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The next version of the polar Regional Atmospheric Climate Model (referred to as RACMO2.4p1) is presented in this study. The principal update includes embedding of the package of physical parameterizations of the Integrated Forecast System (IFS) cycle 47r1. This constitutes changes in the precipitation, convection, turbulence, aerosol and surface schemes and includes a new cloud scheme with more prognostic variables and a dedicated lake model. Furthermore, the standalone IFS radiation physics module ecRad is incorporated into RACMO, and a multilayer snow module for non-glaciated regions is introduced. Other updates involve the introduction of a fractional land-ice mask, new and updated climatological data sets (such as aerosol concentrations and leaf area index), and the revision of several parameterizations specific to glaciated regions. As a proof of concept, we show first results for Greenland, Antarctica and a region encompassing the Arctic. By comparing the results with observations and the output from the previous model version (RACMO2.3p3), we show that the model performs well regarding the surface mass balance, surface energy balance, temperature, wind speed, cloud content and snow depth. The advection of snow hydrometeors strongly impacts the ice sheet's local surface mass balance, particularly in high-accumulation regions such as southeast Greenland and the Antarctic Peninsula. We critically assess the model output and identify some processes that would benefit from further model development.

Because Antarctic surface melt is mostly driven by local processes, its simulation necessitates high-resolution regional climate models (RCMs). However, the current horizontal resolution of RCMs (≈25–30 km) is inadequate for capturing small-scale melt processes. To address this limitation, we present SUPREME (SUPer-REsolution-based Melt Estimation over Antarctica), a deep learning method to downscale surface melt to 5.5 km resolution using a physically-informed super-resolution model. The physical information integrated into the model originates from observations tied to surface melt, specifically remote sensing-derived albedo and elevation. These remote sensing data, in addition to a Regional Atmospheric Climate Model (RACMO) run at 27 km resolution, account for the diverse drivers of surface melt across Antarctica, facilitating effective generalization beyond the training region of the Antarctic Peninsula. A comparison of SUPREME with a dynamically downscaled RACMO run at 5.5 km over the Antarctic Peninsula shows high accuracy, with average yearly RMSE and bias of 5.5 mm w.e. yr−1 and 4.5 mm w.e. yr−1, respectively. Validation at five automatic weather stations reveals SUPREME's marked improvement with substantially lower average RMSE (81 mm w.e.) compared to RACMO 27 km (129 mm w.e.). Beyond the training region, SUPREME aligns more closely with remote sensing products associated with surface melt than super-resolution models lacking physical constraints. While further validation of SUPREME is needed, our study highlights the potential of super-resolution techniques with physical constraints for high-resolution surface melt monitoring in Antarctica, providing insights into the impacts of localized melting on processes affecting ice shelf integrity such as hydrofracturing.

The mass loss of Earth’s land ice has caused 114 mm of global sea-level rise between 1901-2018, or more than half of the total measured sea-level rise (202 mm) in that period. The Greenland ice sheet and its peripheral glaciers contribute 40 mm to this sea-level rise, and are expected to continue to lose mass during the next century. Future projections of the mass loss of grounded ice, including the Greenland ice sheet require robust projections of both surface, basal and calving processes. Climate models are often used to calculate the surface mass balance of the ice sheet, defined as the precipitation minus the ablation at the surface. By far most of the ablation originates from the runoff of meltwater in the low-lying ablation zone, which covers only 10-16% of the ice sheet’s surface. In the ablation zone, surface melt is mainly driven by the absorption of solar radiation and by the sensible heat flux (SHF). The latter is defined as the vertical turbulent exchange of sensible heat between the surface and the overlying atmosphere. This turbulent heat flux explains most of the surface melt variability, and can become the major source of energy during extreme melt events. However, very few direct observations of turbulent fluxes exist on the ice sheet, which makes the simulation of these fluxes in climate models uncertain. This thesis aims to better quantify and therewith reduce the uncertainty of modelling the SHF across the Greenland ice sheet. In chapter 3, we address the issue of measuring the SHF on the ice sheet. A vertical propeller eddy covariance (VPEC) method is developed for this purpose. The large attenuation of the turbulent flux due to the large response times of propeller anemometers is accurately modelled, since the response times and the spectral characteristics of the turbulent fluxes are known. In chapter 4, we develop a novel method to map the surface aerodynamic roughness using either uncrewed aerial vehicles (UAV) or satellite laser altimetry (

Turbulent heat fluxes, that is, the sensible heat flux and latent heat flux, are important sources/sinks of energy for surface melt over glaciers and ice sheets. Therefore, credible simulations of for example, future Greenland Ice Sheet mass loss need an accurate description of these fluxes. However, the parameterization of surface turbulent heat fluxes in climate models requires knowledge about the surface roughness lengths for momentum, heat and moisture, which are currently either unknown or tuned to indirect observations. In this study we take advantage of a large data set of eddy covariance observations acquired during multiple years and at multiple sites over the Greenland Ice Sheet. These in-situ observations are used to develop an improved parameterization for the roughness length for momentum, and update the parameterization for the roughness lengths for heat and moisture over rough ice surfaces. The newly derived parameterizations are implemented in a surface energy balance model that is used to compute surface melt. Sensitivity experiments confirm the high sensitivity of surface melt to the chosen roughness length models. The new parameterization models the sensible heat flux to within 10 W m−2, and the cumulative ice ablation within 10% at three out of four sites. Two case studies demonstrate the important contribution of the turbulent heat fluxes to surface ablation. The presented roughness parameterizations can be implemented in climate models to improve the physical representation of surface roughness over rough snow and ice surfaces, which is expected to improve the modeled turbulent heat fluxes and thus surface melt.

The aerodynamic roughness of heat, moisture, and momentum of a natural surface are important parameters in atmospheric models, as they co-determine the intensity of turbulent transfer between the atmosphere and the surface. Unfortunately this parameter is often poorly known, especially in remote areas where neither high-resolution elevation models nor eddy-covariance measurements are available. In this study we adapt a bulk drag partitioning model to estimate the aerodynamic roughness length (z0m) such that it can be applied to 1D (i.e. unidirectional) elevation profiles, typically measured by laser altimeters. We apply the model to a rough ice surface on the K-transect (west Greenland Ice Sheet) using UAV photogrammetry, and we evaluate the modelled roughness against in situ eddy-covariance observations. We then present a method to estimate the topography at 1 m horizontal resolution using the ICESat-2 satellite laser altimeter, and we demonstrate the high precision of the satellite elevation profiles against UAV photogrammetry. The currently available satellite profiles are used to map the aerodynamic roughness during different time periods along the K-transect, that is compared to an extensive dataset of in situ observations. We find a considerable spatiooral variability in z0m, ranging between 10-4 m for a smooth snow surface and 10-1 m for rough crevassed areas, which confirms the need to incorporate a variable aerodynamic roughness in atmospheric models over ice sheets., Physical and Space Geodesy

We present a conceptual model for the diurnal cycle of the dry atmospheric boundary layer (ABL). It may serve as a framework for future numerical studies on the transitional dynamics that characterize the ABL over land. The conceptual model enables to define expressions for relevant physical scales as a function of the most prominent forcing parameters and the low degree of complexity facilitates a dimensionless description. This is useful to help generalize boundary-layer dynamics that occur on a diurnal timescale. Further, the model’s application for numerical studies is illustrated herein with two examples: A single-column-model study which assesses the effect of wind forcing on the main characteristics of the diurnal cycle, and a large-eddy-simulation study on the daily evolution of turbulence under weak-wind-forcing conditions. The results from these studies sketch the general evolution of the present set of diurnal-cycle systems in more detail. We discuss how the setups are able to reproduce well-known dynamical features of the ABL and also highlight limitations, where the simple conceptual system is unable to describe realistic ABL behavior. We conclude that the present conceptual model has an interesting balance between model-system complexity and physical realism, such that it is useful for future, idealized, studies on the diurnal cycle of the ABL.

We present a conceptual model for the diurnal cycle of the dry atmospheric boundary layer (ABL). It may serve as a framework for future numerical studies on the transitional dynamics that characterize the ABL over land. The conceptual model enables us to define expressions for relevant physical scales as a function of the most prominent forcing parameters and the low degree of complexity facilitates a dimensionless description. This is useful to help generalize boundary layer dynamics that occur on a diurnal time scale. Further, the model's application for numerical studies is illustrated herein with two examples: a single-column-model study that assesses the effect of wind forcing on the main characteristics of the diurnal cycle, and a large-eddy-simulation study on the daily evolution of turbulence under weak-wind-forcing conditions. The results from these studies sketch the general evolution of the present set of diurnal-cycle systems in more detail. We discuss how the setups are able to reproduce well-known dynamical features of the ABL and also highlight limitations, where the simple conceptual system is unable to describe realistic ABL behavior. We conclude that the present conceptual model has an interesting balance between model-system complexity and physical realism, such that it is useful for future idealized studies on the diurnal cycle of the ABL.

We present a conceptual model for the diurnal cycle of the dry atmospheric boundary layer (ABL). It may serve as a framework for future numerical studies on the transitional dynamics that characterize the ABL over land. The conceptual model enables us to define expressions for relevant physical scales as a function of the most prominent forcing parameters and the low degree of complexity facilitates a dimensionless description. This is useful to help generalize boundary layer dynamics that occur on a diurnal time scale. Further, the model’s application for numerical studies is illustrated herein with two examples: a single-column-model study that assesses the effect of wind forcing on the main characteristics of the diurnal cycle, and a large-eddy-simulation study on the daily evolution of turbulence under weak-wind-forcing conditions. The results from these studies sketch the general evolution of the present set of diurnal-cycle systems in more detail. We discuss how the setups are able to reproduce well-known dynamical features of the ABL and also highlight limitations, where the simple conceptual system is unable to describe realistic ABL behavior. We conclude that the present conceptual model has an interesting balance between model-system complexity and physical realism, such that it is useful for future idealized studies on the diurnal cycle of the ABL., Atmospheric Remote Sensing

This report proposes improvements of the land surface model (LSM) used in the turbulence-resolving Dutch Atmospheric Large-Eddy Simulation model (DALES). Important changes include the infiltration of precipitation, the parametrization of the soil hydraulic functions and the formulation of the soil water extraction by vegetation roots. The performance of the improved LSM version is validated using offline simulations and observations from the CESAR meteorological observatory in Cabauw (Netherlands), during the year of 2015. An optimal parameter set for this location set is obtained from both satellite retrievals and in-situ observations. In particular, the seasonal dependence of both the Leaf Area Index (LAI) and the roughness lengths for heat and momentum is prescribed to the model. The offline simulations determined that the improved version of the LSM is able to model the surface fluxes during the year of 2015 with an accuracy of 10 W/m2. This accuracy was found to be strongly dependent on the chosen land surface parameters such as the LAI, the roughness lengths, the soil textures and the vegetation root profiles. Furthermore, the lower boundary for soil water transfer, set to free drainage, was found to cause too much vegetation stress after an extended simulation time. Finally, the LSM is tested in a fully-coupled mode during three different meteorological events observed at the CESAR observatory. Firstly, stratocumulus simulations confirm the importance of the surface evaporation on the development of the stratocumulus layer, which is considerably reduced compared to simulations that assume the surface to be saturated with water. Secondly, the growth of the clear convective boundary layer was found to be greatly affected by the partitioning of the surface fluxes, as the sensible heat flux plays a key role in entrainment. Although the modelled sensible heat flux was found to be in agreement with the observations, the growth of the boundary layer was sti, Geoscience and Remote Sensing