James Ryder

Land management and land-cover change have impacts of similar magnitude on surface temperature

The direct effects of land-cover change on surface climate are increasingly well understood, but fewer studies have investigated the consequences of the trend towards more intensive land management practices. Now, research investigating the biophysical effects of temperate land-management changes reveals a net warming effect of similar magnitude to that driven by changing land cover.

Europe’s forest management did not mitigate climate warming

Europes managed forests contribute to warming For most of the past 250 years, surprisingly it seems that Europes managed forests have been a net source of carbon, contributing to climate warming rather than mitigating it. Naudts et al. reconstructed the history of forest management in Europe in the context of a land-atmosphere model. The release of carbon otherwise stored in litter, dead wood, and soil carbon pools in managed forests was one key factor contributing to climate warming. Second, the conversion of broadleaved forests to coniferous forests has changed the albedo and evapotranspiration of those forests, also leading to warming. Thus, climate change mitigation policies in Europe and elsewhere may need to consider changes in forest management. Science, this issue p. 597 Reconstruction of 250 years of forest management history shows that Europe’s managed forests have contributed to climate warming. Afforestation and forest management are considered to be key instruments in mitigating climate change. Here we show that since 1750, in spite of considerable afforestation, wood extraction has led to Europe’s forests accumulating a carbon debt of 3.1 petagrams of carbon. We found that afforestation is responsible for an increase of 0.12 watts per square meter in the radiative imbalance at the top of the atmosphere, whereas an increase of 0.12 kelvin in summertime atmospheric boundary layer temperature was mainly caused by species conversion. Thus, two and a half centuries of forest management in Europe have not cooled the climate. The political imperative to mitigate climate change through afforestation and forest management therefore risks failure, unless it is recognized that not all forestry contributes to climate change mitigation.

Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations

Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation) into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique) improve the simulation accuracy of mean seasonal (October throughout May) snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the magnitude of which is almost comparable to that due to CO2 (2.83 W m-2) increases since 1750. Our results thus highlight the necessity of realistic representation of snow albedo in the model and demonstrate the use of satellite-based snow albedo to improve model behaviors, which opens new avenues for constraining snow albedo feedback in earth system models.

Spring Snow‐Albedo Feedback Analysis Over the Third Pole: Results From Satellite Observation and CMIP5 Model Simulations

The snow‐albedo feedback is a crucial component in high‐altitude cryospheric change but is poorly quantified over the Third Pole, encompassing the Karakoram and Tibetan Plateau. Here we present an analysis of present‐day and future spring snow‐albedo feedback over the Third Pole, using a 28 year satellite‐based albedo and the latest climate model simulations. We show that present‐day spring snow‐albedo feedback strength is primarily determined by the decrease in albedo due to snow metamorphosis, rather than that due to reduced snow cover in the Karakoram, but not found in Southeastern Tibet. We further demonstrate an emergent relationship between snow‐albedo feedback from the seasonal cycle and that from climate change across models. Combined with contemporary satellite‐based snow‐albedo feedback from seasonal cycle, this relationship enables us to estimate that the feedback strength for the Karakoram with a relatively high glaciated area is −2.42 ± 0.48% K−1 under an unmitigated scenario, which is much stronger than that for Southeastern Tibet (−1.64 ± 0.48% K−1) and for the Third Pole (−0.89 ± 0.44% K−1), respectively. Moreover, it is noteworthy that the magnitude of the constrained strength is only half of the unconstrained model estimate for the Third Pole, suggesting that current climate models generally overestimate the feedback of spring snow change to temperature change based on the unmitigated scenario.