Biogeophysical impacts of peatland forestation on regional climate changes in Finland

Abstract. Land cover changes can impact the climate by influencing the surface energy and water balance. Naturally treeless or sparsely treed peatlands were extensively drained to stimulate forest growth in Finland over the second half of 20th century. The aim of this study is to investigate the biogeophysical effects of peatland forestation on regional climate in Finland. Two sets of 18-year climate simulations were done with the regional climate model REMO by using land cover data based on pre-drainage (1920s) and post-drainage (2000s) Finnish national forest inventories. In the most intensive peatland forestation area, located in the middle west of Finland, the results show a warming in April of up to 0.43 K in monthly-averaged daily mean 2 m air temperature, whereas a slight cooling from May to October of less than 0.1 K in general is found. Consequently, snow clearance days over that area are advanced up to 5 days in the mean of 15 years. No clear signal is found for precipitation. Through analysing the simulated temperature and energy balance terms, as well as snow depth over five selected subregions, a positive feedback induced by peatland forestation is found between decreased surface albedo and increased surface air temperature in the snow-melting period. Our modelled results show good qualitative agreements with the observational data. In general, decreased surface albedo in the snow-melting period and increased evapotranspiration in the growing period are the most important biogeophysical aspects induced by peatland forestation that cause changes in climate. The results from this study can be further integrally analysed with biogeochemical effects of peatland forestation to provide background information for adapting future forest management to mitigate climate warming effects. Moreover, they provide insights about the impacts of projected forestation of tundra at high latitudes due to climate change.

[1]  Richard G. Jones,et al.  An inter-comparison of regional climate models for Europe: model performance in present-day climate , 2007 .

[2]  K. Korhonen,et al.  Suomen suometsät 1951–1994 , 1970 .

[3]  C. Müller,et al.  Uncertainties in climate responses to past land cover change: First results from the LUCID intercomparison study , 2009 .

[4]  Martin Wild,et al.  A new snow cover fraction parametrization for the ECHAM4 GCM , 2001 .

[5]  C. Zou,et al.  Impacts of woody plant encroachment on regional climate in the southern Great Plains of the United States , 2013 .

[6]  A. Pitman.  The evolution of, and revolution in, land surface schemes designed for climate models , 2003 .

[7]  Benjamin Smith,et al.  Biogeophysical feedbacks enhance the Arctic terrestrial carbon sink in regional Earth system dynamics , 2014 .

[8]  Syukuro Manabe,et al.  THE ATMOSPHERIC CIRCULATION AND THE HYDROLOGY OF THE EARTH ’ S SURFACE , 1969 .

[9]  K. Minkkinen,et al.  Vegetation heterogeneity and ditches create spatial variability in methane fluxes from peatlands drained for forestry , 2006, Plant and Soil.

[10]  Ulrike Lohmann,et al.  A global data set of land-surface parameters , 1994 .

[11]  Perrin Selcer.  Fabricating unity: The FAO-UNESCO Soil Map of the World , 2015 .

[12]  Benjamin Smith,et al.  Hotspots of vegetation-climate feedbacks under future greenhouse forcing in Europe , 2010 .

[13]  S. Manabe.  CLIMATE AND THE OCEAN CIRCULATION1 , 1969 .

[14]  A. Venäläinen,et al.  On the influence of peatland draining on local climate , 1999 .

[15]  J. Huisman.  The Netherlands , 1996, The Lancet.

[16]  R. Betts.  Offset of the potential carbon sink from boreal forestation by decreases in surface albedo , 2000, Nature.

[17]  R. O G E,et al.  Interactions between the atmosphere and terrestrial ecosystems : influence on weather and climate , 1998 .

[18]  Stefan Hagemann,et al.  An improved land surface parameter dataset for global and regional climate models , 2002 .

[19]  D. Legates,et al.  Mean seasonal and spatial variability in global surface air temperature , 1990 .

[20]  Edzer J. Pebesma,et al.  Multivariable geostatistics in S: the gstat package , 2004, Comput. Geosci..

[21]  M. Køltzow,et al.  The effect of a new snow and sea ice albedo scheme on regional climate model simulations , 2007 .

[22]  D. Jacob,et al.  Influence of sea ice treatment in a regional climate model on boundary layer values in the Fram Strait region , 2004 .

[23]  K. Korhonen,et al.  Suomen metsät 2004–2008 ja niiden kehitys 1921–2008 , 2013 .

[24]  Devon E. Worth,et al.  Boreal lichen woodlands: A possible negative feedback to climate change in eastern North America , 2011 .

[25]  R. Betts,et al.  Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C Earth system model , 2012 .

[26]  G. Meehl,et al.  The Importance of Land-Cover Change in Simulating Future Climates , 2005, Science.

[27]  R. Betts,et al.  Land use/land cover changes and climate: modeling analysis and observational evidence , 2011 .

[28]  Thomas Raddatz,et al.  Parameterization of snow-free land surface albedo as a function of vegetation phenology based on MODIS data and applied in climate modelling , 2009 .

[29]  T. Laurila,et al.  Forestation of boreal peatlands: Impacts of changing albedo and greenhouse gas fluxes on radiative forcing , 2010 .

[30]  Andrew E. Suyker,et al.  Albedo estimates for land surface models and support for a new paradigm based on foliage nitrogen concentration , 2010, Global Change Biology.

[31]  U. Karstens,et al.  A comprehensive model inter-comparison study investigating the water budget during the BALTEX-PIDCAP period , 2001 .

[32]  Liming Zhou,et al.  Change in snow phenology and its potential feedback to temperature in the Northern Hemisphere over the last three decades , 2013 .

[33]  Jeffrey R. White,et al.  A synthesis of methane emissions from 71 northern, temperate, and subtropical wetlands , 2014, Global change biology.

[34]  Annett Wolf,et al.  Influence of changed vegetations fields on regional climate simulations in the Barents Sea Region , 2008 .

[35]  Stefan Hagemann,et al.  Improving a subgrid runoff parameterization scheme for climate models by the use of high resolution data derived from satellite observations , 2003 .

[36]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[37]  H. Davies,et al.  A lateral boundary formulation for multi-level prediction models. [numerical weather forecasting , 1976 .

[38]  Alan K. Betts,et al.  Albedo over the boreal forest , 1997 .

[39]  Yao Gao,et al.  Implementation of the CORINE land use classification in the regional climate model REMO , 2015 .

[40]  Erkki Tomppo,et al.  Designing and Conducting a Forest Inventory - case: 9th National Forest Inventory of Finland , 2011 .

[41]  Jouni Pulliainen,et al.  Evaluation of North Eurasian snow-off dates in the ECHAM5.4 atmospheric GCM , 2014 .

[42]  Diana Rechid,et al.  Influence of monthly varying vegetation on the simulated climate in Europe , 2006 .

[43]  V. Brovkin,et al.  Interactive comment on “Present state of global wetland extent and wetland methane modelling: conclusions from a model intercomparison project (WETCHIMP)” by J. R. Melton et al , 2012 .

[44]  Tobias Stacke,et al.  Impact of the soil hydrology scheme on simulated soil moisture memory , 2013, Climate Dynamics.

[45]  P. Jones,et al.  A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006 , 2008 .

[46]  Sven Kotlarski,et al.  A subgrid glacier parameterisation for use in regional climate modelling , 2007 .

[47]  J. Laine,et al.  Long-Term Effects of Water Level Drawdown on the Vegetation of Drained Pine Mires in Southern Finland , 1995 .

[48]  Richard G. Jones,et al.  Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results , 2005 .

[49]  D. Rechid,et al.  On biogeophysical interactions between vegetation phenology and climate simulated over Europe , 2009 .

[50]  R. Korhonen,et al.  Carbon balance and radiative forcing of Finnish peatlands 1900–2100 – the impact of forestry drainage , 2002 .

[51]  S. Warren,et al.  A Model for the Spectral Albedo of Snow. I: Pure Snow , 1980 .

[52]  E. Tomppo.  National Forest Inventories : pathways for common reporting , 2010 .

[53]  Michael Botzet,et al.  Derivation of global GCM boundary conditions from 1 km land use satellite data , 1999 .

[54]  Erkki Tomppo,et al.  Article in Press G Model International Journal of Applied Earth Observation and Geoinformation Linear Unmixing of Modis Albedo Composites to Infer Subpixel Land Cover Type Albedos , 2022 .

[55]  J. McGregor.  Regional climate modelling , 1997 .

[56]  V. Brovkin,et al.  Combined biogeophysical and biogeochemical effects of large-scale forest cover changes in the MPI earth system model , 2010 .

[57]  B. Hånell,et al.  Peatland ecology and forestry : a sound approach , 2012 .

[58]  K. Caldeira,et al.  Combined climate and carbon-cycle effects of large-scale deforestation , 2006, Proceedings of the National Academy of Sciences.

[59]  Timo Penttilä,et al.  Dynamics of plant‐mediated organic matter and nutrient cycling following water‐level drawdown in boreal peatlands , 2003 .

[60]  Limin Yang,et al.  Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data , 2000 .

[61]  Alexander Loew,et al.  Combined evaluation of MPI‐ESM land surface water and energy fluxes , 2012 .

[62]  E. Todini,et al.  A rainfall–runoff scheme for use in the Hamburg climate model , 1992 .

[63]  G. Bonan.  Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests , 2008, Science.

[64]  D. Jacob,et al.  Sensitivity studies with the regional climate model REMO , 1997 .

[65]  Juha Heikkinen,et al.  Spatial interpolation of monthly climate data for Finland: comparing the performance of kriging and generalized additive models , 2013, Theoretical and Applied Climatology.

[66]  Kees Klein Goldewijk,et al.  Biogeophysical effects of land use on climate : Model simulations of radiative forcing and large-scale temperature change , 2007 .

[67]  Swantje Preuschmann,et al.  Regional surface albedo characteristics - analysis of albedo data and application to land-cover changes for a regional climate model , 2012 .

[68]  Regional climate modeling activities in relation to the CLAVIER project , 2008 .

[69]  S. Warren,et al.  A Model for the Spectral Albedo of Snow. II: Snow Containing Atmospheric Aerosols , 1980 .

[70]  D. Jacob,et al.  Regional characteristics of climate change altering effects of afforestation , 2011 .

[71]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .