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At least 73 records · Page 4

Contributions of GRACE to Climate Monitoring

The NASA/German Gravity Recovery and Climate Experiment (GRACE) was launched in March 2002. Rather than looking downward, GRACE continuously monitors the locations of and precise distance between twin satellites which orbit in tandem about 200 km apart. Variations in mass near Earth's surface cause heterogeneities in its gravity field, which in turn affect the orbits of satellites. Thus scientists can use GRACE data to map Earth's gravity field with enough accuracy to discern month to month changes caused by ocean circulation and redistribution of water stored on and in the land. Other gravitational influences, such as atmospheric circulation, post-glacial rebound, and solid earth movements are either independently determined and removed or are negligible on a monthly to sub-decadal timescale. Despite its coarse spatial (>150,000 sq km at mid-latitudes) and temporal (approx monthly) resolutions, GRACE has enabled significant advancements in the oceanic, hydrologic, and cryospheric science, and has great potential for climate monitoring, because it is the only global observing system able to measure ocean bottom pressures, total terrestrial water storage, and ice mass changes. The best known GRACE results are estimates of Greenland and Antarctic ice sheet loss rates. Previously, scientists had estimated ice mass losses using ground and satellite based altimetry and surface mass balance estimates based on snowfall accumulation and glacier discharge. While such measurements are still very useful for their spatial detail, they are imperfectly correlated with large-scale ice mass changes, due to snow and ice compaction and incomplete spatial coverage. GRACE enables scientists to generate monthly time series of Greenland and Antarctic ice mass, which have confirmed the shrinking of the polar ice sheets, one of the most obvious and indisputable manifestations of climate change. Further, GRACE has located and quantified hot spots of ice loss in southeastern Greenland and western Antarctica. For 2002 to present, the rate of ice mass loss has been 200 to 300 GT/yr in Greenland and 70 to 210 GT/yr in Antarctica, and some scientists are suggesting that the rates are accelerating. Similarly, GRACE has been used to monitor mass changes in alpine glaciers. Tamisiea et al. first characterized glacier melt along the southern coast of Alaska, more recently estimated to be occurring at a rate of 84 GT/yr. Chen et al. estimated that Patagonian glaciers are melting at a rate of 28 GT/yr, and estimated that the high mountains of central Asia lose ice at a rate of 47 GT/yr. Tapley et al. and Wahr et al. presented the first GRACE based estimates of changes in column-integrated terrestrial water storage (TWS; the sum of ground-water, soil moisture, surface waters, snow, ice, and water stored in vegetation) at continental scales. Since then, dozens of studies have shown that GRACE based estimates of regional to continental scale TWS variations agree with independent information, and some innovative uses of GRACE data have been developed. Rodell et al. (2004) and Swenson and Wahr (2006) demonstrated that by combining GRACE derived terrestrial water storage changes with observations of precipitation and runoff in a river basin scale water budget, it was possible to produce new estimates of evapotranspiration and atmospheric moisture convergence, essential climate variables that are difficult to estimate accurately. Similarly, GRACE has been used to constrain estimates of global river discharge and the contribution of changes in TWS to sea level rise. Crowley et al. observed a negative correlation between interannual TWS anomalies in the Amazon and the Congo River basin. Yeh et al. and Rodell et al. estimated regionally averaged groundwater storage variations based on GRACE and auxiliary observations. Rodell et al. and Tiwari et al. applied that method to quantify massive groundwater depletion in northern India caused by over reliance on aquifers for irration, and Famiglietti et al. found a similar situation in California's Central Valley. Zaitchik et al. and Lo et al. described approaches to use GRACE to constrain hydrological models, enabling integration of GRACE data with other observations and achieving much higher spatial and temporal resolutions than GRACE alone. Such approaches are now supporting applications including drought and water resources monitoring. Oceanography has likewise benefitted from the independent nature of GRACE observations. One application is measurement of the mass component of sea level rise, which complements radar altimetry and in situ measurements. GRACE also measures ocean bottom pressures (OBP), which help to refine understanding and modeling of ocean circulation and the ocean's fresh water budget, among other things. For example, Hayakawa et al. showed that GRACE observes OBP patterns absent from the background models of oceanic variability. Morison et al. used GRACE to describe important decadal scale shifts in circulation and an ongoing trend of freshening of the western Arctic, important indicators of climate variability. The research of Song and Zlotnicki and Chambers and Willis on GRACE-derived ocean bottom pressures in the sub-polar gyre led to the discovery of an ENSO teleconnection and a long-term change in OBP in the North Pacific sub-polar gyre that was not predicted by an ocean model. Further, Chambers and Willis were able to identify an internal redistribution of mass between Atlantic and Pacific Oceans lasting at least six years, which was not predicted by ocean models and was the first direct evidence of sustained mass transport from one ocean basin to another on periods longer than a year. Boening et al. observed a record increase in OBP over part of the southeastern Pacific in late 2009 and early 2010, primarily caused by wind stress curl associated with a strong and persistent anticyclone and likely related to the concurrent Central Pacific El Nino. GRACE has far surpassed its 5-year design lifetime, but it will likely succumb to the aging of batteries and instrument systems sometime in the next few years. NASA has begun initial development of a follow-on to GRACE with very similar design, which could launch as soon as 2016 and would provide continuity in the data record while improving resolution slightly. Higher resolution time variable gravity missions are also on the drawing board .

Rodell, Matthew↗

NASA Observations and Modeling During ICE-POP

Recap: NASA-Specific Objectives for ICE-POP: Provide real-time observational and NWP data in support of ICE-POP, participate in significant international science effort; GPM (Global Precipitation Measurement) Ground Validation and NASA Weather Program -Direct/physical validation of active/passive satellite-based snowfall retrieval algorithms over coastline and mountains; melting layer interaction with terrain -Physics of snow, coupling to snow water equivalent rate and satellite remote sensor retrieval algorithm assumptions - -Size distributions, types/habit, water equivalent, profiles -NU-WRF (NASA-Unified Weather Research and Forecasting) Model plus Observational analyses: Movement toward “level IV products” leverage intensive and multi-faceted NWP (Numerical Weather Prediction) component -Model precipitation processes (liquid, mixed phase and frozen); Build model testing database for further active/passive remote sensing algorithm development (e.g., satellite data simulators) -"Integrated" validation of products in operational context.

Precipitation Science↗

Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder

Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.

Mahyar Garshasbi↗

Long-Term Photovoltaic System Performance in Cold, Snowy Climates

As countries around the world transition towards renewable energy, there is increasing interest in using photovoltaic (PV) technologies to help decarbonize northern and alpine communities due to their scalability and affordability. However, a barrier to large-scale adoption of PV in cold climates is long-term performance uncertainty under snowfall, freeze-thaw cycles, low temperatures, and high winds. In this work, we provide a comprehensive review of published silicon degradation rates in cold Koppen-Geiger climate classifications of Dfb (humid continental), Dfc (subarctic), and ET (tundra). We first analyze the system degradation rates of three subarctic ground-mounted photovoltaic sites in North America using the RdTools year-on-year method: an Al-BSF double-axis tracking site in Fairbanks, Alaska (65degrees N); a PERC and silicon heterojunction bifacial vertical and south-tilted site in Fairbanks, Alaska; and a PERC south-facing fixed-tilt site in Fort Simpson, Northwest Territories (62degrees N). Degradation rates of these newly analyzed sites vary between -0.4%/year and -1.5%/year. Combining these data with previously reported cold climate degradation rates, we show that the distribution of cold climate degradation peaks at -0.1%/year to -0.2%/year but has a large tail with rates above -0.5%/year. The average reported cold climate degradation rate is -0.45%/year, whereas the median value is -0.33%/year. These results suggest that despite frequent freeze-thaw cycles and potential exposure to high wind and snow loads, PV systems in cold climates tend to degrade slower than PV systems in warmer climates. The limited sample size of reported degradation rates in cold climates (27) motivates the need for further data acquisition and monitoring efforts as new technologies are deployed.

14 SOLAR ENERGY↗

Anticipating how rain-on-snow events will change through the 21st century: lessons from the 1997 new year’s flood event

The California-Nevada 1997 New Year’s flood was an atmospheric river (AR)-driven rain-on-snow (RoS) event and remains the costliest in their history. The joint occurrence of saturated soils, rainfall, and snowmelt generated inundation throughout northern California-Nevada. Although AR RoS events are projected to occur more frequently with climate change, the warming sensitivity of their flood drivers across scales remains understudied. We leverage the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) to recreate the 1997 New Year’s flood with horizontal grid spacings of 3.5 km across California, with forecast lead times of up to 4 days, and across six warming levels ranging from pre-industrial conditions to +3.5° C. We describe the sensitivity of the flood drivers to warming including AR duration and intensity, precipitation phase, intensity and efficiency, snowpack mass and energy changes, and runoff efficiency. Our findings indicate current levels of climate change negligibly influence the flood drivers. At warming levels ≥ 1.7° C, AR hazard potential increases, snowpack nonlinearly decreases, antecedent soil moisture decreases (except where the snowline retreats), and runoff decreases (except in the southern Sierra Nevada where antecedent snowpack persists). Storm total precipitation increases, but at rates below warming-induced increases in saturation-specific humidity. Warming intensifies short-duration, high-intensity rainfall, particularly where snowfall-to-rainfall transitions occur. This study highlights the nonlinear tradeoffs in 21st-century RoS flood hazards with warming and provides water management and infrastructure investment adaptation considerations.

54 ENVIRONMENTAL SCIENCES↗

Retrieval of Normalized Gamma Size Distribution Parameters Using Precipitation Imaging Package (Pip) Snowfall Observations During Ice-Pop 2018

Parameters of the normalized gamma particle size distribution (PSD) have been retrieved from the Precipitation Image Package (PIP) snowfall observations collected during the International Collaborative Experiment - PyeongChang Olympics and Paralympic (ICE-POP 2018). Two of the gamma PSD parameters, the mass weighted particle diameter (Dmass) and the normalized intercept parameter NW, have median values of 1.15-1.31 mm and 2.84-3.04 log(mm-1 m-3), respectively. This range arises from the choice of the relationship between the maximum versus equivalent diameter, Dmx-Deq, and the relationship between the Reynolds and Best numbers, Re-X. Normalization of snow water equivalent rate (SWER) and ice water content (W) by NW reduces the range in NW resulting in well fitted power law relationship, between SWER/NW and Dmass and between W/NW and Dmass. The bulk descriptors of snowfall are calculated from PIP observations and from the gamma PSD with values of the shape parameter (μ) ranging from -2 to 10. NASA’s Global Precipitation Measurement (GPM) mission, which adopted the normalized gamma PSD, assumes μ = 2 and μ = 3 in its two separate algorithms. The mean fractional bias (MFB) of the snowfall parameters changes with μ, where the functional dependence on μ depends on the specific snowfall parameter of interest. The MFB of the total concentration was underestimated by 0.23-0.34 when μ = 2 and by 0.29-0.40 when μ = 3, while the MFB of SWER had a much narrower range (-0.03 to 0.04) for the same μ values.

Snowfall↗

Performance Tests of Snow-Related Variables Over the Tibetan Plateau and Himalayas Using a New Version of NASA GEOS-5 Land Surface Model that Includes the Snow Darkening Effect

The snow darkening effect, i.e. the reduction of snow albedo, is caused by absorption of solar radiation by absorbing aerosols (dust, black carbon, and organic carbon) deposited on the snow surface. This process is probably important over Himalayan and Tibetan glaciers due to the transport of highly polluted Atmospheric Brown Cloud (ABC) from the Indo-Gangetic Plain (IGP). This effect has been incorporated into the NASA Goddard Earth Observing System model, version 5 (GEOS-5) atmospheric transport model. The Catchment land surface model (LSM) used in GEOS-5 considers 3 snow layers. Code was developed to track the mass concentration of aerosols in the three layers, taking into account such processes as the flushing of the compounds as liquid water percolates through the snowpack. In GEOS-5, aerosol emissions, transports, and depositions are well simulated in the Goddard Chemistry Aerosol Radiation and Transport (GO CART) module; we recently made the connection between GOCART and the GEOS-5 system fitted with the revised LSM. Preliminary simulations were performed with this new system in "replay" mode (i.e., with atmospheric dynamics guided by reanalysis) at 2x2.5 degree horizontal resolution, covering the period 1 November 2005 - 31 December 2009; we consider the final three years of simulation here. The three simulations used the following variants of the LSM: (1) the original Catchment LSM with a fixed fresh snowfall density of 150 kg m-3 ; (2) the LSM fitted with the new snow albedo code, used here without aerosol deposition but with changes in density formulation and melting water effect on snow specific surface area, (3) the LSM fitted with the new snow albedo code as same as (2) but with fixed aerosol deposition rates (computed from GOCART values averaged over the Tibetan Plateau domain [Ion.: 60-120E; lat.: 20-50N] during March-May 2008) applied to all grid points at every time step. For (2) and (3), the same setting on the fresh snowfall density as in (1) was used.

Yasunari, Tppei J.↗

The Climates of Earth's Next Supercontinent: Effects of Tectonics, Rotation Rate, and Insolation

We explore two possible Earth climate scenarios, 200 and 250 million years into the future, using projections of the evolution of plate tectonics, solar luminosity, and rotation rate. In one scenario, a supercontinent forms at low latitudes, whereas in the other it forms at high northern latitudes with an Antarctic subcontinent remaining at the south pole. The climates between these two end points are quite stark, with differences in mean surface temperatures approaching several degrees. The main factor in these differences is related to the topographic height of the high latitude supercontinents where higher elevations promote snowfall and subsequent higher planetary albedos. These results demonstrate the need to consider multiple boundary conditions when simulating Earth-like exoplanetary climates.

insolation↗

NASA Global Precipitation Mission Ground Validation Implementation

The Global Precipitation Mission (GPM; core-satellite launch 2013) will provide Ka/Ku-band dual-frequency precipitation radar (DPR) and accompanying passive microwave radiometer-diagnosed precipitation estimates over a latitude range of 65 N to 65 S. The extended latitudinal domain of GPM coverage combined with requirements to detect (and in the case of liquid, estimate) liquid and frozen precipitation rates for values ranging from several hundred to just a few tenths of a millimeter per hour present new challenges to the development of physically-based satellite precipitation retrieval algorithms. On regional scales select national and international resources such as existing calibrated radar and rain gauge networks can provide basic datasets that enable direct statistical validation of GPM core-satellite reflectivitys and core/constellation rain rate measurements. Near-term planned field campaign involvements include Finland/Baltic Sea (fall 2010; joint CloudSat,GPM, and European study of precipitation in low-altitude melting layers and snowfall in the vicinity of the Helsinki testbed), central Oklahoma (spring 2011; joint with DOE ARM- precipitation retrievals over a mid-latitude continental land surface), and the Great Lakes region (winter 2011-12, snowfall retrieval).

Petersen, Walter A.↗

Strong fluctuation theory for scattering, attenuation, and transmission of microwaves through snowfall

The strong fluctuation theory is applied to the study of the atmospheric snowfall which is modeled as a layer of random discrete-scatterers medium. As functions of size distribution, fractional volume, and radius of scatterers, the relationship is illustrated between the reflectivity factor and precipitation rate, the attenuation of the centimeter and millimeter waves, and the line-of-sight transmission of coherent and incoherent wave components. The theoretical results are shown to match favorably with experimental data.

Jin, Y.-Q.↗

Detecting Falling Snow from Space

There is an increased interest in detecting and estimating the amount of falling snow reaching the Earth's surface in order to fully capture the atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms includes determining the thresholds of detection for various active and passive sensor channel configurations, snow event cloud structures and microphysics, snowflake particle electromagnetic properties, and surface types. In this work, cloud resolving model simulations of a lake effect and synoptic snow event were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W -band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) Ku and Ka band, and the GPM Microwave Imager (GMI) channels from 10 to 183 plus or minus 7 GHz. Eleven different snowflake shapes were used to compute radar reflectivities and passive brightness temperatures. Notable results include: (1) the W-Band radar has detection thresholds more than an order of magnitude lower than the future GPM sensors, (2) the cloud structure macrophysics influences the thresholds of detection for passive channels, (3) the snowflake microphysics plays a large role in the detection threshold for active and passive instruments, (4) with reasonable assumptions, "the passive 166 GHz channel has detection threshold values comparable to the GPM DPR Ku and Ka band radars with approximately 0.05 g per cubic meter detected at the surface, or an approximately 0.5-1 millimeter per hr. melted snow rate (equivalent to 0.5-2 centimeters per hr. solid fluffy snowflake rate). With detection levels of falling snow known, we can focus current and future retrieval efforts on detectable storms and concentrate advances on achievable results. We will also have an understanding of the light snowfall events missed by the sensors and not captured in the global estimates.

Gail Skofronick-Jackson↗

The GPM Ground Validation Program

We present a detailed overview of the structure and activities associated with the NASA-led ground-validation component of the NASA-JAXA Global Pre­cipitation Measurement (GPM) mission. The overarching philosophy and approaches for NASA's GV program are presented with primary focus placed on aspects of direct validation and a summary of physical validation campaigns and results. We describe a spectrum of key instruments, methods, field campaigns and data products developed and used by NASA's GV team to verify GPM level-2 precipitation products in rain and snow. We describe the tools and analysis framework used to confirm that NASA's Level-I science requirements for GPM are met by the GPM Core Observatory. Examples of routine validation activities related to verification of Integrated Multi­satellitE Retrievals for GPM (IMERG) products for two different regions of the globe (Korea and the US) are provided, and a brief analysis related to IMERG performance in the extreme rainfall event associated with Hurricane Florence is discussed.

precipitation↗

Sublimation of Snow Field Campaign Report

Snow is a vital part of water resources, but sublimation may remove 10% to 90% of snowfall from the system. The processes controlling sublimation span multiple scales of measurement and multiple disciplinary fields. Due to a critical lack of reliable direct measurements of snow sublimation, we do not fully understand the physics that govern current rates of sublimation, let alone how those amounts might change with the climate.

54 ENVIRONMENTAL SCIENCES↗

Antarctic Sea Ice Thickness and Snow-to-Ice Conversion from Atmospheric Reanalysis and Passive Microwave Snow Depth

Passive microwave snow depth, ice concentration, and ice motion estimates are combined with snowfall from the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis (ERA-40) from 1979-200 1 to estimate the prevalence of snow-to-ice conversion (snow-ice formation) on level sea ice in the Antarctic for April-October. Snow ice is ubiquitous in all regions throughout the growth season. Calculated snow- ice thicknesses fall within the range of estimates from ice core analysis for most regions. However, uncertainties in both this analysis and in situ data limit the usefulness of snow depth and snow-ice production to evaluate the accuracy of ERA-40 snowfall. The East Antarctic is an exception, where calculated snow-ice production exceeds observed ice thickness over wide areas, suggesting that ERA-40 precipitation is too high there. Snow-ice thickness variability is strongly controlled not just by snow accumulation rates, but also by ice divergence. Surprisingly, snow-ice production is largely independent of snow depth, indicating that the latter may be a poor indicator of total snow accumulation. Using the presence of snow-ice formation as a proxy indicator for near-zero freeboard, we examine the possibility of estimating level ice thickness from satellite snow depths. A best estimate for the mean level ice thickness in September is 53 cm, comparing well with 51 cm from ship-based observations. The error is estimated to be 10-20 cm, which is similar to the observed interannual and regional variability. Nevertheless, this is comparable to expected errors for ice thickness determined by satellite altimeters. Improvement in satellite snow depth retrievals would benefit both of these methods.

Markus, Thorsten↗

Impact of GPM Rainrate Data Assimilation on Simulation of Hurricane Harvey (2017)

Built upon Tropical Rainfall Measuring Mission (TRMM) legacy for next-generation global observation of rain and snow. The GPM was launched in February 2014 with Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) onboard. The GPM has a broad global coverage approximately 70deg S -70deg N with a swath of 245/125-km for the Ka (35.5 GHz)/Ku (13.6 GHz) band radar, and 850-km for the 13-channel GMI. GPM also features better retrievals for heavy, moderate, and light rain and snowfall To develop methodology to assimilate GPM surface precipitation data with Grid-point Statistical Interpolation (GSI) data assimilation system and WRF ARW model To investigate the potential and the value of utilizing GPM observation into NWP for operational environment The GPM rain rate data has been successfully assimilated using the GSI rain data assimilation package. Impacts of rain rate data have been found in temperature and moisture fields of initial conditions. 2.Assimilation of either GPM IMERG or GPROF rain product produces significant improvement in precipitation amount and structure for Hurricane Harvey (2017) forecast. Since IMERG data is available half-hourly, further forecast improvement is expected with continuous assimilation of IMERG data

Precipitation↗

Characterization of Orography-Influenced Riming and Secondary Ice Production and Their Effects on Precipitation Rates Using Radar Polarimetry and Doppler Spectra (CORSIPP-SAIL)

The Characterization of Orography-Influenced Riming and Secondary Ice Production and Their Effects on Precipitation Rates Using Radar Polarimetry and Doppler Spectra (CORSIPP) project was conducted to help improve the understanding of precipitation formation in orographically influenced terrain. Special focus is put on the two processes of riming and secondary ice production and their external drivers. Two instruments, a polarimetric W-band simultaneous transmission simultaneous reception (STSR) Doppler cloud radar manufactured by Radiometer Physics GmbH (RPG, instrument type RPG-FMCW-94-DP), from now on named LIMRAD94, and the video in situ snowfall sensor (VISSS), were deployed at the U. S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Surface Atmosphere Integrated Field Laboratory (SAIL) site in Gothic, Colorado between November 2022 and June 2023 during the second SAIL winter. Note that the exact dates of data availability differ between the instruments. Both instruments arrived at Gothic on November 2, 2022, 09:20 local time. VISSS, described by Maahn et al., is equipped with two camera systems with telecentric lenses. The two cameras are at a 90° angle to each other. This configuration allows for size-independent measurements by capturing images of hydrometeors from two sides at a high frame rate of 250 Hz. With a minimum detection size of 200 μm, VISSS provides valuable insights into particle size, number, shape, complexity, and fall velocity. The VISSS was deployed on the grassland next to the ARM facility with the amazing help of the ARM employees on site. The setup started on November 2, 2022, and was finished on November 5, 2022, without major problems. VISSS measurements were started on November 6, 2022. LIMRAD94 was installed on a scaffolding platform near Orehouse (Gothic) on November 9, 2022, with the great help of RMBL staff. LIMRAD94 was mounted on a cold temperature scanner prototype. After a short test of the setup on November 9, 2022, the digital control of the scanner elevation stopped working for (at that time) unknown reasons. All attempts to resolve the problem failed. This malfunction made it impossible to operate LIMRAD94 in scanning mode. The scanner was then manually moved to zenith pointing mode and between November 10 and November 15, 2022, vertical observations for polarimetric calibration were performed. On November 15, 2022, after the polarimetric calibration was applied, the scanner was manually moved to 40° elevation with azimuthal view towards the Ka-band ARM Zenith Radar (KAZR) and measurements were continued at constant elevation. Investigation of the scanner malfunction on February 6, 2023, by Benn Schmatz revealed a disengagement between the cogwheel of the elevation motor and the cogwheel moving the scanner in elevation. This mechanical issue was temporarily solved by re-engaging the cogwheels. This made the scanner operational again for about four weeks, until mechanical force disengaged the cogwheels again on March 15, 2023. This repeated scanner failure remained undetected for about three weeks until April 8, 2023; during this time the scanner was stuck at 72° elevation. However, the radar software continued to produce data files falsely indicating that the scanner was still operational. After the scanner failure was noticed, scanning was stopped again, and we returned to constant elevation measurements. On May 15, 2023, the cogwheels of the elevation motor were secured with additional screws sent by the manufacturer. At some point in May, the cogwheels of the azimuth motor were also disengaged by mechanical force, which still allowed for range height indicator (RHI) but no plan position indicator (PPI) scans in the last weeks of the campaign. The azimuth motor was repaired in Germany after the end of the campaign. Throughout the campaign, RMBL and ARM staff kept the radar and the VISSS free of snow.

54 ENVIRONMENTAL SCIENCES↗

Accelerating Ice Loss from the Fastest Greenland and Antarctic Glaciers

Ice discharge from the fastest glaciers draining the Greenland and Antarctic ice sheets . Jakobshavn Isbrae (JI) and Pine Island Glacier (PIG). continues to increase, and is now more than double that needed to balance snowfall in their catchment basins. Velocity increase probably resulted from decreased buttressing from thinning (and, for JI, breakup) of their floating ice tongues, and from reduced basal drag as grounding lines on both glaciers retreat. JI flows directly into the ocean as it becomes afloat, and here creep rates are proportional to the cube of bed depth. Rapid thinning of the PIG ice shelf increases the likelihood of its breakup, and subsequent rapid increase in discharge velocity. Results from a simple model indicate that JI velocities should almost double to >20 km/a by 2015, with velocities on PIG increasing to >10 km/a after breakup of its ice shelf. These high velocities would probably be sustained over many decades as the glaciers retreat within their long, very deep troughs. Resulting sea ]level rise would average about 1.5 mm/a.

Thomas, R.↗

Coarse woody debris decomposition assessment tool: Model development and sensitivity analysis

Coarse woody debris (CWD) is an important component in forests, hosting a variety of organisms that have critical roles in nutrient cycling and carbon (C) storage. We developed a process-based model using literature, field observations, and expert knowledge to assess woody debris decomposition in forests and the movement of wood C into the soil and atmosphere. The sensitivity analysis was conducted against the primary ecological drivers (wood properties and ambient conditions) used as model inputs. The analysis used eighty-nine climate datasets from North America, from tropical (14.2° N) to boreal (65.0° N) zones, with large ranges in annual mean temperature (26.5°C in tropical to -11.8°C in boreal), annual precipitation (6,143 to 181 mm), annual snowfall (0 to 612 kg m -2 ), and altitude (3 to 2,824 m above mean see level). The sensitivity analysis showed that CWD decomposition was strongly affected by climate, geographical location and altitude, which together regulate the activity of both microbial and invertebrate wood-decomposers. CWD decomposition rate increased with increments in temperature and precipitation, but decreased with increases in latitude and altitude. CWD decomposition was also sensitive to wood size, density, position (standing vs downed), and tree species. The sensitivity analysis showed that fungi are the most important decomposers of woody debris, accounting for over 50% mass loss in nearly all climatic zones in North America. The model includes invertebrate decomposers, focusing mostly on termites, which can have an important role in CWD decomposition in tropical and some subtropical regions. The role of termites in woody debris decomposition varied widely, between 0 and 40%, from temperate areas to tropical regions. Woody debris decomposition rates simulated for eighty-nine locations in North America were within the published range of woody debris decomposition rates for regions in northern hemisphere from 1.6° N to 68.3° N and in Australia.

54 ENVIRONMENTAL SCIENCES↗