Urban trees influence temperatures in cities. However, their effectiveness at mitigating urban heat in different climatic contexts and in comparison to treeless urban green spaces has not yet been sufficiently explored. Here, we use high-resolution satellite land surface temperatures (LSTs) and land-cover data from 293 European cities to infer the potential of urban trees to reduce LSTs. We show that urban trees exhibit lower temperatures than urban fabric across most European cities in summer and during hot extremes. Compared to continuous urban fabric, LSTs observed for urban trees are on average 0-4 K lower in Southern European regions and 8-12 K lower in Central Europe. Treeless urban green spaces are overall less effective in reducing LSTs, and their cooling effect is approximately 2-4 times lower than the cooling induced by urban trees. By revealing continental-scale patterns in the effect of trees and treeless green spaces on urban LST our results highlight the importance of considering and further investigating the climate-dependent effectiveness of heat mitigation measures in cities.

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Observational evidence suggests that compared to non-forested areas, forests have a cooling effect on daytime land surface temperature (LST) and a warming effect on nighttime LST in many regions of the world, thus implying that forests dampen the diurnal temperature range. This feature is not captured by current climate models. Using the Community Land Model 5.0 (CLM5.0), we show that this diurnal behavior can be captured when accounting for biomass heat storage (BHS). The nighttime release of energy absorbed by the vegetation biomass during the day increases both nighttime LST and ambient air temperature in forested regions by more than 1 K. The daytime cooling is weaker than the nighttime warming effect, because the energy uptake by the biomass is compensated by a reduction in the turbulent heat fluxes during day. This diurnal asymmetry of the temperature response to BHS leads to a warming of daily mean temperatures, which is amplified during boreal summer warm extremes. Compared to MODIS, CLM5.0 overestimates the diurnal LST range over forested areas. The inclusion of BHS reduces this bias due to its dampening effect on diurnal LST variations. Further, BHS attenuates the negative bias in the nighttime LST difference of forest minus grassland and cropland, when compared to MODIS observations. These results indicate that it is essential to consider BHS when examining the influence of forests on diurnal temperature variations. BHS should thus be included in land surface models used to assess the climatic consequences of land use changes such as deforestation or afforestation.

Abstract. In this study, we assess the climate mitigation potential from afforestation in a mountainous snow-rich region (Switzerland) with strongly varying environmental conditions. Using radiative forcing calculations, we quantify both the carbon sequestration potential and the effect of albedo change at high resolution. We calculate the albedo radiative forcing based on remotely sensed data sets of albedo, global radiation and snow cover. Carbon sequestration is estimated from changes in carbon stocks based on national inventories. We first estimate the spatial pattern of radiative forcing (RF) across Switzerland assuming homogeneous transitions from open land to forest. This highlights where forest expansion still exhibits climatic benefits when including the radiative forcing of albedo change. Second, given that forest expansion is currently the dominant land-use change process in the Swiss Alps, we calculate the radiative forcing that occurred between 1985 and 1997. Our results show that the net RF of forest expansion ranges from −24 W m −2 at low elevations of the northern Prealps to 2 W m −2 at high elevations of the Central Alps. The albedo RF increases with increasing altitude, which offsets the CO 2 RF at high elevations with long snow-covered periods, high global radiation and low carbon sequestration. Albedo RF is particularly relevant during transitions from open land to open forest but not in later stages of forest development. Between 1985 and 1997, when overall forest expansion in Switzerland was approximately 4 %, the albedo RF offset the CO 2 RF by an average of 40 %. We conclude that the albedo RF should be considered at an appropriately high resolution when estimating the climatic effect of forestation in temperate mountainous regions.

Forests influence climate through a myriad of chemical, physical and biological processes and are an essential lever in the efforts to counter climate change. The majority of studies investigating potential climate benefits from forests have focused on forest area changes, while changes to forest management, in particular those affecting species composition, have received much less attention. Using a statistical model based on remote sensing observations over europe, we show that broadleaved tree species locally reduce land surface temperatures in summer compared to needle-leaved species. The summer mean cooling effect related to an increase in broad-leaved tree fraction of 80% is relatively modest (~ 0.3-0.75 K), but is amplified during exceptionally warm periods. The reduction of daily maximum temperatures during the hottest days reaches up to 1.8 K in the Atlantic region and up to 1.5 K in Continental and Mediterranean regions. Hot temperature extremes adversely affect humans and ecosystems and are expected to become more frequent in a future climate. thus, forest management strategies aiming to increase the fraction of broad-leaved species could help to reduce some of the adverse local impacts caused by hot temperature extremes. However, the overall benefits and trade-offs related to an increase in the broad-leaved tree fraction in European forests needs to be further investigated and assessed carefully when adapting forest management strategies. Forests are expected to play an essential role in climate change mitigation as they can generally sequester more carbon than non-forested ecosystems 1-3. In addition, forests affect water and energy fluxes at the earth surface through biogeophysical processes including changes in evapotranspiration, albedo, and surface roughness 4,5. Various observation-based studies have shown that forests, through these biogeophysical processes, either reduce or increase local temperatures depending on location and time of observation 6-9. In contrast to a comparison of forested and non-forested ecosystems, the potential impacts on temperatures of forest management or more generally changes in forest characteristics are less well documented 10-12. Facilitating an increase of the broad-leaved tree fraction (BTF) in forests is a promising management strategy to enhance the provision of ecosystem services and to adapt to climate change 13-16. For example, increasing the BTF can lead to reduced risk of fires, wind throw and bark beetle outbreaks 15,17. However, the potential benefits of broad-leaved trees through their biogeophysical influence on temperature, in particular on extreme temperatures, have not yet been investigated beyond the site-level scale 18 even though changes on extreme temperatures are highly relevant in terms of impacts on humans and ecosystems 19,20. To investigate how an increase in the BTF in Europe would influence local land surface temperature (LST) we linked observed patterns of LST with patterns of the BTF. In contrast to previous studies, we use remote sens...

Flow diagram of a generic Genetic Algorithm. Right: Flow diagram of an example for a combined mutation operator. Here we display the combination of four operators: RBM_RCM_BRM_BCPM. The probabilities that the algorithm enters a mutation are called indpb_patch, indpb_block and indpb. Each of them is per default 0.1. A random number between 0 and 1 (r) is selected every time for comparison with the probabilities.

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