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

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

Biases in the albedo sensitivity to deforestation in CMIP5 models and their impacts on the associated historical radiative forcing

Climate model biases in the representation of albedo variations between land cover classes contribute to uncertainties on the climate impact of land cover changes since pre-industrial times, especially on the associated radiative forcing. Recent publications of new observation-based datasets offer opportunities to investigate these biases and their impact on historical surface albedo changes in simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Conducting such an assessment is, however, complicated by the non-availability of albedo values for specific land cover classes in CMIP and the limited number of simulations isolating the land use forcing. In this study, we demonstrate the suitability of a new methodology to extract the albedo of trees and crops–grasses in standard climate model simulations. We then apply it to historical runs from 17 CMIP5 models and compare the obtained results to satellite-derived reference data. This allows us to identify substantial biases in the representation of the albedo of trees and crops–grasses as well as the surface albedo change due to the transition between these two land cover classes in the analysed models. Additionally, we reconstruct the local surface albedo changes induced by historical conversions between trees and crops–grasses for 15 CMIP5 models. This allows us to derive estimates of the albedo-induced radiative forcing from land cover changes since pre-industrial times. We find a multi-model range from 0 to −0.17 W m−2, with a mean value of −0.07 W m−2. Constraining the surface albedo response to transitions between trees and crops–grasses from the models with satellite-derived data leads to a revised multi-model mean estimate of −0.09 W m−2 but an increase in the multi-model range. However, after excluding one model with unrealistic conversion rates from trees to crops–grasses the remaining individual model results vary between −0.03 and −0.11 W m−2. These numbers are at the lower end of the range provided by the IPCC AR5 (−0.15±0.10 W m−2). The approach described in this study can be applied to other model simulations, such as those from CMIP6, especially as the evaluation diagnostic described here has been included in the ESMValTool v2.0

7. L’usage des terres

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7. L’usage des terres

La reconnaissance du rôle de l’Homme sur le climat est généralement associée à l’augmentation de la concentration atmosphérique en gaz à effet de serre* (GES) et en aérosols d’origine anthropique, et à leurs implications sur le forçage radiatif* de la Terre (IPCC 2007). Pourtant l’Homme a également profondément modifié les paysages dès sa sédentarisation et pour divers usages. Le terme « usage des sols » regroupe des perturbations variées (mises en cultures, pâturages, urbanisation, exploitat..

Le climat à découvert

Qu'est ce que l'effet de serre ? Le rôle de l'homme sur le climat est-il détectable et comment ? Comment mesure-t-on la fonte de la banquise, le recul des glaciers de montagne ou bien encore l'élévation du niveau de la mer ? Comment les chercheurs font-ils pour modéliser un système aussi complexe que la planète terre ? Quelles données permettent de décrire et modéliser les climats passés ? Comment s'y prend-on pour prévoir l'évolution à venir du climat ? À l'écart de la polémique médiatique, Catherine Jeandel et Rémy Mosseri ont mobilisé plus d'une centaine de contributeurs qui livrent ici un panorama large des méthodes et outils mis en œuvre pour étudier notre climat et son avenir. Ils montrent que, pour résoudre cette question extraordinairement complexe, une approche pluridisciplinaire est plus que jamais nécessaire, a la croisée de l'expérimentation, de l'observation, de la simulation et de la théorie. Un livre majeur