric processes in the planetary boundary layer (PBL). A grassland strip in a semi-desert (hereinafter called desert) is presupposed, so as to simulate the case of heterogeneous vegetation cover.Modeling results indicate that every term in the equation of the surface energy balance changes as the air flows over the grassland. The striking contrast of water and energy conditions between the grassland and the desert means that the air over the grassland is cooler and wetter than that over the desert. Consequently, in the heating and dynamic forcing of the air by the underlying surface, heterogeneities arise and are then transferred upward by the turbulent motions. Horizontal differences thus develop in the PBL, resulting in a local circulation. Meanwhile, the horizontal differences affect the free atmosphere through vertical motion at the top of the PBL.List of symbols d ₁,d ₂,d ₃ depths of surface, middle and lower layers of soil - T _c ,T ₁,T ₂,T ₃ temperatures of canopy, surface, middle and lower layers of soil - R _nc net radiation of canopy layer - _c shielding factor of vegetation - Ew, Etc evaporation from wet fraction of foliage and transpiration from dry fraction of foliage - Et ₁,Et ₂ transpiration of foliage water absorbed by the root in the upper and lower soil, respectively - H _c sensible heat of canopy - P _c ,D _c precipitation rate and drainage of canopy - C _s ,C _c ,C _w heat capacity of soil, canopy and water - _w , _s density of water and air near the surface - D hydraulic permeability of soil - _s saturated value of the ratio of volumetric soil moisture - S _g , _g solar radiation and surface reflection - H _g ,R _{L g} turbulent heat flux and long wave radiation of surface - P _g ,E _g precipitation rate and evaporation of soil surface - K _s soil thermal diffusivity - K ^(m),K ^(H),K ^(q) eddy coefficients of momentum, heat and moisture - u, v, w components of wind speed in three directions - air potential temperature - e turbulent kinetic energy - p atmospheric pressure - C _p specific heat of air under constant pressure - R _d gas constant - u _* friction velocity - _* feature temperature - h height of the PBL - f Coriolis parameter - L ₀ Monin-Obukhov length - latent heat of vaporization - q specific humidity - M _c ,M _cm interception water storage of canopy and its maximum - ₀ Exner number of largescale background field - perturbation Exner number - u _g ,v _g components of the geostrophic wind speed Sponsored by the National Natural Science Foundation of China.     

Refining rainfall projections for the Murray Darling Basin of south-east Australia—the effect of sampling model results based on performance

One of the aims of developing new climate projections is to better address the requirements of stakeholders—particularly those who require less uncertainty and/or probabilistic information to work with. Projections are continually updated over time as more, and newer, climate model simulations of the future become available but this can introduce problems when it comes to interpreting large samples with differing results. Regional projections of rainfall are characterised by a high level of uncertainty, partly because of different sensitivities of the different models. Some models can be demonstrated to perform relatively poorly when assessed by their ability to simulate present-day means and variability and here we show that the uncertainty in model projections can potentially be reduced when the projection from these models are either discounted or ignored entirely. When applied to the Murray Darling Basin of south east Australia, it is possible to demonstrate a clustering of the results from the better performing models. These indicate that the rainfall changes to be expected as a result of increased greenhouse gas concentrations into the future are more likely to be at the drier end of the full set of model results. This occurs because the better performing models indicate decreases in winter and spring which are significantly different to the changes indicated by the other models. These results suggest that there are compelling reasons for discounting, if not entirely dismissing, some model results based on their failure to satisfy some basic performance criteria.     

Comment on “Study on the reliable computation time of the numerical model using the sliding temporal correlation method”

The paper, “Study on the reliable computation time of the numerical model using the sliding temporal correlation method,” was published in Theoretical and Applied Climatology. In that work, the sliding temporal correlation analysis is employed to investigate the predictable time of two typical chaotic numerical models, namely the Lorenz system and the Chen chaotic system. However, it has been recently shown by us when using a linear scaling in time and state variables that generically, the Chen system is only a particular case of the Lorenz system, with time reversion if the parameter c is positive. Consequently, to study the Chen chaotic system is simply to consider the Lorenz system integrated backwards.     

Surface‐absorbed and top‐of‐atmosphere radiation fluxes for the Mackenzie River basin from satellite observations and a regional climate model and an evaluation of the model

Abstract

Both the earth‐reflected shortwave and outgoing longwave radiation (OLR) fluxes at the top of the atmosphere (TOA) as well as surface‐absorbed solar fluxes from Canadian Regional Climate Model (CRCM) simulations of the Mackenzie River Basin for the period March 2000 to September 2003 are compared with the radiation fluxes deduced from satellite observations. The differences between the model and satellite solar fluxes at the TOA and at the surface, which are used in this paper to evaluate the CRCM performance, have opposite biases under clear skies and overcast conditions, suggesting that the surface albedo is underestimated while cloud albedo is overestimated. The slightly larger differences between the model and satellite fluxes at the surface compared to those at the TOA indicate the existence of a small positive atmospheric absorption bias in the model. The persistent overestimation of TOA reflected solar fluxes and underestimation of the surface‐absorbed solar fluxes by the CRCM under all sky conditions are consistent with the overestimation of cloud fraction by the CRCM. This results in a larger shortwave cloud radiative forcing (CRF) both at the TOA and at the surface in the CRCM simulation. The OLR from the CRCM agrees well with the satellite observations except for persistent negative biases during the winter months under all sky conditions. Under clear skies, the OLR is slightly underestimated by the CRCM during the winter months and overestimated in the other months. Under overcast conditions the OLR is underestimated by the CRCM, suggesting an underestimation of cloud‐top temperature by the CRCM. There is an improvement in differences between model and satellite fluxes compared to previously reported results largely because of changes to the treatment of the surface in the model.