Method and models in meteorological research

A core of meteorological research and development is numerical computational systems. We work on research and development to continuously improve these systems and we use them in our research projects.

Today, computational models in the meteorological field can be part of larger model systems developed in international collaboration. Development efforts may include the addition of new observational sources, more sophisticated algorithms for more complete description of initial state for forecast calculations, and improved descriptions of atmospheric and surface processes.

Weather forecasting system

In the field of weather forecasting, we collaborate within the HIRLAM and ACCORD consortia for the development of the HARMONIE-AROME weather forecasting system, which is the basis for our weather forecast production. Part of the work is done together with the weather services in Norway, Finland, Estonia, Latvia and Lithuania in the MetCoOp project.

Our research and development has contributed to transform the NWP (Numerical Weather Prediction) system into a modern ensemble forecast system (MEPS) that is currently used as the basis for SMHI's operational weather forecasts and for various special forecasts, for example in renewable energy and road weather applications.

We are also behind the development of MESAN and KNEP, two numerical models for local short-term forecasts and short precipitation forecasts, which are used in SMHI's weather forecast production. For both MESAN and KNEP, radar data are used as part of the basis for analysis and forecasting.

Solar radiation model, STRÅNG

To calculate surface solar radiation, SMHI's research, together with the Swedish Radiation Safety Authority and the Swedish Environmental Protection Agency, has created the model system STRÅNG. STRÅNG calculates a series of radiation parameters at the ground surface over north-western Europe for each hour.

Solar radiation research

Tools and models for air quality

In the field of air quality, we have developed the MATCH atmospheric chemistry dispersion model that can be used to study air pollution over the Northern Hemisphere. With the MATCH model, calculations can be made to find out how different types of particles are dispersed in the air, for example from emissions and wear particles from road traffic, soot from fires, dust from volcanic eruptions and large sandstorms in desert areas, or emissions from possible nuclear accidents. The MATCH model can also be used to study the consequences of air pollution, such as acidification and eutrophication, health problems and negative impacts on vegetation.

MATCH - transport and chemistry model

The MATCH model is used within the Copernicus Atmosphere Monitoring Service (CAMS) to calculate air quality in Europe, in the framework of which calculations are being developed for the distribution of certain pollens (birch, grass, olive, ragweed, alder and graywood). You can see current air quality forecasts via the CAMS website.

SMHI contributes to improved air quality services in the CAMS consortium

SMHI's air quality consultants use the SIMAIR tool, a tool based on SMHI's air quality research.

Research and development for radar and satellite

SMHI has a long tradition in research and development to use data from radar and satellite in various meteorological applications. Satellite and weather radar observations provide good resolution in both time and space and are also available where few other observations are available, such as at sea.

SMHI participates in the European meteorological collaborations EUMETNET and EUMETSAT where we work on research and development for radar and satellite. We develop methodology and software to receive and process data from radar and satellite so that they can be rapidly used by national weather services for forecasts and warnings. This is particularly important in nowcasting, i.e. short-term forecasts for the next few hours.

In the satellite field, we are working on research and development to create software and algorithms for the automatic analysis of clouds and precipitation in satellite images. Forecasters use this for nowcasting and in the automatic generation of basic analyses of the current weather situation with high resolution in time and space. We also conduct research and development on methodology and analysis of clouds on longer time scales, for climatological studies. This work is carried out through the projects Nowcasting SAF and Climate Monitoring SAF (Satellite Application Facilities), funded through the European Union Meteorological Satellite Organisation (EUMETSAT).


EUMETSAT Climate Monitoring SAF

Pytroll, Open source satellite software network

The Pytroll project started in 2009 as a collaborative project between SMHI and the Danish DMI to develop and maintain Python-based Open Source software for reading and processing Earth observations from satellites. Pytroll has now grown into an international community with contributors from all over the world and several hundred users, including many of the European weather services. Sharing resources between countries brings cost efficiencies, and with free and open source code, production systems become better and more robust.

Pytroll – international code collaboration for satellite applications


Radar data is a very important source of information for forecasters who need to assess and make forecasts on a short timescale, especially in extreme weather situations such as heavy downpours and snowstorms.

The Baltrad project started in 2009 to provide weather radar imagery over the Baltic Sea area. SMHI developed software to relay the radar images.

To BALTRAD website

Cloud Radar

ACTRIS Sweden is a research infrastructure for long-term and quality-assured observation of short-term climate pollution (greenhouse gases) including aerosols and clouds. SMHI contributes to ACTRIS with a cloud radar located at the research station in Norunda outside Uppsala. A cloud radar monitors the vertical structure of clouds and whether they consist of water droplets or ice crystals. This improves our understanding of the impact of clouds on weather and climate. Data from a cloud radar can be used to evaluate clouds in satellite data and models and provides opportunities for research in air dynamics, cloud physics, precipitation and model evaluation.

There is also a disdrometer installed in Norunda. A disdrometer measures the drop size distribution of precipitation passing the sensor. Data is also available from this disdrometer.