The subseasonal forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts) wer... more The subseasonal forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts) were used to construct weekly mean wind speed forecasts for the spatially aggregated area in Finland. Reforecasts for the winters (November, December and January) of 2016-2017 and 2017-2018 were analysed. The ERA-Interim reanalysis was used as observations and climatological forecasts. We evaluated two types of forecasts, the deterministic forecasts and the probabilistic forecasts. Non-homogeneous Gaussian regression was used to bias-adjust both types of forecasts. The forecasts proved to be skilful until the third week, but the longest skilful lead time depends on the reference data sets and the verification scores used. 2 Data and Methods 2.1 Forecasts and reference observations The forecasts used in this study were extended-range forecasts of 10 m wind speed, provided by the ensemble prediction system (EPS) from the ECMWF (European Centre for Medium-Range Weather Forecasts) (ECMWF, 2016). The forecasts were issued twice a week, on Mondays and
Seasonal forecasts for forestry have been developed in the Finnish Meteorological Institute in co... more Seasonal forecasts for forestry have been developed in the Finnish Meteorological Institute in cooperation with Finnish end-users. Such forecasts could help forest companies in preparing for adverse conditions of timber harvesting operations. Bearing capacity for harvesting operations is dependent on soil moisture, and skillful forecasts have potentially large economic value. Using the ECMWF seasonal forecasts, we evaluated the monthly mean soil moisture forecasts for four different start months, with lead times from 0 to 2 months. Forecasts were bias adjusted, and showed skill in the first month for all four months. After the first lead month, winter months fared a bit better than summer months.
Seasonal forecasts for forestry have been developed in the Finnish Meteorological Institute in co... more Seasonal forecasts for forestry have been developed in the Finnish Meteorological Institute in cooperation with Finnish end-users. Such forecasts could help forest companies in preparing for adverse conditions of timber harvesting operations. Bearing capacity for harvesting operations is dependent on soil moisture, and skillful forecasts have potentially large economic value. Using the ECMWF seasonal forecasts, we evaluated the monthly mean soil moisture forecasts for four different start months, with lead times from 0 to 2 months. Forecasts were bias adjusted, and showed skill in the first month for all four months. After the first lead month, winter months fared a bit better than summer months.
Forest fire risk indexes assess the risk of forest fire occurrences. In addition to this, if a fi... more Forest fire risk indexes assess the risk of forest fire occurrences. In addition to this, if a fire does take place, it is useful to have assessment of the probability that the fire will become large and erratic. Stability of lower atmosphere plays a key role in this. Conventional sta- bility indexes that indicate the instable and moist atmospheric conditions cannot be used, because the atmosphere in a severe fire event is usually very dry. Consequently, special fire weather indexes have been developed and utilized. In this study, we investigated the widely used Haines fire index. The suitability of Haines Index to Finnish conditions has not been evaluated earlier. Thus our study was twofold, first, we explored Haines Index using radiosoundings and, second, we tried to assess what extra information satellite measurements can give. We took the advantage of ready-made profiles for both MODIS and AIRS instruments, available from NASA. The results were promising, but no definite conclus...
We compared fires detected by different satellite systems with in-situ data mainly for Finland fr... more We compared fires detected by different satellite systems with in-situ data mainly for Finland from year 2002 to year 2005. We had access to fires detected by the Finnish detection system for AVHRR images developed by VTT (Technical Research Centre of Finland), the MODIS based system developed by NASA and the University of Maryland, and the (A)ATSR based system developed by ESA. For in-situ data, we have at our disposal the database of reported Finnish fires and information about fires detected by the VTT system. We found that very few fires detected by satellite can be matched with fires from in-situ data or fires from other satellite systems. Furthermore, most of the hot spots are from controlled burning and are not reported in the Finnish fire database.
Land Surface Analysis Satellite Applications Facility (LandSAF) has been producing daily snow cov... more Land Surface Analysis Satellite Applications Facility (LandSAF) has been producing daily snow cover products for two years with a baseline algorithm using MSG/SEVIRI data. A new improved version of the product has been developed.
This guidebook addresses recent knowledge and good practices on the risk of adverse weather event... more This guidebook addresses recent knowledge and good practices on the risk of adverse weather events for passenger as well as air cargo services. It offers best practice guidance on how passengers may react and how companies should be prepared. It describes what kind of information can be used as support and how information networks and information sharing technologies between the different means of transportation may lead to higher customer satisfaction. This guidebook shall help to optimise the use of financial and environmental resources and lead to higher resilience towards induced negative effects in the global air traffic system.
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008
Hydrological processes and climate are highly affected by the seasonal changes in snow cover. Are... more Hydrological processes and climate are highly affected by the seasonal changes in snow cover. Areal extent of snow cover is essential information both for hydrology and climatology. EUMETSAT's Land Surface Analysis Satellite Applications Facility (LandSAF) has been producing fully automatic daily snow cover products for two years with a baseline algorithm (version 1.12). New algorithm (version 2.08) is now in operational use. In this paper, we describe and compare these two versions of LandSAF snow cover product to NOAA/NESDIS snow cover product in Europe. Our analysis shows that the new version is significantly better than the old version and agrees reasonably well with NOAA/NESDIS IMS product. In clear sky conditions, both products present a reasonable and realistic snow cover, particularly during the winter season.
Forecasters need climatological forecasting tools because of limitations of numerical weather pre... more Forecasters need climatological forecasting tools because of limitations of numerical weather prediction models. In this article, using Finnish SYNOP observations and ERA-40 model reanalysis data, low visibility cases are studied using subjective and objective analysis techniques. For the objective analysis, we used an AutoClass clustering algorithm, concentrating on three Finnish airports, namely, the Rovaniemi in northern Finland, Kauhava in western Finland, and Maarianhamina in southwest Finland. These airports represent different climatological conditions. Results suggested that combining of subjective analysis with an objective analysis, e.g., clustering algorithms such as the AutoClass method, can be used to construct climatological guides for forecasters. Some higher level subjective ''meta-clustering'' was used to make the results physically more reasonable and easier to interpret by the forecasters.
The subseasonal forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts) wer... more The subseasonal forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts) were used to construct weekly mean wind speed forecasts for the spatially aggregated area in Finland. Reforecasts for the winters (November, December and January) of 2016-2017 and 2017-2018 were analysed. The ERA-Interim reanalysis was used as observations and climatological forecasts. We evaluated two types of forecasts, the deterministic forecasts and the probabilistic forecasts. Non-homogeneous Gaussian regression was used to bias-adjust both types of forecasts. The forecasts proved to be skilful until the third week, but the longest skilful lead time depends on the reference data sets and the verification scores used. 2 Data and Methods 2.1 Forecasts and reference observations The forecasts used in this study were extended-range forecasts of 10 m wind speed, provided by the ensemble prediction system (EPS) from the ECMWF (European Centre for Medium-Range Weather Forecasts) (ECMWF, 2016). The forecasts were issued twice a week, on Mondays and
Seasonal forecasts for forestry have been developed in the Finnish Meteorological Institute in co... more Seasonal forecasts for forestry have been developed in the Finnish Meteorological Institute in cooperation with Finnish end-users. Such forecasts could help forest companies in preparing for adverse conditions of timber harvesting operations. Bearing capacity for harvesting operations is dependent on soil moisture, and skillful forecasts have potentially large economic value. Using the ECMWF seasonal forecasts, we evaluated the monthly mean soil moisture forecasts for four different start months, with lead times from 0 to 2 months. Forecasts were bias adjusted, and showed skill in the first month for all four months. After the first lead month, winter months fared a bit better than summer months.
Seasonal forecasts for forestry have been developed in the Finnish Meteorological Institute in co... more Seasonal forecasts for forestry have been developed in the Finnish Meteorological Institute in cooperation with Finnish end-users. Such forecasts could help forest companies in preparing for adverse conditions of timber harvesting operations. Bearing capacity for harvesting operations is dependent on soil moisture, and skillful forecasts have potentially large economic value. Using the ECMWF seasonal forecasts, we evaluated the monthly mean soil moisture forecasts for four different start months, with lead times from 0 to 2 months. Forecasts were bias adjusted, and showed skill in the first month for all four months. After the first lead month, winter months fared a bit better than summer months.
Forest fire risk indexes assess the risk of forest fire occurrences. In addition to this, if a fi... more Forest fire risk indexes assess the risk of forest fire occurrences. In addition to this, if a fire does take place, it is useful to have assessment of the probability that the fire will become large and erratic. Stability of lower atmosphere plays a key role in this. Conventional sta- bility indexes that indicate the instable and moist atmospheric conditions cannot be used, because the atmosphere in a severe fire event is usually very dry. Consequently, special fire weather indexes have been developed and utilized. In this study, we investigated the widely used Haines fire index. The suitability of Haines Index to Finnish conditions has not been evaluated earlier. Thus our study was twofold, first, we explored Haines Index using radiosoundings and, second, we tried to assess what extra information satellite measurements can give. We took the advantage of ready-made profiles for both MODIS and AIRS instruments, available from NASA. The results were promising, but no definite conclus...
We compared fires detected by different satellite systems with in-situ data mainly for Finland fr... more We compared fires detected by different satellite systems with in-situ data mainly for Finland from year 2002 to year 2005. We had access to fires detected by the Finnish detection system for AVHRR images developed by VTT (Technical Research Centre of Finland), the MODIS based system developed by NASA and the University of Maryland, and the (A)ATSR based system developed by ESA. For in-situ data, we have at our disposal the database of reported Finnish fires and information about fires detected by the VTT system. We found that very few fires detected by satellite can be matched with fires from in-situ data or fires from other satellite systems. Furthermore, most of the hot spots are from controlled burning and are not reported in the Finnish fire database.
Land Surface Analysis Satellite Applications Facility (LandSAF) has been producing daily snow cov... more Land Surface Analysis Satellite Applications Facility (LandSAF) has been producing daily snow cover products for two years with a baseline algorithm using MSG/SEVIRI data. A new improved version of the product has been developed.
This guidebook addresses recent knowledge and good practices on the risk of adverse weather event... more This guidebook addresses recent knowledge and good practices on the risk of adverse weather events for passenger as well as air cargo services. It offers best practice guidance on how passengers may react and how companies should be prepared. It describes what kind of information can be used as support and how information networks and information sharing technologies between the different means of transportation may lead to higher customer satisfaction. This guidebook shall help to optimise the use of financial and environmental resources and lead to higher resilience towards induced negative effects in the global air traffic system.
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008
Hydrological processes and climate are highly affected by the seasonal changes in snow cover. Are... more Hydrological processes and climate are highly affected by the seasonal changes in snow cover. Areal extent of snow cover is essential information both for hydrology and climatology. EUMETSAT's Land Surface Analysis Satellite Applications Facility (LandSAF) has been producing fully automatic daily snow cover products for two years with a baseline algorithm (version 1.12). New algorithm (version 2.08) is now in operational use. In this paper, we describe and compare these two versions of LandSAF snow cover product to NOAA/NESDIS snow cover product in Europe. Our analysis shows that the new version is significantly better than the old version and agrees reasonably well with NOAA/NESDIS IMS product. In clear sky conditions, both products present a reasonable and realistic snow cover, particularly during the winter season.
Forecasters need climatological forecasting tools because of limitations of numerical weather pre... more Forecasters need climatological forecasting tools because of limitations of numerical weather prediction models. In this article, using Finnish SYNOP observations and ERA-40 model reanalysis data, low visibility cases are studied using subjective and objective analysis techniques. For the objective analysis, we used an AutoClass clustering algorithm, concentrating on three Finnish airports, namely, the Rovaniemi in northern Finland, Kauhava in western Finland, and Maarianhamina in southwest Finland. These airports represent different climatological conditions. Results suggested that combining of subjective analysis with an objective analysis, e.g., clustering algorithms such as the AutoClass method, can be used to construct climatological guides for forecasters. Some higher level subjective ''meta-clustering'' was used to make the results physically more reasonable and easier to interpret by the forecasters.
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Papers by Otto Hyvärinen