18 Jun 2020
| 18 Jun 2020
Statistics of sea-effect snowfall along the Finnish coastline based on regional climate model data
Finnish Meteorological Institute, PL 503, 00101 Helsinki, Finland
Anna Luomaranta
Finnish Meteorological Institute, PL 503, 00101 Helsinki, Finland
Kirsti Jylhä
Finnish Meteorological Institute, PL 503, 00101 Helsinki, Finland
Julia Jeworrek
Department of Earth, Ocean and Atmospheric Sciences, University of
British Columbia, Vancouver, Canada
Tuuli Perttula
Finnish Meteorological Institute, PL 503, 00101 Helsinki, Finland
Christian Dieterich
Swedish Meteorological and Hydrological Institute, Norrköping,
Sweden
Lichuan Wu
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Anna Rutgersson
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Centre of Natural Hazards and Disaster Science (CNDS), Uppsala
University, Uppsala, Sweden
Antti Mäkelä
Finnish Meteorological Institute, PL 503, 00101 Helsinki, Finland
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A natural hazard is a naturally occurring extreme event with a negative effect on people, society, or the environment; major events in the study area include wind storms, extreme waves, high and low sea level, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. In the future, an increase in sea level, extreme precipitation, heat waves, and phytoplankton blooms is expected, and a decrease in cold spells and severe ice winters is anticipated.
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Revised manuscript not accepted
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Climate change impacts on floods in Finland were estimated on several locations. Regional climate model data was bias corrected and then used as input of a hydrological model and the function of the bias correction was evaluated. The bias correction improved the simulation of floods, but some scenarios are still unable to match the observed hydrology adequately. The changes in floods by 2070–2099 vary in different regions in Finland depending on season and the main flood producing mechanism.
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Adv. Sci. Res., 14, 231–239, https://doi.org/10.5194/asr-14-231-2017, https://doi.org/10.5194/asr-14-231-2017, 2017
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A new national daily snowfall record was measured in Finland in January 2016 when it snowed 73 cm in less than a day at a small town on the western coast of Finland. The area of the most intense snowfall was very small, which is common in convective precipitation. In this work we used hourly weather radar images to identify the sea-effect snowfall case and found that a weather prediction model worked quite well in simulating the snowbands.
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With most scenarios the DBS method used preserves the temperature and precipitation trends of the uncorrected RCM data and produces more realistic projections for mean annual and seasonal changes in discharges than the uncorrected RCM data in Finland. However, if the biases in the mean or the standard deviation of the uncorrected temperatures are large, significant biases after DBS adjustment may remain or temperature trends may change, increasing the uncertainty of climate change projections.
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Kévin Dubois, Morten Andreas Dahl Larsen, Martin Drews, Erik Nilsson, and Anna Rutgersson
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Anna Rutgersson, Erik Kjellström, Jari Haapala, Martin Stendel, Irina Danilovich, Martin Drews, Kirsti Jylhä, Pentti Kujala, Xiaoli Guo Larsén, Kirsten Halsnæs, Ilari Lehtonen, Anna Luomaranta, Erik Nilsson, Taru Olsson, Jani Särkkä, Laura Tuomi, and Norbert Wasmund
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Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-314, https://doi.org/10.5194/nhess-2021-314, 2021
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Matthias Gröger, Christian Dieterich, Jari Haapala, Ha Thi Minh Ho-Hagemann, Stefan Hagemann, Jaromir Jakacki, Wilhelm May, H. E. Markus Meier, Paul A. Miller, Anna Rutgersson, and Lichuan Wu
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Jens Daniel Müller, Bernd Schneider, Ulf Gräwe, Peer Fietzek, Marcus Bo Wallin, Anna Rutgersson, Norbert Wasmund, Siegfried Krüger, and Gregor Rehder
Biogeosciences, 18, 4889–4917, https://doi.org/10.5194/bg-18-4889-2021, https://doi.org/10.5194/bg-18-4889-2021, 2021
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Roope Tervo, Ilona Láng, Alexander Jung, and Antti Mäkelä
Nat. Hazards Earth Syst. Sci., 21, 607–627, https://doi.org/10.5194/nhess-21-607-2021, https://doi.org/10.5194/nhess-21-607-2021, 2021
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Predicting the number of power outages caused by extratropical storms is a key challenge for power grid operators. We introduce a novel method to predict the storm severity for the power grid employing ERA5 reanalysis data combined with a forest inventory. The storms are first identified from the data and then classified using several machine-learning methods. While there is plenty of room to improve, the results are already usable, with support vector classifier providing the best performance.
Christian Dieterich, Matthias Gröger, Lars Arneborg, and Helén C. Andersson
Ocean Sci., 15, 1399–1418, https://doi.org/10.5194/os-15-1399-2019, https://doi.org/10.5194/os-15-1399-2019, 2019
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Robinson Hordoir, Lars Axell, Anders Höglund, Christian Dieterich, Filippa Fransner, Matthias Gröger, Ye Liu, Per Pemberton, Semjon Schimanke, Helen Andersson, Patrik Ljungemyr, Petter Nygren, Saeed Falahat, Adam Nord, Anette Jönsson, Iréne Lake, Kristofer Döös, Magnus Hieronymus, Heiner Dietze, Ulrike Löptien, Ivan Kuznetsov, Antti Westerlund, Laura Tuomi, and Jari Haapala
Geosci. Model Dev., 12, 363–386, https://doi.org/10.5194/gmd-12-363-2019, https://doi.org/10.5194/gmd-12-363-2019, 2019
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Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and the North Sea area and is used as a forecast model by the Swedish Meteorological and Hydrological Institute. It is also used as a research tool by scientists of several countries to study, for example, the effects of climate change on the Baltic and North seas. Using such a model permits us to understand key processes in this coastal ecosystem and how such processes will change in a future climate.
Tiina Ervasti, Hilppa Gregow, Andrea Vajda, Terhi K. Laurila, and Antti Mäkelä
Adv. Sci. Res., 15, 99–106, https://doi.org/10.5194/asr-15-99-2018, https://doi.org/10.5194/asr-15-99-2018, 2018
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An online survey was used to map the needs and preferences of the Finnish general public about extended-range forecasts and their presentation. Survey results guided the co-design process of novel extended-range forecasts in the project. The respondents considered that the tailored extended-range forecasts would be beneficial in planning activities, preparing for weather risks and scheduling everyday life. They also valued impact information higher than advice on how to prepare for the impacts.
Sofia Saraiva, H. E. Markus Meier, Helén Andersson, Anders Höglund, Christian Dieterich, Robinson Hordoir, and Kari Eilola
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2018-16, https://doi.org/10.5194/esd-2018-16, 2018
Revised manuscript not accepted
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Uncertainties are estimated in Baltic Sea climate projections by performing scenarios combining 4 Global Climate Models, 2 future gas emissions (RCP4.5, RCP8.5) and 3 nutrient load scenarios. Results on primary production, nitrogen fixation, and hypoxic areas show that uncertainties caused by the nutrients loads are greater than uncertainties due to GCMs and RCPs. In all scenarios, nutrient load abatement strategy, Baltic Sea Action Plan, will lead to an improvement in the environmental state.
Gaëlle Parard, Anna Rutgersson, Sindu Raj Parampil, and Anastase Alexandre Charantonis
Earth Syst. Dynam., 8, 1093–1106, https://doi.org/10.5194/esd-8-1093-2017, https://doi.org/10.5194/esd-8-1093-2017, 2017
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Coastal environments and shelf sea represent 7.6 % of the total oceanic surface area. They are, however, biogeochemically more dynamic and probably more vulnerable to climate change than the open ocean. Whatever the responses of the open ocean to climate change, they will propagate to the coastal ocean. We used the self-organizing multiple linear output (SOMLO) method to estimate the ocean surface pCO2 in the Baltic Sea from remotely sensed measurements and we estimated the air–sea CO2 flux.
Noora Veijalainen, Juho Jakkila, Taru Olsson, Leif Backman, Bertel Vehviläinen, and Jussi Kaurola
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-602, https://doi.org/10.5194/hess-2017-602, 2017
Revised manuscript not accepted
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Climate change impacts on floods in Finland were estimated on several locations. Regional climate model data was bias corrected and then used as input of a hydrological model and the function of the bias correction was evaluated. The bias correction improved the simulation of floods, but some scenarios are still unable to match the observed hydrology adequately. The changes in floods by 2070–2099 vary in different regions in Finland depending on season and the main flood producing mechanism.
Björn Claremar, Karin Haglund, and Anna Rutgersson
Earth Syst. Dynam., 8, 901–919, https://doi.org/10.5194/esd-8-901-2017, https://doi.org/10.5194/esd-8-901-2017, 2017
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Shipping is the most cost-effective option for the global transport of goods, and over 90 % of world trade is carried by sea. The shipping sector, however, contributes to emissions of pollutants into the air and water. Estimates of deposition and near-surface concentrations of sulfur, nitrogen, and particulate matter originating from shipping in the Baltic Sea region have been developed for present conditions concerning traffic intensity and fuel as well as for future scenarios until 2050.
Taru Olsson, Tuuli Perttula, Kirsti Jylhä, and Anna Luomaranta
Adv. Sci. Res., 14, 231–239, https://doi.org/10.5194/asr-14-231-2017, https://doi.org/10.5194/asr-14-231-2017, 2017
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A new national daily snowfall record was measured in Finland in January 2016 when it snowed 73 cm in less than a day at a small town on the western coast of Finland. The area of the most intense snowfall was very small, which is common in convective precipitation. In this work we used hourly weather radar images to identify the sea-effect snowfall case and found that a weather prediction model worked quite well in simulating the snowbands.
Julia Jeworrek, Lichuan Wu, Christian Dieterich, and Anna Rutgersson
Earth Syst. Dynam., 8, 163–175, https://doi.org/10.5194/esd-8-163-2017, https://doi.org/10.5194/esd-8-163-2017, 2017
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Convective snow bands develop in response to a cold air outbreak from the continent over an open water surface. In the Baltic Sea region these cause intense snowfall and can cause serious problems for traffic, infrastructure and other important establishments of society. The conditions for these events to occur were characterized and the potential of using a regional modelling system was evaluated. The modelling system was used to develop statistics of these events to occur in time and space.
Matti Kämäräinen, Otto Hyvärinen, Kirsti Jylhä, Andrea Vajda, Simo Neiglick, Jaakko Nuottokari, and Hilppa Gregow
Nat. Hazards Earth Syst. Sci., 17, 243–259, https://doi.org/10.5194/nhess-17-243-2017, https://doi.org/10.5194/nhess-17-243-2017, 2017
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Freezing rain is a high-impact wintertime weather phenomenon. The direct damage it causes to critical infrastructure (transportation, communication and energy) and forestry can be substantial. In this work a method for estimating the occurrence of freezing rain was evaluated and used to derive the climatology. The method was able to accurately reproduce the observed, spatially aggregated annual variability. The highest frequencies of freezing rain were found in eastern and central Europe.
Erik Gregow, Antti Pessi, Antti Mäkelä, and Elena Saltikoff
Hydrol. Earth Syst. Sci., 21, 267–279, https://doi.org/10.5194/hess-21-267-2017, https://doi.org/10.5194/hess-21-267-2017, 2017
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A new lightning data assimilation method has been implemented and validated within the Finnish Meteorological Institute – Local Analysis and Prediction System. Lightning data do improve the analysis when no radars are available, and even with radar data, lightning data have a positive impact on the results.
We also investigate the usage of different time integration intervals: 1, 6, 12, 24 h and 7 days, where the 1 h integration time length gives the best results.
Tito Maldonado, Anna Rutgersson, Eric Alfaro, Jorge Amador, and Björn Claremar
Adv. Geosci., 42, 35–50, https://doi.org/10.5194/adgeo-42-35-2016, https://doi.org/10.5194/adgeo-42-35-2016, 2016
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We studied the relationship between the midsummer drought (MSD) in Central America, and the sea surface temperatures (SST) of the neighbouring ocean in interannual scales. Besides, the motivation of this study is also to provide a systematic method for forecasting the MSD period. We found that the intensity and the magnitude of the MSD shown a strong association with the contrast in the surface temperatures between the eastern tropical Pacific, and the tropical north Atlantic.
T. Olsson, J. Jakkila, N. Veijalainen, L. Backman, J. Kaurola, and B. Vehviläinen
Hydrol. Earth Syst. Sci., 19, 3217–3238, https://doi.org/10.5194/hess-19-3217-2015, https://doi.org/10.5194/hess-19-3217-2015, 2015
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With most scenarios the DBS method used preserves the temperature and precipitation trends of the uncorrected RCM data and produces more realistic projections for mean annual and seasonal changes in discharges than the uncorrected RCM data in Finland. However, if the biases in the mean or the standard deviation of the uncorrected temperatures are large, significant biases after DBS adjustment may remain or temperature trends may change, increasing the uncertainty of climate change projections.
G. Parard, A. A. Charantonis, and A. Rutgerson
Biogeosciences, 12, 3369–3384, https://doi.org/10.5194/bg-12-3369-2015, https://doi.org/10.5194/bg-12-3369-2015, 2015
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In this paper, we used combines two existing methods (i.e. self-organizing maps and multiple linear regression) to estimate the ocean surface partial pressure of CO2 in the Baltic Sea from the remotely sensed sea surface temperature, chlorophyll, coloured dissolved organic matter, net primary production, and
mixed-layer depth. The outputs of this research have a horizontal resolution of 4km and cover the 1998–2011 period. These outputs give a monthly map of the Baltic Sea.
H. Gregow, P. Poli, H. M. Mäkelä, K. Jylhä, A. K. Kaiser-Weiss, A. Obregon, D. G. H. Tan, S. Kekki, and F. Kaspar
Adv. Sci. Res., 12, 63–67, https://doi.org/10.5194/asr-12-63-2015, https://doi.org/10.5194/asr-12-63-2015, 2015
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Many users of climate information are unaware of the availability of reanalysis feedback data and input observations, and uptake of feedback data is rather low. The most important factors limiting the use of this data is that the users feel that there is no easy interface to get the data or they do not find it at all. The relevant communities should invest resources to develop tools and provide training to bridge the gap between current capabilities and comprehensive exploitation of the data.
P. Räisänen, A. Luomaranta, H. Järvinen, M. Takala, K. Jylhä, O. N. Bulygina, K. Luojus, A. Riihelä, A. Laaksonen, J. Koskinen, and J. Pulliainen
Geosci. Model Dev., 7, 3037–3057, https://doi.org/10.5194/gmd-7-3037-2014, https://doi.org/10.5194/gmd-7-3037-2014, 2014
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Short summary
Snowmelt influences greatly the climatic conditions in spring. This study evaluates the timing of springtime end of snowmelt in the ECHAM5 model. A key finding is that, in much of northern Eurasia, snow disappears too early in ECHAM5, in spite of a slight cold bias in spring. This points to the need for a more comprehensive treatment of the surface energy budget. In particular, the surface temperature for the snow-covered and snow-free parts of a climate model grid cell should be separated.
E. Podgrajsek, E. Sahlée, D. Bastviken, J. Holst, A. Lindroth, L. Tranvik, and A. Rutgersson
Biogeosciences, 11, 4225–4233, https://doi.org/10.5194/bg-11-4225-2014, https://doi.org/10.5194/bg-11-4225-2014, 2014
L. Wu, Y. Wen, D. Wu, J. Zhang, and C. Xiao
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-2-4907-2014, https://doi.org/10.5194/nhessd-2-4907-2014, 2014
Revised manuscript has not been submitted
A. Virkkula, J. Levula, T. Pohja, P. P. Aalto, P. Keronen, S. Schobesberger, C. B. Clements, L. Pirjola, A.-J. Kieloaho, L. Kulmala, H. Aaltonen, J. Patokoski, J. Pumpanen, J. Rinne, T. Ruuskanen, M. Pihlatie, H. E. Manninen, V. Aaltonen, H. Junninen, T. Petäjä, J. Backman, M. Dal Maso, T. Nieminen, T. Olsson, T. Grönholm, J. Aalto, T. H. Virtanen, M. Kajos, V.-M. Kerminen, D. M. Schultz, J. Kukkonen, M. Sofiev, G. De Leeuw, J. Bäck, P. Hari, and M. Kulmala
Atmos. Chem. Phys., 14, 4473–4502, https://doi.org/10.5194/acp-14-4473-2014, https://doi.org/10.5194/acp-14-4473-2014, 2014
L. C. Wu, Y. Q. Wen, and D. Y. Wu
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-1-1857-2013, https://doi.org/10.5194/nhessd-1-1857-2013, 2013
Revised manuscript not accepted
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Short summary
Statistics of the frequency and intensity of snow bands affecting the Finnish coast during years 2000–2010 was conducted. A set of criteria for meteorological variables favoring the formation of the snow bands were applied to regional climate model (RCA4) data. We found on average three days per year with favorable conditions for coastal sea-effect snowfall. The heaviest convective snowfall events were detected most frequently over the southern coastline.
Statistics of the frequency and intensity of snow bands affecting the Finnish coast during years...
