Role of land surface processes and diffuse/direct radiation partitioning in simulating the European climate

The influence of land processes and in particular of diffuse/direct radiation partitioning on surface fluxes and associated regional-scale climate feedbacks is investigated using ERA-40 driven simulations over Europe performed with the COSMO-CLM2 Regional Climate Model (RCM). Two alternative Land Surface Models (LSMs), a 2nd generation LSM (TERRA_ML) and a more advanced 3rd generation LSM (Community Land Model version 3.5), and two versions of the atmospheric component are tested, as well as a revised coupling procedure allowing for variations in diffuse/direct light partitioning at the surface, and their accounting by the land surface component. Overall, the RCM performance for various variables (e.g., surface fluxes, temperature and precipitation) is improved when using the more advanced 3rd generation LSM. These improvements are of the same order of magnitude as those arising from a new version of the atmospheric component, demonstrating the benefit of using a realistic representation of land surface processes for regional climate simulations. Taking into account the variability in diffuse/direct light partitioning at the surface further improves the model performance in terms of summer temperature variability at the monthly and daily time scales. Comparisons with observations show that the RCM realistically captures temporal variations in diffuse/direct light partitioning as well as the evapotranspiration sensitivity to these variations. Our results suggest that a modest but consistent fraction (up to 3 %) of the overall variability in summer temperature can be explained by variations in the diffuse to direct ratio.ISSN:1726-4170ISSN:1726-417

What determines the sign of the evapotranspiration response to afforestation in European summer?

Uncertainties in the evapotranspiration response to afforestation constitute a major source of disagreement between model-based studies of the potential climate benefits of forests. Forests typically have higher evapotranspiration rates than grasslands in the tropics, but whether this is also the case in the midlatitudes is still debated. To explore this question and the underlying physical processes behind these varying evapotranspiration rates of forests and grasslands in more detail, a regional model study with idealized afforestation scenarios was performed for Europe. In the first experiment, Europe was maximally forested, and in the second one, all forests were turned into grassland. The results of this modeling study exhibit the same contradicting evapotranspiration characteristics of forests and grasslands as documented in observational studies, but by means of an additional sensitivity simulation in which the surface roughness of the forest was reduced to grassland, the mechanisms behind these varying evapotranspiration rates could be revealed. Due to the higher surface roughness of a forest, solar radiation is more efficiently transformed into turbulent sensible heat fluxes, leading to lower surface temperatures (top of vegetation) than in grassland. The saturation deficit between the vegetation and the atmosphere, which depends on the surface temperature, is consequently reduced over forests. This reduced saturation deficit counteracts the transpiration-facilitating characteristics of a forest (deeper roots, a higher leaf area index, LAI, and lower albedo values than grassland). If the impact of the reduced saturation deficit exceeds the effects of the transpiration-facilitating characteristics of a forest, evapotranspiration is reduced compared to grassland. If not, evapotranspiration rates of forests are higher. The interplay of these two counteracting factors depends on the latitude and the prevailing forest type in a region.ISSN:1726-4170ISSN:1726-417

Is land surface processes representation a possible weak link in current Regional Climate Models?

The representation of land surface processes and fluxes in climate models critically affects the simulation of near-surface climate over land. Here we present an evaluation of COSMO-CLM2, a model which couples the COSMO-CLM Regional Climate Model to the Community Land Model (CLM4.0). CLM4.0 provides a more detailed representation of land processes compared to the native land surface scheme in COSMO-CLM. We perform historical reanalysis-driven simulations over Europe with COSMO-CLM2 following the EURO-CORDEX intercomparison protocol. We then evaluate simulations performed with COSMO-CLM2, the standard COSMO-CLM and other EURO-CORDEX RCMs against various observational datasets of temperature, precipitation and surface fluxes. Overall, the results indicate that COSMO-CLM2 outperforms both the standard COSMO-CLM and the other EURO-CORDEX models in simulating sensible, latent and surface radiative fluxes as well as 2-meter temperature across different seasons and regions. The performance improvement is particularly strong for turbulent fluxes and for daily maximum temperatures and more modest for daily minimum temperature, suggesting that land surface processes affect daytime even more than nighttime conditions. COSMO-CLM2 also alleviates a long-standing issue of overestimation of interannual summer temperature variability present in most EURO-CORDEX RCMs. Finally, we show that several factors contribute to these improvements, including the representation of evapotranspiration, radiative fluxes and ground heat flux. Overall, these results demonstrate that land processes represent a key area of development to tackle current deficiencies in RCMs.ISSN:1748-9326ISSN:1748-931

Influence of Amazonian deforestation on the future evolution of regional surface fluxes, circulation, surface temperature and precipitation

The extent of the Amazon rainforest is projected to drastically decrease in future decades because of land-use changes. Previous climate modelling studies have found that the biogeophysical effects of future Amazonian deforestation will likely increase surface temperatures and reduce precipitation locally. However, the magnitude of these changes and the potential existence of tipping points in the underlying relationships is still highly uncertain. Using a regional climate model at a resolution of about 50 km over the South American continent, we perform four ERA-interim-driven simulations with prescribed land cover maps corresponding to present-day vegetation, two deforestation scenarios for the twenty-first century, and a totally-deforested Amazon case. In response to projected land cover changes for 2100, we find an annual mean surface temperature increase of 0.5 °C over the Amazonian region and an annual mean decrease in rainfall of 0.17 mm/day compared to present-day conditions. These estimates reach 0.8 °C and 0.22 mm/day in the total-deforestation case. We also compare our results to those from 28 previous (regional and global) climate modelling experiments. We show that the historical development of climate models did not modify the median estimate of the Amazonian climate sensitivity to deforestation, but led to a reduction of its uncertainty. Our results suggest that the biogeophysical effects of deforestation alone are unlikely to lead to a tipping point in the evolution of the regional climate under present-day climate conditions. However, the conducted synthesis of the literature reveals that this behaviour may be model-dependent, and the greenhouse gas-induced climate forcing and biogeochemical feedbacks should also be taken into account to fully assess the future climate of this region.ISSN:0930-7575ISSN:1432-089

Hydrological and biogeochemical constraints on terrestrial carbon cycle feedbacks

The feedbacks between climate, atmospheric CO2 concentration and the terrestrial carbon cycle are a major source of uncertainty in future climate projections with Earth systems models. Here, we use observation-based estimates of the interannual variations in evapotranspiration (ET), net biome productivity (NBP), as well as the present-day sensitivity of NBP to climate variations, to constrain globally the terrestrial carbon cycle feedbacks as simulated by models that participated in the fifth phase of the coupled model intercomparison project (CMIP5). The constraints result in a ca. 40% lower response of NBP to climate change and a ca. 30% reduction in the strength of the CO2 fertilization effect relative to the unconstrained multi-model mean. While the unconstrained CMIP5 models suggest an increase in the cumulative terrestrial carbon storage (477 PgC) in response to an idealized scenario of 1%/year atmospheric CO2 increase, the constraints imply a ca. 19% smaller change. Overall, the applied emerging constraint approach offers a possibility to reduce uncertainties in the projections of the terrestrial carbon cycle, which is a key determinant of the future trajectory of atmospheric CO2 concentration and resulting climate change.ISSN:1748-9326ISSN:1748-931

Historical deforestation locally increased the intensity of hot days in northern mid-latitudes

ISSN:1758-679

Impact of soil map specifications for European climate simulations

ISSN:0930-7575ISSN:1432-089

COSMO-CLM^2: A new version of the COSMO-CLM model coupled to the Community Land Model

ISSN:0930-7575ISSN:1432-089

A spatially explicit representation of conservation agriculture for application in global change studies

Conservation agriculture (CA) is widely promoted as a sustainable agricultural management strategy with the potential to alleviate some of the adverse effects of modern, industrial agriculture such as large‐scale soil erosion, nutrient leaching and overexploitation of water resources. Moreover, agricultural land managed under CA is proposed to contribute to climate change mitigation and adaptation through reduced emission of greenhouse gases, increased solar radiation reflection, and the sustainable use of soil and water resources. Due to the lack of official reporting schemes, the amount of agricultural land managed under CA systems is uncertain and spatially explicit information about the distribution of CA required for various modeling studies is missing. Here, we present an approach to downscale present‐day national‐level estimates of CA to a 5 arcminute regular grid, based on multicriteria analysis. We provide a best estimate of CA distribution and an uncertainty range in the form of a low and high estimate of CA distribution, reflecting the inconsistency in CA definitions. We also design two scenarios of the potential future development of CA combining present‐day data and an assessment of the potential for implementation using biophysical and socioeconomic factors. By our estimates, 122–215 Mha or 9%–15% of global arable land is currently managed under CA systems. The lower end of the range represents CA as an integrated system of permanent no‐tillage, crop residue management and crop rotations, while the high estimate includes a wider range of areas primarily devoted to temporary no‐tillage or reduced tillage operations. Our scenario analysis suggests a future potential of CA in the range of 533–1130 Mha (38%–81% of global arable land). Our estimates can be used in various ecosystem modeling applications and are expected to help identifying more realistic climate mitigation and adaptation potentials of agricultural practices.ISSN:1354-1013ISSN:1365-248

Biomass heat storage dampens diurnal temperature variations in forests

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.ISSN:1748-9326ISSN:1748-931