Nonhydrostatic Atmospheric Model Research Articles

Role of rotational and divergence effects induced by wind turbines wakes on near-ground air warming

Various studies, involving numerical simulations, satellite measurements, and field measurement campaigns, have demonstrated that wind turbine wakes can lead to changes in near-ground air temperature. To investigate these phenomena an Actuator Disk with Rotation (ADR) is implemented within the LES non-hydrostatic atmospheric model Meso-NH and validated using the NewMEXICO wind tunnel measurements and the VERTEX field measurement campaign. The NewMEXICO case allows the aerodynamic validation of the approach, especially the effect of the wake on wind speed components. On the VERTEX case, meteorological effects of wind turbines are studied under various atmospheric stability conditions through the application of homogeneous sensible heat fluxes at the ground level. Results show wake-related warming and cooling near the ground for stable and unstable conditions respectively, and no significant change for neutral conditions. These results show a good tendency agreement with the VERTEX campaign’s measurements. The comparison between an Actuator Disk with No Rotation (ADNR) and an ADR simulation show the dual contribution of the rotation of the wake and the growth of the stream tube on the temperature change in the wake but also on the near-ground air temperature.

Sea-ice thermodynamics can determine waterbelt scenarios for Snowball Earth

Abstract. Snowball Earth refers to multiple periods in the Neoproterozoic during which geological evidence indicates that the Earth was largely covered in ice. A Snowball Earth results from a runaway ice–albedo feedback, but there is an ongoing debate about how the feedback stopped: with fully ice-covered oceans or with a narrow strip of open water around the Equator. The latter states are called waterbelt states and are an attractive explanation for Snowball Earth events because they provide a refugium for the survival of photosynthetic aquatic life, while still explaining Neoproterozoic geology. Waterbelt states can be stabilized by bare sea ice in the subtropical desert regions, which lowers the surface albedo and stops the runaway ice–albedo feedback. However, the choice of sea-ice model in climate simulations significantly impacts snow cover on ice and, consequently, surface albedo. Here, we investigate the robustness of waterbelt states with respect to the thermodynamical representation of sea ice. We compare two thermodynamical sea-ice models, an idealized zero-layer Semtner model, in which sea ice is always in equilibrium with the atmosphere and ocean, and a three-layer Winton model that is more sophisticated and takes into account the heat capacity of ice. We deploy the global icosahedral non-hydrostatic atmospheric (ICON-A) model in an idealized aquaplanet setup and calculate a comprehensive set of simulations to determine the extent of the waterbelt hysteresis. We find that the thermodynamic representation of sea ice strongly influences snow cover on sea ice over the range of all simulated climate states. Including heat capacity by using the three-layer Winton model increases snow cover and enhances the ice–albedo feedback. The waterbelt hysteresis found for the zero-layer model disappears in the three-layer model, and no stable waterbelt states are found. This questions the relevance of a subtropical bare sea-ice region for waterbelt states and might help explain drastically varying model results on waterbelt states in the literature.

How do different pathways connect the stratospheric polar vortex to its tropospheric precursors?

Abstract. Processes involving troposphere–stratosphere coupling have been identified as important contributors to an improved subseasonal to seasonal prediction in the mid-latitudes. However, atmosphere models still struggle to accurately predict stratospheric extreme events. Based on a novel approach in this study, we use ERA5 reanalysis data and ensemble simulations with the ICOsahedral Non-hydrostatic atmospheric model (ICON) to investigate tropospheric precursor patterns, localised troposphere–stratosphere coupling mechanisms, and the involved timescales of these processes in the Northern Hemisphere extended winter. We identify two precursor regions: mean sea level pressure in the Ural region is negatively correlated with the strength of the stratospheric polar vortex for the following 5–55 d with a maximum at 25–45 d, and the pressure in the extended Aleutian region is positively correlated with the strength of the stratospheric polar vortex the following 10–50 d with a maximum at 20–30 d. A simple precursor index based on the mean pressure difference of these two regions is very strongly linked to the strength of the stratospheric polar vortex in the following month. The pathways connecting these two regions to the strength of the stratospheric polar vortex, however, differ from one another. Whereas a vortex weakening can be connected to prior increased vertical planetary wave forcing due to high-pressure anomalies in the Ural region, the pathway for the extended Aleutian region is less straightforward. A low-pressure anomaly in this region can trigger a Pacific–North American-related (PNA-related) pattern, leading to geopotential anomalies of the opposite sign in the mid-troposphere over central North America. This positive geopotential anomaly travels upward and westward in time, directly penetrating into the stratosphere and thereby strengthening the stratospheric Aleutian High, a pattern linked to the displacement towards Eurasia and subsequent weakening of the stratospheric polar vortex. Overall, this study emphasises the importance of the time-resolved and zonally resolved picture for an in-depth understanding of troposphere–stratosphere coupling mechanisms. Additionally, it demonstrates that these coupling mechanisms are realistically reproduced by the global atmosphere model ICON.

Large Ensemble Simulation for Investigating Predictability of Precursor Vortices of Typhoon Faxai in 2019 With a 14‐km Mesh Global Nonhydrostatic Atmospheric Model

AbstractTyphoon Faxai hit Japan in 2019 and severely damaged the Tokyo metropolitan area. To mitigate such damages, a good track forecast is necessary even before the typhoon formation. To investigate the predictability of the genesis and movement of a precursor vortex and its relationship with the synoptic‐scale flow, 100‐member ensemble simulations of Typhoon Faxai were performed using a 14‐km mesh global nonhydrostatic atmospheric model, which started from 16 different initial days (i.e., 1,600 members in total). The results show that the model could predict an enhanced risk of a Faxai‐like vortex heading toward Japan 2 weeks before landfall, which was up to 70%. The reason for the enhancement was a rapid increase in the members reproducing a precursor vortex from 15 to 12 days before landfall in Japan. In addition, the upper‐tropospheric vortex played an essential role in the track simulation of Faxai.

Response of convective systems to the orbital forcing of the last interglacial in a global nonhydrostatic atmospheric model with and without a convective parameterization

Nonhydrostatic Icosahedral Atmospheric Model (NICAM) coupled with a slab ocean model was applied to a paleoclimate research for the first time. The model was run at a horizontal resolution of 56 km with and without a convective parameterization, given the orbital parameters of the last interglacial (127,000 years before present). The simulated climatological mean-states are qualitatively similar to those in previous studies reinforcing their robustness, however, the resolution of this model enables to represent the narrow precipitation band along the southern edge of the Tibetan Plateau. A particular focus was given to convectively coupled disturbances in our analysis. The simulated results show a greater signal of the Madden–Julian Oscillation and weakening of the moist Kelvin waves. Although the model's representation of the boreal summer intraseasonal oscillation in the present-day simulations is not satisfactory, a significant enhancement of its signal is found in the counterpart of the last interglacial. The density of the tropical cyclones decreases over the western north Pacific, north Atlantic and increases over the south Indian Ocean and south Atlantic. The model's performance is generally better when the convective parameterization is used, but the tropical cyclones are better represented without the convective parameterization. Additional simulations using the low-resolution topography reveals that the better representation of the Tibetan Plateau enhances the boreal summer Asian monsoon and its impact is similar and comparable to that of the orbital parameters over the south Asia and the Indian Ocean.

Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation

Diverse and severe weather conditions and rapid climate change rates in the Arctic emphasize the need for high-resolution climatic and environmental data that cannot be obtained from the scarce observational networks. This study presents a new detailed hydrometeorological dataset for the Russian Arctic region, obtained as a long-term hindcast with the nonhydrostatic atmospheric model COSMO-CLM for the 1980–2016 period. The modeling workflow, evaluation techniques, and preliminary analysis of the obtained dataset are discussed. The model domain included the Barents, Kara, and Laptev Seas with ≈12-km grid spacing. The optimal model setup was chosen based on preliminary simulations for several summer and winter periods with varied options, and included the usage of ERA-Interim reanalysis data as forcing data, the new model version 5.05 with so-called ICON-based physics, and a spectral nudging technique. The wind speed and temperature climatology in the new COSMO-CLM dataset closely agreed with the ERA-Interim reanalysis, but with detailed spatial patterns. The added value of the higher-resolution COSMO-CLM data with respect to the ERA-Interim was most pronounced for higher wind speeds during downslope windstorms with the influence of mountain ranges on the temperature patterns, including surface temperature inversions. The potential applications and plans of further product development are also discussed.

Improved Circulation in the Northern Hemisphere by Adjusting Gravity Wave Drag Parameterizations in Seasonal Experiments With ICON‐NWP

AbstractThe stratosphere is one of the main potential sources for subseasonal to seasonal predictability in midlatitudes in winter. The ability of an atmospheric model to realistically simulate the stratospheric dynamics is essential in order to move forward in the field of seasonal predictions in midlatitudes. Earlier studies with the ICOsahedral Nonhydrostatic atmospheric model (ICON) point out that stratospheric westerlies in ICON are underestimated. This is the first extensive study on the evaluation of Northern Hemisphere stratospheric winter circulation with ICON in numerical weather prediction (NWP) mode. Seasonal experiments with the default setup are able to reproduce the basic climatology of the stratospheric polar vortex. However, westerlies are too weak and major stratospheric warmings too frequent in ICON. Both a reduction of the nonorographic, and a reduction of the orographic gravity wave and wake drag lead to a strengthening of the stratospheric vortex and a bias reduction, in particular in January. However, the effect of the nonorographic gravity wave drag scheme on the stratosphere is stronger. Stratosphere‐troposphere coupling is intensified and more realistic due to a reduced gravity wave drag. Furthermore, an adjustment of the subgrid‐scale orographic drag parameterization leads to a significant error reduction in the mean sea level pressure. As a result of these findings, we present our current suggested improved setup for seasonal experiments with ICON‐NWP.

Prediction Skill of the Boreal Summer Intra-Seasonal Oscillation in Global Non-hydrostatic Atmospheric Model Simulations with Explicit Cloud Microphysics

Prediction Skill of the Boreal Summer Intra-Seasonal Oscillation in Global Non-hydrostatic Atmospheric Model Simulations with Explicit Cloud Microphysics

全球非静力学大気モデルにおける粒径解像エアロゾル微物理モジュール: モデルの記述と検証

全球非静力学大気モデルにおける粒径解像エアロゾル微物理モジュール: モデルの記述と検証

A new detailed long-term hydrometeorological dataset: first results of extreme characteristics estimations for the Russian Arctic seas

A detailed long-term hydrometeorological dataset for Russian Arctic seas has been created using hydrodynamic modelling via a regional nonhydrostatic atmospheric model, COSMO-CLM, for 1980-2016. This paper presents evaluation techniques of long-term experiments and a preliminary analysis of the dataset. The experiments are conducted for a model domain including the Barents, Kara, and Laptev Seas, with a 12 km grid. Many test experiments have been evaluated to determine the best model configuration, which includes a new model version 5.06, a “spectral nudging” technique, and an ERA-Interim reanalysis as forcing data. A reinitialization scheme of additional “assimilation” of soil properties reanalysis data is suggested to avoid possible errors, particularly due to soil draining in the model. The primary assessment has shown that a wind speed climatology based on COSMO-CLM experiments is very close to the ERA-Interim pattern, besides many details of wind speed distributions in different Arctic regions. At the same time, the high wind speed frequencies based on the COSMO-CLM data are increased compared to the ERA-Interim, especially over the Barents Sea, the Arctic islands (Novaya Zemlya), and some seacoasts and mainland areas. Regional details are manifested in a wind speed increase up to 0.5 – 1 m/s and marked well for large lakes, orography, as well as over the polar region. At the same time, there is a mesoscale wind speed decrease compared to the ERA-Interim data for the Pechora and Laptev Sea coasts and the New Siberian islands. Comparison of two periods (1980 – 1990 and 2010 – 2016) has shown that the spatial distributions of high wind speed frequencies are very similar, but there are some detailed differences. The wind speed frequencies above 17.2 and 20.8 m/s decreased in the last decade over Novaya Zemlya, southwest of Svalbard, Northern Atlantic, and the middle Siberia continent; at the same time, it increased between Franz Josef Land and Severnaya Zemlya and in the polar regions. The preliminary assessment of the results has revealed that the dataset is promising for analysis of regional wind speed regimes and estimation of severe wind speed risks. The next step of this work is to run simulations on a 3-km grid and collaborate with the scientific community to sufficiently use this dataset.

High-resolution wind speed modeling, and an assessment of mesoscale peculiarities caused by coastline parameters and relief of near-shore Kara Sea regions

Complex shorelines and coastal relief strongly influence wind speeds. Since the Arctic is poorly covered by ground observations, one of the most reasonable approaches to investigating these events is hydrodynamical high-resolution modeling. In this work we apply a model COSMO-CLM to reproduce wind fields and characteristics in different rugged shore conditions. Some model experiments are designed with this regional climate non-hydrostatic atmospheric model COSMO-CLM to investigate the best configuration to reproduce the mesoscale circulations in the Arctic coastal zones considering different relief conditions on the example of the Kara Sea. Some mid-term experiments of a three-month timespan, Aug-Oct of 2012 and Jul-Sep of 2014, are conducted over the Arctic domain and specially over the Kara Sea region using a downscaling approach with ∼12 and ∼3 km horizontal grids. These periods are characterized by some storm events. The purpose of these experiments is to reproduce the surface wind and wave characteristics in the best way, especially near the shorelines during the storm events. Verification of these experiments has shown the best configuration of the COSMO-CLM with a “spectral nudging” technique and reducing the model time step. However, the verification and detailed investigation of the model runs raise a question about the quality of this verification, and how relevant are the wind station data in different coastline and relief conditions. Therefore, an additional analysis is carried out from a synoptic overview of the influence of the coastline configuration on different mesoscales and for different regions. Malye Karmakuly (Novaya Zemlya island), Belyi and Dikson Islands are considered as different examples to study the wind and wave regimes. Although the model cannot describe the dynamics on all scales using a 3-km resolution, it can realistically simulate the islands’ wind shadows, tip jets, downslope winds, vortex chains, etc. on different scales. It justifies further research to apply a finer resolution to learn detailed properties of mesoscale circulations and extreme winds. This analysis has shown a need to predict better these circulations by using numerical modelling.

The North Atlantic High-Resolution Regional Climate Model Experiment for Oceanic and Atmospheric Applications

We present a high-resolution historical analysis of the atmosphere over the North Atlantic for the period from January 1979 to December 2018. The dataset was obtained using the nonhydrostatic atmospheric model WRF-ARW version 3.8.1 and contains two experiments that differ in spatial resolution: 14 km (HiRes) and 77 km (LoRes). Except for the spatial resolution, the configuration remained identical in both experiments: 50 vertical sigma-levels (starting from ~12 m up to 50 hPa); ERA-Interim reanalysis was used as forcing and spectral nudging. The dataset for HiRes and LoRes experiments was named NAAD (North Atlantic Atmospheric Downscaling). Preliminary results of both HiRes and LoRes reveal good agreement with observations and the ERA-Interim, ERA5, and ASRv2 reanalyses. The NAAD dataset is available online at http://www.naad.ocean.ru and provides a variety of surface and upper-troposphere atmospheric variables with a time step of 3 h.

The Marine Hindcast and Forecast System for Diagnosis and Prediction of Hydrometeorological Characteristics of the Caspian Sea and Forecast Verification Based on Field Measurements

The possibility of using the Marine Hindcast and Forecast System (MHFS) developed at Zubov State Oceanographic Institute for short-term forecasting of hydrometeorological and ice characteristics of the Caspian Sea is demonstrated. The presented implementation of the system is based on the regional nonhydrostatic atmospheric model WRF (Weather Research and Forecast Model) and model of marine circulation INMOM (Institute of Numerical Mathematics Ocean Model). The system performance is assessed for the period from January 1 to March 31, 2017 by comparing the forecasts of hydrometeorological characteristics with observational data from hydrometeorological stations. The quality of reproducing sea ice characteristics based on ESIMO objective data is also evaluated.

A Global Nonhydrostatic Atmospheric Model with a Mass- and Energy-conserving Vertically Implicit Correction (VIC) Scheme

Abstract Global nonhydrostatic atmospheric models are becoming increasingly important for studying the climates of planets and exoplanets. However, such models suffer from computational difficulties due to the large aspect ratio between the horizontal and vertical directions. To overcome this problem, we developed a global model using a vertically implicit correction (VIC) scheme in which the integration time step is no longer limited by the vertical propagation of acoustic waves. We proved that our model, based on the Athena++ framework and its extension for planetary atmospheres—SNAP (Simulating Nonhydrostatic Atmospheres on Planets), rigorously conserves mass and energy in finite-volume simulations. We found that traditional numerical stabilizers such as hyperviscosity and divergence damping are not needed when using the VIC scheme, which greatly simplifies the numerical implementation and improves stability. We present simulation results ranging from 1D linear waves to 3D global circulations with and without the VIC scheme. These tests demonstrate that our formulation correctly tracks local turbulent motions, produces Kelvin–Helmholtz instability, and generates a super-rotating jet on hot Jupiters. Employing this VIC scheme improves the computational efficiency of global simulations by more than two orders of magnitude compared to an explicit model and facilitates the capability of simulating a wide range of planetary atmospheres both regionally and globally.

A development of reduction scenarios of the short-lived climate pollutants (SLCPs) for mitigating global warming and environmental problems

This study presents the results of the ERTDF S-12 project for searching an optimum reduction scenario of the short-lived climate pollutants (SLCPs) to simultaneously mitigate the global warming and environmental problems. The study utilized REAS emission inventory, Asia-Pacific Integrated Model-Enduse (AIM/Enduse), MIROC6 climate model, NICAM non-hydrostatic atmospheric model, and models for estimating environmental damages to health, agriculture, and flood risks. Results of various scenario search indicate that it is difficult to attain simultaneous reduction of global warming and environmental damages, unless a significant reduction of CO2 is combined with carefully designed SLCP reductions for CH4, SO2, black carbon (BC), NOx, CO, and VOCs. In this scenario design, it is important to take into account the impact of small BC reduction to the surface air temperature and complex atmospheric chemical interactions such as negative feedback between CH4 and NOx reduction. We identified two scenarios, i.e., B2a and B1c scenarios which combine the 2D-scenario with SLCP mitigation measures using End-of-Pipe (EoP) and new mitigation technologies, as promising to simultaneously mitigate the temperature rise by about 0.33 °C by 2050 and air pollution in most of the globe for reducing damages in health, agriculture, and flood risk. In Asia and other heavy air pollution areas, health-care measures have to be enhanced in order to suppress the mortality increase due to high temperature in hot spot areas caused by a significant cut of particulate matter. For this situation, the B1b scenario is better to reduce hot spot areas and high-temperature damage to the public health.

Tropical Variability Simulated in ICON‐A With a Spectral Cumulus Parameterization

AbstractWe implemented a spectral cumulus parameterization based on a cloud‐resolving model (SC scheme) in the icosahedral nonhydrostatic atmospheric model (ICON‐A). We compared the resulting simulated climatology and tropical variability with results from the standard version of ICON‐A using a variant of the Tiedtke‐Nordeng scheme (TK scheme) using observational and reanalysis data. The climatological errors of the SC scheme were similar to those of the TK scheme, but several biases, such as properties of meridional winds and precipitation pattern in the western Pacific, were much improved. For tropical variability, we found that the SC scheme improved the interannual response of the precipitation in the western Pacific and was able to simulate Madden‐Julian oscillation (MJO) features much better than the TK scheme. We investigated the reason for the better simulation of the MJO using composite analysis and column process analysis for moisture. Our results suggest that the entrainment parameterization of the SC scheme is necessary to reproduce the MJO; however, spectral representation and improved convective closure are also found to contribute for better MJO simulation. These parameterizations improved moisture supply from low‐level clouds and cloud mass flux which were needed to sustain the MJO.

Vertical Discretization for a Nonhydrostatic Atmospheric Model Based on High-Order Spectral Elements

AbstractThis study addresses the treatment of vertical discretization for a high-order, spectral element model of a nonhydrostatic atmosphere in which the governing equations of the model are separated into horizontal and vertical components by introducing a coordinate transformation, so that one can use different orders and types of approximations in both directions. The vertical terms of the decoupled governing equations are discretized using finite elements based on either Lagrange or basis-spline polynomial functions in the sigma coordinate, while maintaining the high-order spectral elements for the discretization of the horizontal terms. This leads to the fact that the high-order model of spectral elements with a nonuniform grid, interpolated within an element, can be easily accommodated with existing physical parameterizations. Idealized tests are performed to compare the accuracy and efficiency of the vertical discretization methods, in addition to the central finite differences, with those of the standard high-order spectral element approach. Our results show, through all the test cases, that the finite element with the cubic basis-spline function is more accurate than the other vertical discretization methods at moderate computational cost. Furthermore, grid dependency studies in the tests with and without orography indicate that the convergence rate of the vertical discretization methods is lower than the expected level of discretization accuracy, especially in the Schär mountain test, which yields approximately first-order convergence.

Modeling extreme precipitation over East China with a global variable-resolution modeling framework (MPASv5.2): impacts of resolution and physics

Abstract. The non-hydrostatic atmospheric Model for Prediction Across Scales (MPAS-A), a global variable-resolution modeling framework, is applied at a range of resolutions from hydrostatic (60, 30, 16 km) to non-hydrostatic (4 km) scales using regional refinement over East Asia to simulate an extreme precipitation event. The event is triggered by a typical wind shear in the lower layer of the Meiyu front in East China on 25–27 June 2012 during the East Asian summer monsoon season. The simulations are evaluated using ground observations and reanalysis data. The simulated distribution and intensity of precipitation are analyzed to investigate the sensitivity to model configuration, resolution, and physics parameterizations. In general, simulations using global uniform-resolution and variable-resolution meshes share similar characteristics of precipitation and wind in the refined region with comparable horizontal resolution. Further experiments at multiple resolutions reveal the significant impacts of horizontal resolution on simulating the distribution and intensity of precipitation and updrafts. More specifically, simulations at coarser resolutions shift the zonal distribution of the rain belt and produce weaker heavy precipitation centers that are misplaced relative to the observed locations. In comparison, simulations employing 4 km cell spacing produce more realistic features of precipitation and wind. The difference among experiments in modeling rain belt features is mainly due to the difference in simulated wind shear formation and evolution during this event. Sensitivity experiments show that cloud microphysics have significant effects on modeling precipitation at non-hydrostatic scales, but their impacts are relatively small compared to that of convective parameterizations for simulations at hydrostatic scales. This study provides the first evidence supporting the use of convection-permitting global variable-resolution simulations for studying and improving forecasting of extreme precipitation over East China and motivates the need for a more systematic study of heavy precipitation events and the impacts of physics parameterizations and topography in the future. The key points are as follows. Model for Prediction Across Scales (MPAS) simulations at global uniform and variable resolutions share similar characteristics of precipitation and wind in the refined region. Numerical experiments reveal significant impacts of resolution on simulating the distribution and intensity of precipitation and updrafts. This study provides evidence supporting the use of convection-permitting global variable-resolution simulation to study extreme precipitation.

Deep learning approach for detecting tropical cyclones and their precursors in the simulation by a cloud-resolving global nonhydrostatic atmospheric model

We propose a deep learning approach for identifying tropical cyclones (TCs) and their precursors. Twenty year simulated outgoing longwave radiation (OLR) calculated using a cloud-resolving global atmospheric simulation is used for training two-dimensional deep convolutional neural networks (CNNs). The CNNs are trained with 50,000 TCs and their precursors and 500,000 non-TC data for binary classification. Ensemble CNN classifiers are applied to 10 year independent global OLR data for detecting precursors and TCs. The performance of the CNNs is investigated for various basins, seasons, and lead times. The CNN model successfully detects TCs and their precursors in the western North Pacific in the period from July to November with a probability of detection (POD) of 79.9–89.1% and a false alarm ratio (FAR) of 32.8–53.4%. Detection results include 91.2%, 77.8%, and 74.8% of precursors 2, 5, and 7 days before their formation, respectively, in the western North Pacific. Furthermore, although the detection performance is correlated with the amount of training data and TC lifetimes, it is possible to achieve high detectability with a POD exceeding 70% and a FAR below 50% during TC season for several ocean basins, such as the North Atlantic, with a limited sample size and short lifetime.

How Are Turbulent Sensible Heat Fluxes and Snow Melt Rates Affected by a Changing Snow Cover Fraction?

The complex interaction between the atmospheric boundary layer and the heterogeneous land surface is typically not resolved in numerical models approximating the turbulent heat exchange processes. In this study, we consider the effect of the land surface heterogeneity on the spatial variability of near-surface air temperature fields and on snow melt processes. For this purpose we calculated turbulent sensible heat fluxes and daily snow depth depletion rates with the physics-based surface process model Alpine3D. To account for the effect of a heterogeneous land surface (such as patchy snow covers) on the local energy balance over snow, Alpine3D is driven by two-dimensional atmospheric fields of air temperature and wind velocity, generated with the non-hydrostatic atmospheric model ARPS. The atmospheric model is initialized with a set of snow distributions (snow cover fraction and number of snow patches) and atmospheric conditions (wind velocities) for an idealized flat test site. Numerical results show that the feedback of the heterogeneity of the land surface (snow, no snow) on the near-surface variability of the atmospheric fields result in a significant increase in the mean air temperature ∆TA= 1.8 K (3.7 K, 4.9 K) as the snow cover fraction is decreased from a continuous snow cover to 55 % (25 %, 5 %). Surface turbulent sensible heat fluxes and daily snow depth depletion rates are strongly correlated to mean air temperatures, leading to 22-40 % larger daily snow depth depletion rates for patchy snow covers. Mean air temperatures over snow heavily increase with increasing initial wind velocities and weakly increase with an increasing number of snow patches. Numerical results from the idealized test site are compared with a test site in complex terrain. As slope-induced atmospheric processes (such as the development of katabatic flows) modify turbulent sensible heat fluxes, the variation of the surface energy balance is larger in complex terrain than for an idealized flat test site.