Solar irradiance dominates our world and influences not only climate dynamics but also our health, driving our group’s interest in understanding its full spectrum impact, from UV to VIS, NIR, and SWIR wavelengths. Our group specializes in both satellite processing and in-situ remote sensing data acquisition and analysis, utilizing satellite data to gain valuable insights into aerosols, clouds, water vapor, and more. We dedicate our efforts to developing atmospheric correction algorithms for extracting reliable surface-related information from satellite observations. With ground-based measurements, we continuously monitor atmospheric composition, including ozone concentration, UV radiation, and aerosols, generating highly valuable long-term datasets. Our group brings substantial expertise in these fields, fostering collaborations with international partners and actively participating in numerous international projects. Contact us to join as we delve into the intricacies of atmospheric radiation, advancing our understanding of Earth’s dynamic systems.

Get to know our work better:

Aerosol retrieval, air quality, and atmospheric correction

Our group is dedicated to aerosol retrieval and characterization from satellite-based measurements (e.g., SLSTR, MODIS), high-resolution air quality retrievals using advanced statistical inference methods, and the development of atmospheric correction algorithms, particularly for hyperspectral instruments. At the ground level, we utilize e.g., CIMEL instruments, which are part of the AERONET and SKYNET international networks.

Aerosol-Cloud Interactions 

We study aerosol-cloud interactions and the related radiative forcing mainly using satellite and meteorological re-analysis data. The focus has been both on the Twomey effect and rapid adjustments of warm marine boundary layer clouds.

Solar-induced vegetation fluorescence

During photosynthesis, a small fraction of the absorbed light energy is re-emitted as solar-induced fluorescence (SIF) in the form of longer-wavelength light (650-800) nm. This fluorescence signal provides valuable information about the photosynthetic activity, vegetation carbon uptake, and physiological status of plants. In our group, we have developed our own fluorescence retrieval method (SIFFI), we actively participate in the preparatory activities of the ESA FLEX explorer satellite mission, and we monitor the Arctic vegetation response to climate change with a FLOX ground-based system. 

UV radiation 

Our research focuses on analyzing long-term ozone column concentration and UV radiation data records. The UV research also includes the effects of UV radiation on material aging, health, plant growth and planning of build environment.

The experts of the group

Our group members work at FMI offices in Kuopio, Helsinki, Rovaniemi, and Sodankylä.

email: firstname.lastname@fmi.fi

Veijo Aaltonen, PhLic, Scientist (aerosol measurements)

Antti Arola, PhD, Head of Group, Research Professor (remote sensing of aerosols, atmospheric radiative transfer), tel. +358 29539 2129, gsm +358 50 307 2131

Anu Heikkilä, PhD, Senior Scientist (UV radiation)

Pekka Kolmonen, PhD, Senior Scientist (remote sensing of aerosols and clouds, atmospheric radiative transfer, solar-induced fluorescence retrievals)

Antti Kukkurainen, MSc, Scientist (remote sensing of aerosols, atmospheric radiative transfer, solar-induced fluorescence retrievals)

Kaisa Lakkala, PhD, Senior Scientist (UV radiation), Title of docent (Arctic climate and UV radiation research)

Antti Lipponen, PhD, Senior Scientist (remote sensing of aerosols, statistical analysis, inverse problems, machine learning)

Mikko Pitkänen, MSc, Scientist (remote sensing of aerosols)

Neus Sabater Medina, PhD, Senior Scientist (atmospheric correction algorithms, solar-induced fluorescence retrievals)

Larisa Sogacheva, PhD, Adj. Prof., Senior Scientist (remote sensing of aerosols and clouds, Climate Data Records)

Timo Virtanen, PhD, Senior Scientist (remote sensing of aerosols and clouds, atmospheric radiative transfer)

Arttu Väisänen, MSc, Scientist (remote sensing of aerosols, machine learning)