National Snow and Ice Data Center

Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40 year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012–2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived ‘higher-level’ Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements.

Abstract The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time‐evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.

Formal planning and development of what became the first Landsat satellite commenced over 50 years ago in 1967. Now, having collected earth observation data for well over four decades since the 1972 launch of Landsat-1, the Landsat program is increasingly complex and vibrant. Critical programmatic elements are ensuring the continuity of high quality measurements for scientific and operational investigations, including ground systems, acquisition planning, data archiving and management, and provision of analysis ready data products. Free and open access to archival and new imagery has resulted in a myriad of innovative applications and novel scientific insights. The planning of future compatible satellites in the Landsat series, which maintain continuity while

Abstract A review of in situ and remote-sensing data covering the ice shelves of the Antarctic Peninsula provides a series of characteristics closely associated with rapid shelf retreat: deeply embayed ice fronts; calving of myriad small elongate bergs in punctuated events; increasing flow speed; and the presence of melt ponds on the ice-shelf surface in the vicinity of the break-ups. As climate has warmed in the Antarctic Peninsula region, melt-season duration and the extent of ponding have increased. Most break-up events have occurred during longer melt seasons, suggesting that meltwater itself, not just warming, is responsible. Regions that show melting without pond formation are relatively unchanged. Melt ponds thus appear to be a robust harbinger of ice-shelf retreat. We use these observations to guide a model of ice-shelf flow and the effects of meltwater. Crevasses present in a region of surface ponding will likely fill to the brim with water. We hypothesize (building on Weertman (1973), Hughes (1983) and Van der Veen (1998)) that crevasse propagation by meltwater is the main mechanism by which ice shelves weaken and retreat. A thermodynamic finite-element model is used to evaluate ice flow and the strain field, and simple extensions of this model are used to investigate crack propagation by meltwater. The model results support the hypothesis.

Abstract Using RADARSAT synthetic aperture radar data, we have mapped the flow velocity over much of the Greenland ice sheet for the winters of 2000/01 and 2005/06. These maps provide a detailed view of the ice-sheet flow, including that of the hundreds of glaciers draining the interior. The focused patterns of flow at the coast suggest a strong influence of bedrock topography. Differences between our two maps confirm numerous early observations of accelerated outlet glacier flow as well as revealing previously unrecognized changes. The overall pattern is one of speed-up accompanied by terminus retreat, but there are also several instances of surge behavior and a few cases of glacier slowdown. Comprehensive mappings such as these, at regular intervals, provide an important new observational capability for understanding ice-sheet variability.

Abstract Laser altimetry (lidar) is a remote-sensing technology that holds tremendous promise for mapping snow depth in snow hydrology and avalanche applications. Recently lidar has seen a dramatic widening of applications in the natural sciences, resulting in technological improvements and an increase in the availability of both airborne and ground-based sensors. Modern sensors allow mapping of vegetation heights and snow or ground surface elevations below forest canopies. Typical vertical accuracies for airborne datasets are decimeter-scale with order 1 m point spacings. Ground-based systems typically provide millimeter-scale range accuracy and sub-meter point spacing over 1 m to several kilometers. Many system parameters, such as scan angle, pulse rate and shot geometry relative to terrain gradients, require specification to achieve specific point coverage densities in forested and/or complex terrain. Additionally, snow has a significant volumetric scattering component, requiring different considerations for error estimation than for other Earth surface materials. We use published estimates of light penetration depth by wavelength to estimate radiative transfer error contributions. This paper presents a review of lidar mapping procedures and error sources, potential errors unique to snow surface remote sensing in the near-infrared and visible wavelengths, and recommendations for projects using lidar for snow-depth mapping.

Abstract. Ice discharge from large ice sheets plays a direct role in determining rates of sea-level rise. We map present-day Antarctic-wide surface velocities using Landsat 7 and 8 imagery spanning 2013–2015 and compare to earlier estimates derived from synthetic aperture radar, revealing heterogeneous changes in ice flow since ∼ 2008. The new mapping provides complete coastal and inland coverage of ice velocity north of 82.4° S with a mean error of < 10 m yr−1, resulting from multiple overlapping image pairs acquired during the daylight period. Using an optimized flux gate, ice discharge from Antarctica is 1929 ± 40 Gigatons per year (Gt yr−1) in 2015, an increase of 36 ± 15 Gt yr−1 from the time of the radar mapping. Flow accelerations across the grounding lines of West Antarctica's Amundsen Sea Embayment, Getz Ice Shelf and Marguerite Bay on the western Antarctic Peninsula, account for 88 % of this increase. In contrast, glaciers draining the East Antarctic Ice Sheet have been remarkably constant over the period of observation. Including modeled rates of snow accumulation and basal melt, the Antarctic ice sheet lost ice at an average rate of 183 ± 94 Gt yr−1 between 2008 and 2015. The modest increase in ice discharge over the past 7 years is contrasted by high rates of ice sheet mass loss and distinct spatial patters of elevation lowering. The West Antarctic Ice Sheet is experiencing high rates of mass loss and displays distinct patterns of elevation lowering that point to a dynamic imbalance. We find modest increase in ice discharge over the past 7 years, which suggests that the recent pattern of mass loss in Antarctica is part of a longer-term phase of enhanced glacier flow initiated in the decades leading up to the first continent-wide radar mapping of ice flow.

Why we are losing sea ice Arctic sea ice is disappearing rapidly, leading to predictions of an ice-free summer in the near future. Simulations of the timing of summer sea-ice loss differ substantially, making it difficult to evaluate the pace of the loss. Notz and Stroeve observed a linear relationship between the monthly-mean September sea-ice area and cumulative CO 2 emissions. This allowed them to predict Arctic summer sea ice directly from the observational record. Interestingly, most models underestimate this loss. Science , this issue p. 747

The Arctic Ocean is currently on a fast track toward seasonally ice-free conditions. Although most attention has been on the accelerating summer sea ice decline, large changes are also occurring in winter. This study assesses past, present, and possible future change in regional Northern Hemisphere sea ice extent throughout the year by examining sea ice concentration based on observations back to 1950, including the satellite record since 1979. At present, summer sea ice variability and change dominate in the perennial ice-covered Beaufort, Chukchi, East Siberian, Laptev, and Kara Seas, with the East Siberian Sea explaining the largest fraction of September ice loss (22%). Winter variability and change occur in the seasonally ice-covered seas farther south: the Barents Sea, Sea of Okhotsk, Greenland Sea, and Baffin Bay, with the Barents Sea carrying the largest fraction of loss in March (27%). The distinct regions of summer and winter sea ice variability and loss have generally been consistent since 1950, but appear at present to be in transformation as a result of the rapid ice loss in all seasons. As regions become seasonally ice free, future ice loss will be dominated by winter. The Kara Sea appears as the first currently perennial ice-covered sea to become ice free in September. Remaining on currently observed trends, the Arctic shelf seas are estimated to become seasonally ice free in the 2020s, and the seasonally ice-covered seas farther south to become ice free year-round from the 2050s.

Over the past decade, the Arctic has warmed by 0.75°C, far outpacing the global average, while Antarctic temperatures have remained comparatively stable. As Earth approaches 2°C warming, the Arctic and Antarctic may reach 4°C and 2°C mean annual warming, and 7°C and 3°C winter warming, respectively. Expected consequences of increased Arctic warming include ongoing loss of land and sea ice, threats to wildlife and traditional human livelihoods, increased methane emissions, and extreme weather at lower latitudes. With low biodiversity, Antarctic ecosystems may be vulnerable to state shifts and species invasions. Land ice loss in both regions will contribute substantially to global sea level rise, with up to 3 m rise possible if certain thresholds are crossed. Mitigation efforts can slow or reduce warming, but without them northern high latitude warming may accelerate in the next two to four decades. International cooperation will be crucial to foreseeing and adapting to expected changes.

Defined in the early 1990s for use with gridded satellite passive microwave data, the Equal-Area Scalable Earth Grid (EASE-Grid) was quickly adopted and used for distribution of a variety of satellite and in situ data sets. Conceptually easy to understand, EASE-Grid suffers from limitations that make it impossible to format in the widely popular GeoTIFF convention without reprojection. Importing EASE-Grid data into standard mapping software packages is nontrivial and error-prone. This article defines a standard for an improved EASE-Grid 2.0 definition, addressing how the changes rectify issues with the original grid definition. Data distributed using the EASE-Grid 2.0 standard will be easier for users to import into standard software packages and will minimize common reprojection errors that users had encountered with the original EASE-Grid definition.

Recent warming in the Arctic, which has been amplified during the winter1–3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is not known and has not been well represented by ecosystem models or empirically based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from Arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1,662 TgC per year from the permafrost region during the winter season (October–April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (−1,032 TgC per year). Extending model predictions to warmer conditions up to 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario—Representative Concentration Pathway 4.5—and 41% under business-as-usual emissions scenario—Representative Concentration Pathway 8.5. Our results provide a baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions. Winter warming in the Arctic will increase the CO2 flux from soils. A pan-Arctic analysis shows a current loss of 1,662 TgC per year over the winter, exceeding estimated carbon uptake in the growing season; projections suggest a 17% increase under RCP 4.5 and a 41% increase under RCP 8.5 by 2100.

Abstract. Greenland ice sheet mass loss has accelerated in the past decade responding to combined glacier discharge and surface melt water runoff increases. During summer, absorbed solar energy, modulated at the surface primarily by albedo, is the dominant factor governing surface melt variability in the ablation area. Using satellite-derived surface albedo with calibrated regional climate modeled surface air temperature and surface downward solar irradiance, we determine the spatial dependence and quantitative impact of the ice sheet albedo feedback over 12 summer periods beginning in 2000. We find that, while albedo feedback defined by the change in net solar shortwave flux and temperature over time is positive over 97% of the ice sheet, when defined using paired annual anomalies, a second-order negative feedback is evident over 63% of the accumulation area. This negative feedback damps the accumulation area response to warming due to a positive correlation between snowfall and surface air temperature anomalies. Positive anomaly-gauged feedback concentrated in the ablation area accounts for more than half of the overall increase in melting when satellite-derived melt duration is used to define the timing when net shortwave flux is sunk into melting. Abnormally strong anticyclonic circulation, associated with a persistent summer North Atlantic Oscillation extreme since 2007, enabled three amplifying mechanisms to maximize the albedo feedback: (1) increased warm (south) air advection along the western ice sheet increased surface sensible heating that in turn enhanced snow grain metamorphic rates, further reducing albedo; (2) increased surface downward shortwave flux, leading to more surface heating and further albedo reduction; and (3) reduced snowfall rates sustained low albedo, maximizing surface solar heating, progressively lowering albedo over multiple years. The summer net infrared and solar radiation for the high elevation accumulation area approached positive values during this period. Thus, it is reasonable to expect 100% melt area over the ice sheet within another similar decade of warming.

The waters of the Colorado River serve 27 million people in seven states and two countries but are overallocated by more than 10% of the river's historical mean. Climate models project runoff losses of 7-20% from the basin in this century due to human-induced climate change. Recent work has shown however that by the late 1800s, decades prior to allocation of the river's runoff in the 1920s, a fivefold increase in dust loading from anthropogenically disturbed soils in the southwest United States was already decreasing snow albedo and shortening the duration of snow cover by several weeks. The degree to which this increase in radiative forcing by dust in snow has affected timing and magnitude of runoff from the Upper Colorado River Basin (UCRB) is unknown. Here we use the Variable Infiltration Capacity model with postdisturbance and predisturbance impacts of dust on albedo to estimate the impact on runoff from the UCRB across 1916-2003. We find that peak runoff at Lees Ferry, Arizona has occurred on average 3 wk earlier under heavier dust loading and that increases in evapotranspiration from earlier exposure of vegetation and soils decreases annual runoff by more than 1.0 billion cubic meters or ∼5% of the annual average. The potential to reduce dust loading through surface stabilization in the deserts and restore more persistent snow cover, slow runoff, and increase water resources in the UCRB may represent an important mitigation opportunity to reduce system management tensions and regional impacts of climate change.

We report on the maturation of optical satellite-image-based ice velocity mapping over the ice sheets and large glacierized areas, enabled by the high radiometric resolution and internal geometric accuracy of Landsat 8's Operational Land Imager (OLI). Detailed large-area single-season mosaics and time-series maps of ice flow were created using data spanning June 2013 to June 2015. The 12-bit radiometric quantization and 15-m pixel scale resolution of OLI band 8 enable displacement tracking of subtle snow-drift patterns on ice sheet surfaces at ~ 1 m precision. Ice sheet and snowfield snow-drift features persist for typically 16 to 64 days, and up to 432 days, depending primarily on snow accumulation rates. This results in spatially continuous mapping of ice flow, extending the mapping capability beyond crevassed areas. Our method uses image chip cross-correlation and sub-pixel peak-fitting in matching Landsat path/row pairs. High-pass filtering is applied to the imagery to enhance local surface texture. The current high image acquisition rates of Landsat 8 (725 scenes per day globally) reduces the impact of high cloudiness in polar and mountain terrain and allows rapid compilation of large areas, or dense temporal coverage of seasonal ice flow variations. The results rival the coverage and accuracy of interferometric Synthetic Aperture Radar (InSAR) mapping.

Abstract Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land‐atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO 2 ) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process‐based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century‐long (1901–2010) estimates of SOC storage and heterotrophic respiration (Rh) from 10 terrestrial biosphere models (TBMs) in the Multi‐scale Synthesis and Terrestrial Model Intercomparison Project and two observation‐based data sets. The 10 TBM ensemble shows that global SOC estimate ranges from 425 to 2111 Pg C (1 Pg = 10 15 g) with a median value of 1158 Pg C in 2010. The models estimate a broad range of Rh from 35 to 69 Pg C yr −1 with a median value of 51 Pg C yr −1 during 2001–2010. The largest uncertainty in SOC stocks exists in the 40–65°N latitude whereas the largest cross‐model divergence in Rh are in the tropics. The modeled SOC change during 1901–2010 ranges from −70 Pg C to 86 Pg C, but in some models the SOC change has a different sign from the change of total C stock, implying very different contribution of vegetation and soil pools in determining the terrestrial C budget among models. The model ensemble‐estimated mean residence time of SOC shows a reduction of 3.4 years over the past century, which accelerate C cycling through the land biosphere. All the models agreed that climate and land use changes decreased SOC stocks, while elevated atmospheric CO 2 and nitrogen deposition over intact ecosystems increased SOC stocks—even though the responses varied significantly among models. Model representations of temperature and moisture sensitivity, nutrient limitation, and land use partially explain the divergent estimates of global SOC stocks and soil C fluxes in this study. In addition, a major source of systematic error in model estimations relates to nonmodeled SOC storage in wetlands and peatlands, as well as to old C storage in deep soil layers.

Abstract. A long-term, consistent, and reproducible satellite-based passive microwave sea ice concentration climate data record (CDR) is available for climate studies, monitoring, and model validation with an initial operation capability (IOC). The daily and monthly sea ice concentration data are on the National Snow and Ice Data Center (NSIDC) polar stereographic grid with nominal 25 km × 25 km grid cells in both the Southern and Northern Hemisphere polar regions from 9 July 1987 to 31 December 2007. The data files are available in the NetCDF data format at http://nsidc.org/data/g02202.html and archived by the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA) under the satellite climate data record program (http://www.ncdc.noaa.gov/cdr/operationalcdrs.html). The description and basic characteristics of the NOAA/NSIDC passive microwave sea ice concentration CDR are presented here. The CDR provides similar spatial and temporal variability as the heritage products to the user communities with the additional documentation, traceability, and reproducibility that meet current standards and guidelines for climate data records. The data set, along with detailed data processing steps and error source information, can be found at http://dx.doi.org/10.7265/N55M63M1.

Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO 2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO 2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models' ability to simulate the seasonal cycle of CO 2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.

The fate of currently frozen permafrost carbon as high-latitude climate warms remains highly uncertain and existing models give widely varying estimates of the permafrost carbon-climate feedback. This uncertainty is due to many factors, including the role that permafrost thaw-induced transitions in soil hydrologic conditions will have on organic matter decomposition rates and the proportion of aerobic to anaerobic respiration. Large-scale permafrost thaw, as predicted by the Community Land Model (CLM) under an unmitigated greenhouse gas emissions scenario, results in significant soil drying due to increased drainage following permafrost thaw, even though permafrost domain water inputs are projected to rise (net precipitation minus evaporation >0). CLM predicts that drier soil conditions will accelerate organic matter decomposition, with concomitant increases in carbon dioxide (CO _2 ) emissions. Soil drying, however, strongly suppresses growth in methane (CH _4 ) emissions. Considering the global warming potential (GWP) of CO _2 and CH _4 emissions together, soil drying weakens the CLM projected GWP associated with carbon fluxes from the permafrost zone by more than 50% compared to a non-drying case. This high sensitivity to hydrologic change highlights the need for better understanding and modeling of landscape-scale changes in soil moisture conditions in response to permafrost thaw in order to more accurately assess the potential magnitude of the permafrost carbon-climate feedback.