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2. Especially sensible heat flux seems to have a strong annual cycle with observed increases especially during the growing season (Beringer et al., 2005, their Fig. 7) and warmer daytime (Beringer et al., 2001, 2005). Over Norway and Sweden, previous studies found simulated decreases in Sept.-Feb. and increases otherwise (see Snyder and Liess (2014, Climate Dyn. 42, 487–503, their Fig. 6), Jeong et al., (2014, Environ. Res. Lett. 9, 094007, doi:10.1088/1748-9326/9/9/094007, their Table 1), and Jeong et al. (2011, Climate Dyn. 37, 821-833, their Fig. 5). The present study finds a decrease in sensible heat flux with resulting decrease in 2m temperature. This should be discussed and maybe related to possible changes in simulated precipitation (see also technical comments 15, 18, and 21).


Introduction
Amplified warming at high latitudes over past decades has led to changes in the boreal and arctic climate system, such as structural changes in high latitude ecosystems (Serreze and Barry, 2011;Chapin et al., 2010).This polar amplification of global warming is in part due to a cascade of local feedback mechanisms that act to increase the initial greenhouse gas forcing (Serreze and Barry, 2011;Overpeck et al., 1997) Extensive evidence gathered over the past decades, has established that changes in high latitude ecosystems are part of these mechanisms, through redistribution of physical properties of the surface controlling processes that act to amplify or reduce initial warming (Bonan, 2008;Beringer et al., 2001;Sturm et al., 2001;Chapin et al., 2005).Important mechanisms include changes in surface energy and water flux partitioning, which could affect regional or continental scale evapotranspirationprecipitation feedbacks (Thompson et al., 2004;Beringer et al., 2005;Eugster et al., 2000), and surface albedo (e.g.Betts and Ball, 1997;Chapin et al., 2005;Serreze and Barry, 2011).Physical changes may have the largest direct impacts on the local scale.However, local scale feedbacks may propagate to regional and continental scales through cross-scale links, and possibly lead to critical transitions in the large scale climate (Rietkerk et al., 2011).Bonan (2008) suggests that the boreal forest might through its control on high latitude surface albedo, especially during winter, have the highest biophysical effect of all biomes on the mean global temperature.Several global vegetation modelling studies have predicted potential vegetation changes in response to future warming and elevated CO 2 concentrations (e.g.Alo and Wang, 2008;Strengers et al., 2010;Sitch et al., 2008;Lucht et al., 2006).Common features in these studies include migration of boreal forest towards higher and latitudes and altitudes, i.e. northward expansion of trees and shrubs into tundra ecosystems, and replacement of boreal forest by more temperate vegetation species along the southern edges of the boreal zone.Soja et al. (2007) concluded that substantial observational evidence across the circumpolar boreal region over the past several decades, indicates that the biosphere in the region has already responded to climate changes in accordance with modelled predictions, if not faster.They found upper and lower tree lines in mountainous regions across Siberia to have altered in response to a warmer climate, as predicted by global dynamic vegetation models.Some of the observed changes to vegetation are increased biomass production in high latitude ecosystems as response to higher temperatures and longer growing season.Several studies based on remote sensing have confirmed increased photosynthetic activity related to increased plant growth and increased growing seasons over the past decades (Myneni et al., 1997;Piao et al., 2011;Bhatt et al., 2010).Bhatt et al. (2010), link increased high latitude ecosystem productivity to a decrease in near-coastal sea ice and summer tundra surface temperatures.In addition, the northward expansion of boreal and arctic vegetation into to previously tundra covered regions, also referred to as the arctic greening, is a widely observed feature across the arctic region.Chapin et al. (2005) calculated that 2.3 % of the treeless area in Northern Alaska has been converted to forest from tundra over the past 50 years, corresponding to an area of 11 600 km 2 .They highlight the importance of this redistribution in vegetation on surface albedo and temperatures.By analyzing a wide range of independent sets of measurement data, they found that the changes in terrestrial summer albedo enhances high latitude warming locally by as much as 3 W m −2 per decade, comparable to long term regional effects of an atmospheric CO 2 doubling.Although the heating signal is mainly due to a prolonged snow free season, they expect that the expansion of shrubs and trees into the former tundra zones is likely to contribute to enhance summer warming in the future.Xu et al. (2013) found that a decrease of high latitude temperature seasonality equivalent to a climatic 4 • latitudinal shift equator-ward, has been observed in the Arctic region over the past 30 years.They estimate that a further diminishment in temperature seasonality equivalent to a full 20 latitudinal degrees southward shift, could occur within this century.
However, not all boreal and arctic sites respond to increased temperatures with an increased biomass production.A second type of response to warming is a reduction in photosynthetic activity, referred to as browning.Lloyd and Bunn (2007) observed that while most high latitude ecosystems have shown a positive trend in seasonal photosynthetic activity over the past few decades, some boreal ecosystems, mostly in the continental interior, showed significant downward trends in photosynthetic activity as response to increased temperatures, especially in the last two decades.They Figures

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Full explain this as a result of temperature stress, or temperature-induced moisture stress, related to increased rates of evapotranspiration.Changes in surface vegetation properties have a direct effect on the surface fluxes of latent and sensible heat.The ratio between the two, the Bowen ratio (sensible to latent heat flux), is an important climatic measure and highly sensitive to surface physical properties (Wilson et al., 2002;Baldocchi et al., 2000).For instance, based on an analysis of available data on surface energy balance of the arctic and boreal ecosystems, Eugster et al. (2000) found that in general evergreen conifer forests have a canopy conductance half of that of deciduous forests, resulting in a higher sensible heat flux, and lower latent heat flux over evergreen conifer forests.They estimate a reduction in Bowen ratio in areas where a warming-induced shift from conifer forest to deciduous forest should occur.Arctic ecosystems, like light taiga and tundra ecosystems, have a higher ground heat flux due to less shade by canopies, compared to forested sites.Thompson et al. (2004) found that increasing canopy complexity greatly affect radiation terms, and is closely linked to the sensible heat flux.They conclude that the heating associated with complex canopies may influence regional feedback processes by increasing boundary layer height.These findings were supported by Beringer et al. (2005), who measured warmer and drier fluxes moving along the transition zone from arctic tundra to boreal forest.They found a relative increase in sensible heat flux resulting in an increase in Bowen ratio from 0.94 to 1.22 going from tundra to forested sites.They also argue that shifting the vegetation type towards one with higher leaf area index, may cause a shift in the relationship between latent heat flux and the state of the overlying atmosphere and mesoscale weather systems, rather than influence the link to soil water content.
Changing vegetation and surface properties will through its control on surface fluxes of heat and moisture influence the planetary boundary layer, and general circulations patterns (Beringer et al., 2001;Pielke and Vidale, 1995;Liess et al., 2011).Recently, Liess et al. (2011)  of a moderate northward forest replacement of shrub ecosystems along the southern tundra circumpolar border zone, on the summer time polar front.They estimated a regional broadening and strengthening of the polar jet stream of up to 3 m s −1 , and concluded that the effects of the regional forest expansion could reach even the stratospheric circulation.
Uncertainties within vegetation-climate modelling are large, especially with regard to future species redistribution and climate feedback (e.g.Friedlingstein et al., 2013).Investigating the response of the overlying atmosphere to specific structural changes in vegetation, may yield valuable information that might reduce uncertainties with regard to climate response to the complex present and future changes in boreal ecosystems.
In this study, we investigate the sensitivity to altered land cover on fine resolution surface fluxes and regional scale atmospheric response mechanisms by conducting two experiments with manually altered vegetation distribution.These experiments represent two potential future boreal and arctic ecosystem changes, and are compared to a control present day state of vegetation distribution.A time-indifferent vegetation distribution in each simulation aims to isolate effects of structural vegetation changes on regional climate.Meteorological forcing data in both simulations matches that of the control run to further isolate the long term effects of vegetation changes on the overlying atmosphere.

Model and methodology
The Weather Research and Forecasting model (WRF) is a non-hydrostatic, mesoscale weather prediction system (Skamarock and Klemp, 2008).It is a model with a wide variety of applications, across scales ranging from large-eddy to global simulations.Simulation time scales vary between short-term case studies of a few hours or less, to regional climate studies spanning decades.In this study the model has been run with the Noah land surface model (Tewari et al., 2004).In Noah, the ground surface consists of four soil layers, that are 10, 30, 60 and 100 cm thick respectively, adding up Figures to a total soil depth of 2 m.The top layer is a combined vegetation, snow and soil layer, and surface properties are dependent on soil-and vegetation category.The model computes surface water-and energy fluxes between the surface and the atmosphere, and controls the surface and soil water budget.The model is run at a spatial resolution of 27 km, with 52 vertical layers.The time resolution is two minutes, and output is written every 3 h.The model setup further includes the Mellor-Yamada-Janjic planetary boundary layer parameterization (Janjić, 1994), Morrison two moment microphysics (Morrison et al., 2009), RRTMG short-and long wave radiation options (Iacono et al., 2008) and the Kain-Fritsch cumulus scheme (Kain, 2004).The choise of model configuration is based in part on sensitivity testing of various schemes (not shown), and in part out of considerations of available output variables of different parameterizations.A review of literature with regard to choices best suited for a cold region intermediate resolution simulation, and a consideration of the NCAR cold climate medium resolution example setup (Skamarock et al., 2008), and the Polar WRF setup (Hines et al., 2011), also contributed to the current model configuration.
For the initial-and boundary conditions, we use the ERA Interim 6 hourly reanalysis.Boundary conditions for the years 2000-2010 are used for the simulations, where the first year is regarded a spinup year and not included in the analyses.The same boundary conditions are applied in all three simulations to isolate the effect of structural vegetation changes on the overlying atmosphere and climate.The 10 year simulation length was chosen in order to achieve a good estimate of the mean responses of the overlying atmosphere to vegetation changes without inter annual variation influencing the results.Although even longer simulations might be advantageous, 10 years was chosen as a compromise between length and computational cost while keeping high temporal and spatial resolutions in the simulations.The time period chosen as meteorological forcing (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) is coherent with the selected set of vegetation data and acts as a suitable reference period for present day conditions.Figures

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Full For static land data, the MODIS IGBP modified 21 class land surface data is used.This dataset is available with the standard WRF package download.The dataset is based on the original 1 km resolution MODIS IGBP vegetation map (Friedl et al., 2010), but excludes permanent wetland and has three tundra classes and lakes added by the Land Team at EMC/NCEP.To represent high latitude and altitude ecosystems more accurately, the vegetation category of open shrub land has been replaced by various tundra vegetation classes north of 60 • latitude in the modified MODIS dataset.This replacement results in an artificial shift in vegetation that can be detected along this latitude across a mountain plateau in southern Norway.In this study, the remaining grid cells of shrub land south of 60 • and west of 15 • east, are adjusted into wooded tundra below-, and mixed tundra above the height of the local tree line, to achieve a vegetation distribution more consistent with local ecosystems in this area.In the rest of the domain the vegetation shift along the 60 • latitude has no abrupt shifts or other negative implications for the purpose of this study.The study area, which covers the northern European boreal zone, is shown in Fig. 1, represented by evergreen needle leaf forest as this is the dominant vegetation type in this area.

Experiments
The goal of the experimental setup is to represent a northward migration of boreal ecosystems based on the aforementioned observed and anticipated features in vegetation migration patterns.Experiments are designed to induce atmospheric response and feedback mechanisms, while keeping perturbation complexity low enough to be able to identify the respective response mechanisms related to each of the applied vegetation shifts.The aim has been to induce moderate and realistic scale changes, representative of actual vegetation shifts on a century long timescale.
Changes in species distribution in response to climatic changes vary greatly across species types.As ecosystems consist of complex, co-dependent, compositions of wide ranges of species, the total ecosystem migration speed will be equally complex.However, cross-species observational studies confirm a general northward-and Figures

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Full altitudinal shifts in the boreal area, a trend matching climate change predictions (Parmesan and Yohe, 2003;Chen et al., 2011).On a global scale, Chen et al. ( 2011) derived a median cross species migrations rate of 16.9 km per decade, nearly doubling the estimate of Parmesan and Yohe (2003) who derived an average range shift of 6.1 km per decade in their meta-analyses based on some 1700 species across the globe.These average rates of migration estimates are often seen in contrast to those of dynamic vegetation models, which often assume strict relationships between species redistribution and altered climatic environment, yielding sometimes abrupt changes in species composition in large areas over short time spans.To assess two extreme scenarios, in which species follow their climatic environment completely, or do not move out of their current habitats at all in spite of changing climatic conditions, Mckenney et al. (2007) investigated potential migration scenarios of 130 North American tree species, based on future climate predictions.They found that on average, a northward distribution shift of between 330 and 700 km depending on the species' ability to migrate at the same rate as their current climatic conditions, was likely to occur by the end of this century, along with large decreases in future potential habitats.
In this study, we isolate the effects of specific vegetation changes by applying simplified perturbations to the dominant vegetation categories as given by the selected set of land use data.The perturbations each represent a given trend of forest migration in this area.As such, the perturbations are not to be regarded as estimates of future state of vegetation distribution in the area under a specific climate scenario.Here, a 10 year simulation period is used, and averages regarded as a good indicator of mean climate response to the perturbations.Assuming vegetation changes induced by a changing climate, this experimental setup is not relevant for an unlimited time span; rather it reflects moderate changes in simulated vegetation shifts.Keeping in line with the meta-analyses of migrations speeds across species and assuming a time horizon on the scale of about a century, an upper limit of a moderate 100 km vegetation migration is applied to vegetation redistribution.Perturbations related to vegetation shifts only imply changes in the biophysical properties of the surface, while Introduction

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Full biochemical, atmospheric and hydrological properties are not perturbed.The applied changes in dominant vegetation category for each experiment, as compared to the control simulation, are illustrated in Fig. 2.

Experiment 1
The main emphasis in the first experiment (hereafter Ex 1), is the widely documented feature of arctic shrub expansion into tundra regions.This change involves increase in surface roughness and wintertime albedo, as documented by e.g.Chapin et al. (2005).This is also regarded the most rapid of the applied vegetation shifts, and as such occupies the largest area of applied changes.To represent this vegetation shift, a moderate change in tundra vegetation is applied by changing the areas covered by the vegetation category of "mixed tundra" into "wooded tundra", thereby slightly increasing the roughness length, and reducing the wintertime albedo (Table 1).
In addition, to account for another important trend in the northernmost latitudes of our domain, we have allowed for the northward migration of the boreal forest, by applying the migration of evergreen needle leaf forest into areas previously covered by wooded tundra.The shift is applied up to 108 km to represent a slow migration towards higher latitudes in areas that already are covered by vegetation.This northward migration of dense forest implies an increase in LAI and decrease in albedo, owing to the denser canopy of the evergreen forest (Table 1).For Ex 1 these two vegetation changes imply changes in a total area of 563 517 km 2 of shrub expansion/tundra conversion and a minor area of 181 521 km 2 of northward migrating evergreen forest (Fig. 2, left panel).

Experiment 2
In the second experiment (hereafter Ex 2), the northward migration of the southern edges of boreal forest is also taken into account by allowing for a northward migration of the southern border of the evergreen forest and its replacement of more temperate Introduction

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Full species.To achieve this, the southern border of the evergreen needle leaf forest is allowed to migrate northward by up to 108 km (similar to the migration of evergreen forest on the northern border), being replaced by the mixed forest, representing a slow transition towards more temperate forest type.For the physical properties of the surface this implies a decrease in maximum and minimum LAI values and increase in maximum and minimum albedo (Table 1).These vegetation changes cover a total area of 392 202 km 2 of northward migrating mixed forest, and represents as such a substantial shift in vegetation, although consistent with the northern vegetation perturbations in Ex 1.

Results
The only difference between the simulations is the described changes in vegetation distribution and resulting feedback effects of these, as simulations are in all other aspects identical.As such, results are largely presented as differences between experiment simulations as compared to the control run.The effect of vegetation changes on the atmosphere varies greatly both spatially and temporally, and the various feedback mechanisms vary in relative importance across time and spatial scales.To account for inter-seasonal and inter-annual variations, we start by examining the long term average effects across the full length of the 10 year simulation period (excluding the spinup-year), largely focusing on regional means.Time averages are all based on the three hour output frequency, and as such represents mean day and night values.In addition, average changes over selected areas of specified vegetation shifts are presented to highlight the effects of individual vegetation changes.The main emphasis is on alterations in surface fluxes and near-surface atmosphere; however a short investigation of effects on soil moisture content is also conducted.We further investigate the seasonal variations in feedback mechanisms in Sect.The applied vegetation changes lead to alterations in key surface parameters such as surface albedo and leaf area index (LAI).The 10 year average change in albedo due to structural vegetation changes is shown in Fig. 3.Here the difference between Ex 2 and the control run is shown to account for all applied vegetation changes.The effect on albedo and LAI changes is not constant throughout the year (see Sect. 3.2) and across the domain.The annual average features represented here show that in areas with a northward migrating evergreen needle leaf forest, vegetation changes largely leads to a decrease in surface albedo, whereas areas with simulated shrub expansion do not affect the 10 year average albedo notable.The southern border change from evergreen needle leaf-to mixed forest leads to an increase in surface albedo.A general increase in LAI is seen in areas with a northward expanding evergreen needle leaf forest, whereas a decrease is seen across the area of mixed forest migration (Fig. 3 A contrasting pattern is seen in the effect on the latent heat flux (Fig. 4, right panel).The northward migrating forest and shrub expansion in Ex 1 are both enhancing the latent heat flux, with areas experiencing a northward migrating evergreen needle leaf forest, dominating the results (upper panels).The 10 year average response in Ex 1 is an increase in the latent heat flux by 1.2 W m −2 .This number also includes areas with tundra change, and the mean change over areas with northward expanding evergreen forest only, is 4.4 W m −2 .In Ex 2, the mean effect of vegetation migration is a reduction of the latent heat flux by 0.4 W m −2 , mainly influenced by the negative effect of the mixed forest expansion, in which areas the average latent heat flux is reduced by 3.5 W m −2 .
The surface fluxes of latent and sensible heat greatly influence the planetary boundary layer, and the influence of the vegetation changes on the planetary boundary layer height (PBLH) for both experiments as compared to the control run, are seen in Fig. 5. Contradictory to the heat fluxes, the areas with the largest changes in PBLH are those with shrub expansion, causing a mean increase in the PBLH in the northernmost areas of the domain.Changes in the physical surface properties include the roughness length and small changes in wintertime albedo, whereas there are no changes in LAI.The northward migrating evergreen needle leaf forest is also influencing the boundary layer height although to a lesser degree, causing a mean increase, whereas the southern border mixed forest expansion causes an average reduction in the boundary layer height of about 22 m.The boundary layer height changes are, as the fluxes, closely restricted to areas with vegetation changes.
Figure 6 shows the 10 year average effect of vegetation changes on near surface atmospheric variables.The 2 m temperature (left panels) is sensitive to surface fluxes of sensible and latent heat, and to the surface radiative budget.The overall effect on this variable is a good climatic indicator of the effects of vegetation changes on the atmosphere.In Ex 1 we see the largest effect in the north-eastern part of the domain (upper left panel).The areas with the highest increase in temperature are dominated by, although not restricted to, areas with a northward expanding evergreen needle leaf Figures forest.Temperature increase is also seen along areas of shrub expansion, although with a weaker average response.The 10 year average increase in 2 m temperature in these areas (total area of changed vegetation in Ex 1) is a moderate 0.11 • C, however with large seasonal variations (Sect.3.2).
In Ex 2 (Fig. 6, lower left panel) the dominant feature is the contrasting cooling effect of the southern border mixed forest northward migration.The annual average effect of this vegetation change is a cooling of 0.19 • C, which together with the northern vegetation shifts results in a total average effect of combined vegetation shifts of 0.0 • C, averaged over all grid cells with vegetation changes.Figure 7 summarizes changes in near surface atmospheric variables, given as average effects resulting from vegetation changes in Ex 1 (left bars), Ex 2-Ex 1 (middle bars) and all of the vegetation changes, applied in Ex 2 (right bars).10 year average changes in surface pressure resulting from vegetation changes is shown in Fig. 8, left panels, along with changes in annual average wind patterns (right panels).Changes in wind components (Ex 2 compared to control run) are shown for the eastward wind (upper, right), the northward wind component (lower, right).A pattern of increased surface pressure along the northern coastline of the domain is clear, together with a mean decrease in both eastward and northward winds, especially over regions of northward expanding evergreen forest.
Figure 9  increase in the latent heat flux in this area.The other vegetation changes do not affect the soil moisture content to any great extent.

Seasonal averages; when are various effects largest?
Seasonal variations in surface-and near surface variables as results of the various vegetation changes are presented in Fig. 10.Each stippled line shows 10 year monthly mean changes for one type of vegetation change as averages only over the grid cells with the corresponding vegetation shift.The overall mean effect of all vegetation changes, averaged over the total area of all vegetation shifts, is shown in the black line marked Ex 2-Ctrl.
For the albedo (Fig. 10, upper left panel), the decrease due to the northward migrating mixed forest is most prominent in spring and autumn months, whereas the increase is less over the summer and smallest during winter.The contrasting negative effect on the albedo resulting from the evergreen needle leaf tree northward migration is largest in fall and the mean effect throughout the year is a lowering of the surface albedo.The maximum change in spring and autumn months, reflect the close dependence on the LAI, which varies throughout the year.The effect in the winter months is on average small because of snow covering the vegetation.The spatial variability across the domain is largest in spring and autumn months (not shown), and smallest in summer, reflecting the fact that LAI changes occur at an uneven rate across the domain in these transitional periods.
The largest effect on the sensible heat flux (Fig. 10, middle left panel), is seen in areas of evergreen needle leaf forest expansion in summer, on average reducing the heat flux by 11. zero in winter, and a reduction in heat transfer to the atmosphere is seen over the summer.
For the latent heat flux (Fig. 10, middle right panel), the effect of the shrub expansion is very small, and the two types of forest expansion dominate the results in contrasting ways.The evergreen needle leaf forest expansion causes a sharp increase in summer time latent heat fluxes compared to the control run, with a peak in July of on average as much as 18 W m −2 .The mixed forest expansion on the other hand, acts to decrease latent heat fluxes all year round, and the decreasing effect is largest in June with an average reduction of about 10.3 W m −2 .The net effect is a year-round slight decrease in latent heat fluxes from the surface to the atmosphere, with largest effect in spring (solid line).
The 2 m humidity varies on a monthly basis similar to the latent heat flux, as these two variables are closely linked.The effect on humidity is dominated by the two types of forest migration, whereas the effect of shrub expansion is small.The evergreen needle leaf forest expansion has a prominent positive effect, increasing the humidity especially in summer, whereas the mixed forest expansion acts to decrease the 2 m humidity in these areas, having the largest effect over the summer months (not shown).
The overall combined effect of all vegetation changes on the height of planetary boundary layer (PBL) is lowest in summer and largest in spring (Fig. 10, lower left panel, solid line).The vegetation change most influential on the PBL is the shrub expansion during winter and spring, increasing the PBL all year round and by as much as 33.7 m on average in March.Also the northward expansion of evergreen needle leaf forest contributes to an increase in boundary layer height in the winter months; however in summer this vegetation change causes a sharp decrease as compared to the control run, possibly related to decreases in sensible heat flux and surface temperature.The northward expansion of mixed forest along the southern border of the boreal forest causes a year-round decrease in PBL height, with the smallest effect in summer months, and the most pronounced decrease in May.Introduction

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Full The effects of vegetation changes on the 2 m temperature is complex and varies across the areas of vegetation shifts and seasons (Fig. 10, lower right panel).In areas with shrub expansion there is a persistent year-round positive effects on the temperature compared to the control run, with the largest effects occurring in fall and winter months.In areas with evergreen forest expansion we see a wintertime heating, whereas the summer time effect is opposite, causing a cooling of the 2 m temperature in June through August.The effect of the mixed forest migration is a year-round cooling of the 2 m temperature, and the effect is largest in the spring and autumn months, and lowest in mid-summer.The overall effect is a net increase in 2 m temperatures in winter, and decreasing 2 m temperatures in summer (solid line).This is accounting for all vegetation shifts.

Conditional effects; under which conditions are effects largest?
The latent heat flux is mainly the combined effect of soil evaporation, transpiration and evaporation from interception.The part most closely linked to the specific type of vegetation cover is the evapotranspiration (i.e.transpiration and evaporation of intercepted water), which depends on water availability (either as intercepted water or to the plant through the roots), the efficiency of turbulent transfer and the evaporative power of the ambient atmosphere.As both the number of soil layers available to the plants roots, and the LAI and thereby the rate of evapotranspiration, varies across vegetation types, the dependence of latent heat (and thus the evapotranspiration) on soil moisture as compared to the vapor pressure deficit (VPD) in the surrounding air, may shift as vegetation category changes.To investigate these effects in more detail, the effects of selected vegetation changes on the relationship between the latent heat flux and soil moisture, and latent heat flux and ambient air vapor pressure deficit, are shown in Fig. 11.The effect of shrub expansion on surface heat fluxes is low, and so we focus here on areas with forest migration.As fluxes and flux response to vegetation shifts are largest in summer months, only monthly averages of the summer season (JJA) are used, and correlation coefficients based on averages in each area are given.Introduction

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Full Changes averaged over areas with evergreen forest expansion into tundra is shown in the upper panels, and mixed forest northward migration in the lower panels.The white circles indicate monthly mean values as simulated in the control run, and black dots represent monthly mean values averaged over the same area after vegetation shifts.
For the evergreen forest expansion the correlation coefficient between latent heat flux and soil moisture content is low, regardless of vegetation type.This indicates that the soil moisture content does not limit the rate of latent heat, suggesting that the latent heat flux is energy limited rather than water limited.The latent heats correlation to VPD is increased from 0.68 to 0.74 when changing vegetation from tundra to evergreen forest, indicating that the evergreen forest latent heat flux is more dependent on the ambient atmosphere than the tundra vegetation it replaces.For the mixed forest northward expansion, the same shifts in correlation occurs, indicating that shifting vegetation type from evergreen forest to mixed forest also acts to increase the latent heat flux dependence on VPD rather than soil moisture.

Discussion of results
Perturbations in this study were limited to changing the dominant land category in given areas, and accordingly to changes in certain physical properties of the surface.The parameterization of physical processes in the model has not been altered, in order to maintain a high relevance to other studies.The modified IGBP MODIS vegetation dataset is regarded a suitable basis for perturbations, although many alternatives do exist with regard to datasets, and vegetation perturbations that will influence the results.land use change than the ones applied in our study, although in good agreement with observational data and estimates for future changes in the area (Liess et al., 2011).The perturbations applied here represent simplified estimates of future vegetation distribution, based on observed trends in vegetation migration in the area.As such, the results are not possible to validate against time-and site-specific observations.However, some general features resulting from similar vegetation changes, as observed in large scale, cross-site measurement studies, may help determine whether modelled results are in line with expectations or differ substantially.In the following we relate our results to a few such studies in order to point to possible strengths and weaknesses in model parameterization and configuration.
Changes in albedo are largest in spring and autumn months, reflecting the differences in LAI in these periods.In summer, the broadleaved deciduous species reach their peak LAI values, and the difference to the evergreen needle leaf trees is smallest.In winter, the effect of difference in LAI is at its largest; however its effect on the surface albedo is to a great extent masked by snow cover.The areas of evergreen needle leaf forest expansion has a profound impact on summer-and autumn-months albedo, but interestingly a low impact on modelled albedo during winter months.In fact, the effect of the evergreen forest migration on winter albedo is nearly zero during winter months.
It has been suggested that the lowering of surface albedo over snow covered ground, as result of taller and more complex canopies as compared to snow covered tundra, will greatly affect wintertime surface heat fluxes and that the lower wintertime albedo would also increase snowmelt and prolong growing seasons (e.g.Bonan et al., 1992;Betts and Ball, 1997).However, the parameterization of snow albedo in relation to high latitude vegetation has been pointed out as a source of uncertainty in high latitude climate modelling (e.g.Qu and Hall, 2006;Loranty et al., 2014).Loranty et al. (2014) found that on average the CMIP5 model tree cover and albedo do not correlate well.They also point out that the observed general decreasing albedo with increasing tree

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Full cover south of the latitudinal tree line seems badly represented in coupled climate models.
In WRF (Noah), the vegetation-specific surface albedo is weighted against a corresponding vegetation-specific snow albedo value from Robinson and Kukla (1985).A vegetation-dependent threshold value with regard to snow water equivalent (SWE) is used to determine if the ground is fully snow-covered, and for fresh snow, a higher albedo value is estimated to decay towards the fixed vegetation snow albedo values over a period of a few days.This parameterization is based on Koren et al. (1999), after revisions by Livneh et al. (2010).The snow albedo parameterization in WRF-Noah has been subject to a number of studies in recent years, some revealing weaknesses related to early snowmelt as a result of too low snow albedo values.However, recent improvements were suggested by Wang et al. (2010), who found that an increase in the snow cover threshold value for high vegetation, and lowering for low vegetation, reduced over (under-) estimation of snow albedo over high (low) vegetation.This alteration, together with other minor improvements, has recently been made available as an option in Noah and Noah-MP (Noah land surface model with multiparameterization options) (Yang et al., 2011;Niu et al., 2011), and as such it would be of interest to test this version in a further study.A verification of estimated snow cover and snow albedo against observations for the simulated study area is beyond the focus of this study, however, the results herein suggest that the rather low wintertime warming seen in the evergreen forest expanding areas, may be somewhat underestimated.Beringer et al. (2005) examined the potential influence of structural vegetation changes by measuring surface energy exchanges along tundra-to forest transition zone in Alaska during the summer of 1999.They measured sensible heat fluxes and evapotranspiration in five different sites (tundra, low shrub, tall shrub, woodland and forest) acting as an analogue to vegetation transitions that might occur under enhanced warming.They reported small differences in latent energy flux between the sites, and a decrease in ground evaporation was compensated by an increase in evapotranspiration moving from tundra towards more complex canopies.Sensible heat flux was greatly increased going from tundra to more complex canopy vegetation, with both shrubs and trees greatly enhancing the sensible heat flux to the atmosphere.Despite the fact that measurement sites in Beringer et al. (2005) and the simulation domain herein differ in both time and continent, comparing the results points to some general features of summer surface energy partitioning related to vegetation changes, and may as such be useful.Measured differences in sensible heat fluxes between vegetation types, stand in contrast to our simulated fluxes, which are reduced in summertime as result of tree-and shrub expansion into previously tundra covered regions.In areas with changing tundra (from mixed tundra to wooded tundra), the largest monthly mean effect is seen in June, with an average reduction of sensible heat of 1.3 W m −2 , and in areas with northward expanding evergreen forest the main effect is seen in July, with a mean reduction of the sensible heat flux by 11.2 W m −2 .

BGD
The discrepancy in sensible and latent heat flux response points out some important features of the model parameterization.The simulated sensible heat flux is closely related to wind speed.In areas where wind speeds are lowered, the sensible heat fluxes decrease.At the same time, a decrease in surface heat flux results in lower summer-time 2 m temperatures and boundary layer height.
Based on a broad analysis of available observational data from arctic and boreal ecosystems, Eugster et al. (2000) found a general increase in latent heat flux in areas with deciduous trees replacing evergreen needle leaf forest, due to lower canopy conductance in conifer trees.A similar, yet less drastic replacement was made in our Ex 2, where replacement of evergreen needle leaf forest by mixed forest (representing a mix of conifer and deciduous trees.This shift in vegetation causes a modelled year-round reduction in latent heat.This is a result of the model parameterization, which causes a decrease in LAI, but no increase in stomatal conductance given the vegetation shift in Ex 2, and thereby acts to decrease the latent heat release to the atmosphere.Our experiments suggest a significant increase in latent heat flux in summer months in areas with evergreen forest expansion.Introduction

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Full Based on summer season observations of flux partitioning over 66 site years within the FLUXNET project (Baldocchi et al., 2001), Wilson et al. (2002) found that deciduous forest sites in general had a lower summer Bowen ratio (∼ 0.25-0.5)than conifer forest sites (∼ 0.5-1.0),which again were slightly lower than tundra Bowen ratios.In our simulations, areas with a northward migrating evergreen forest (northern border) reduce the summer season (JJA) Bowen ratio by a factor two, going from wooded tundra to evergreen forest.In areas of northward migrating mixed forest (southern boarder), the decrease in both sensible and latent heat fluxes results in a slightly decreasing Bowen ratio from 0.51 to 0.49.
The modelled increase in evapotranspiration in areas of northward migrating evergreen forest also affect the soil moisture, with more water being extracted from especially the deeper layers of soil, owing to the increased number of available soil layers by evergreen forest.However, the latent heat flux is not highly correlated to the soil moisture content in this domain, as fluxes are largely energy limited rather than moisture limited.Shifting the vegetation type towards higher LAI vegetation, acts to reduce correlations for summer months between latent heat and soil moisture, and increase correlations with VPD.These results are in agreement with the findings of e.g.Kasurinen et al. (2014), who measured latent heat fluxes over a total 65 different boreal and arctic sites.They found a general increase in latent heat release and a higher correlation to VPD in observations from forested boreal sites, compared to tundra ecosystems.

Concluding remarks
In this study, observed trends of boreal forest migration were represented by applying perturbations to the current boreal vegetation distribution in two separate experiments.
The perturbations were simple enough to extract their separate effects on the overlying atmosphere, and moderate enough that they induce realistic and relevant information on atmospheric response to vegetation structural changes.The atmospheric response resulting from the vegetation changes made in Ex 1 and Ex 2 largely points in different directions.The Ex 1 high north shrub-and evergreen forest expansion largely leads to a decreasing albedo and larger latent heat fluxes, which subsequently lead to enhanced near surface temperatures and deeper and wetter planetary boundary layer.Reduced wind speed leads to lower sensible heat flux, causing a lowering of the Bowen ratio changing from tundra to conifer forest.On the other hand, the Ex 2 replacement of evergreen forest by more broadleaved species along the southern border of the boreal forest, leads to lower LAI, higher albedo and lower surface fluxes, resulting in lower heating of the boundary layer and lower near surface temperatures and humidity.The differing response of the various vegetation changes results in that the overall effect on the domain is a near zero temperature response on a 10 year average.However, there are large seasonal differences in atmospheric response for the individual vegetation shifts.
The study has been successful in uncovering some special features of model parameterization that might yield unexpected results relative to physical observations of vegetation changes, such as the masking of albedo changes by snow cover, reducing the expected warming in winter and spring, and the lowering instead of increase in sensible heat for more complex canopies.Although latent heat and soil moisture content are closely linked variables, the low correlations found between the two prove that the high latitude study domain is energy, rather than water-limited throughout the year.
In our simulations the perturbations are kept moderate enough to be achieved within this century, and although a result of large climatic average changes in the area, the mean response of the present day atmosphere is not regarded very different from what can be expected as feedbacks from the one accompanying such vegetation changes.We have mainly focused on long term average effects and seasonal mean variations.Many feedback processes are not possible to study in this time resolution, and shorter, more specific time periods might be advantageous in this respect.include the use of these long term simulations as framework for nested, finer resolution simulations, focusing on more specific processes in vegetation atmosphere feedbacks.This study will to that end act as a screening of long term, large feature effects, and as downscaling of boundary conditions for more detailed perturbations and possibly tests of alternative parameterizations in the next, finer scale study.Introduction

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Full  Full Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | modelled whether or not changing vegetation cover in the arctic zone could influence even mesoscale circulation patterns.They simulated the effects Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 3.2 and try to further isolate conditional effects with regard to water deficits in soil and air in Sect.3.3.Discussion Paper | Discussion Paper | Discussion Paper | 3.1 10 year averages: what are the overall effects of vegetation changes?
, right panel).The areas of shrub expansion do not influence the LAI.The 10 year average changes in sensible-and latent surface fluxes as compared to control simulation are presented in Fig. 4 for both experiments (all numbers refer to averages in areas with vegetation changes only).The overall average effect of vegetation changes is a decrease in sensible heat flux to the atmosphere (left panels).Shrub expansion has only a minor influence on the average sensible heat flux.As seen in the lower left panel, the most pronounced negative effect is a result of the northward advancement of mixed forest (Ex 2).The northernmost expansion of evergreen trees into tundra also reduces the sensible heat flux, but not to the same degree.The reduction in sensible heat flux over the entire 10 year period compared to control run is for Ex 1 0.7 W m −2 for areas averaged over both shrub expansion and northward migrating evergreen forest.The corresponding number for Ex 2, considering all vegetation changes, is a reduction of 1.4 W m −2 , mostly a response to the mixed forest northward migration (Fig. 7).Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | show the 10 year average percentage change in volumetric liquid soil water content for Ex 2 compared to control run, for each of the four simulated soil layers.As demonstrated by the figure, the vegetation change most influential on the water content is the area of northward expanding evergreen forest into previously tundra covered area in the north of the domain.The change is larger deeper down in the soil, reflecting the fact that the number of root layers for the evergreen forest increases to four, as compared to the tundra, which only influences the three upper layers.The lowering of soil water content is a result of the ability of the evergreen forest to extract more water from the ground compared to the tundra vegetation, and is reflected in the Discussion Paper | Discussion Paper | Discussion Paper | 2 W m −2 in July.In winter and autumn the effect on the sensible heat flux is reversed as result of this vegetation change, increasing the heat flux in these areas, especially in autumn.The shrub expansion only has a weak decreasing effect on the sensible heat flux in summer.The mixed forest migration has a pronounced year-round effect on the sensible heat flux, with the most prominent reduction in spring and early summer.The overall effect of all vegetation changes (solid line) is close to Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Liess et al. (2011) used the IGBP MODIS land cover dataset in which no alterations have been made to the land use category of "open shrub land" as is the case for the modified MODIS dataset (where replaced by various tundra vegetation classes).They found the open shrub land use class a suitable category for forest conversion across the arctic and northern boreal domain.This represents a similar, but somewhat larger Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | For the purpose of more detailed investigation on finer temporal and spatial scale, future work Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Figure 1 .Figure 2 .Figure 3 .
Figure 1.The northern European boreal forest domain, represented here by evergreen needle leaf forest as fraction of grid cell, remapped from the modified IGBP MODIS data to 27 km × 27 km resolution.

Figure 4 .Figure 5 .
Figure 4. Changes in 10 year average surface sensible heat flux (left panels) and latent heat flux (right panels), as compared to control simulation.Ex 1 in upper panels, Ex 2 in lower panels.

Table 1 .
Key parameters for the dominant vegetation categories used in Ex 1 and Ex 2.