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An adequate representation of the interaction between the land surface and the atmosphere is critical for both numerical weather prediction and climate models. The surface energy and mass balances are tightly coupled to the terrestrial water cycle, mainly through the state of soil moisture. An inadequate representation of the terrestrial water cycle will deteriorate the state of the land surface model and introduce biases to the atmospheric model. The validation of land surface models is challenging, as there are very few observations and the soil is highly heterogeneous. In this paper, a validation framework for land surface schemes based on catchment mass balances is presented. The main focus of our development lies in the application to kilometer-resolution numerical weather prediction and climate models, although the approach is scalable in both space and time. The methodology combines information from multiple observation-based datasets. Observational uncertainties are estimated by using independent sets of observations. It is shown that the combination of observation-based datasets and river discharge measurements close the water balance fairly well for the chosen catchments. As a showcase application, the framework is then applied to compare and validate four different versions of TERRA ML, the land surface scheme of the COSMO numerical weather prediction and climate model over five mesoscale catchments in Switzerland ranging from 105 to 1713 km2. Despite large observational uncertainties, validation results clearly suggest that errors in terrestrial storage changes are closely linked to errors in runoff generation and emphasize the crucial role of infiltration processes.

The response of the lower atmosphere to resolved versus parametrized orographic drag over moderately complex terrain is investigated. Typically, larger terrain scales may trigger propagating gravity waves and generate flow blocking, while the smaller scales (smaller than 5 km) may modify the turbulent atmospheric boundary layer leading to turbulent orographic form drag (TOFD). We perform high-resolution numerical simulations to evaluate the ability of a TOFD parametrization to reproduce the impact of small-scale orographic features on the flow over moderately complex terrain. The tool selected to perform the simulations is the Icosahedral Nonhydrostatic (ICON) numerical model, a unified modelling system for global numerical weather prediction (NWP) and climate studies. In the present study, the model is used in its limited-area and Large Eddy Simulation (LES) modes. In the TOFD parametrization (NWP), the surface stress and the vertical distribution of the resulting momentum flux are formulated in terms of the orography spectrum, meaning that it only depends on the statistical properties of the orography in the box (more specifically, only on the variance of the sub-grid scale orography). First, the simulations using different grid spacings, from the km scale to the 100 m scale, are evaluated with respect to data collected during the intensive observational period (IOP) of the Perdigão field experiment. The km-scale simulations in NWP mode are run continuously for the complete 49-day IOP using ERA5 data for initial and boundary conditions. The large-eddy simulations, at O(100 m) grid spacing, are run for selected periods nested into the NWP runs. The impact of the resolved orography on the wind field is derived by considering the difference between the high-resolution experiments with high (130 m) and the experiment with low (1 km) resolution orography. This is then compared with the impact of parametrized TOFD, deduced from NWP-resolution experiments with and without TOFD parametrization. The experiments focus on a moderately complex terrain to the north of the Perdigão site, the Serra da Estrela mountain range. Preliminary results show an important contribution of the TOFD parametrization (in terms of the accumulate TOFD tendency of wind) when the wind flow is aligned perpendicular to the mountain range, which is frequently observed during the second phase of the IOP characterized by weak synoptic conditions. During such periods, the simulation using the TOFD parametrization tends to be closer to the high resolution LES simulation, suggesting that the TOFD parametrization has a net positive effect on the simulations.

Fundamental research addressing the challenges of weather forecasts and climate monitoring is required in order to steadily improve the quality of meteorological and climatological services. However, the potential of transferring results from this research into operations increases significantly if carried out in collaboration with national meteorological and hydrometeorological services (NMHS). Out of this motivation and experience, the German “Hans-Ertel-Centre for Weather Research” (HErZ) has been established in 2011 as a virtual competence centre. HErZ develops and organizes a lasting national consortium along common objectives between the German Meteorological Service (DWD), German universities and scientific institutes to accelerate innovation in DWD’s weather, climate and environmental services. HErZ carries out excellent research, strengthens university education and promotes early career scientists, ensures personnel and strategical development, and facilitates the establishment and success of new cooperation, also outside of Germany. Moreover, HErZ grants access to DWD’s infrastructure, including (global) observation data and prediction models. With the strong support of the German Federal Ministry of Digital and Transport, HErZ was able to overcome the difficulties within initiating a cooperation between partners of different institutional communities and established an unprecedented sustainable and national transdisciplinary network. The current research and objectives of HErZ cover the whole value chain expected from this year’s EMS Annual Meeting’s additional focus on “Connecting Communities”: Bringing together fundamental and applied research, observations with prediction models, research institutions with NHMS, and developers with end-users. This intertwined and progressive structure in science and communication ultimately results in acquiring value for society as a whole. Establishing and managing HErZ and its scientific, strategic and structural goals is challenging. The complex tasks of achieving excellence in science and long-term success require a suitable balance between demands and needs of all institutions involved as well as an independent and strong governance by national and international high-level experts. In the future, HErZ must respond to new societal challenges in a targeted but flexible manner with new topics and competences, national and international partners, and a strengthened dialog with stakeholders and users. With this contribution, we would like to share with the audience the establishment, structure and peculiarities of HErZ, the lessons learnt from a transdisciplinary consortium connecting NHMS, universities and research institutes, and our visions towards future seamless science and services.

Measurements of vertical velocity from vertically pointing Doppler lidars are used to derive the profiles of normalized vertical velocity variance. Observations were taken during the FESSTVaL (Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg) campaign during the warm seasons of 2020 and 2021. Normalized by the square of the convective velocity scale, the average vertical velocity variance profile follows the universal profile of Lenschow et al. (1980). However, daily profiles still show a high day-to-day variability. We found that moisture transport and the content of moisture in the boundary layer could explain the remaining variability of the normalized vertical velocity variance. The magnitude of the normalized vertical velocity variance is highest on clear-sky days and decreases as the absolute humidity increases and surface latent heat flux decreases on cloud-topped days. This suggests that moisture content and moisture transport are limiting factors for the intensity of turbulence in the convective boundary layer. We also found that the intensity of turbulence decreases with an increase in the boundary layer cloud fraction during FESSTVaL, while the latent heating in the cloud layer was not a relevant source of turbulence in this case. We conclude that a new vertical velocity scale has to be defined that would take into account the moist processes in the convective boundary layer.

Radiation in the atmosphere provides the energy that drives atmospheric dynamics and physics on all scales, from cloud particle growth to global weather and climate. Radiation schemes in global weather and climate models make assumptions to simplify the complex interaction of radiation with the Earth system. Capturing cloud-radiation interactions is particularly challenging since clouds vary strongly on small spatial and temporal scales not resolved in the models, and interact strongly with radiation. Uncertainties in these assumptions in the radiation scheme and the cloud, aerosol, gas and surface inputs lead to uncertainties in multiple weather and climate processes, such as energy balance, cloud development and dynamics. The modular radiation scheme ecRad (Hogan and Bozzo, 2018, Rieger et al. 2019) is operational in ICON at DWD since April 2021 and provides the opportunity to vary parametrisations and assumptions individually to determine their impact. Several options are available for the radiation solver, cloud vertical overlap and horizontal inhomogeneity treatment and cloud hydrometeor optical property parametrisations. The solver SPARTACUS is the only radiation solver in a global model that can treat 3D radiative effects. Using global satellite and surface data and high-resolution surface radiation measurements gathered during the FESSTVaL campaign (https://fesstval.de), we evaluate the radiation and cloud parametrisations on local to global scales and investigate the sensitivity of radiation results to model assumptions and cloud properties and the role of cloud-radiation interactions. In ICON, ecRad improves the global radiation balance, model physics and forecast performance as evaluated against observations.References: Hogan, R. J., & Bozzo, A. (2018), A flexible and efficient radiation scheme for the ECMWF model. Journal of Advances in Modeling Earth Systems, 10, 1990-2008. https://doi.org/10.1029/2018MS001364Rieger, Daniel, Martin Köhler, Robin J. Hogan, Sophia A. K. Schäfer, Axel Seifert, Alberto de Lozar and Günther Zängl (2019). ecRad in ICON - Implementation Overview, Reports on ICON

Large-Eddy Simulations (LES) are set up to complement the FESSTVaL Field Experiment on sub-mesoscale spatio-temporal variability in Lindenberg using the Icosahedral Nonhydrostatic (ICON) model in a limited-area mode. The LES represent realistic conditions in the area around the observational site and are forced by the ICON-D2 analysis and forecasts. Four nested domains are used of which the innermost one has a horizontal grid resolution of about 75 m. This presentation will focus on the sensitivity of surface turbulent heat fluxes and their spatial variability on soil moisture to explain the discrepancies between the modeled and observed sensible heat flux. In-situ measurements provide the surface heat flux representative of different land cover conditions, crops and forests, while the area-averaged flux is measured along a scintillometer path of several kilometers. Next, a series of experiments will test the sensitivity of the strength of convective circulations on soil moisture. In these experiments, the initial soil moisture is increased, decreased or perturbed in different ways to find what role the variability of soil moisture plays in setting the strength of the convective circulations. The variance of vertical velocity is then compared to the FESSTVaL measurements derived from Doppler Lidar in vertical stare mode to find how realistic the circulations in LES are. This analysis focuses on several "golden days" that include a clear-sky day, three shallow-convective days of which one developed boundary-layer rolls and two precipitating days in June 2021. The complete set of the LES covers the intensive observational period of FESSTVaL from the 7. June to 4. July 2021.

The variability of vertical profiles of the normalized vertical velocity variance was examined to characterize turbulence and to investigate its dependence on meteorological parameters in the convective boundary layer. The vertical profiles of the vertical velocity variance were calculated using the Doppler lidar dataset from the FESSTVaL measurement campaign collected during two consecutive summer periods. The measurements took place around the Lindenberg meteorological observatory (MOL-RAO), near Berlin, Germany, representative of a flat-terrain covered with crops and patches of forest. The variability of a daily average of the normalized variance was analyzed during a period of a well-developed boundary layer. We classified the dataset into three main categories based on the presence of clouds and extracting only the periods without precipitation: clear-sky, cloud-topped, and rainy days. The mean profile of the normalized variance of the vertical velocity systematically increases from the rainy, cloud-topped to clear-sky days categories. The magnitude of the mean profile during the clear-sky and cloud-topped days is similar to the reference profile of Lenschow et al. (1980), although the variability among the days is large. The dependence of this variability of the normalized variance on the meteorological parameters was examined. We found that the relative humidity, Bowen ratio, surface latent heat flux, and cloud fraction relate to the variability of the normalized variance. A closer look at the cloud fraction during the cloud-topped days shows an increment of the normalized variance with a decrease of humidity in the boundary layer similar to the increment from rainy to cloudy and clear-sky days.

The response of the lower atmosphere to resolved versus parametrized orographic drag over moderately complex terrain is investigated. The larger terrain scales may trigger propagating gravity waves and generate flow blocking, while the smaller scales (smaller than 5 km) may modify the turbulent atmospheric boundary layer leading to turbulent orographic form drag (TOFD). We perform high-resolution numerical simulations to evaluate the ability of a TOFD parametrization to reproduce the impact of small-scale orographic features on the flow over complex terrain. The tool selected to perform the simulations is the Icosahedral Nonhydrostatic (ICON) numerical model, a unified modelling system for global numerical weather prediction (NWP) and climate studies. In the present study, the model is used in its limited-area mode. In the TOFD parametrization, the surface stress and its vertical distribution are formulated in terms of the orography spectrum, meaning that it only depends on the orography characteristics in the box (more specifically, only on the variance of the sub-grid scale orography).As a first step, simulations using different grid spacings, from the km scale (NWP mode) to the O100 m scale (large-eddy simulations, LES), are carried out to reproduce the intensive observational period (IOP) of the Perdigão field experiment. The high-resolution LES is used to assess the performance of the TOFD parametrization (used in NWP mode) in simulating the surface stress, the near-surface atmosphere and to highlight possible issues resulting in a miss-representation of the flow over moderately complex terrain. The km-scale simulations are run continuously for the complete 49-day IOP using the ERA5 reanalysis dataset for initial and boundary conditions. LES at 130 m grid spacing, are run for the whole IOP nested into the NWP runs (offline nesting). Initial results of the NWP control simulation show good performance compared to the tower wind observations for the whole IOP. The model performance was especially good for the second part of the IOP when a high-pressure regime and weak synoptic forcing were observed.Larger-scale thermally driven flows from the mountain ranges surrounding the Perdigão site impact the wind flow system at the double ridge, and when decomposed into along- and cross-valley, the performance of the model in the cross-valley direction tends to be very good. However, the model failed to reproduce the transition between anabatic- and katabatic-slope flow in the Serra da Estrela mountain range (NE of Perdigão). The latter negatively impacted the reproduction of the along-valley flow during the afternoon hours at the Perdigão site, when the most important deviations from observations were observed.

Currently, major efforts are under way to refine the horizontal resolution of weather and climate models to kilometer-scale grid spacing (Dx). Besides refining the representation of the atmospheric dynamics and enabling the use of explicit convection, this will also provide higher resolution in the representation of orography. This study investigates the influence of these resolution increments on the simulation of orographic moist convection. Nine days of fair-weather thermally driven flow over the Alps are analyzed. Two sets of simulations with the COSMO model are compared, each consisting of three runs at Dx of 4.4, 2.2, and 1.1 km: one set using a fixed representation of orography at a resolution of 8.8 km, and one with varying representation at the resolution of the computational mesh. The spatial distribution of precipitation during daytime is only marginally affected by the orographic details, but nighttime convection to the south of the Alps-triggered by cold-air outflow from the valleys-is very sensitive to orography and precipitation is enhanced if more detailed orography is provided. During daytime, the onset of precipitation is delayed. The amplitude of the diurnal cycle of precipitation is reduced, even though more moisture converges toward the Alpine region during the afternoon. The hereby accumulated moisture sustains precipitation during the evening and nighttime over the surrounding plains. For these differences, the effects of changes in orographic detail are more important than changes in grid spacing. In addition, the individual convective cells are weaker, but their number increases with higher resolved orography. © 2020 American Meteorological Society ISSN:1520-0493 ISSN:0027-0644

The “gray zone” of convection is defined as the range of horizontal grid-space resolutions at which convective processes are partially but not fully resolved explicitly by the model dynamics (typically estimated from a few kilometers to a few hundred meters). The representation of convection at these scales is challenging, as both parameterizing convective processes or relying on the model dynamics to resolve them might cause systematic model biases. Here, a regional climate model over a large European domain is used to study model biases when either using parameterizations of deep and shallow convection or representing convection explicitly. For this purpose, year-long simulations at horizontal resolutions between 50- and 2.2-km grid spacing are performed and evaluated with datasets of precipitation, surface temperature, and top-of-the-atmosphere radiation over Europe. While simulations with parameterized convection seem more favorable than using explicit convection at around 50-km resolution, at higher resolutions (grid spacing ≤ 25 km) models tend to perform similarly or even better for certain model skills when deep convection is turned off. At these finer scales, the representation of deep convection has a larger effect in model performance than changes in resolution when looking at hourly precipitation statistics and the representation of the diurnal cycle, especially over nonorographic regions. The shortwave net radiative balance at the top of the atmosphere is the variable most strongly affected by resolution changes, due to the better representation of cloud dynamical processes at higher resolutions. These results suggest that an explicit representation of convection may be beneficial in representing some aspects of climate over Europe at much coarser resolutions than previously thought, thereby reducing some of the uncertainties derived from parameterizing deep convection.

The response of the boundary layer flow to resolved versus parametrized orographic drag over moderately complex terrain is investigated. The larger terrain scales may trigger propagating gravity waves and generate flow blocking, while the smaller scales (smaller than 5 km) may modify the turbulent boundary layer leading to turbulent orographic form drag (TOFD). We perform high-resolution numerical simulations to evaluate the ability of a TOFD parametrization to reproduce the impact of small-scale orographic features on the flow over complex terrain. The tool selected to perform the simulations is the Icosahedral Nonhydrostatic (ICON) numerical model, a unified modelling system for global numerical weather prediction (NWP) and climate studies. In the present study, the model is used in its limited-area mode. In the TOFD parametrization used for the present simulations, the surface stress and its vertical distribution are formulated in terms of the spectrum of the orography, meaning that it only depends on the orography characteristics in the domain. As a first step simulations using different grid spacings, from the km scale to the 100 m scale, are carried out to reproduce the intensive observational period (IOP) of the Perdigão field experiment. The km-scale simulations in NWP mode are run continuously for the complete 49-day IOP using ERA5 data for initial and boundary conditions. The large-eddy simulations, at O(100 m) grid spacing, are run for selected periods nested into the NWP runs. The initial results of the NWP control simulation show good performance when compared to the tower wind observations for selected periods, but not for the entire IOP. The reasons for the variable performance is investigated.

ICON-seamless entwickelt ein neues Erdsystemmodell, als Grundlage für Wettervorhersage, saisonale und dekadische Klimavorhersagen, bis hin zu Klimaprojektionen. Dabei nutzen wir die Expertise, die ICON-NWV als zuverlässiges Modell für numerische Wettervorhersage (NWV) betreibt und pflegt sowie die Erfahrungen mit der ersten ICON-Erdsystemversion basierend auf der Physik der MPI-Atmosphäre ECHAM. Das Ziel ist, gemeinsame Komponenten für alle meteorologischen Zeitskalen nutzen zu können. Der erste Schritt entwickelt ein Modell für saisonale und dekadische Zeitskalen. ICON-seamless baut auf der Kopplung der Komponenten ICON-NWV (Atmosphäre) und ICON-O (Ozean) auf. Mit Hilfe des speziell entwickelten Kopplungs-Tools YAC können beide Komponenten Variablen austauschen, die für die Wechselwirkung zwischen Atmosphäre und Ozean wichtig sind. Auch die Parametrisierung von Meereis stellt einen wichtigen Baustein dar. Zur Wiedergabe eines geschlossenen hydrologischen Kreislaufs und um den Kohlenstoffkreislauf sauber darzustellen, wird ferner ein geeignetes Bodenmodell, ICON-L, an die Atmosphärenphysik von ICON-NWV gekoppelt. Zudem werden transiente Aerosolfelder, Treibhausgase, und Strahlungsantriebe neu in ICON-NWV eingelesen, um historische Zeiträume nachzuvollziehen. Parallel hierzu werden die ART Module (Aerosol and Reactive Trace gases), die eine dynamische Behandlung von Gasen und Aerosolen gestatten, an die modifizierte Modellphysik angepasst. Eine intensive Modelldiagnostik unterstützt das Tuning. Für die zukünftige Verwendung im Bereich der (Wetter- und) Klimavorhersagen wird parallel die gekoppelte Datenassimilation entwickelt. Wir geben einen Überblick über den aktuellen Stand der Entwicklung, der Experimente und potentieller Anwendungsbereiche.

Over the last decade kilometer-scale weather predictions and climate projections have become established. Thereby both the representation of atmospheric processes, as well as land-surface processes need adaptions to the higher-resolution. Soil moisture is a critical variable for determining the exchange of water and energy between the atmosphere and the land surface on hourly to seasonal time scales, and a poor representation of soil processes will eventually feed back on the simulation quality of the atmosphere. Especially the partitioning between infiltration and surface runoff will feed back on the hydrological cycle. Several aspects of the coupled system are affected by a shift to kilometer-scale, convection-permitting models. First of all, the precipitation-intensity distribution changes to more intense events. Second, the time-step of the numerical integration becomes smaller. The aim of this study is to investigate the numerical convergence of the one-dimensional Richards Equation with respect to the soil hydraulic model, vertical layer thickness and time-step during the infiltration process. Both regular and non-regular (unequally spaced) grids typical in land surface modelling are considered, using a conventional semi-implicit vertical discretization. For regular grids, results from a highly idealized experiment on the infiltration process show poor numerical convergence for layer thicknesses larger than approximately 5 cm and for time steps greater than 40 s, irrespective of the soil hydraulic model. The velocity of the wetting front decreases systematically with increasing time step and decreasing vertical resolution. For non-regular grids, a new discretization based on a coordinate transform is introduced. In contrast to simpler vertical discretizations, it is able to represent the solution second-order accurate. The results for non-regular grids are qualitatively similar, as a fast increase in layer thickness with depth is equivalent to a lower vertical resolution. It is argued that the sharp gradients in soil moisture around the propagating wetting front must be resolved properly in order to achieve an acceptable numerical convergence of the Richards Equation. Furthermore, it is shown that the observed poor numerical convergence translates directly into a poor convergence of infiltration-runoff partitioning for precipitation time series characteristic of weather and climate models. As a consequence, soil simulations with low resolution in space and time may produce almost twice the amount of surface runoff within 24 hours than their high-resolution counterparts. Our analysis indicates that the problem is particularly pronounced for kilometer-resolution models.

Doppler wind lidars are used to measure boundary layer turbulence, which is an important process to transfer heat and moisture within the boundary layer. Turbulence measurements using Doppler wind lidars were conducted during FESSTVaL@MOL field experiment from June to August 2020. The FESSTVaL@MOL 2020 is a part of the FESSTVaL (Field Experiment on sub-mesoscale spatio-temporal variability in Lindenberg) measurement campaign conducted at the boundary layer site Falkenberg, a part of the Lindenberg Meteorological Observatory – Richard-Aßmann-Observatorium (MOL-RAO). One Doppler wind lidar has been operated in vertical stare mode to characterize turbulence in the convective boundary layer during the summer. Two other Doppler wind lidars have been operated in low elevation angle PPI scan mode and one Doppler wind lidar has been operated in RHI scan mode. These three scanning configurations are used to investigate the dominant coherent structures near the surface.The retrieved wind data from vertical stare mode are categorized into cloud-topped boundary layer and cloud-free boundary layer days. We will analyze the intensity of the turbulence using vertical velocity variance and dissipation rate of the turbulent kinetic energy and the source of turbulence using a skewness profile for both categories. These profiles will be combined with low elevation angle PPI scan mode to categorize the coherent structures near the surface by their intensity and origin. Besides, we will present the overview of the preliminary study about the evolution of mixing layer height before and after cold-pool passage from several cases during FESSTVaL@MOL 2020 using vertical stare and RHI scan data.

Six strategies to couple the dynamical core with physical parameterizations in atmospheric models are analyzed from a numerical perspective. Thanks to a suitably designed theoretical framework featuring a high level of abstraction, the truncation error analysis and the linear stability study are carried out under weak assumptions. Indeed, second-order conditions are derived which are not influenced either by the specific formulation of the governing equations, nor by the number of parameterizations, nor by the structural design and implementation details of the time-stepping methods. The theoretical findings are verified on two idealized test beds. Particularly, a hydrostatic model in isentropic coordinates is used for vertical slice simulations of a moist airflow past an isolated mountain. Self-convergence tests show that the sensitivity of the prognostic variables to the coupling scheme may vary. For those variables (e.g., momentum) whose evolution is mainly driven by the dry dynamics, the truncation error associated with the dynamical core dominates and hides the error due to the coupling. In contrast, the coupling error of moist variables (e.g., the precipitation rate) emerges gradually as the spatio-temporal resolution increases. Eventually, each coupling scheme tends toward the formal order of accuracy, upon a careful treatment of the grid cell condensation. Indeed, the well-established saturation adjustment may cap the convergence rate to first order. A prognostic formulation of the condensation and evaporation process is derived from first principles. This solution is shown effective to alleviate the convergence issues in our experiments. Potential implications for a complete forecasting system are discussed. ISSN:1942-2466

Thermally driven upslope flows in mountainous areas provide favorable conditions for diurnal deep moist convection especially during episodes of weak synoptic forcing. The present study investigates the response of deep convection to axisymmetric orography as a function of orographic width and height by running ensembles of idealized convection-resolving simulations with a horizontal grid spacing of Δx = 1 km, full-physics parameterizations, and an interactive land surface. Deep convection is explicitly resolved and not parameterized. To cover a wide range of orographic scales, simulations are conducted with heights between 250 and 4000 m and widths between 5 and 30 km. The mountain slope strongly affects upslope wind speed characteristics, the timing and intensity of local updrafts, and local rain intensity. Although the day-to-day variability is substantial, the statistical-mean rain amount extracted by the mountain scales almost linearly with the mountain volume. Simulations with alternative mountain geometries, multiple peaks, and large-scale flow suggest that the linear scaling is valid for a surprisingly large portion of the parameter space. The scaling breaks down in the limit of relatively strong large-scale flows, sufficiently tall mountains, or elongated mountains. The existence of the simple linear scaling over such a wide range of configurations suggests that the response of thermally driven orographic deep convection over many mountainous areas is strongly affected by mountain volume. As a consequence, the rain amount is disproportionally dominated by the large horizontal scales of orography, as they contribute mostly to the mountain volume.

Currently major efforts are underway toward refining the horizontal resolution (or grid spacing) of climate models to about 1 km, using both global and regional climate models (GCMs and RCMs). Several groups have succeeded in conducting kilometer-scale multiweek GCM simulations and decadelong continental-scale RCM simulations. There is the well-founded hope that this increase in resolution represents a quantum jump in climate modeling, as it enables replacing the parameterization of moist convection by an explicit treatment. It is expected that this will improve the simulation of the water cycle and extreme events and reduce uncertainties in climate change projections. While kilometer-scale resolution is commonly employed in limited-area numerical weather prediction, enabling it on global scales for extended climate simulations requires a concerted effort. In this paper, we exploit an RCM that runs entirely on graphics processing units (GPUs) and show examples that highlight the prospects of this approach. A particular challenge addressed in this paper relates to the growth in output volumes. It is argued that the data avalanche of high-resolution simulations will make it impractical or impossible to store the data. Rather, repeating the simulation and conducting online analysis will become more efficient. A prototype of this methodology is presented. It makes use of a bit-reproducible model version that ensures reproducible simulations across hardware architectures, in conjunction with a data virtualization layer as a common interface for output analyses. An assessment of the potential of these novel approaches will be provided.

Land-Atmosphere coupling is a fundamental process of the earth system. From the perspective of atmospheric sciences, a quantitative understanding of the surface energy and mass balances is of vital importance for both numerical weather prediction and climate modeling and needs to be represented adequately in land surface schemes. The partitioning of net radiation into sensible, latent and ground heat fluxes is dependent on the state of the land surface with soil moisture being an important state variable, introducing memory effects of monthly to annual timescales to the coupling. An inadequate representation of the terrestrial water cycle will therefore degrade forecasts and introduce biases in climate simulations. While there exist reasonable estimates for the terrestrial water cycle on subcontinental scales and various observations for evapotranspiration on the point-scale, the validation of land-surface-schemes on the kilometer-scale remains challenging. The fundamental unit on which one can validate all terms of the water balance is the catchment. Here, we present a validation framework based on water balances of mesoscale catchments. The framework incorporates observations of precipitation and streamflow as well as estimates for evapotranspiration from remote sensing data.The methodology is applied to five mesoscale catchments in Switzerland ranging from 105 km2 to 1713 km2 for the years 2010-2012. Observations include MeteoSwiss operational analyses, hourly discharge measurements provided by the federal office for the environment and the MODIS MOD16A2 evapotranspiration product. While relying on observations, these datasets are subject to substantial uncertainties. We aim to quantify the major part of this observational uncertainty by using data from FLUXNET sites in the Alpine region and a rain-gauge based precipitation dataset from MeteoSwiss (RhiresM).As a showcase application, the validation framework is used in order to compare and validate two different parameterizations for soil/ groundwater hydrology in TERRA, the land surface scheme of the COSMO numerical weather prediction and regional climate model. While both versions are based on Richard’s equation, one is implemented with a free drainage boundary condition, while the other one is implemented with a simple parameterization for groundwater. Results from TERRA standalone runs forced with COSMO analysis fields suggest that errors in terrestrial storage change are mostly driven by errors in runoff. In turn, runoff is very sensitive to the parameterization of infiltration and to soil hydraulic parameter. We show that despite large uncertainties in the observations at hand, it is possible to identify respective shortcomings of the two different groundwater formulations and to improve the simulated water balance by introducing a mathematically sound formulation for infiltration and by tuning key parameter associated to ground water discharge.

Convection-resolving models (CRMs) can explicitly simulate deep convection and resolve interactions between convective updrafts. They are thus increasingly used in numerous weather and climate applications. However, the truncation of the continuous energy cascade at scales of $$\mathcal {O}$$ (1 km) poses a serious challenge, as in kilometer-scale simulations the size and properties of the simulated convective cells are often determined by the horizontal grid spacing ( $$\Delta x$$ ).In this study, idealized simulations of deep moist convection over land are performed to assess the convergence behavior of a CRM at $$\Delta x =$$ 8, 4, 2, 1 km and 500 m. Two types of convergence estimates are investigated: bulk convergence addressing domain-averaged and integrated variables related to the water and energy budgets, and structural convergence addressing the statistics and scales of individual clouds and updrafts. Results show that bulk convergence generally begins at $$\Delta x =4$$ km, while structural convergence is not yet fully achieved at the kilometer scale, despite some evidence that the resolution sensitivity of updraft velocities and convective mass fluxes decreases at finer resolution. In particular, at finer grid spacings the maximum updraft velocity generally increases, and the size of the smallest clouds is mostly determined by $$\Delta x$$ . A number of different experiments are conducted, and it is found that the presence of orography and environmental vertical wind shear yields more energetic structures at scales much larger than $$\Delta x$$ , sometimes reducing the resolution sensitivity. Overall the results lend support to the use of kilometer-scale resolutions in CRMs, despite the inability of these models to fully resolve the associated cloud field.

This review paper explores the field of mesoscale to microscale modeling over complex terrain as it traverses multiple so-called gray zones. In an attempt to bridge the gap between previous large-scale and small-scale modeling efforts, atmospheric simulations are being run at an unprecedented range of resolutions. The gray zone is the range of grid resolutions where particular features are neither subgrid nor fully resolved, but rather are partially resolved. The definition of a gray zone depends strongly on the feature being represented and its relationship to the model resolution. This paper explores three gray zones relevant to simulations over complex terrain: turbulence, convection, and topography. Taken together, these may be referred to as the gray continuum. The focus is on horizontal grid resolutions from ∼10 km to ∼10 m. In each case, the challenges are presented together with recent progress in the literature. A common theme is to address cross-scale interaction and scale-awareness in parameterization schemes. How numerical models are designed to cross these gray zones is critical to complex terrain applications in numerical weather prediction, wind resource forecasting, and regional climate modeling, among others., Atmosphere, 10 (5), ISSN:2073-4433

Under radiative-convective equilibrium (RCE), surface moisture fluxes drive convection, while convection-driven winds regulate surface fluxes. Most simulations of RCE do not resolve the boundary-layer turbulence that drives near-surface winds due to too coarse grid spacing and instead parameterize its effects by enforcing a minimum wind speed in the computation of the ocean-atmosphere exchange. We show from RCE simulations with fully resolved boundary-layer turbulence that capturing wind dynamics at low speeds impacts the spatially averaged surface moisture flux, as well as its spatial distribution. A minimum wind speed constraint of only 1 m s−1 leads to ∼10% increase in spatially averaged surface flux in the evolution towards RCE and reduces the surface flux differences between windy and calm regions with more than a factor of two. Hence, the ability of simulations to let wind vanish is key in representing the wind-induced surface heat exchange feedback and is potentially important in convective self-aggregation.

This study investigates the interplay between atmospheric moisture and deep convective clouds via cold-pool dynamics in the absence of large-scale forcing in a series of cloud-resolving modelling studies. More specifically, the contribution of moisture advection, evaporation of rain and surface fluxes to the moisture budget over particular regions of the domain is investigated. This is done both for a continental case and an oceanic case although both cases show very similar behaviour. The accumulation of moisture in confined regions of the sub-cloud layer that constitute preferred locations for future cloud development mainly results from the advection of moisture. The latter contributes ~86%, minor evaporation of precipitation contributes ~4%, whereas surface moisture fluxes yield ~11% in the continental case. In the oceanic case advection contributes ~125%, surface moisture fluxes ~−32% and evaporation of precipitation ~7%. To further identify the origin of the advected moisture, additional scalars marking moisture originating from the surface and from the evaporation of rain are introduced into the model. It is seen that the surface moisture and the evaporated rain water released within the last 2 h only make 55% of the moisture accumulated in the moist patches in the land case, the rest stemming from older moisture. In the ocean case, this share increases to 72%. The contribution of recently released moisture drops to 28% at cloud base in the continental case and to 56% in the ocean case. The contribution at cloud base is dominated by surface fluxes; the evaporation of rain is negligible.

Current climate models often predict fractional cloud cover on the basis of a diagnostic probability density function (PDF) describing the subgrid-scale variability of the total water specific humidity, qt, favouring schemes with limited complexity. Standard shapes are uniform or triangular PDFs, the widths of which are assumed to scale with the grid-box mean qt or the grid-box mean saturation specific humidity, qs. In this study, the qt variability is analysed from large-eddy simulations for two stratocumulus, two shallow cumulus, and one deep convective cases. We find that, in most cases, triangles are a better approximation to the simulated PDFs than uniform distributions. In 2 of the 24 slices examined, the actual distributions were so strongly skewed that the simple symmetric shapes could not capture the PDF at all. The distribution width for either shape scales acceptably well with both the mean values of qt and qs, the former being a slightly better choice. The qt variance is underestimated by the fitted PDFs, but overestimated by the existing parametrizations. While the cloud fraction is in general relatively well diagnosed from fitted or parametrized uniform or triangular PDFs, it fails to capture cases with small partial cloudiness, and in 10–30% of the cases misdiagnoses clouds in clear skies or vice versa. The results suggest choosing a parametrization with a triangular shape, where the distribution width would scale with the grid-box mean qt using a scaling factor of 0.076. However, this is subject to the caveat that the reference simulations examined here were partly for rather small domains and driven by idealised boundary conditions.

On summertime fair-weather days, thermally driven wind systems play an important role in determining the initiation of convection and the occurrence of localized precipitation episodes over mountainous terrain. This study compares the mechanisms of convection initiation and precipitation development within a thermally driven flow over an idealized double-ridge system in large-eddy (LESs) and convection-resolving (CRM) simulations. First, LES at a horizontal grid spacing of 200 m is employed to analyze the developing circulations and associated clouds and precipitation. Second, CRM simulations at horizontal grid length of 1 km are conducted to evaluate the performance of a kilometer-scale model in reproducing the discussed mechanisms. Mass convergence and a weaker inhibition over the two ridges flanking the valley combine with water vapor advection by upslope winds to initiate deep convection. In the CRM simulations, the spatial distribution of clouds and precipitation is generally well captured. However, if the mountains are high enough to force the thermally driven flow into an elevated mixed layer, the transition to deep convection occurs faster, precipitation is generated earlier, and surface rainfall rates are higher compared to the LES. Vertical turbulent fluxes remain largely unresolved in the CRM simulations and are underestimated by the model, leading to stronger upslope winds and increased horizontal moisture advection toward the mountain summits. The choice of the turbulence scheme and the employment of a shallow convection parameterization in the CRM simulations change the strength of the upslope winds, thereby influencing the simulated timing and intensity of convective precipitation.

The influence of soil moisture and atmospheric stability on mid-latitude diurnal convection and land–atmosphere exchange is investigated in an idealized cloud-resolving modelling framework using a full set of parametrization schemes. In each member of a series of month-long experiments, the model attains a state where deep, precipitating convection is triggered every day. This state is referred to as equilibrium diurnal convection. The triggering occurs via different mechanisms depending on the atmosphere–soil setting. In our framework latent heat fluxes comprise the primary control over the precipitation amounts. We find that evaporation is regulated by the availability of energy on the one hand and the availability of soil moisture and the near-surface saturation deficit of the atmosphere on the other. Increased cloud cover over wet soils reduces net short-wave radiation but increases net long-wave radiation, leading to a near-compensation of the two effects on available energy. Increased boundary layer moisture is removed by deep convection, thus increasing the near-surface saturation deficit and preventing a negative feedback of boundary layer moisture content on the latent heat fluxes. We also find that there is a spatial correlation between soil moisture and precipitation anomalies, suggesting that the soil moisture precipitation feedback acts on a scale of 10–50 km. Copyright © 2012 Royal Meteorological Society

Ensembles of convection-resolving simulations with a simplified land surface are conducted to dissect the isolated and combined impacts of soil-moisture and orography on deep-convective precipitation under weak synoptic forcing. In particular, the deep-convective precipitation response to a uniform and a non-uniform soil-moisture perturbation is investigated both in settings with and without orography. In the case of horizontally uniform perturbations, we find a consistently positive soil moisture-precipitation feedback, irrespective of the presence of low orography. On the other hand, a negative feedback emerges with localized perturbations: a dry soil heterogeneity substantially enhances rain amounts that scale linearly with the dryness of the soil, while a moist heterogeneity suppresses rain amounts. If the heterogeneity is located in a mountainous region, the relative importance of soil-moisture heterogeneity decreases with increasing mountain height: A mountain 500m in height is sufficient to neutralize the local soil moisture-precipitation feedback.

This paper introduces an idealized cloud-resolving modeling (CRM) framework for the study of midlatitude diurnal convection over land. The framework is used to study the feedbacks among soil, boundary layer, and diurnal convection. It includes a setup with explicit convection and a full set of parameterizations. Predicted variables are constantly relaxed toward prescribed atmospheric profiles and soil conditions. The relaxation is weak in the lower troposphere and upper soil to allow the development of a realistic diurnal planetary boundary layer. The model is run to its own equilibrium (30 days). The framework is able to produce a realistic timing of the diurnal cycle of convection. It also confirms the development of deeper convection in a more unstably stratified atmosphere. With this relaxation method, the simulated “diurnal equilibrium convection” determines the humidity profile of the lower atmosphere, and the simulation becomes insensitive to the reference humidity profile. However, if a faster relaxation time is used in the lower troposphere, the convection and rainfall become much more sensitive to the reference humidity, consistent with previous studies.

This study investigates how precipitation-driven cold pools aid the formation of wider clouds that are essential for a transition from shallow to deep convection. In connection with a temperature depression and a depletion of moisture inside developing cold pools, an accumulation of moisture in moist patches around the cold pools is observed. Convective clouds are formed on top of these moist patches. Larger moist patches form with time supporting more and larger clouds. Moreover, enhanced vertical lifting along the leading edges of the gravity current triggered by the cold pool is found. The interplay of moisture aggregation and lifting eventually promotes the formation of wider clouds that are less affected by entrainment and become deeper. These mechanisms are corroborated in a series of cloud-resolving model simulations representing different atmospheric environments. A positive feedback is observed in that, in an atmosphere in which cloud and rain formation is facilitated, stronger downdrafts will form. These stronger downdrafts lead to a stronger modification of the moisture field, which in turn favors further cloud development. This effect is not only observed in the transition phase but also active in prolonging the peak time of precipitation in the later stages of the diurnal cycle. These findings are used to propose a simple way for incorporating the effect of cold pools on cloud sizes and thereby entrainment rate into parameterization schemes for convection. Comparison of this parameterization to the cloud-resolving modeling output gives promising results.

The importance of soil moisture anomalies on airmass convection over semiarid regions has been recognized in several studies. The underlying mechanisms remain partly unclear. An open question is why wetter soils can result in either an increase or a decrease of precipitation (positive or negative soil moisture–precipitation feedback, respectively). Here an idealized cloud-resolving modeling framework is used to explore the local soil moisture–precipitation feedback. The approach is able to replicate both positive and negative feedback loops, depending on the environmental parameters. The mechanism relies on horizontal soil moisture variations, which may develop and intensify spontaneously. The positive expression of the feedback is associated with the initiation of convection over dry soil patches, but the convective cells then propagate over wet patches where they strengthen and preferentially precipitate. The negative feedback may occur when the wind profile is too weak to support the propagation of convective features from dry to wet areas. Precipitation is then generally weaker and falls preferentially over dry patches. The results highlight the role of the midtropospheric flow in determining the sign of the feedback. A key element of the positive feedback is the exploitation of both low convective inhibition (CIN) over dry patches (for the initiation of convection) and high CAPE over wet patches (for the generation of precipitation).

Extreme precipitation events along the Alpine south side (AS) are often forced by upper-level positive potential vorticity (PV) anomalies over western Europe. These so-called PV streamers go along with a dynamical forcing for upward motion, a reduction of the static stability in the troposphere (hence facilitating convection), and are associated with low-level winds that transport moisture toward the Alps. A case of heavy precipitation is examined using the 40-yr ECMWF Re-Analysis data. Piecewise PV inversion (PPVI) and the limited-area Climate High Resolution Model (CHRM) are used to assess the influences of mesoscale parts of the streamer on the precipitation event. The impacts on the vertical stability are quantified by the convective available potential energy (CAPE) and an index of static stability. Very sensitive areas in terms of the stability are located beneath the southern tip of the streamer; smaller changes in the stability are observed in the Alpine region. The moisture transport toward the Alps is sensitive to the amplitude of the streamer, which influences the amount of water that can be transported along its eastern flank. The impacts of the topography on the flow are assessed by calculating an average inverse Froude number. Whether or not the air parcels are blocked by or lifted over the barrier (going along with suppressed and enhanced precipitation, respectively) depends on the vertical stability and the impinging wind velocity, two parameters that are inherently linked to the PV streamer and its substructure.