Snowmelt duration controls red algal blooms in the snow of the European Alps.

Algae populate multiple habitats, including snow and ice, where they can form red blooms. These decrease snow albedo, accelerating snowmelt and potentially feeding back on snow and glacier decline caused by climate change. Quantifying this feedback requires the understanding of bloom evolution with climate change. Little, however, is known about the drivers of red snow blooms. Here, we develop an algorithm to analyze 5 y of satellite data from the European Alps and separate bloom occurrences from similarly colored Saharan dust depositions. In a second step, we combine the occurrences of blooms with meteorological data and snow simulations to identify the drivers of blooms. Results show that the upward migration of algae from the ground and blooming requires the presence of liquid water throughout the whole snow column for at least 46 d. Our limited data suggest that moderate dust amounts provide nutrients favorable to bloom, whereas large dust amounts hasten snowmelt and reduce its duration below the threshold required for blooming. Over the period studied, blooms cover 1.3% of the area above 1,800 m elevation, advancing the snow melt-out date by 4 to 21 d in these areas. Under warmer climates, maximum snow mass will decrease whereas snowmelt duration, that controls algal blooms' occurrences, is less sensitive to global temperature increase. In this respect, the impact of bloom on snowmelt will either remain stable (RCP4.5) or decrease (RCP8.5). Algal blooms in the Alps therefore do not constitute a positive climate feedback.

Black carbon and dust alter the response of mountain snow cover under climate change.

By darkening the snow surface, mineral dust and black carbon (BC) deposition enhances snowmelt and triggers numerous feedbacks. Assessments of their long-term impact at the regional scale are still largely missing despite the environmental and socio-economic implications of snow cover changes. Here we show, using numerical simulations, that dust and BC deposition advanced snowmelt by 17 ± 6 days on average in the French Alps and the Pyrenees over the 1979-2018 period. BC and dust also advanced by 10-15 days the peak melt water runoff, a substantial effect on the timing of water resources availability. We also demonstrate that the decrease in BC deposition since the 1980s moderates the impact of current warming on snow cover decline. Hence, accounting for changes in light-absorbing particles deposition is required to improve the accuracy of snow cover reanalyses and climate projections, that are crucial for better understanding the past and future evolution of mountain social-ecological systems.

Climate models generally underrepresent the warming by Central Africa biomass-burning aerosols over the Southeast Atlantic.

The radiative budget, cloud properties, and precipitation over tropical Africa are influenced by solar absorption by biomass-burning aerosols (BBA) from Central Africa. Recent field campaigns, reinforced by new remote-sensing and aerosol climatology datasets, have highlighted the absorbing nature of the elevated BBA layers over the South-East Atlantic (SEA), indicating that the absorption could be stronger than previously thought. We show that most of the latest generation of general circulation models (GCMs) from the sixth phase of the Coupled Model Intercomparison Project 6 (CMIP6) underestimates the absorption of BBA over the SEA. This underlines why many (~75%) CMIP6 models do not fully capture the intense positive (warming) direct radiative forcing at the top of the atmosphere observed over this region. In addition, underestimating the magnitude of the BBA-induced solar heating could lead to misrepresentations of the low-level cloud responses and fast precipitation feedbacks that are induced by BBA in tropical regions.

The Climate Response to Emissions Reductions Due to COVID-19: Initial Results From CovidMIP.

Many nations responded to the corona virus disease-2019 (COVID-19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. 12 models performed multiple initial-condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near-surface temperature or rainfall during 2020-2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID-19-related emission reductions on near-term climate.