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At least 163 records · Page 9

Joint Winter Runway Friction Program Accomplishments

The major program objectives are: (1) harmonize ground vehicle friction measurements to report consistent friction value or index for similar contaminated runway conditions, for example, compacted snow, and (2) establish reliable correlation between ground vehicle friction measurements and aircraft braking performance. Accomplishing these objectives would give airport operators better procedures for evaluating runway friction and maintaining acceptable operating conditions, providing pilots information to base go/no go decisions, and would contribute to reducing traction-related aircraft accidents.

Yager, Thomas J.↗

An Operational Assessment of the MODIS False Color Composite with the Great Falls, Montana National Weather Service

The close and productive collaborations between the NWS Warning and Forecast Office (WFO) in Great Falls, MT and the Short Term Prediction and Research Transition (SPORT) Center at NASA/Marshall Space Flight Center have provided a unique opportunity for science sharing and technology transfer. In particular, SPoRT has provided a false color composite product derived from MODIS data, which is part of NASA's Earth Observing System. This product is designed to delineate snow and ice covered ground, bare ground and clouds. The Great Falls WFO has been a test bed of the MODIS false color composite as a tool in operations to monitor the development and dissipation of snow cover In particular, preliminary applications have shown that the product can be used to monitor snow cover in remote locations as well as ice in rivers. This information can lead to improved assessments of flooding potential during post event conditions where rapid melting and runoff are anticipated. The potential of this product on future geostationary satellites may substantially contribute to the NWS mission by providing enhanced situational awareness. The operational use of this product has been transitioned at WFO Great Falls through a process of product implementation, discussions with the service hydrologist and forecasters, and post event analysis. A concentrated assessment period from January to March, 2008 was initiated to investigate the impact of the MODIS false color product on WFO Great Falls' operations. This presentation will emphasize the impact the MODIS false color product had in the WFO's situational awareness and how best this information can be used to influence operational decisions.

Loss, GIna↗

Snow4Flow: Concept Paper for a NASA Earth Venture Suborbital-4 Investigation

Snow4Flow was proposed as a large ($30M cost cap) Earth Venture Suborbital (EVS-4) mission in April 2023 and selected as such in April 2024. It will commence pending an Investigation Confirmation Review in 2025. Its airborne and ground campaigns are presently expected to occur in March–May 2027–2029. Quantifying the ongoing retreat of glaciers and ice sheets – and projecting their futures – are major societal concerns due to their contribution to sea-level rise and influence on water resources, natural hazards, and associated socioeconomic impacts. The ability to confidently project glacier and ice-sheet mass change is limited by a severe lack of observations that reliably constrain both their input (Snow) and output (Flow) mass fluxes. Snow4Flow will capture the spatial variability in snow accumulation and ice volume across 4 Northern Hemisphere (NH) regions containing hundreds of rapidly changing glaciers to deliver more reliable, societally relevant projections of land-ice change. This major advance requires spatially extensive radar-sounding surveys that are not possible from orbit (Fig. 1). This EVS-4 mission will drive foundational improvements to NH land-ice boundary conditions and forcing data – including orographic precipitation patterns in alpine environments, ice thickness and subglacial topography – and directly leverages them into state-of-the-art models and projections. Our key science questions are: 1. How will NH glaciers respond to climate change through the end of the 21st century? 2. How does snow accumulation vary in regions of high topographic relief?

Jack W Holt↗

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

Tan, Bin↗

Grand-scale Atmospheric Imaging Apparatus (GAIA) and Wind LiDAR Multi-scale Measurements in the Atmospheric Surface Layer

Understanding the organization and dynamics of turbulence structures in the atmospheric surface layer (ASL) is important for fundamental and applied research in different fields, including weather prediction, snow settling, particle and pollutant transport, and wind energy. The main challenges associated with probing and modeling turbulence in the ASL are: i) the broad range of turbulent scales associated with the different eddies present in high Reynolds-number boundary layers ranging from the viscous scale ($\mathcal{O}$(mm)) up to large energy-containing structures ($\mathcal{O}$(km)); ii) the non-stationarity of the wind conditions and the variability associated with the daily cycle of the atmospheric stability; iii) the interactions among eddies of different sizes populating different layers of the ASL, which contribute to momentum, energy, and scalar turbulent fluxes. Creative and innovative measurement techniques are required to probe near-surface turbulence by generating spatio-temporally-resolved data in the proximity of the ground and, at the same time, covering the entire ASL height with large enough streamwise extent to characterize the dynamics of larger eddies evolving aloft. To this aim, the U.S. National Science Foundation sponsored the development of the Grand-scale Atmospheric Imaging Apparatus (GAIA) enabling super-large snow particle image velocimetry (SLPIV) in the near-surface region of the ASL. This inaugural version of GAIA provides a comprehensive measuring system by coupling SLPIV and two scanning Doppler LiDARs to probe the ASL at an unprecedented resolution. A field campaign performed in 2021–2022 and its preliminary results are presented herein elucidating new research opportunities enabled by the GAIA measuring system.

17 WIND ENERGY↗

Possible Impacts of Snow Darkening Effects on the Hydrological Cycle over Western Eurasia and East Asia

In this paper, we investigated the possible impact of snow darkening effect (SDE) by light-absorbing aerosols on the regional changes of the hydrological cycle over Eurasia using the NASA GEOS-5 Model with aerosol tracers and a state-of-the-art snow darkening module, the Goddard SnoW Impurity Module (GOSWIM) for the land surface. Two sets of ten-member ensemble experiments for 10 years were carried out forced by prescribed sea surface temperature (2002–2011) with different atmospheric initial conditions, with and without SDE, respectively. Results show that SDE can exert a significant regional influence in partitioning the contributions of evaporative and advective processes on the hydrological cycle, during spring and summer season. Over western Eurasia, SDE-induced rainfall increase during early spring can be largely explained by the increased evaporation from snowmelt. Rainfall, however, decreases in early summer due to the reduced evaporation as well as moisture divergence and atmospheric subsidence associated with the development of an anomalous mid- to upper-tropospheric anticyclonic circulation. On the other hand, in the East Asian monsoon region, moisture advection from the adjacent ocean is a main contributor to rainfall increase in the melting season. A warmer land-surface caused by earlier snowmelt and subsequent drying further increases moisture transport and convergence significantly enhancing rainfall over the region. Our findings suggest that the SDE may play an important role in leading to hotter and drier summers over western Eurasia, through coupled land-atmosphere interaction, while enhancing East Asian summer monsoonal precipitation via enhanced land-ocean thermal contrast and moisture transport due to the SDE-induced warmer Eurasian continent.

snow darkening effect↗

No Need to Wait for the Clean Air Dividend

Controlling smog and soot is the classic win-win situation, so it's great that the world is finally waking up to the idea. WHAT if there was a way to simultaneously slow down climate change, save millions of lives, improve crop yields and contribute to sustainable development and energy security? It sounds too good to be true, but it is possible. It won't be free or easy, but with some effort and moderate investment, it can be done. The way to do it is to reduce emissions leading to two types of pollution: black carbon and ozone. These are the only pollutants that we know contribute to both global warming and poor air quality. Black carbon is essentially soot, emitted from incomplete combustion of fossil fuels and biomass. It warms the climate in two ways: by absorbing heat in the atmosphere - similar to the greenhouse effect - and by reducing Earth's albedo, or ability to reflect sunlight. Inhaled into the lungs, it leads to cancer and cardiovascular disease. Ozone in the atmosphere also acts as a greenhouse gas, while ground-level ozone is toxic to humans and plants, so leads to both premature death and reduced crop yields. Ozone is not emitted directly but is produced by the action of sunlight on other pollutants, which are known as ozone precursors. Since black carbon and ozone are important components of soot and smog, a great deal of effort has already been put into developing methods to reduce emissions. So effective technology is available, but needs wider implementation. The recommended control measures for black carbon include widespread and tight emission standards on diesel cars and trucks; improved solid fuel cooking stoves, brick kilns and coke ovens in the developing world; and a ban on the open burning of agricultural waste. Implementation of these measures would have a rapid impact on the climate and human health, and also have the added benefit of greatly reducing emissions of carbon monoxide, an important ozone precursor. A second key ozone precursor is methane, which is also a powerful greenhouse gas in its own right. Control measures include reducing leaks from natural gas pipelines and storage tanks, and capturing it from coal, gas and oil extraction, landfills and wastewater treatment plants. Aeration of rice paddies and manure management can also reduce methane releases. Captured methane can often be sold or turned into power. In Monterrey, Mexico, for example, electricity generated from methane collected from the city landfill powers the public transportation system. So such measures can be beneficial even when ignoring the health and climate effects, as they can contribute to energy security and often pay for themselves. According to calculations by me and my colleagues, phasing in all these measures over the next 20 years would reduce global warming by about 0.5 degC in 2050, half of the projected increase between now and then (Science, vol 335, p 183). Regional benefits would be even greater, as black carbon disrupts rainfall patterns and magnifies warming and melting of snow and ice in parts of the world including the Arctic and the Himalayas. On top of the climate benefits, cutting black carbon and ozone would prevent over 3 million premature deaths from air pollution, and increase yields of staple crops by roughly 50 million tonnes a year. Improved cooking stoves would also decrease the demand for firewood in the developing world, reducing deforestation and freeing up time for those who collect wood - primarily women and children - to pursue other activities such as education. Similarly, improved brick kilns now being used in parts of Latin America and Asia require half as much fuel as traditional ones and are less time-intensive for the operators. This means that in addition to their environmental benefits, these measures can contribute to sustainable and human development. Tackling black carbon and methane is clearly a great idea, so why hasn't it been done already? There are many barriers. The upfront costs of some measures can be prohibitive even when they eventually pay for themselves. But this can be overcome by mechanisms such as international financing of capital costs. For other measures, the costs are typically borne by a few while the benefits accrue to everybody. In such cases civil society and governments must get involved. Governments are starting to act. In February, the US, Canada, Sweden, Bangladesh, Ghana and Mexico launched the Climate and Clean Air Coalition to support implementation of measures like these. This coalition will hopefully expand and achieve rapid, widespread adoption of measures to cut black carbon and ozone. While the climate benefits will be substantial, it is important to note that these measures cannot substitute for cuts in carbon dioxide. Black carbon, ozone, carbon monoxide and methane stay in the atmosphere for a fairly short time - a few days for black carbon and about a decade for methane. They thus respond quickly to emissions changes and give us substantial leverage over near-term climate change. In contrast, carbon dioxide is very long-lived and so responds slowly to emissions changes. This means that cuts have little immediate impact, but it also means they must be made now to avoid disastrous changes later on. Controlling short-lived climate pollutants is thus an issue of fairness. Much as failure to reduce carbon dioxide emissions soon would condemn future generations to disastrous change, failure to reduce near-term climate change condemns those alive today to suffer worsening effects of the sort already seen. Some wonder if we really can do both. We can, and we must.

Shindell, Drew↗

The Climatic Impact‐Driver Framework for Assessment of Risk‐Relevant Climate Information

Abstract The climate science and applications communities need a broad and demand‐driven concept to assess physical climate conditions that are relevant for impacts on human and natural systems. Here, we augment the description of the “climatic impact‐driver” (CID) approach adopted in the Working Group I (WGI) contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. CIDs are broadly defined as “physical climate system conditions (e.g., means, events, and extremes) that affect an element of society or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral, or a mixture of each across interacting system elements and regions.” We give background information on the IPCC Report process that led to the development of the 7 CID types (heat and cold, wet and dry, wind, snow and ice, coastal, open ocean, and other) and 33 distinct CID categories, each of which may be evaluated using a variety of CID indices. This inventory of CIDs was co‐developed with WGII to provide a useful collaboration point between physical climate scientists and impacts/risk experts to assess the specific climatic phenomena driving sectoral responses and identify relevant CID indices within each sector. The CID Framework ensures that a comprehensive set of climatic conditions informs adaptation planning and risk management and may also help prioritize improvements in modeling sectoral dynamics that depend on climatic conditions. CIDs contribute to climate services by increasing coherence and neutrality when identifying and communicating relevant findings from physical climate research to risk assessment and planning activities.

54 ENVIRONMENTAL SCIENCES↗

Applications of remote sensing to watershed management

Aircraft and satellite remote sensing systems which are capable of contributing to watershed management are described and include: the multispectral scanner subsystem on LANDSAT and the basic multispectral camera array flown on high altitude aircraft such as the U-2. Various aspects of watershed management investigated by remote sensing systems are discussed. Major areas included are: snow mapping, surface water inventories, flood management, hydrologic land use monitoring, and watershed modeling. It is indicated that technological advances in remote sensing of hydrological data must be coupled with an expansion of awareness and training in remote sensing techniques of the watershed management community.

Rango, A.↗

What is the Time Scale for Orbital Forcing of the Martian Water Cycle?

Calculation of the periodic variations in the martian orbital parameters by Ward and subsequent refinements to the theory have inspired numerous models of variation of the martian water cycle. Most of these models have focused on variations in planetary obliquity on a both a short-term (110 kyr) time scale as well as larger oscillations occuring over millions of years. To a lesser extent, variations in planetary eccentricity have also been considered. The third and fastest mode of variation, the precession of the longitude of perihelion, has generally been deemphasized because, among the three parameters, it is the only one that does not change the integrated annual insolation. But as a result of this precession, the asymmetry in peak summer insolation between the poles exceeds 50%, with the maximum cycling between poles every 25.5 kyrs. The relative contribution of these different elements to orbital forcing of climate takes on particular importance in the context of apparently recent waterrelated features such as gullies or polar layered deposits (PLD). Christensen, for example, recently indentified mantling of heavily gullied crater walls as residual dust-covered snow deposits that were responsible for the formation of the gullies in a previous epoch. Christensen assumed that the snow was originally deposited at a period of high obliquity which was stabilized against sublimation by a lag deposit of dust. It is suggested here that not obliquity, but the shortterm oscillations associated with precession of the perihelion may play the dominant role in the formation of gullies, major strata in the polar layered deposits (PLD), and other water-related features.

M H Hecht↗

Global Climate Forcing from Albedo Change Caused by Large-scale Deforestation and Reforestation: Quantification and Attribution of Geographic Variation

Large-scale deforestation and reforestation have contributed substantially to historical and contemporary global climate change in part through albedo-induced radiative forcing, with meaningful implications for forest management aiming to mitigate climate change. Associated warming or cooling varies widely across the globe due to a range of factors including forest type, snow cover, and insolation, but resulting geographic variation remain spoorly described and has been largely based on model assessments. This study provides an observation-based approach to quantify local and global radiative forcings from large-scale deforestation and reforestation and further examines mechanisms that result in the spatial heterogeneity of radiative forcing. We incorporate a new spatially and temporally explicit land cover-specific albedo product derived from Moderate Resolution Imaging Spectroradiometer with a historical land use data set (Land Use Harmonization product). Spatial variation in radiative forcing was attributed to four mechanisms, including the change in snow-covered albedo, change in snow-free albedo, snow cover fraction, and incoming solar radiation. We find an albedo-only radiative forcing (RF) of -0.819 W m(exp -2) if year 2000 forests were completely deforested and converted to croplands. Albedo RF from global reforestation of present-day croplands to recover year 1700 forests is estimated to be 0.161 W m)exp -2). Snow-cover fraction is identified as the primary factor in determining the spatial variation of radiative forcing in winter, while the magnitude of the change in snow-free albedo is the primary factor determining variations in summertime RF. Findings reinforce the notion that, for conifers at the snowier high latitudes, albedo RF diminishes the warming from forest loss and the cooling from forest gain more so than for other forest types, latitudes, and climate settings.

Jiao, Tong↗

Aconcagua Basin Agriculture: Analyzing Hydrological Norms, Evapotranspiration, and Soil Moisture to Assess Crop Water Demand and Water Usage in Chile’s Aconcagua River Basin

The Aconcagua basin has experienced a prolonged drought since 2010, posing a significant concern to the agricultural sector, which contributes to 12% of the national agriculture output. Reduced precipitation and warmer conditions have led to water constraints for agricultural activities. As the agriculture sector relies more on irrigation, there has been a decline in surface water availability and a shrinking groundwater supply, both primarily sourced from snow and glacial melt. This study focuses on evaluating crop water demand and water usage in the Aconcagua Basin, leveraging in-situ and available satellite data from Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS), 1-km downscaled Soil Moisture Active Passive (SMAP), Global Precipitation Measurement Mission IMERG (GPM), and Landsat 8 Operational Land Imager (OLI). Remote sensing hydrologic norms from pre- and intra-drought conditions provided a baseline for our water use analysis. We have identified areas of the basin where water usage is exaggerated compared to other regions by analyzing soil moisture, evapotranspiration, and vegetation index trends across agricultural lands. The study highlights the presence of irrigation and exaggerated water usage categorized by crop type while normalizing the data by the quantity of water allocation (m3/s) to each subregion. The findings have the potential to assist our partners, the Centro de Información de Recursos Naturales (CIREN) and the Ministry of Agriculture, in refining water allocation approaches; showcasing the feasibility of leveraging remote sensing and earth observation datasets to monitor agricultural practices within the context of water scarcity.

Remote sensing↗

Modulation of the Seasonal Cycle of the Antarctic Sea Ice Extent By Sea Ice Processes and Feedbacks With the Ocean and the Atmosphere

The seasonal cycle of the Antarctic sea ice extent is strongly asymmetric, with a relatively slow increase after the summer minimum followed by a more rapid decrease after the winter maximum. This cycle is intimately linked to the seasonal cycle of the insolation received at the top of the atmosphere, but sea ice processes as well as the exchanges with the atmosphere and ocean may also play a role. To quantify these contributions, a series of idealized sensitivity experiments have been performed with an eddy-permitting (∘) NEMO-LIM3 (Nucleus for European Modelling of the Ocean–Louvain-la-Neuve sea ice model version 3) Southern Ocean configuration, including a representation of ice shelf cavities, in which the model was either driven by an atmospheric reanalysis or coupled to the COSMO-CLM2 regional atmospheric model. In those experiments, sea ice thermodynamics and dynamics as well as the exchanges with the ocean and atmosphere are strongly perturbed. This perturbation is achieved by modifying snow and ice thermal conductivities, the vertical mixing in the ocean top layers, the effect of freshwater uptake and release upon sea ice growth and melt, ice dynamics, and surface albedo. We find that the evolution of sea ice extent during the ice advance season is largely independent of the direct effect of the perturbation and appears thus mainly controlled by initial state in summer and subsequent insolation changes. In contrast, the melting rate varies strongly between the experiments during the retreat, in particular if the surface albedo or sea ice transport are modified, demonstrating a strong contribution of those elements to the evolution of ice coverage through spring and summer. As with the advance phase, the retreat is also influenced by conditions at the beginning of the melt season in September. Atmospheric feedbacks enhance the model winter ice extent response to any of the perturbed processes, and the enhancement is strongest when the albedo is modified. The response of sea ice volume and extent to changes in entrainment of subsurface warm waters to the ocean surface is also greatly amplified by the coupling with the atmosphere.

regional atmosphere ocean sea ice model↗

TPSAS-NF1676L-31979-DND

The rapid, and in many cases, unprecedented changes in the Arctic climate system observed since 1979 are having devastating impacts on both natural and human systems. These changes are marked by warming Arctic temperatures, rapid declines in sea ice and snow cover, permafrost thaw, mountain glacier melt, and Greenland Ice Sheet mass loss. A common thread through each of these changes is the impact on the surface energy budget. However, our understanding of the controls on and variability of the Arctic surface energy budget is incomplete and this contributes to the significant biases in the climate models. To better understand the controls on the variability of the Arctic surface energy budget and CMIP5 model biases, we use an atmospheric regime-based perspective of the Arctic surface energy budget decomposing variability by atmospheric dynamic and thermodynamic properties.

Patrick C. Taylor↗

Contribution to Solar Brightness of Small-Size Magnetic Elements

Irradiance variability is mostly driven by surface magnetism, each magnetic feature contributing in a different manner. The contribution of small-size magnetic elements observed ubiquitously at high-spatial resolution on the solar photosphere, is still debated, as such features are mostly unresolved on full-disk images employed to model irradiance variability. Understanding the contribution to solar brightness of small-size magnetic elements, especially in quiet regions, will help understanding irradiance variability on the decadal and longer temporal scales, which, in turn, are fundamental to understand the role of the Sun on the Earth’s climate. We present a preliminary study of the brightness of small-size magnetic elements using high-spatial resolution spectro-polarimetric observations acquired with the National Science Foundations Daniel K. Inouye Solar Telescope (DKIST) during Commissioning Phase 1. We focus on the Intensity contrast vs magnetic field relation, which is a fundamental observable in irradiance studies. Previous studies mostly focused on the FeI 630.1/630.2 nm spectral range and so to contextualize our results we focus here on this spectral region as well. By comparing DKIST results with MURaM magneto-hydrodynamic simulations, and with previous results published in the literature, we conclude that our results are in agreement with studies conducted on HINODE observations. We plan to extend the analysis to UV and IR ViSP observations and VBI blue continuum in order to better constrain the quiet sun contribution to spectral irradiance variations.

SMD↗

Improved Understanding of Multicentury Greenland Ice Sheet Response to Strong Warming in the Coupled CESM2‐CISM2 With Regional Grid Refinement

The simulation of ice sheet‐climate interactions, such as surface mass balance fluxes, is sensitive to model grid resolution. Here we simulate the multi‐century evolution of the Greenland Ice Sheet (GrIS) and its interaction with the climate using the Community Earth System Model version 2.2 (CESM2.2) including an interactive GrIS component (the Community Ice Sheet Model v2.1 [CISM2.1]) under an idealized warming scenario (atmospheric CO 2 increases by 1% yr -1 until quadrupling the pre‐industrial level and then is held fixed). A variable‐resolution (VR) grid with 1/4° regional refinement over the broader Arctic and 1° resolution elsewhere is applied to the atmosphere and land components, and the results are compared with conventional 1° lat‐lon grid simulations to investigate the impact of grid refinement. Compared with the 1° runs, the VR run features a slower rate of surface melt, especially over the western and northern GrIS, where the ice surface slopes gently toward the periphery. This difference pattern originates primarily from higher snow albedo and, thus, weaker albedo feedback in the VR run. The VR grid better captures the CISM ice sheet topography by reducing elevation discrepancies between CAM and CISM and is, therefore, less reliant on the downscaling algorithm, which is known to underestimate albedo gradients. The sea level rise contribution from the GrIS in the VR run is 53 mm by year 150 and 831 mm by year 350, approximately 40% and 20% less than that of the 1° runs, respectively.

Earth System Model↗

NASA's Potential Contributions to Avalanche Forecasting Using Active and Passive Microwave Measurements

This Candidate Solution is based on using active and passive microwave measurements acquired from NASA satellites to improve USDA (U.S. Department of Agriculture) Forest Service forecasting of avalanche danger. Regional Avalanche Centers prepare avalanche forecasts using ground measurements of snowpack and mountain weather conditions. In this Solution, range of the in situ observations is extended by adding remote sensing measurements of snow depth, snow water equivalent, and snowfall rate acquired by satellite missions that include Aqua, CloudSat, future GPM (Global Precipitation Measurement), and the proposed SCLP (Snow and Cold Land Processes). Measurements of snowpack conditions and time evolution are improved by combining the in situ and satellite observations with a snow model. Recurring snow observations from NASA satellites increase accuracy of avalanche forecasting, which helps the public and the managers of public facilities make better avalanche safety decisions.

Blonski, Slawomir↗

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗