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The roughness of the land surface (z0) is a key property, exerting significant influence on the amount of near-surface turbulent activity and consequently the turbulent exchange of energy, water, momentum, and chemical species between the land and the atmosphere. Variations in z0 are substantial across different types of land cover, ranging from typically less than 1 mm over fresh snow or sand deserts up to more than 1 m over urban areas or forests. In this study, we revise the parameterizations and parameter choices related to z0 in the Community Land Model 5.1 (CLM), the land component of the Community Earth System Model (CESM). We propose a number modifications for z0 in CLM, guided by observational data. Most importantly, we find that the observations support an increase in z0 for all types of forests and a decrease in the momentum z0 for bare soil, snow, glaciers, and crops. We then assess the effect of those modifications in land-only and land–atmosphere coupled simulations. With the revised parameterizations, diurnal variations of the land surface temperature (LST) are dampened in forested regions and are amplified over warm deserts. These changes mitigate model biases compared to MODerate resolution Imaging Spectroradiometer (MODIS) remote sensing observations. The changes in LST are generally stronger during the day than at night. For example, the LST increases by 5.1 K at 13:30 local solar time but only by 0.6 K at 01:30 during boreal summer across the entire Sahara. The induced changes in the diurnal variability of near-surface air temperatures are generally of the opposite sign and of smaller magnitude. Near-surface winds accelerate in areas where the momentum z0 was lowered, such as the Sahara, the Middle East, and Antarctica, and decelerate in regions with forests. Overall, this study finds that the current representation of z0 in CLM is not in agreement with observational constraints for several types of land cover. The proposed model modifications are shown to considerably alter the simulated climate in terms of temperatures and wind speed at the land surface. [ABSTRACT FROM AUTHOR]

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. Urban trees influence temperatures in cities. The authors here investigate in spatio-temporal variations in their cooling effect and find 8-12 K decreased temperatures for tree-rich urban areas in Central Europe during hot summers, and up to 4 K for Southern Europe, respectively. [ABSTRACT FROM AUTHOR]

The roughness of the land surface (z0) is a key property for the amount of turbulent activity above the land surface and through that for the turbulent exchange of energy, water, momentum, and chemical species between the land and the atmosphere. Variations in z0 are substantial across different types of land cover from typically less than 1 mm over fresh snow or sand deserts up to more than 1 m over urban areas or forests. In this study, we revise the parameterizations and parameter choices related to z0 in the Community Land Model 5.1 (CLM), the land component of the Community Earth System Model 2.1.2 (CESM). We propose a number modifications for z0 in CLM, which are guided by observational data. Most importantly, we increase the z0 for all types of forests, while we decrease the momentum z0 for bare soil, snow, glaciers, and crops. We then assess the effect of those modifications in land-only (CLM) and land-atmosphere coupled (CESM) simulations. Diurnal variations of the land surface temperature (LST) are dampened in regions with forests, while they are amplified over warm deserts. These changes mitigate model biases compared to MODIS remote sensing observations, which have been identified in several earlier studies. The alterations in LST are mostly stronger during the day than at night. For example, the LST at 13:30 increases by more than 4.80 K during boreal summer across the entire Sahara. The induced changes in the diurnal variability of air temperatures at the bottom of the atmosphere generally oppose changes in LST in sign and are of smaller magnitude. Further, winds close to the land surface accelerate in areas where the momentum z0 was lowered, such as the Sahara desert, the Middle East, or the Antarctica, and decelerate in regions with forests. Overall, this study highlights that the current representation of z0 in CLM is not in agreement with observational constraints for several types of land cover. The resultant model modifications are shown to considerably alter the simulated climate in terms of temperatures and wind speed at the land surface. [ABSTRACT FROM AUTHOR]

Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remotesensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate. [ABSTRACT FROM AUTHOR]

Forest management (FM) can help to mitigate climate change by altering biogeochemical and biophysical processes at the earth surface. However, the biophysical climate effects of FM are not yet sufficiently understood and decision-makers lack scientific evidence when designing sustainable FM strategies. To enhance our understanding of the biophysical climate effect of FM, we used two LST datasets over Europe (MODIS, LSA SAF) derived from satellite remote sensing observations. We assessed the link between spatial patterns of LST and spatial patterns of forest structure and forest type, which can be related to different FM strategies. Our results show that the two management strategies of increasing tree cover density and broadleaf tree fraction provide local cooling during the day in summer. During nights and in winter both FM strategies mainly cause warming. During the day an increased broadleaf tree fraction seems to provide cooling in the afternoon, while an increased tree cover density provides largest cooling at around noon. In mediterranean forests, the summer cooling caused by an increased tree cover density is more than two times higher than the one caused by an increased broadleaf tree fraction. In the boreal forest both strategies provide a cooling of similar magnitude. In boreal and alpine forests an increase in tree cover density and broadleaved tree fraction leads to an increase in yearly mean temperatures. However, for all regions we observe a reduction in maximum temperatures in summer and potentially during heatwaves. [ABSTRACT FROM AUTHOR]