Europe - especially the northern and middle latitudes - is one of Earth’s mire-rich regions. Among the main distribution areas for mires in Central Europe the coastal region along the southeastern corner of the North Sea (Frisia) shows the highest density of mires. Despite of the important role of mires acting as a carbon sink and modifying the Bowen ratio with influence on screen level meteorological parameters their adequate representation in land-surface schemes used in numerical weather prediction and climate models is still insufficient. With the recent version 5.06 the COSMO model (Baldauf et al., 2017) offers a parameterization of mires based on Yurova et al. (2014). In this approach the heat diffusion in the vertical domain of the soil multilayer model TERRA is considered with modified equations describing the thermal conductivity for peat with given water/ice contents. The mire hydrology is parameterized by the solution of the Richard's equation in the vertical domain extended by the formulation of a lower boundary condition as a climatological layer of permanent saturation used to simulate the water table position, in conjunction with a mire‐specific evapotranspiration and runoff parameterization. The impact of the mire parameterization on screen level meteorological parameters and mesoscale processes was investigated in two numerical experiments with COSMO-D2 in a convection permitting limited-area numerical weather prediction (NWP) framework for summer 2018 and winter 2018/2019. We will present results from the objective verification system and discuss the impact of geospatial physiographic data for an improved representation of mires in the NWP framework.

Snow as a major part of the cryosphere is an important component of Earth’s hydrological cycle and energy balance. Understanding the microstructural, macrophysical, thermal and optical properties of the snowpack is essential for integration into numerical models and there is a great need for accurate snow data at different spatial and temporal resolutions to address the challenges of changing snow conditions. Physical snow properties are currently determined by traditional ground-based measurements as well as remote sensing, over a range of temporal and spatial scales, following considerable developments in instrument technology over recent years. Data assimilation (DA) methods are widely used to combine data from different observations with numerical model using uncertainties of observed and modeled variables to produce an optimal estimate. DA provides a reliable improvement of the initial states of the numerical model and a benefit for hydrological and snow model forecasts. European efforts to harmonize approaches for validation, and methodologies of snow measurement practices, instrumentation, algorithms and data assimilation techniques were coordinated by the European Cooperation in Science and Technology (COST) Action ES1404 “HarmoSnow”, entitled, “A European network for a harmonized monitoring of snow for the benefit of climate change scenarios, hydrology and numerical weather prediction” (2014-2018) . One of the key objectives of the action was “Advance the application of snow DA in numerical weather prediction (NWP) and hydrological models, and show its benefit for weather and hydrological forecasting as well as other applications.” One key result from COST HarmoSnow is a better knowledge about the diversity of usage of snow observations in DA, forcing, monitoring, validation, or verification within NWP, hydrology, snow and climate models. The main parts of this knowledge are retrieved from a COST HarmoSnow survey exploring the common practices on the use of snow observations in different modeling environments. We will show results from the survey and their implications towards standardized and improved usage of snow observations in various data assimilation applications.

The 1 st Snow Data Assimilation Workshop, organized under the COST Action ESSEM 1404 HarmoSnow, took place in Offenbach, Germany, on 8-9 March 2017.Of particular relevance for the workshop were thematic sessions on i) data assimilation methods and the use of snow observations, ii) snow observations and evaluation, iii) snow observations and physical snow models, and iv) snow observations and hydrological models.This report summarizes the scientific contributions presented at the workshop.The discussions mainly focused on methods for combining satellite observations with conventional in-situ snow measurements and modeling results, as well as on errors in the spatial and temporal representation of snow measurements for data assimilation in NWP and hydrological models.It has been shown that the assimilation of in-situ and satellite-based snow observations improves the quality of the snow analysis and forecast.However, in order to achieve this positive impact, a thorough quality control of the observational data is necessary, in particular because of the automation of the ground-based networks.

The European Cooperation in Science and Technology (COST) Action ES1404 “HarmoSnow”, entitled, “A European network for a harmonized monitoring of snow for the benefit of climate change scenarios, hydrology and numerical weather prediction” (2014-2018) aims to coordinate efforts in Europe to harmonize approaches to validation, and methodologies of snow measurement practices, instrumentation, algorithms and data assimilation (DA) techniques. One of the key objectives of the action was “Advance the application of snow DA in numerical weather prediction (NWP) and hydrological models and show its benefit for weather and hydrological forecasting as well as other applications.” This paper reviews approaches used for assimilation of snow measurements such as remotely sensed and in situ observations into hydrological, land surface, meteorological and climate models based on a COST HarmoSnow survey exploring the common practices on the use of snow observation data in different modeling environments. The aim is to assess the current situation and understand the diversity of usage of snow observations in DA, forcing, monitoring, validation, or verification within NWP, hydrology, snow and climate models. Based on the responses from the community to the questionnaire and on literature review the status and requirements for the future evolution of conventional snow observations from national networks and satellite products, for data assimilation and model validation are derived and suggestions are formulated towards standardized and improved usage of snow observation data in snow DA. Results of the conducted survey showed that there is a fit between the snow macro-physical variables required for snow DA and those provided by the measurement networks, instruments, and techniques. Data availability and resources to integrate the data in the model environment are identified as the current barriers and limitations for the use of new or upcoming snow data sources. Broadening resources to integrate enhanced snow data would promote the future plans to make use of them in all model environments.

The impact of the ECOCLIMAP land use and the Harmonized World Soil Database (HWSD) data on simulations with the Consortium for Small-scale Modeling model in CLimate Mode (CCLM) regional climate model is investigated. ECOCLIMAP has information about vegetation characteristics as monthly data for 215 climatic units. With the HWSD implementation in CCLM, the spatial resolution of the soil data has been increased to 30 arc seconds and has an improved texture definition and handling in the soil model TERRA_ML. Simulations in the MED-CORDEX modeling domain over the period 1986-2000 reveal that differences of up to 1.8 K in the area monthly mean temperature as well as of up to 21% in the area monthly mean precipitation can be attributed to the differences in the soil data time-invariant boundary input. Differences related to changes in land use are with 0.4 K and 5% moderate. Differences resulting from the soil data and its processing in CCLM indicate that regional climate model simulations might benefit from further improvements in this area.

Maritime cumulus clouds, which typically extend to no greater than 4 km altitude are some of the most prevalent cloud types on Earth. They are ubiquitous over much of the tropical oceans, and characterizing their properties is important to understand the global energy balance and climate. To consider these clouds and how rain develops within them in numerical models, a wide range of scales (from micro-meters to tens of kilometers) have to be taken into account. However, key processes, which influence shallow cumulus cloud development and initiation of precipitation are often subgrid-scale in numerical weather prediction (NWP) models. The broad objective of the Rain in Cumulus over the Ocean (RICO) experiment was to measure and understand the properties of trade wind cumulus at all scales, with particular emphasis on determining the importance of the development of rain. The RICO field campaign took place during November 2004-January 2005 off the Caribbean islands of Antigua and Barbuda within the northeast trades of the western Atlantic (see e.g., Rauber et al., 2007 for details).

The multiscale model system LM-MUSCAT consists of two online coupled codes: the operational forecast model LM (Local Model) of the German Weather Service and the chemistry transport model MUSCAT (Multi-Scale Atmospheric Transport Model). The coupler provides MUSCAT with meteorological fields like temperature, humidity and density from LM. An improved coupling scheme was developed to optimize the parallel efficiency of the model system.

A new regional model system was developed for simulation of emission, transport, deposition, and radiative effects of Saharan desert aerosol within the framework of the Saharan Mineral Dust Experiment (SAMUM). For this the mesoscale meteorological model LM, a dust emission scheme and a transport model were coupled. To test the model performance, two major Saharan dust outbreaks directed to Europe in August and October 2001 are simulated. Comparisons with sounding data and 10‐m wind speeds from north African sites show that the LM provides reliable meteorological fields to describe the emission and near‐source transport of dust. As shown by comparisons with satellite observations, lidar profiles, and Sun photometer measurements at selected stations, the spatiotemporal evolution of the dust plume is reasonably well reproduced by the model. The predicted dust interacts with the LM radiation at solar and thermal wavelengths. Saharan dust causes a negative effect on the net radiative budget at the top of the atmosphere in the source regions and accounts for a reduction in 10‐m wind speeds. Thus it is responsible for a reduction in the dust production of up to about 50% during the October 2001 event.

On the basis of a new regional dust model system, the sensitivity of radiative forcing to dust aerosol properties and the impact on atmospheric dynamics were investigated. Uncertainties in optical properties were related to uncertainties in the complex spectral refractive index of mineral dust. The climatological‐based distribution of desert‐type aerosol in the radiation scheme of the nonhydrostatic regional model LM was replaced by dust optical properties from spectral refractive indices, derived from in situ measurements, remote sensing, bulk measurements, and laboratory experiments, employing Mie theory. The model computes changes in the solar and terrestrial irradiance from a spatially and temporally varying atmospheric dust load for five size classes. A model study of a Saharan dust outbreak in October 2001 was carried out when large amounts of Saharan dust were transported to Europe. The dust optical thickness computed from the simulation results in values of about 0.5 in large regions of the Saharan desert but can be larger than 5.0 near large dust sources (for example, Bodélé depression). During the dust outbreak, the aerosol in the southern Sahara causes a daytime reduction in 2‐m temperature of 3 K in average with differences of 10% depending on used dust optical properties. The simulations indicated that the large variability in radiative properties due to different mixture of clay aggregates in Saharan dust can lead in regional average to differences of up to 48% in net forcing efficiency at top of the atmosphere.

We present regional model simulations of the dust emission events during the Bodélé Dust Experiment (BoDEx) that was carried out in February and March 2005 in Chad. A box model version of the dust emission model is used to test different input parameters for the emission model, and to compare the dust emissions computed with observed wind speeds to those calculated with wind speeds from the regional model simulation. While field observations indicate that dust production occurs via self-abrasion of saltating diatomite flakes in the Bodélé, the emission model based on the assumption of dust production by saltation and using observed surface wind speeds as input parameters reproduces observed dust optical thicknesses well. Although the peak wind speeds in the regional model underestimate the highest wind speeds occurring on 10–12 March 2005, the spatio-temporal evolution of the dust cloud can be reasonably well reproduced by this model. Dust aerosol interacts with solar and thermal radiation in the regional model; it is responsible for a decrease in maximum daytime temperatures by about 5 K at the beginning the dust storm on 10 March 2005. This direct radiative effect of dust aerosol accounts for about half of the measured temperature decrease compared to conditions on 8 March. Results from a global dust model suggest that the dust from the Bodélé is an important contributor to dust crossing the African Savannah region towards the Gulf of Guinea and the equatorial Atlantic, where it can contribute up to 40% to the dust optical thickness.