Regional Atmospheric Modeling Research Articles

Wind-wave forecasting in enclosed basins using statistically downscaled global wind forcing

Accurate wind-wave forecasting in enclosed and semi-enclosed basins is a challenging task, demanding primarily for high-resolution wind forcing at regional scale. This is generally obtained with dynamical downscaling from a low-to-mid resolution atmospheric model. In this context, a new wave forecasting system for the marginal Adriatic Sea is herein presented aimed at proposing an alternative strategy for accurate wind-wave forecasting in (semi-) enclosed basins that does not require an ad-hoc regional atmospheric model. The system is based on the state-of-the-art WAVEWATCH III® spectral wave model forced by the global IFS-ECMWF forecast. At first, wind speed is quantile-corrected to account for the systematic underestimation over the Adriatic Sea. Then, the significant wave height in the target region and for regimes associated with marine storms is calibrated following standard procedure. Wind and wave observations from different sources are used for calibration and validation of the wave forecasts, which achieve satisfactory scores. We also compare results with those of other forecasting systems in the area, highlighting the importance of the wind forcing accuracy and the wave model calibration. Doing so, we discuss the challenges that characterise (semi-) enclosed environments in order to propose effective solutions for them and future developments.

A Daily 1‐km Resolution Greenland Rainfall Climatology (1958–2020) From Statistical Downscaling of a Regional Atmospheric Climate Model

AbstractA daily, gridded 1‐km rainfall climatology (1958–2020) for Greenland is presented, including the Greenland ice sheet (GrIS), the peripheral glaciers and ice caps (GIC), and ice‐free tundra. It is obtained by statistically downscaling the 5.5 km output of the regional atmospheric climate model version 2 to a resolution of 1 km, using the elevation dependence of snowfall fraction. Based on this new product, the average total annual rainfall in Greenland during 1958–2020 is estimated to be 111.4 ± 11.2 Gt/year, of which 28.6 ± 6.1 Gt/year falls on the GrIS, 11.4 ± 1.4 Gt/year on the GIC, and 71.4 ± 9.0 Gt/year on the tundra. The downscaled 1 km product better resolves especially the relatively small GIC, more than doubling (+124%) their rainfall compared to the 5.5 km product. The relatively warm southern regions of Greenland have the highest rainfall amounts, with annual values locally exceeding 1,000 mm. We confirm a significant positive trend in Greenland rainfall (>40 mm/decade), notably in the northwest and mainly due to an increase in rainfall fraction (>3.5%/decade) during July and August. For the whole of Greenland, during 1991–2020 the seasonal rainfall peak has shifted from July to August, with significant increases in September, which receives more rain than June. An analysis of rainfall fraction and near‐surface temperature shows that local warming rates are a good predictor of recent rainfall changes.

Fully Dynamic High–Resolution Model for Dispersion of Icelandic Airborne Mineral Dust

Icelandic topsoil sediments, as confirmed by numerous scientific studies, represent the largest and the most important European source of mineral dust. Strong winds, connected with the intensive cyclonic circulation in the North Atlantic, induce intense emissions of mineral dust from local sources all year and carry away these fine aerosol particles for thousands of kilometers. Various impacts of airborne mineral dust particles on local air quality, human health, transportation, climate and marine ecosystems motivated us to design a fully dynamic coupled atmosphere–dust numerical modelling system in order to simulate, predict and quantify the Icelandic mineral dust process including: local measurements and source specification over Iceland. In this study, we used the Dust Regional Atmospheric Model (DREAM) with improved Icelandic high resolution dust source specification and implemented spatially variable particle size distribution, variable snow cover and soil wetness. Three case studies of intense short- and long-range transport were selected to evaluate the model performance. Results demonstrated the model’s capability to forecast major transport features, such as timing, and horizontal and vertical distribution of the processes. This modelling system can be used as an operational forecasting system, but also as a reliable tool for assessing climate and environmental Icelandic dust impacts.

Urban ventilation assessment with improved vertical wind profile in high-density cities – Comparisons between LiDAR and conventional methods

The vertical wind speed profile is crucial to urban ventilation assessment and urban planning/design. This study uses Light Detection and Ranging (LiDAR) observation as benchmark to evaluate accuracy of wind profiles estimated by conventional methods. The conventional methods include Boundary Layer Wind Tunnel (BLWT), Regional Atmospheric Modeling System (RAMS), Power Law (PL), and Weather Research and Forecasting (WRF). The evaluation involves two typical urban sites with different densities under summer weak-wind conditions. Large Eddie Simulations (LES) are conducted to further investigate the sensitivity of urban ventilation assessment results to the deviations of wind profiles. The results indicate significant deviations in LES caused by conventional methods. The largest deviations of wind velocity ratio are found in mesoscale meteorological models (RAMS and WRF (>65%)). Deviations caused by physical and empirical models are smaller but still significant (BLWT (>25%) and PL (>40%)). Consequently, large deviations (>100%) of wind-relevant criterion for outdoor thermal comfort are observed. Finally, to balance accuracy and data availability, we recommend power law method as the optimal method to provide inflow boundary condition for numerical simulations when LiDAR observation is not available. We provide new and valuable understandings to improve urban ventilation assessment in high-density cities.

Precipitation extremes over the tropical Americas under RCP4.5 and RCP8.5 climate change scenarios: Results from dynamical downscaling simulations

AbstractThe Regional Atmospheric Modelling System (RAMS) driven by data from the CMIP5 Earth System Model HadGEM2‐ES was used to simulate daily precipitation over the tropical Americas for both current and future climate, including distinct scenarios (representative concentration pathways 4.5 and 8.5) and different time horizons (short‐term, mid‐term and long‐term changes). The major objective was to evaluate possible future changes in extreme events, with emphasis on the intensity of precipitation events and the duration of wet and dry spells. According to RAMS, longer dry spells are expected over most regions of the tropical Americas in the future, with indications for Northeast Brazil, Caribbean, Northern Amazon, and shorter wet spells over Central America and Amazon. With the exception of the Caribbean, there is a general tendency towards the increased frequency of intense precipitation in the tropical Americas.

Evaluation of regional climate models and future wave characteristics in an enclosed sea: A case study of the Black Sea

The main objective of this study is to evaluate a possible climate change impact on wave climate in an enclosed sea (Black Sea) until the end of the 21st century. To achieve the goal, the wave data are generated from a third-generation wave model forced with the widely used reanalysis data (Climate Forecast System Reanalysis), and the hindcast wind fields simulated by a Regional Climate Model, namely Rossby Centre regional atmospheric model (version RCA4). The pattern of change in the wave climate is discussed by comparing the historical (1970–2005) with the future for periods 2021–2060 and 2061–2100 under two climate scenarios. The projected changes in the mean wave characteristics are characterized by an increase in the near future for both RCP scenarios that is more prominent under RCP8.5 scenario in the eastern basin. The middle future under RCP8.5 scenario suggests more significant changes in annual mean values than those obtained under RCP4.5 scenario. In the context of climate change, the possible effects are more prominent on extreme wave heights. For example, the increases in the wave heights for the 100-year return period reach the value of 5% and 25% in the western and eastern Black Sea, respectively.

High-Resolution Ammonia Emissions from Nitrogen Fertilizer Application in China during 2005–2020

The accurate estimation of ammonia emission is essential for quantifying secondary inorganic aerosol formation and reactive nitrogen deposition. During the last decades, both fertilizer type and the total amount of nitrogen fertilizer in China have changed, while the resulting changes in ammonia emissions and their spatio-temporal variations are unclear. In this study, we compile a long-term (2005–2020) high-resolution ammonia emission inventory for synthetic fertilizer in China with bottom-up method. We parameterized emissions factors (EFs) considering the impacts of soil properties, method of fertilizer application, fertilizer type, crop type, ambient temperature and wind speed. Meanwhile, the monthly nitrogen fertilizer application is calculated by detailed information on crop-specific fertilizer application practices. For the spatial distribution, the ammonia emissions from fertilizer mostly concentrate in eastern and southwestern China, coincident with the high density of agriculture activity and population in these regions. For the seasonal variation, the ammonia emissions from fertilizer application peak in spring and summer because of dense fertilizer application and high ambient temperature. For the long-term trend, we estimate that the emissions from synthetic fertilizer increased from 5.38 Tg in 2005 to 5.53 Tg in 2008 and remained nearly unchanged during 2008–2012, then decreased to 3.96 Tg in 2020. Urea, ammonium bicarbonate (ABC) and nitrogenous compound fertilizer are major fertilizer types used in China. Despite the increased use of nitrogen fertilizer, ammonia emissions remained stable throughout 2008–2012 with the declined use of ABC. This stable period also reflects ammonia emission increases in western China, offsetting the decreases in eastern China. Furthermore, our emission inventory provides a monthly estimation at a spatial resolution of 0.1 degrees, which can be applied to global and regional atmospheric chemistry model simulations.

Assessing the contribution of dynamical downscaling to austral autumn Northeast Brazil seasonal precipitation prediction performance

This study aims to assess the contribution to prediction performance of dynamically downscaling seasonal precipitation for the Brazilian Northeast region (NEB) produced in February with a global climate model for the austral autumn (March-April-May). This season includes the peak precipitation period of a large portion of this region. To achieve this aim, 32 years of hindcasts for the period 1979–2010 were produced with a regional model known as the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) run at 30 km spatial resolution, which was unidirectional nested to a global model run at approximately 200 km spatial resolution. The used global model was the Atmospheric General Circulation Models of the Brazilian Center for Weather Forecast and Climate Studies (CPTEC/AGCM), which provided initial and lateral boundary conditions for BRAMS. Hindcast ensembles of 10 members were produced with both the global and the regional models, simulating an operational prediction environment using persisted sea surface temperature (SST) anomalies observed in the previous January of each of the 32 hindcast years as oceanic boundary conditions. A comparative deterministic and probabilistic performance assessment of the two models was conducted. The deterministic assessment included the investigation of the mean error (bias) of the produced seasonal precipitation hindcasts, the degree of linear association between the observed and predicted precipitation anomalies measuring phase error through the correlation of the ensemble means with the corresponding observations, and amplitude error investigated through the ratio between the hindcast ensemble mean and observed variances. The probabilistic assessment was performed investigation the reliability, resolution, and discrimination characteristics of tercile probability predictions for the above normal and below normal categories, and also for probabilistic predictions for the occurrence of the symmetric event positive (or negative) precipitation anomaly. The two investigated modeling approaches showed similar performance, with an indication for dynamically downscaled predictions to have reduced amplitude error and slightly improved reliability and resolution compared to the predictions produced with the global model.

Development of Forecast System for the Upwelled Coastal Cold Waters in the Eastern Coast of Korea

In this study, a forecast system for the occurrence of cold waters in the eastern coast of Korea was developed by combining the ROMS ocean model and the WRF regional atmospheric model. The 1-day hindcast and 3.5-day forecasts from April 1 to August 31, 2021, successfully reproduced and forecasted the temporal and spatial changes of coastal cold waters. Three case studies with different surface boundary conditions in the ROMS model confirmed that the wind is a primary driver for the occurrence of cold waters in the region. The performance of the ROMS was improved by high-resolution WRF outputs, and through error correction using the water temperature data from the real-time stations, the average RMSE of 9 stations for Forecast Day-3 was 0.73℃, indicating a prossibility of high-precision forecast.

Developing a new wind dataset by blending satellite data and WRF model wind predictions

This paper presents an approach to improve wind datasets developed using the regional atmospheric model Weather Research Forecasting by combining its predictions with remotely sensed wind observations in enhanced wind speed analyses that leads to blended winds. In this study, satellite data derived from scatterometers, radiometers, and synthetic aperture radar are used. The spatial and temporal features of each wind product are thoroughly analysed. For the probabilistic evaluation of their skill, comprehensive comparisons with available buoy data are carried out. The statistical analysis shows that the combined use of satellite and numerical weather prediction model data improves the agreement with buoy measurements, demonstrating the added value of using the blended product. As an application of the method, new improved satellite wind speeds are presented in the form of a wind energy assessment along the Iberian coastal area. From inspection of the provided wind power maps, northern and central regions emerge as the most promising areas for wind harnessing offshore despite some seasonal variations. Finally, potential wind farm sites are provided, along with insights into multi-year wind speed distribution. The results show how the new dataset can be used for the selection of promising areas for wind exploitation.

Simulation of an orographic gravity wave above the Amazon rainforest and its influence on gases transport near the surface

The influence of the topography at the ATTO site (Amazon Tall Tower Observatory) in the formation of Gravity Waves (GW) was investigated in this work. The role of these waves in gas transport on different heights in the nocturnal boundary layer, was also investigated. For this, were analyzed: experimental data of wind speed, temperature, humidity and CO2 to identify the GW. Furthermore satellite images, ECMWF ERA5 (European Center for Medium-Range Weather Forecasts) reanalysis, and numerical simulations from the mesoscale JULES-CCATT-BRAMS model (Brazilian Regional Atmospheric Modeling System) version 5.3 were used to perform GW simulations. The simulations involved two configurations (Control-With Topography and No Topography). The sattelite images made it clear that the GW was not associated with convective activities. The simulations showed clear ondulatory signs in air temperature, vertical component of the wind, and gases like CO and O3. Moreover, they also reveal that the wave originated by the presence of the local topography and this orograph gravity wave had and important role in the transport of gases above the ATTO site.

Mars Exploration Using Sailplanes

We present the preliminary design of sailplanes, used for Mars exploration. The sailplanes mitigate the weight and energy storage limitations traditionally associated with powered flight by instead exploiting atmospheric wind gradients for dynamic soaring, and slope/thermal updrafts for static soaring. Equations of motion for the sailplanes were combined with wind profiles from the Mars Regional Atmospheric Modeling System (MRAMS) for two representative sites: Jezero crater, Perseverance’s landing site, and over a section of the Valles Marineris canyon. Optimal flight trajectories were obtained from the constrained optimization problem, using the lift coefficient and the roll angle as control parameters. Numerical results for complete dynamic soaring cycles demonstrated that the total sailplane energy at the end of a soaring cycle increases by 6.8–11%. The absence of a propulsion system, allowing for a compact form factor, means the sailplanes can be packaged into CubeSats and deployed as secondary payloads at a relatively low cost; providing scientific data over locations inaccessible by current landers and rovers. Various sailplane deployment methods are considered, including rapid deployment during Entry, Descent, and Landing (EDL) of a Mars Science Laboratory-class (MSL) vehicle and slow deployment using a blimp.

Surface Wind Responses to Mesoscale Sea Surface Temperature over Western Boundary Current Regions Assessed by Spectral Transfer Functions

Abstract Satellite observations have revealed that mesoscale sea surface temperature (SST) perturbations can exert distinct influence on sea surface wind by modifying the overlying atmospheric boundary layer. Recently, spectral transfer functions have been shown to be useful to elucidate the wind response features. Spectral transfer functions can represent spatially lagged responses, their horizontal scale dependence, and background wind speed dependence. By adopting the transfer function analysis, the present study explores seasonality and regional differences in the wind response over the major western boundary current regions. Transfer functions estimated from satellite observations are found to be largely consistent among seasons and regions, suggesting that the underlying dominant dynamics are ubiquitous. Nevertheless, the wind response exhibits statistically significant seasonal and regional differences depending on background wind speed. When background wind is stronger (weaker) than 8.5 m s−1, the wind response is stronger (weaker) in winter than in summer. The Agulhas Retroflection region exhibits stronger wind response typically by 30% than the Gulf Stream and Kuroshio Extension regions. Although observed wind distributions are reasonably reconstructed from the transfer functions and observed SST, surface wind convergence zones along the Gulf Stream and Kuroshio Extension are underrepresented. The state-of-the-art atmospheric reanalysis and regional model represent well the structure of the transfer functions in the wavenumber space. The amplitude is, however, underestimated by typically 30%. The transfer function analysis can be adapted to many other atmospheric responses besides sea surface wind, and thus provide new insights into the climatic role of the mesoscale air–sea coupling.

Assessment on the Water Vapor Flux from Atmospheric Reanalysis Data in the South China Sea on 2019 Summer

Abstract This paper assesses the water vapor flux performance of three reanalysis datasets (ERA5, JRA55, NCEP-2) on the South China Sea. The radiosonde data were from the South China Sea Scientific Expedition organized by Sun Yat-sen University in the 2019 summer (SCSEX2019). The comparison shows that all reanalyses underestimate the temperature and specific humidity under 500 hPa. As for the wind profile, the most significant difference appeared at 1800 UTC when there was no conventional radiosonde observation around the experiment area. As for the water vapor flux, ERA5 seems to give the best zonal flux but the worst meridional one. A deeper analysis shows that the bias in the wind mainly caused the difference in water vapor flux from ERA5. As for JRA55 and NCEP-2, the humidity and wind field bias coincidentally canceled each other, inducing a much smaller bias, especially in meridional water vapor flux. Therefore, to get a more realistic water vapor flux, a correction in the wind profile was most needed for ERA5. In contrast, the simultaneous improvement on both wind and humidity fields might produce a better water vapor flux for JRA55 and NCEP-2. Significance Statement This paper mainly aims to assess three atmospheric reanalyses from the viewpoint of the water vapor flux over the South China Sea during the monsoon period. The observation data contain more than 120 radiosonde profiles. Our work has given an objective comparison among the reanalyses and observations. We also tried to explain the bias in the water vapor flux over the ocean from the reanalyses. The results of our work might help understand the monsoon precipitation given by atmospheric reanalyses or regional climate models and enlighten the development of atmospheric assimilation products.

Development of the Real‐Time 30‐s‐Update Big Data Assimilation System for Convective Rainfall Prediction With a Phased Array Weather Radar: Description and Preliminary Evaluation

AbstractWe present the first ever real‐time numerical weather prediction system with 30‐s update cycles at a 500‐m grid spacing for the prediction of convective precipitation in the subsequent 30 min using a new‐generation multi‐parameter phased array weather radar. The system comprises a regional atmospheric model known as the SCALE and the local ensemble transform Kalman filter (LETKF). To accelerate the SCALE‐LETKF system, data transfer between the two aforementioned components is performed using a memory copy instead of a file I/O. A complete real‐time workflow including domain nesting and observational data transfer is constructed. A real‐time test in July and August 2020 showed that the system is fast enough for a real‐time application of 30‐s forecast‐analysis cycles and 30‐min prediction. The development includes a new thinning method considering the spatially correlated observation errors in the dense radar data. This new thinning method is effective in two past case studies in the summer of 2019.

Influence of the recent winter Arctic sea ice loss in short-term simulations of a regional atmospheric model

Notable changes in the wintertime Arctic atmospheric circulation have occurred over the last few decades. Despite its importance in understanding the recent changes in the Northern Hemisphere midlatitude climate, it remains unclear whether and how these changes are affected by recent Arctic sea ice loss. In this study, a regional scale model is used to separate the direct sea ice influence from the natural variability of large-scale atmospheric circulation. Results show that, in response to sea ice loss, the increase of geopotential height in the mid-to-upper troposphere is robust across the simulations, but the magnitude of the response is highly dependent on the background state of the atmosphere. In most cases the sea ice loss-induced atmospheric warming is trapped near the surface due to the high vertical stability of winter Arctic lower troposphere, accordingly, resulting in a small response of geopotential height. However, when a low-pressure system is located over the Barents Sea, the relatively weak stability allows an upward transport of the surface warming, causing a significantly larger geopotential height increase. This strong state-dependence of atmospheric response which is also found in recent studies using global-scale model experiments, highlights the importance of accurately representing the atmospheric background state for numerical model assessments of sea ice influence.

Importance of ocean prediction for heavy rainfall prediction over Japan in July 2020

AbstractHindcast experiments were performed for heavy rainfall events over Japan in July 2020 using a regional atmospheric model and a regional coupled model to examine the importance of ocean prediction for predicting heavy rainfall events. Both models were able to predict the first peak of accumulated rainfall over western Japan occurring in the first half of July. However, only the coupled model predicted the second peak that occurred in the second half of July. Sea level pressure (SLP) and low‐level moisture inflow originating from an existing atmospheric river (AR) were found to differ in each model. In the regional atmospheric model, the error associated with the inaccurate low‐level moisture inflow grew with rising excessive latent heat flux, which enhanced convection and resulted in incorrect SLP patterns. This trend seems to be enhanced by having a prescribed sea surface temperature (SST), which affects the surface heat flux. When ocean conditions are predicted as in the coupled model, such error growth is suppressed by changes in SST that adjust surface heat flux, and it leads to generation of the correct SLP patterns. With correct SLP especially for Pacific high in this case, favorable conditions for inflow from the AR can also be predicted, thus making it possible to predict the heavy rainfall. In conclusion, considering the atmospheric feedback on SST, ocean prediction can improve the predictability of heavy rainfall over Japan, the conditions for which are influenced by the nearby AR. Ocean prediction may therefore extend the range of weather forecasting.

Modeling the Convective Boundary Layer in the Terra Incognita: Evaluation of Different Strategies with Real-Case Simulations

Abstract Modeling atmospheric turbulence in the convective boundary layer is challenging at kilometer and subkilometer resolutions, as the horizontal grid spacing approaches the size of the most energetic turbulent eddies. In this range of resolutions, termed terra incognita or gray zone, partially resolved convective structures are grid dependent and neither traditional 1D mesoscale parameterizations nor 3D large-eddy simulations closures are theoretically appropriate. Leveraging on a new set of one-way nested, full-physics multiscale numerical experiments, we quantify the magnitude of the errors introduced at gray zone resolutions in a real-case application and we provide new perspectives on recently proposed modeling approaches. The new set of experiments is forced by real-time-varying boundary conditions, spans a wide range of scales, and includes traditional 1D schemes, 3D closures, scale-aware parameterizations, and strategies to suppress resolved convection at gray zone resolutions. The study area is Riyadh (Saudi Arabia), where deep CBLs develop owing to strong convective conditions. Detailed analyses of our experiments, including validation with radiosonde data, calculations of spectral features, and partitioning of turbulent fluxes between resolved and subgrid scales, show that (i) grid-dependent convective structures entail minor impacts on the first-order characteristics of the fully developed boundary layer due to some degree of implicit scale awareness of 1D parameterizations and (ii) 3D closures and scale-aware schemes outperform traditional 1D schemes especially in the surface layer, among other findings. The new suite of experiments provides a benchmark of real simulations that can be extended to assess how new turbulence closures perform at gray zone resolutions. Significance Statement As recent advances in high-performance computing are leading to a new era in numerical simulations, regional atmospheric models can now increase their resolution to the widely unexplored kilometer and subkilometer range. While increasing the resolution of atmospheric models is desirable to (i) have more realistic weather and air quality predictions and (ii) better represent boundary conditions for microscale models, kilometer and subkilometer grid spacings pose some theoretical challenges that need to be addressed by the atmospheric modeling community. In this work we run a set of numerical experiments for a real case study that aim to offer new perspectives on recently developed modeling strategies and identify the most promising directions that should be investigated by follow-up studies.

Efficient Atmospheric Transport of Microplastics over Asia and Adjacent Oceans.

We developed a regional atmospheric transport model for microplastics (MPs, 10 μm to 5 mm in size) over Asia and the adjacent Pacific and Indian oceans, accounting for MPs’ size- and shape-dependent aerodynamics. The model was driven by tuned atmospheric emissions of MPs from the land and the ocean, and the simulations were evaluated against coastal (n = 19) and marine (n = 56) observations. Our tuned atmospheric emissions of MPs from Asia and the adjacent oceans were 310 Gg y–1 (1 Gg = 1 kton) and 60 Gg y–1, respectively. MP lines and fragments may be transported in the atmosphere >1000 km; MP pellets in our model mostly deposited near-source. We estimated that 1.4% of the MP mass emitted into the Asian atmosphere deposited into the oceans via atmospheric transport; the rest deposited over land. The resulting net atmospheric transported MP flux from Asia into the oceans was 3.9 Gg y–1, twice as large as a previous estimate for the riverine-transported MP flux from Asia into the oceans. The uncertainty of our simulated atmospheric MP budget was between factors of 3 and 7. Our work highlighted the impacts of the size and morphology on the aerodynamics of MPs and the importance of atmospheric transport in the source-to-sink relationship of global MP pollution.

Land–atmosphere interactions in sub-polar and alpine climates in the CORDEX Flagship Pilot Study Land Use and Climate Across Scales (LUCAS) models – Part 2: The role of changing vegetation

Abstract. Land cover in sub-polar and alpine regions of northern and eastern Europe have already begun changing due to natural and anthropogenic changes such as afforestation. This will impact the regional climate and hydrology upon which societies in these regions are highly reliant. This study aims to identify the impacts of afforestation/reforestation (hereafter afforestation) on snow and the snow-albedo effect and highlight potential improvements for future model development. The study uses an ensemble of nine regional climate models for two different idealised experiments covering a 30-year period; one experiment replaces most land cover in Europe with forest, while the other experiment replaces all forested areas with grass. The ensemble consists of nine regional climate models composed of different combinations of five regional atmospheric models and six land surface models. Results show that afforestation reduces the snow-albedo sensitivity index and enhances snowmelt. While the direction of change is robustly modelled, there is still uncertainty in the magnitude of change. The greatest differences between models emerge in the snowmelt season. One regional climate model uses different land surface models which shows consistent changes between the three simulations during the accumulation period but differs in the snowmelt season. Together these results point to the need for further model development in representing both grass–snow and forest–snow interactions during the snowmelt season. Pathways to accomplishing this include (1) a more sophisticated representation of forest structure, (2) kilometre-scale simulations, and (3) more observational studies on vegetation–snow interactions in northern Europe.