Quantifying black carbon deposition over the Greenland ice sheet from forest fires in Canada

Black carbon (BC) concentrations observed in 22 snowpits sampled in the northwest sector of the Greenland ice sheet in April 2014 have allowed us to identify a strong and widespread BC aerosol deposition event, which was dated to have accumulated in the pits from two snow storms between 27 July and 2 August 2013. This event comprises a significant portion (57% on average across all pits) of total BC deposition over 10 months (July 2013 to April 2014). Here we link this deposition event to forest fires burning in Canada during summer 2013 using modeling and remote sensing tools. Aerosols were detected by both the Cloud‐Aerosol Lidar with Orthogonal Polarization (on board CALIPSO) and Moderate Resolution Imaging Spectroradiometer (Aqua) instruments during transport between Canada and Greenland. We use high‐resolution regional chemical transport modeling (WRF‐Chem) combined with high‐resolution fire emissions (FINNv1.5) to study aerosol emissions, transport, and deposition during this event. The model captures the timing of the BC deposition event and shows that fires in Canada were the main source of deposited BC. However, the model underpredicts BC deposition compared to measurements at all sites by a factor of 2–100. Underprediction of modeled BC deposition originates from uncertainties in fire emissions and model treatment of wet removal of aerosols. Improvements in model descriptions of precipitation scavenging and emissions from wildfires are needed to correctly predict deposition, which is critical for determining the climate impacts of aerosols that originate from fires

Melt pond fraction and spectral sea ice albedo retrieval from MERIS data – Part 1: Validation against in situ, aerial, and ship cruise data

The presence of melt ponds on the Arctic sea ice strongly affects the energy balance of the Arctic Ocean in summer. It affects albedo as well as transmittance through the sea ice, which has consequences for the heat balance and mass balance of sea ice. An algorithm to retrieve melt pond fraction and sea ice albedo from Medium Resolution Imaging Spectrometer (MERIS) data is validated against aerial, shipborne and in situ campaign data. The results show the best correlation for landfast and multiyear ice of high ice concentrations. For broadband albedo, R2 is equal to 0.85, with the RMS (root mean square) being equal to 0.068; for the melt pond fraction, R2 is equal to 0.36, with the RMS being equal to 0.065. The correlation for lower ice concentrations, subpixel ice floes, blue ice and wet ice is lower due to ice drift and challenging for the retrieval surface conditions. Combining all aerial observations gives a mean albedo RMS of 0.089 and a mean melt pond fraction RMS of 0.22. The in situ melt pond fraction correlation is R2 = 0.52 with an RMS = 0.14. Ship cruise data might be affected by documentation of varying accuracy within the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol, which may contribute to the discrepancy between the satellite value and the observed value: mean R2 = 0.044, mean RMS = 0.16. An additional dynamic spatial cloud filter for MERIS over snow and ice has been developed to assist with the validation on swath data

Impact of melt ponds on Arctic sea ice simulations from 1990 to 2007

The extent and thickness of the Arctic sea ice cover has decreased dramatically in the past few decades with minima in sea ice extent in September 2007 and 2011 and climate models did not predict this decline. One of the processes poorly represented in sea ice models is the formation and evolution of melt ponds. Melt ponds form on Arctic sea ice during the melting season and their presence affects the heat and mass balances of the ice cover, mainly by decreasing the value of the surface albedo by up to 20%. We have developed a melt pond model suitable for forecasting the presence of melt ponds based on sea ice conditions. This model has been incorporated into the Los Alamos CICE sea ice model, the sea ice component of several IPCC climate models. Simulations for the period 1990 to 2007 are in good agreement with observed ice concentration. In comparison to simulations without ponds, the September ice volume is nearly 40% lower. Sensitivity studies within the range of uncertainty reveal that, of the parameters pertinent to the present melt pond parameterization and for our prescribed atmospheric and oceanic forcing, variations of optical properties and the amount of snowfall have the strongest impact on sea ice extent and volume. We conclude that melt ponds will play an increasingly important role in the melting of the Arctic ice cover and their incorporation in the sea ice component of Global Circulation Models is essential for accurate future sea ice forecasts

Greenland ice sheet surface mass loss: recent developments in observation and modeling

Surface processes currently dominate Greenland ice sheet (GrIS) mass loss. We review recent developments in the observation and modelling of GrIS surface mass balance (SMB), published after the July 2012 deadline for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Since IPCC AR5 our understanding of GrIS SMB has further improved, but new observational and model studies have also revealed that temporal and spatial variability of many processes are still poorly quantified and understood, e.g. bio-albedo, the formation of ice lenses and their impact on lateral meltwater transport, heterogeneous vertical meltwater transport (‘piping’), the impact of atmospheric circulation changes and mixed-phase clouds on the surface energy balance and the magnitude of turbulent heat exchange over rough ice surfaces. As a result, these processes are only schematically or not at all included in models that are currently used to assess and predict future GrIS surface mass loss

Strong constraints on aerosol-cloud interactions from volcanic eruptions.

Aerosols have a potentially large effect on climate, particularly through their interactions with clouds, but the magnitude of this effect is highly uncertain. Large volcanic eruptions produce sulfur dioxide, which in turn produces aerosols; these eruptions thus represent a natural experiment through which to quantify aerosol-cloud interactions. Here we show that the massive 2014-2015 fissure eruption in Holuhraun, Iceland, reduced the size of liquid cloud droplets-consistent with expectations-but had no discernible effect on other cloud properties. The reduction in droplet size led to cloud brightening and global-mean radiative forcing of around -0.2 watts per square metre for September to October 2014. Changes in cloud amount or cloud liquid water path, however, were undetectable, indicating that these indirect effects, and cloud systems in general, are well buffered against aerosol changes. This result will reduce uncertainties in future climate projections, because we are now able to reject results from climate models with an excessive liquid-water-path response

Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice

Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0∘ (nadir) and 50∘. Two wind events in November 2019 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coefficients at nadir are observed, coincident with surface topography changes measured by a terrestrial laser scanner. At both frequencies, redistribution caused snow densification at the surface and the uppermost layers, increasing the scattering at the air–snow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previous air–snow interfaces, buried beneath newly deposited snow. The additional scattering from previous air–snow interfaces could therefore affect the range retrieved from Ka- and Ku-band satellite altimeters. With increasing incidence angles, the relative scattering contribution of the air–snow interface decreases, and the snow–sea ice interface scattering increases. Relative to pre-wind event conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Results show substantial backscatter variability within the scan area at all incidence angles and polarizations, in response to increasing wind speed and changes in wind direction. Our results show that snow redistribution and wind compaction need to be accounted for to interpret airborne and satellite radar measurements of snow-covered sea ice.</p

State of the climate in 2018

In 2018, the dominant greenhouse gases released into Earth’s atmosphere—carbon dioxide, methane, and nitrous oxide—continued their increase. The annual global average carbon dioxide concentration at Earth’s surface was 407.4 ± 0.1 ppm, the highest in the modern instrumental record and in ice core records dating back 800 000 years. Combined, greenhouse gases and several halogenated gases contribute just over 3 W m−2 to radiative forcing and represent a nearly 43% increase since 1990. Carbon dioxide is responsible for about 65% of this radiative forcing. With a weak La Niña in early 2018 transitioning to a weak El Niño by the year’s end, the global surface (land and ocean) temperature was the fourth highest on record, with only 2015 through 2017 being warmer. Several European countries reported record high annual temperatures. There were also more high, and fewer low, temperature extremes than in nearly all of the 68-year extremes record. Madagascar recorded a record daily temperature of 40.5°C in Morondava in March, while South Korea set its record high of 41.0°C in August in Hongcheon. Nawabshah, Pakistan, recorded its highest temperature of 50.2°C, which may be a new daily world record for April. Globally, the annual lower troposphere temperature was third to seventh highest, depending on the dataset analyzed. The lower stratospheric temperature was approximately fifth lowest. The 2018 Arctic land surface temperature was 1.2°C above the 1981–2010 average, tying for third highest in the 118-year record, following 2016 and 2017. June’s Arctic snow cover extent was almost half of what it was 35 years ago. Across Greenland, however, regional summer temperatures were generally below or near average. Additionally, a satellite survey of 47 glaciers in Greenland indicated a net increase in area for the first time since records began in 1999. Increasing permafrost temperatures were reported at most observation sites in the Arctic, with the overall increase of 0.1°–0.2°C between 2017 and 2018 being comparable to the highest rate of warming ever observed in the region. On 17 March, Arctic sea ice extent marked the second smallest annual maximum in the 38-year record, larger than only 2017. The minimum extent in 2018 was reached on 19 September and again on 23 September, tying 2008 and 2010 for the sixth lowest extent on record. The 23 September date tied 1997 as the latest sea ice minimum date on record. First-year ice now dominates the ice cover, comprising 77% of the March 2018 ice pack compared to 55% during the 1980s. Because thinner, younger ice is more vulnerable to melting out in summer, this shift in sea ice age has contributed to the decreasing trend in minimum ice extent. Regionally, Bering Sea ice extent was at record lows for almost the entire 2017/18 ice season. For the Antarctic continent as a whole, 2018 was warmer than average. On the highest points of the Antarctic Plateau, the automatic weather station Relay (74°S) broke or tied six monthly temperature records throughout the year, with August breaking its record by nearly 8°C. However, cool conditions in the western Bellingshausen Sea and Amundsen Sea sector contributed to a low melt season overall for 2017/18. High SSTs contributed to low summer sea ice extent in the Ross and Weddell Seas in 2018, underpinning the second lowest Antarctic summer minimum sea ice extent on record. Despite conducive conditions for its formation, the ozone hole at its maximum extent in September was near the 2000–18 mean, likely due to an ongoing slow decline in stratospheric chlorine monoxide concentration. Across the oceans, globally averaged SST decreased slightly since the record El Niño year of 2016 but was still far above the climatological mean. On average, SST is increasing at a rate of 0.10° ± 0.01°C decade−1 since 1950. The warming appeared largest in the tropical Indian Ocean and smallest in the North Pacific. The deeper ocean continues to warm year after year. For the seventh consecutive year, global annual mean sea level became the highest in the 26-year record, rising to 81 mm above the 1993 average. As anticipated in a warming climate, the hydrological cycle over the ocean is accelerating: dry regions are becoming drier and wet regions rainier. Closer to the equator, 95 named tropical storms were observed during 2018, well above the 1981–2010 average of 82. Eleven tropical cyclones reached Saffir–Simpson scale Category 5 intensity. North Atlantic Major Hurricane Michael’s landfall intensity of 140 kt was the fourth strongest for any continental U.S. hurricane landfall in the 168-year record. Michael caused more than 30 fatalities and $25 billion (U.S. dollars) in damages. In the western North Pacific, Super Typhoon Mangkhut led to 160 fatalities and$6 billion (U.S. dollars) in damages across the Philippines, Hong Kong, Macau, mainland China, Guam, and the Northern Mariana Islands. Tropical Storm Son-Tinh was responsible for 170 fatalities in Vietnam and Laos. Nearly all the islands of Micronesia experienced at least moderate impacts from various tropical cyclones. Across land, many areas around the globe received copious precipitation, notable at different time scales. Rodrigues and Réunion Island near southern Africa each reported their third wettest year on record. In Hawaii, 1262 mm precipitation at Waipā Gardens (Kauai) on 14–15 April set a new U.S. record for 24-h precipitation. In Brazil, the city of Belo Horizonte received nearly 75 mm of rain in just 20 minutes, nearly half its monthly average. Globally, fire activity during 2018 was the lowest since the start of the record in 1997, with a combined burned area of about 500 million hectares. This reinforced the long-term downward trend in fire emissions driven by changes in land use in frequently burning savannas. However, wildfires burned 3.5 million hectares across the United States, well above the 2000–10 average of 2.7 million hectares. Combined, U.S. wildfire damages for the 2017 and 2018 wildfire seasons exceeded $40 billion (U.S. dollars)

Open-source algorithm for detecting sea ice surface features in high-resolution optical imagery

Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces control albedo and exert tremendous influence over the energy balance in the Arctic. Increasingly available meter- to decimeter-scale resolution optical imagery captures the evolution of the ice and ocean surface state visually, but methods for quantifying coverage of key surface types from raw imagery are not yet well established. Here we present an open-source system designed to provide a standardized, automated, and reproducible technique for processing optical imagery of sea ice. The method classifies surface coverage into three main categories: snow and bare ice, melt ponds and submerged ice, and open water. The method is demonstrated on imagery from four sensor platforms and on imagery spanning from spring thaw to fall freeze-up. Tests show the classification accuracy of this method typically exceeds 96 %. To facilitate scientific use, we evaluate the minimum observation area required for reporting a representative sample of surface coverage. We provide an open-source distribution of this algorithm and associated training datasets and suggest the community consider this a step towards standardizing optical sea ice imagery processing. We hope to encourage future collaborative efforts to improve the code base and to analyze large datasets of optical sea ice imagery