Laura Rontu

The HARMONIE–AROME Model Configuration in the ALADIN–HIRLAM NWP System

AbstractThe aim of this article is to describe the reference configuration of the convection-permitting numerical weather prediction (NWP) model HARMONIE-AROME, which is used for operational short-range weather forecasts in Denmark, Estonia, Finland, Iceland, Ireland, Lithuania, the Netherlands, Norway, Spain, and Sweden. It is developed, maintained, and validated as part of the shared ALADIN–HIRLAM system by a collaboration of 26 countries in Europe and northern Africa on short-range mesoscale NWP. HARMONIE–AROME is based on the model AROME developed within the ALADIN consortium. Along with the joint modeling framework, AROME was implemented and utilized in both northern and southern European conditions by the above listed countries, and this activity has led to extensive updates to the model’s physical parameterizations. In this paper the authors present the differences in model dynamics and physical parameterizations compared with AROME, as well as important configuration choices of the reference, such...

Snow and ice on Bear Lake (Alaska) – sensitivity experiments with two lake ice models

ABSTRACT Snow and ice thermodynamics of Bear Lake (Alaska) are investigated with a simple freshwater lake model (FLake) and a more complex snow and ice thermodynamic model (HIGHTSI). A number of sensitivity experiments have been carried out to investigate the influence of snow and ice parameters and of different complexity on the results. Simulation results are compared with observations from the Alaska Lake Ice and Snow Observatory Network. Adaptations of snow thermal and optical properties in FLake can largely improve accuracy of the results. Snow-to-ice transformation is important for HIGHTSI to calculate the total ice mass balance. The seasonal maximum ice depth is simulated in FLake with a bias of −0.04 m and in HIGHTSI with no bias. Correlation coefficients between ice depth measurements and simulations are high (0.74 for FLake and 0.9 for HIGHTSI). The snow depth simulation can be improved by taking into account a variable snow density. Correlation coefficients for surface temperature are 0.72 for FLake and 0.81 for HIGHTSI. Overall, HIGHTSI gives slightly more accurate surface temperature than FLake probably due to the consideration of multiple snow and ice layers and the expensive iteration calculation procedure.

Data assimilation and parametrisation of lakes in HIRLAM

ABSTRACT When the resolution of numerical weather prediction (NWP) and climate models increases, it becomes more and more important to correctly account for the lake–atmosphere interactions. One possible way to handle lake effects is to use a lake model, which treats the lake surface temperature and ice conditions as prognostic variables. Such a parametrisation eliminates the traditional for NWP need to prescribe lake characteristics based on long-term climate averages. At the same time, new in situ and satellite measurements are becoming available for an operational practice. This offers the possibility to assimilate lake observations into the NWP models. We study the applicability of the prognostic and observation-based approaches and compare both. As a first step towards integrated lake data assimilation and forecasting in NWP, we suggest using the results of the prognostic lake parametrisation as the background for objective analysis (spatialisation) of the lake water surface temperature observations. We run NWP experiments in the Nordic conditions, where the freezing and melting of lakes can significantly influence local weather. Our results indicate that a lake model, usually used in climate studies, works well also in the NWP model even without assimilation of observations. However, it is possible to improve the description of the changing lake surface state by using good observation data. In this case, the lake model provides a better background for the data assimilation than a lake surface temperature climatology.

Modelling snow and ice thickness in the coastal Kara Sea, Russian Arctic

Abstract Snow and ice thickness in the coastal Kara Sea, Russian Arctic, were investigated by applying the thermodynamic sea-ice model HIGHTSI. The external forcing was based on two numerical weather prediction (NWP) models: the High Resolution Limited Area Model (HIRLAM) and the European Centre for Medium-Range Weather Forecasts (ECMWF) model. A number of model experiments were carried out applying different snow parameterization schemes. The modelled ice thickness was compared with in situ measurements and the modelled snow thickness was compared with the NASA Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) snow thickness. The HIRLAM and ECMWF model results agreed with each other on air temperature and wind. The NWP model precipitation forecasts caught up the synoptic-scale snowfall events, but the magnitude was liable to errors. The ice growth was modelled reasonably well applying HIGHTSI either with a simple parameterization for snow thickness or with the HIRLAM or ECMWF model precipitation as input. For the latter, however, an adjustment of snow accumulation in early winter was necessary to avoid excessive accumulation and consequent underestimation of ice thickness. Applying effective snow heat conductivity improved the modelled ice thickness. The HIGHTSI-modelled snow thickness had a seasonal evolution similar to that of the AMSR-E snow thickness. New field data are urgently needed to validate NWP and ice models and remote-sensing products for snow and sea ice in the Kara Sea.

Evolution of snow and ice temperature, thickness and energy balance in Lake Orajärvi, northern Finland

The seasonal evolution of snow and ice on Lake Orajärvi, northern Finland, was investigated for three consecutive winter seasons. Material consisting of numerical weather prediction model (HIRLAM) output, weather station observations, manual snow and ice observations, high spatial resolution snow and ice temperatures from ice mass balance buoys (SIMB), and Moderate Resolution Imaging Spectroradiometer (MODIS) lake ice surface temperature observations was gathered. A snow/ice model (HIGHTSI) was applied to simulate the evolution of the snow and ice surface energy balance, temperature profiles and thickness. The weather conditions in early winter were found critical in determining the seasonal evolution of the thickness of lake ice and snow. During the winter season (Nov.–Apr.), precipitation, longwave radiative flux and air temperature showed large inter-annual variations. The uncertainty in snow/ice model simulations originating from precipitation was investigated. The contribution of snow to ice transformation was vital for the total lake ice thickness. At the seasonal time scale, the ice bottom growth was 50–70% of the total ice growth. The SIMB is suitable for monitoring snow and ice temperatures and thicknesses. The Mean Bias Error (MBE) between the SIMB and borehole measurements was −0.7 cm for snow thicknesses and 1.7 cm for ice thickness. The temporal evolution of MODIS surface temperature (three seasons) agrees well with SIMB and HIGHTSI results (correlation coefficient, R=0.81). The HIGHTSI surface temperatures were, however, higher (2.8°C≤MBE≤3.9°C) than the MODIS observations. The development of HIRLAM by increasing its horizontal and vertical resolution and including a lake parameterisation scheme improved the atmospheric forcing for HIGHTSI, especially the relative humidity and solar radiation. Challenges remain in accurate simulation of snowfall events and total precipitation.

Impact of satellite-based lake surface observations on the initial state of HIRLAM. Part II: Analysis of lake surface temperature and ice cover

This paper presents results from a study on the impact of remote-sensing Lake Surface Water Temperature (LSWT) observations in the analysis of lake surface state of a numerical weather prediction (NWP) model. Data assimilation experiments were performed with the High Resolution Limited Area Model (HIRLAM), a three-dimensional operational NWP model. Selected thermal remote-sensing LSWT observations provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Along-Track Scanning Radiometer (AATSR) sensors onboard the Terra/Aqua and ENVISAT satellites, respectively, were included into the assimilation. The domain of our experiments, which focussed on two winters (2010–2011 and 2011–2012), covered northern Europe. Validation of the resulting objective analyses against independent observations demonstrated that the description of the lake surface state can be improved by the introduction of space-borne LSWT observations, compared to the result of pure prognostic parameterisations or assimilation of the available limited number of in-situ lake temperature observations. Further development of the data assimilation methods and solving of several practical issues are necessary in order to fully benefit from the space-borne observations of lake surface state for the improvement of the operational weather forecast. This paper is the second part of a series of two papers aimed at improving the objective analysis of lake temperature and ice conditions in HIRLAM.

Influence of the Details of Topography on Weather Forecast – Evaluation of HARMONIE Experiments in the Sochi Olympics Domain over the Caucasian Mountains

New fine-resolution surface elevation data was implemented into HARMONIE-AROME-SURFEX Numerical Weather Prediction (NWP) system. The grid-scale mean orography, used as a basis of the models terrain-following vertical coordinate, as well as variables for suggested new parametrizations of radiation and momentum fluxes were derived. Validation against the surface observations from the Sochi Winter Olympic Games 2014, provided by the WMO FROST-2014 program at the Caucasian mountains, showed minor degradation of the of then screen-level temperature forecast when only the source orography was updated. Implementation of the orographic radiation parametrizations allowed to alleviate the degradation of scores. Detailed sensitivity studies, done by using three-dimensional and single-column experiments, showed that substantial and physically realistic changes in the downwelling short- and longwave radiation fluxes took place locally. However, their influence on the the simulated screen-level temperature remained small. Comparison of the simulated and observed radiation fluxes would offer a reliable alternative for validation of NWP models. Unfortunately, surface-level radiation observations were not made during the Sochi Olympics.

Impact of partly ice-free Lake Ladoga on temperature and cloudiness in an anticyclonic winter situation - a case study using a limited area model

At the end of January 2012, a low-level cloud from partly ice-free Lake Ladoga caused very variable 2-m temperatures in Eastern Finland. The sensitivity of the High Resolution Limited Area Model (HIRLAM) to the lake surface conditions was tested in this winter anticyclonic situation. The lake appeared to be (incorrectly) totally covered by ice when the lake surface was described with its climatology. Both parametrisation of the lake surface state by using a lake model integrated to the NWP system and objective analysis based on satellite observations independently resulted in a correct description of the partly ice-free Lake Ladoga. In these cases, HIRLAM model forecasts were able to predict cloud formation and its movement as well as 2-m temperature variations in a realistic way. Three main conclusions were drawn. First, HIRLAM could predict the effect of Lake Ladoga on local weather, when the lake surface state was known. Second, the current parametrisation methods of air–surface interactions led to a reliable result in conditions where the different physical processes (local surface processes, radiation and turbulence) were not strong, but their combined effect was important. Third, these results encourage work for a better description of the lake surface state in NWP models by fully utilising satellite observations, combined with advanced lake parametrisation and data assimilation methods.

HIRLAM/HARMONIE-Atmospheric Chemical Transport Models Integration

The ‘HIRLAM/HARMONIE-ACTMs Integration’ discussion session was held on Tuesday (22 May 2007) during the COST-728-NetFAM ‘Model Integration’ workshop.

Vorticity budget over mountains, estimated from HIRLAM analyses and forecasts

The analysis of vorticity budgets offers a possibility for validation and diagnosis of a NWP model. The source terms of the equation are related to the resolved and subgrid-scale torque due to the orography and surface properties. In this study, the vorticity method was applied to the diagnosis of High Resolution Limited Area Model (HIRLAM). The terms resolved by the model were estimated from three-dimensional numerical analyses and forecasts. In the vertically integrated equation, these terms sum up to give an estimate of required torque due to the subgrid-scale surface stress, which was compared with the corresponding value given by the physical parametrizations of the model. The magnitude of the parametrized subgrid-scale torque was about a half of that derived from the integrated vorticity budget. Diagnosis of the complicated terms of the equation requires special attention to the discretization and numerical approximations. A detailed discussion of the advantages and disadvantages of the method is included.