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At least 217 records · Page 12

Evaluating Retrieval Algorithm Climate Stability: Estimating 3D Optical Thickness Bias Distributions by Cloud Type

Detecting climate trends on large spatiotemporal scales requires accurate, stable measurements and stable retrieval algorithms. We strive to estimate how time-variant retrieval algorithm biases may impact trend detection. Here we focus on the 3D cloud optical thickness (τc) bias, which is among the largest in passive cloud retrieval algorithms. If this bias is time dependent, a possibility with potential decadal changes in cloud morphology, it may obscure genuine trends in τc. Although previous studies have evaluated the cloud- and sun-view geometry-dependent 3D τc bias on small spatial scales, before our current study none have evaluated the stability of this well-known bias on climate-relevant large spatiotemporal scales. These studies must estimate large scale distributions of the 3D τc bias by cloud type and estimate how cloud type amount may change between two climate states. We employ a novel approach to estimate large scale distributions of 3D τc using a proxy of the bias that quantifies the departure of clouds from satisfying the 1D radiative transfer assumption used in passive τc retrievals. This existing globally-distributed proxy is an angular consistency metric that was developed using fused Moderate-Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) measurements. Calculating the 3D τc bias and the proxy, for known cloud fields enables us to establish statistical relationships between these two quantities, which can be used to calculate large-scale distributions of the 3D τc bias. This approach limits the number of 3D radiative transfer simulations required to only those needed to estimate a statistical relationship between the 3D τc bias for known cloud fields and a proxy of the bias. It is likely that future studies will be needed to evaluate retrieval algorithm bias stability for other geophysical variables as the community develops climate data records from satellite observations and their retrievals. This must be done in addition to monitoring and correcting measurement errors and uncertainties and understanding their impact on retrieved essential climate variables.

Yolanda Shea↗

Long-Term Monitoring of the High-Energy Gamma-Ray Emission from LS I +61 deg 303 and LS 5039

The Fermi Large Area Telescope (LAT) reported the first definitive gigaelectron volts detections of the binaries LS I +61 deg 303 and LS 5039 in the first year after its launch in 2008 June. These detections were unambiguous as a consequence of the reduced positional uncertainty and the detection of modulated gamma-ray emission on the corresponding orbital periods. An analysis of new data from the LAT, comprising 30 months of observations, identifies a change in the gamma-ray behavior of LS I +61 deg 303. An increase in flux is detected in 2009 March and a steady decline in the orbital flux modulation is observed. Significant emission up to 30 gigaelectron volts is detected by the LAT; prior data sets led to upper limits only. Contemporaneous terraelectron volt observations no longer detected the source, or found it-in one orbit-close to periastron, far from the phases at which the source previously appeared at terraelectron volt energies. The detailed numerical simulations and models that exist within the literature do not predict or explain many of these features now observed at gigaelectron volt and terraelectron volt energies. New ideas and models are needed to fully explain and understand this behavior. A detailed phase-resolved analysis of the spectral characterization of LS I +61 deg 303 in the gigaelectron volt regime ascribes a power law with an exponential cutoff spectrum along each analyzed portion of the system's orbit. The on-source exposure of LS 5039 is also substantially increased with respect to our prior publication. In this case, whereas the general gamma-ray properties remain consistent, the increased statistics of the current data set allows for a deeper investigation of its orbital and spectral evolution.

High-energy↗

Detection of Extremes with AIRS and CrIS

Climate change is expected to be detected first as changes in extreme values rather than in mean values. The availability of data of from two instruments in the same orbit, AIRS data for the past eleven years and AIRS and CrIS data from the past year, provides an opportunity to evaluate this using examples of climate relevance: Desertification, seen as changes in hot extremes, severe storm, seen as a change in extremely cold clouds and the warming of the polar zone. We use AIRS to establish trends for the 1%tile, the mean and 99%tile brightness temperatures measured with the 900 cm(exp -1) channel from AIRS for the past 11 years. This channel is in the clearest part of the 11 micron atmospheric window. Substantial trends are seen for land and ocean, which in the case of the 1%tile (cold) extremes are related to the current shift of deep convection from ocean to land. Changes are also seen in the 99%tile for day tropical land, but their interpretation is at present unclear. We also see dramatic changes for the mean and 99%tile of the North Polar area. The trends are an order of magnitude larger than the instrument trend of about 3 mK/year. We use the statistical distribution from the past year derived from AIRS to evaluate the accuracy of continuing the trends established with AIRS with CrIS data. We minimize the concern about differences in the spectral response functions by limiting the analysis to the channel at 900 cm(exp -1).While the two instruments agree within 100 mK for the global day/night land/ocean mean values, there are significant differences when evaluating the1% and 99%tiles. We see a consistent warm bias in the CrIS data relative to AIRS for the 1%tile (extremely cold, cloudy) data in the tropical zone, particularly for tropical land, but the bias is not day/night land/ocean consistent. At this point the difference appears to be due to differences in the radiometric response of AIRS and CrIS to differences in the day/night land/ocean cloud types. Unless the effect can be mitigated by a future reprocessing the CrIS data, it will significantly complicate the concatenation of the AIRS and CrIS data records for the continuation of trends in extreme values.

sampling bias↗

The Earth Model Column Collaboratory (EMC2) v1.1: An Open-Source Ground-Based Lidar and Radar Instrument Simulator and Subcolumn Generator for Large-Scale Models

Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

Earth Model Column Collaboratory↗

Tropical Pacific moisture variability

The objectives are to describe synoptic scale variability of moisture over the tropical Pacific Ocean and the systems leading to this variability; implement satellite analysis procedures in support of this effort, and to incorporate additional satellite information into operational analysis forecast systems at the National Meteorological Center (NMC). Composite satellite radiance patterns describe features detectable well before the development of synoptic scale tropical plumes. These typical features were extracted from historical files of Tiros Operational Vertical Sounder (TOVS) radiance observations for a pair of tropical plumes which developed during January 1989. Signals were inserted into the NMC operational medium range forecast model and a suite of model integrations were conducted. Many of the 48 h model errors of the historical forecasts were eliminated by the inclusion of more complete satellite observations. Three studies in satellite radiance analysis progressed. An analysis which blended TOVS moisture channels, OLR observations and European Center for Medium Weather Forecasts (ECMWF) model analysis to generate fields of total precipitable water comparable to those estimated from Scanning Multichannel Microwave Radiometer (SMMR) mu-wave observations. This study demonstrated that a 10 y climatology of precipitable water over the oceans is feasible, using available infrared observations (OLR and TOVS) and model analysis (ECMWF, NMC or similar quality). The estimates are sensitive to model quality and the estimating model must be updated with operational model changes. Coe developed a set of tropical plume and ITCZ composites from TOVS observations, and from NMC and ECMWF analyses which had been passed through a radiative transfer model to simulate TOVS radiances. The composites have been completed as well as many statistical diagnostics of individual TOVS channels. Analysis of the computations is commencing. Chung has initiated a study of the differences between TOVS observed vapor structure during El Nino Southern Oscillation (ENSO) (1983) and non-ENSO (1984) years. Preliminary diagnosis demonstrates gross moisture changes between warm and cold sea surface temperature episodes.

Mcguirk, James P.↗

TRMM Fire Algorithm, Product and Applications

Land fires are frequent menaces to human lives and property. They also change the state of the vegetation and contribute to the climate forcing by releasing large amount of aerosols and greenhouse gases into the atmosphere. This paper summarizes methodologies of detecting global land fires from the Tropical Rainfall Measuring Mission (TRMM) Visible Infrared Scanner FIRS) measurements. The TRMM Science Data and Information System (TSDIS) fire products include global images of daily hot spots and monthly fire counts at 0.5 deg. x 0.5 deg. resolution, as well as text fiies that details necessary information of all fire pixels. The information includes date, orbit number, pixel number, local time, solar zenith angle, latitude, longitude, reflectance of visible/near infrared channels, brightness temperatures of infrared channels, as well as background brightness temperatures of infrared channels. These products have been archived since January 1998. The TSDIS fire products are compared with the coincidental European Commission (EC) Joint Research Center (JRC) 1 km AVHRR fire products. Analyses of the TSDIS monthly fire products during the period from 1998 to 2003 manifested seasonal cycles of biomass fires over Southeast Asia, Africa, North America and South America. The data also showed interannual variations associated with the 98/99 ENS0 cycle in Central America and the Indonesian region. In order to understand the variability of global land fires and their effects on the distribution of atmospheric aerosols, statistical methods were applied to the TSDIS fire products as well as to the Total Ozone Mapping Spectrometer (TOMS) aerosol index products for a period of five years from January 1998 to December 2002. The variability of global atmospheric aerosol is consistent with the fire variations over these regions during this period. The correlation between fire count and TOMS aerosol index is about 0.55 for fire pixels in Southeast Asia, Indonesia, and Africa. Parallel statistical analyses such as Empirical Orthogonal Function (EOF) analysis and Singular Spectrum Analysis (SSA) methods were applied to pentad TRMM fire data and TOMS aerosol data. The EOF analyses showed contrast between North and South hemispheres and also inter- continental transitions in Africa and America. EOF and SSA analyses also identified 25-60 day intra-seasonal oscillations that were superimposed on the annual cycles of both fire and aerosol data. The intra-seasonal variability of fires showed similarity of tropical rainfall oscillation modes. The TRMM fire products were also compared to the coincident TRMh4 rainfall and other rainfall products to investigate the interaction between rainfall and fire. The results indicate that the annual, interannual and intraseasonal variability of fire are dominated by global rainfall variations. However, the feedback of fire to the rainfall occurrence at regional scale for certain regions is also evident.

Ji, Yi-Min↗

Statistical analysis of stratospheric temperature and ozone profile data for trends and model comparison

Work performed during the project period July 1, 1990 to June 30, 1992 on the statistical analysis of stratospheric temperature data, rawinsonde temperature data, and ozone profile data for the detection of trends is described. Our principal topics of research are trend analysis of NOAA stratospheric temperature data over the period 1978-1989; trend analysis of rawinsonde temperature data for the period 1964-1988; trend analysis of Umkehr ozone profile data for the period 1977-1991; and comparison of observed ozone and temperature trends in the lower stratosphere. Analysis of NOAA stratospheric temperature data indicates the existence of large negative trends at 0.4 mb level, with magnitudes increasing with latitudes away from the equator. Trend analysis of rawinsonde temperature data over 184 stations shows significant positive trends about 0.2 C per decade at surface to 500 mb range, decreasing to negative trends about -0.3 C at 100 to 50 mb range, and increasing slightly at 30 mb level. There is little evidence of seasonal variation in trends. Analysis of Umkehr ozone data for 12 northern hemispheric stations shows significant negative trends about -.5 percent per year in Umkehr layers 7-9 and layer 3, but somewhat less negative trends in layers 4-6. There is no pronounced seasonal variation in trends, especially in layers 4-9. A comparison was made of empirical temperature trends from rawinsonde data in the lower stratosphere with temperature changes determined from a one-dimensional radiative transfer calculation that prescribed a given ozone change over the altitude region, surface to 50 km, obtained from trend analysis of ozonsonde and Umkehr profile data. The empirical and calculated temperature trends are found in substantive agreement in profile shape and magnitude.

Tiao, G. C.↗

Scattering Properties and Brightness Temperatures Associated with Solid Precipitation

In the past few years, early solid precipitation detection and retrieval algorithms have been developed and shown to be applicable for snowing clouds and blizzards. NOAA has an operational snow versus rain classifier based on AMSU-B observations. Solid precipitation retrieval algorithms reported in the literature over the past two years include those that rely on neural nets, statistics, or physical relationships. All of the algorithms require the use of millimeter-wave radiometer observations. The millimeter-wave frequencies are especially sensitive to the scattering and emission properties of frozen particles due to the ice particle refractive index. Passive radiometric channels respond to both the integrated particle mass throughout the volume and field of view, and to the amount, location, and size distribution of the frozen (and liquid) particles with the sensitivity varying for different frequencies and hydrometeor types. This investigation probes the sensitivity of scattering and absorption coefficients, and hence computed brightness temperatures, resulting from variations in solid precipitation cloud profiles. The first study compares the single scattering, absorption, and asymmetry parameters associated with snow particles in clouds. Several methodologies are used to convert the physical characteristics (e.g., shape, size distributions, ice-air-water ratios) of ice particles to electromagnetic properties (e.g., absorption, scattering, and asymmetry factors). These methodologies include: conversion to solid ice particles, homogeneous dielectric mixing, or discrete dipole approximation. Changes in the conversion methodology can produce computed brightness temperature differences greater than 50 Kelvin.

Skofronick-Jackson, Gail M.↗

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Climate change in tundra regions may alter vegetation species composition and ecosystem carbon balance. Remote sensing provides critical tools for monitoring these changes as optical signals provide a way to scale from plot measurements to regional patterns. Gas exchange measurements of pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow AK, show three significantly different values of light use efficiency (LUE) with values of 0.013+/-0.001, 0.0018+/-0.0002, and 0.0012 0.0001 mol C/mol absorbed quanta for vascular plants, mosses and lichens, respectively. Further, discriminant analysis of patch reflectance identifies five spectral bands that can separate each vegetation functional type as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. Patch-level statistical discriminant functions applied to in situ hyperspectral reflectance successfully unmixed cover fractions of the vegetation functional types. These functions, developed from the tram data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine regional variability in distribution of the vegetation functional types and from those distributions, the variability of LUE. Across the landscape, there was a fivefold variation in tundra LUE that was correlated to a spectral vegetation index developed to detect vegetation chlorophyll content.

Huemmrich, Karl F.↗

Innovative Drug Selection, Storage, and Shelf-Life Strategies for Exploration Spaceflight

Medications have been a part of space travel dating back to the Apollo missions. A safe and effective medication formulary is essential to maintaining crew health and performance during long-duration spaceflight outside of low Earth orbit (LEO). Distance from Earth creates four key operational changes that increase medical risks, including communication, resupply, crewmember health, and evacuation. The current spaceflight pharmaceutical formulary consists of medications indicated to treat a variety of anticipated medical events and healthcare needs during spaceflight, but depends on a robust consumables resupply chain, which may be strained for a Lunar, and possibly non-existent for a Mars mission. The specific medications selections for the formulary may change to optimally align with the mission, crew compliment, and spacecraft design. Medical support at long-duration exploration missions will differ from LEO missions due to mission duration, lack of consumables resupply, prolonged exposure to space radiation, and the absence of emergency medical return capability. Loss of medication resupply limits or removes the ability to replace medications that have been exhausted or degraded, potentially exacerbating the medical risk posture. To address these anticipated risks, long-duration missions must consider use of novel medical technologies, treatment modalities, and smart medical systems that offer greater crew autonomy, such as physiologically based pharmacokinetic modeling, drug repurposing, on demand drug synthesis, or wearable drug delivery / monitoring devices. Once an ideal formulary for exploration space is determined, it is essential to establish the chemical and physical stability of each medication compound, as well as its safety by identifying its degradation profiles and products. Although few studies have been conducted to provide evidence on the physicochemical stability of pharmaceuticals during space missions, the data suggests that the spaceflight environment may promote degradation in some pharmaceuticals. Formulary drug purity and efficacy should be verified by pharmaceutical stability assessments, and can be realized non-destructively, and accessed in remote environments. Non-destructive pharmaceutical analysis and statistical modelling techniques could optimize exploration spaceflight medical care by enabling early detection of suboptimal therapeutics. Likewise, novel packaging, storage strategies, and dosage form innovations are promising countermeasures to optimize pharmaceutical shelf life, purity, and quality of exploration spaceflight medications. As we prepare for more distant exploration missions, risk management planning for astronaut healthcare should include the assembly of a medication formulary that is comprehensive enough to prevent or treat anticipated medical events, remains safe and chemically stable, and retains sufficient potency to last for the duration of the mission. Following extensive review of the literature, we will present innovative formulary optimization strategies, pharmaceutical stability assessment techniques, and storage and packaging solutions that could enhance drug safety and efficacy for future exploration spaceflight missions.

Vernie R Daniels↗

Drought Indicators Based on Model Assimilated GRACE Terrestrial Water Storage Observations

The Gravity Recovery and Climate Experiment (GRACE) twin satellites observe time variations in Earth's gravity field which yield valuable information about changes in terrestrial water storage (TWS). GRACE is characterized by low spatial (greater than 150,000 square kilometers) and temporal (greater than 10 day) resolution but has the unique ability to sense water stored at all levels (including groundwater) systematically and continuously. The GRACE Data Assimilation System (GRACE-DAS), based on the Catchment Land Surface Model (CLSM) enhances the value of the GRACE water storage data by enabling spatial and temporal downscaling and vertical decomposition into moisture 39 components (i.e. groundwater, soil moisture, snow), which individually are more useful for scientific applications. In this study, GRACE-DAS was applied to North America and GRACE-based drought indicators were developed as part of a larger effort that investigates the possibility of more comprehensive and objective identification of drought conditions by integrating spatially, temporally and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors. Previously, the Drought Monitors lacked objective information on deep soil moisture and groundwater conditions, which are useful indicators of drought. Extensive datasets of groundwater storage from USGS monitoring wells and soil moisture from the Soil Climate Analysis Network (SCAN) were used to assess improvements in the hydrological modeling skill resulting from the assimilation of GRACE TWS data. The results point toward modest, but statistically significant, improvements in the hydrological modeling skill across major parts of the United States, highlighting the potential value of GRACE assimilated water storage field for improving drought detection.

Houborg, Rasmus↗

A quick look method of detecting water of hydration in small solar system bodies

The action of aqueous alteration of the near-subsurface material on asteroids and probably some satellites in the Solar System constitutes part of the formation history of the Solar System. The C-class asteroids (and subclasses B, G, and F) were initially believed to have undergone aqueous alteration based on their low albedos and neutral broadband visible and near-infrared colors. These spectra exhibit a sharp drop at wavelengths shorter than 0.55 microns due to a strong ferric oxide intervalence change transfer transition. This IVCT comprises multiple absorptions that are not uniquely indicative of phyllosilicates, but rather are present in the spectrum of any object containing Fe(2+) and Fe(3+) in its surface material. A definitive indication of aqueous alteration came when the broad IR absorption feature having a minimum near 3.0 microns indicative of structural hydroxyl (OH) and interlayer and and absorbed water in phyllosilicates was identified in the IR photometry of many C-class asteroids. Additional mineralogical compositional evidence of aqueously-altered asteroids has come as the result of high SNR narrowband spectrophotometry in the visible and near-infrared spectral regions taken using a CCD/spectrograph combination. An absorption feature centered at 0.7 microns indicative of an Fe(2+) - Fe(3+) charge transfer transition in oxidized iron in phyllosilicates in spectra of some low-albedo asteroids, especially C and G class, and CM2 carbonaceous chondrite meteorites was identified in the CCD spectra. The correlation and covariance of the 0.7-micron and 3.0-micron features were examined by comparing observations of asteroids common to both the CCD reflectance spectra and the 3.0-micron multicolor photometry data sets. Thirty-one pairs of observations were included in this training group. The results of the statistical study indicate that with a 95% confidence level, 84% of the objects observed either having or not having the 0.7-micron feature will correspondingly have the 3.0-micron water of hydration feature.

Vilas, F.↗

Interannual Variability in Surface LW Fluxes Over the Tropical Oceans As Seen in ISCCP-FD and GEWEX SRB Data Sets

One notable aspect of Earth s climate is that although the planet appears to be very close to radiative balance at top-of-atmosphere (TOA), the atmosphere itself and underlying surface are not. Profound exchanges of energy between the atmosphere and oceans, land and cryosphere occur over a range of time scales. Recent evidence from broadband satellite measurements suggests that even these TOA fluxes contain some detectable variations. Our ability to measure and reconstruct radiative fluxes at the surface and at the top of atmosphere is improving rapidly. In this work we will evaluate two recently released estimates of radiative fluxes, focusing primarily on surface estimates. The International Satellite Cloud Climatology Project FD radiative flux profiles are available from mid-1 983 to near present and have been constructed by driving the radiative transfer physics from the Goddard Institute for Space Studies (GISS) global model with ISCCP clouds and TOVS (TIROS Operational Vertical Sounder)thermodynamic profiles. Fu!l and clear sky SW and LW fluxes are produced. A similar product from the NASA/GEWEX Surface Radiation Budget Project using different radiative flux codes and thermodynamics from the NAS/Goddard Earth Observing System (GEOS-1) assimilation model makes a similar calculation of surface fluxes. However this data set currently extends only through 1995. Significant differences in both interannual variability as well as trends are found between among these data sets. For radiative fluxes these differences are traced to TOVS thermodynamic soundings used to drive the ISCCP-FD calculations. Errors in near surface temperature and precipitable water cascade into ISCCP upward and downward IR flux components, demonstrably affecting interannual variability. Revised estimates of clear-sky fluxes over ocean are made using statistical algorithms and water vapor from the (SSM/I) Special Sensor Microwave Imager. These calculations show strong near-surface water vapor feedback over the tropical oceans in association with SST changes. However, it is also shown that ISCCP longwave cloud forcing, common to both the ISCCP-FD and GEWEX SRB retrievals, is the main driver of a long-term decrease in net LW flux to the surface during the near-20 year period covered by these revised estimates.

Robertson, F. R.↗

Assessment of climate variability of the Greenland ice sheet: Integration of in situ and satellite data

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland ice sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meterological data sets. Data analysis showed the following results: (1)cloud classification based on longwave sky radiation revealed that overcast sky occurred for 25% of the time in winter, and for 15% in spring and summer respectively (winter and summer both show the same occurrence of clear sky of approximately 26%); (2) comparison of aerodynamic profile method with eddy correlation method to derive sensible and latent heat flux showed good agreement in the diurnal cycle and the turbulent fluxes were underestimated with the aerodynamic method by 10 - 30% as compared to the in situ eddy flux method; (3) the katabatic wind shows a distinct diurnal cycle with a maximum in the morning (7-9 h solar time) and a minimum in the later afternoon (18 h solar time); (4) snow grain size was modeled with a surface energy balance model (SNTHERM) and compared with in situ measurements. Sharp decreases in the modeled snow grain size, caused by accumulation events such as precipitation and deposition, could be verified with observational data; (4) radiative transfer modeling of firn supports our beliefs that the observed trends in 18 and 19 GHz passive microwave brightness temperatures are attributable to accumulation rate changes (modeling also indicates the above relationship is detectable because of the presence of depth hoar; (5) snow melt can be detected by a distinct signal in the passive microwave cross-polarized gradient ratio (19h-37v)/(19h+37v) and has been used for wet/dry snow classification; (6) top of the atmosphere (TOA) broadband albedos were derived from AVHRR visible and near infrared reflectances for the entire ice sheet from May 1990 - June 1991, and the highest albedo values are found along the southeast coast of the ice sheet which is consistent with the summer peak of precipitation due to onshore flow loaded with high water vapor content (TOA albedo values dropped to around 40% along the south-western coast during July and August due to bare ice surfaces); and (7) the net all-wave radiation balance at the top of the atmosphere is negative over the entire ice sheet except for the summer months - June-July-August (in June, the net radiation balance is slightly positive over the dry snow areas--15 W/m2).

Steffen, K.↗

Goldstone Orbital Debris Radar: A Historical Review from a Decade of Observations (2007 – 2017)

The NASA Orbital Debris Program Office (ODPO) has utilized the Goldstone bistatic radar since the early1990’s to statistically characterize the low Earth orbit(LEO) sub-centimeter population. The radar provides a unique capability to detect orbital debris population sizes down to an approximate size of 3 mm for altitudes less than 1000 km, and even smaller sizes at lower altitudes. Due to the limited number of hours that are available from this radar each year, it is often used to validate measurements obtained by other radar data sources in the range of orbital debris sizes where the radar systems have an overlap. Additionally, the Goldstone radar provides significantly improved sensitivity than is available from other ground-based radar data sources, which enables it to observe orbital debris populations that, although smaller, still represent a significant risk to both robotic and human missions in LEO. Over the decade of observations from 2007 to2017, a number of significant on-orbit events have occurred including the anti-satellite test againstFengyun-1C, and the accidental collision between Cosmos 2251 and Iridium 33. The orbital debris flux as measured by the Goldstone radar over this important time period is reviewed in this paper, as well as the evolution of the environment over the ensuing years since these events. In addition, the measurements provided by this radar in the years prior to the deployment of large constellations into the environment, as well as the significant increase in missions and mission participants in recent years, is of interest since it provides a baseline for monitoring the effects of these and other changes in the coming years. In 2018, the Goldstone bistatic orbital debris radar pointing geometry changed due to the decommissioning of the nearby receiver antenna, Deep Space Station (DSS) 15, located approximately 500 m from the transmitter antenna. The historical combination of the DSS-14 transmitter and DSS-15receiver enabled all of LEO to be observed using a single pointing due to the close proximity of the two antenna stations and the resulting beam overlap of the bistatic radar geometry. The updated bistatic Goldstone geometry, following the decommissioning of DSS-15,utilizes one of the pair of DSS-25 or DSS-26 antennas that are located approximately 10 km from the transmitter station. The resulting beam overlap with this pointing is such that in LEO, only a small fraction of LEO altitude coverage is observable at one time. Given the operational change of the radar, it is of interest to review the data collected by the original Goldstone bistatic radar over the final decade preceding this change.

Rossina Miller↗

Analysis of Darkened Fragments Resulting from Laboratory Hypervelocity Experiments

NASA’s Orbital Debris Program Office (ODPO) relies on measurements from optical, radar, and in situ measurements to facilitate the development of data-driven orbital debris environmental engineering models such as the NASA Orbital Debris Engineering Model (ORDEM). For optical measurements, the ODPO relies on ground-based optical telescopes to statistically assess objects in geosynchronous orbit and, in the future, low Earth orbit (LEO). The data collected include the detected object’s orbital parameters, time of observation, and optical magnitude. The latter parameter can be converted to a size using NASA’s optical Size Estimation Model (oSEM). It is well known that the observed magnitude of orbital debris can vary based on an object's material constituents, observational geometry, and the effects of space weathering. To assess these magnitude variations, the ODPO uses the Optical Measurement Center (OMC) at NASA Johnson Space Center to characterize a variety of materials and fragments from laboratory impact tests representative of fragments that constitute the orbital debris population. One experiment was DebriSat: a 56 kg spacecraft was built to incorporate structural elements of a modern LEO spacecraft and was subjected to a hypervelocity impact test at the U.S. Air Force’s Arnold Engineering Development Complex using test parameters that may be encountered in LEO. The DebriSat project has provided an abundance of information for assessing fragmentation debris in terms of material, color, shape, size, density, mass, and other derived parameters. Prior to the impact test, the ODPO collected spectral measurements on a subset of the materials used to construct DebriSat for a “ground-truth” of their optical properties. After the successful hypervelocity impact test, the DebriSat team observed a fine, dark dust coating all the fragments. Prior research has suggested that this came from ablated material deposited on the fragments during the impact test, causing a change in the reflective properties [1]. Given that this lower reflectivity on the DebriSat fragments will influence the laboratory-acquired magnitudes used to calculate size and inform potential updates to the oSEM, it is critical to assess if this darkening effect on the DebriSat fragments is a laboratory bias or something that could occur in on-orbit breakup events. This paper will provide a brief overview of the OMC and DebriSat experiment, focused on the optical characterization of a subset of materials using broadband photometric measurements and spectroscopic measurements. In addition, elemental analysis of various DebriSat fragments and the soft-catch foam used in the hypervelocity experiment compared with pristine foam will be examined to further evaluate the source of the dark material coating all fragments. Finally, the authors will present a twofold plan 1) for assessing potential biases in laboratory impact experiments that could affect laboratory optical characterization and 2) for mitigating biases when compared with ground-based optical telescopic measurements of the orbital debris environment.

Heather Cowardin↗

Analysis of Darkened Fragments Resulting from Laboratory Hypervelocity Experiments

NASA’s Orbital Debris Program Office (ODPO) relies on measurements from optical, radar, and in situ measurements to facilitate the development of data-driven orbital debris environmental engineering models such as the NASA Orbital Debris Engineering Model (ORDEM). For optical measurements, the ODPO relies on ground-based optical telescopes to statistically assess objects in geosynchronous orbit and, in the future, low Earth orbit (LEO). The data collected include the detected object’s orbital parameters, time of observation, and optical magnitude. The latter parameter can be converted to a size using NASA’s optical Size Estimation Model (oSEM). It is well known that the observed magnitude of orbital debris can vary based on an object's material constituents, observational geometry, and the effects of space weathering. To assess these magnitude variations, the ODPO uses the Optical Measurement Center (OMC) at NASA Johnson Space Center to characterize a variety of materials and fragments from laboratory impact tests representative of fragments that constitute the orbital debris population. One experiment was DebriSat: a 56 kg spacecraft was built to incorporate structural elements of a modern LEO spacecraft and was subjected to a hypervelocity impact test at the U.S. Air Force’s Arnold Engineering Development Complex using test parameters that may be encountered in LEO. The DebriSat project has provided an abundance of information for assessing fragmentation debris in terms of material, color, shape, size, density, mass, and other derived parameters. Prior to the impact test, the ODPO collected spectral measurements on a subset of the materials used to construct DebriSat for a “ground-truth” of their optical properties. After the successful hypervelocity impact test, the DebriSat team observed a fine, dark dust coating all the fragments. Prior research has suggested that this came from ablated material deposited on the fragments during the impact test, causing a change in the reflective properties [1]. Given that this lower reflectivity on the DebriSat fragments will influence the laboratory-acquired magnitudes used to calculate size and inform potential updates to the oSEM, it is critical to assess if this darkening effect on the DebriSat fragments is a laboratory bias or something that could occur in on-orbit breakup events. This presentation will provide a brief overview of the OMC and DebriSat experiment, focused on the optical characterization of a subset of materials using broadband photometric measurements and spectroscopic measurements. In addition, elemental analysis of various DebriSat fragments and the soft-catch foam used in the hypervelocity experiment compared with pristine foam will be examined to further evaluate the source of the dark material coating all fragments. Finally, the authors will present a twofold plan 1) for assessing potential biases in laboratory impact experiments that could affect laboratory optical characterization and 2) for mitigating biases when compared with ground-based optical telescopic measurements of the orbital debris environment.

Heather Cowardin↗

Stratospheric Ozone Intercomparison Campaign (STOIC) 1989: Overview

The NASA Upper Atmosphere Research Program organized a Stratospheric Ozone Intercomparison Campaign (STOIC) held in July-August 1989 at the Table Mountain Facility (TMF) of the Jet Propulsion Laboratory (JPL). The primary instruments participating in this campaign were several that had been developed by NASA for the Network for the Detection of Stratospheric Change: the JPL ozone lidar at TMF, the Goddard Space Flight Center trailer-mounted ozone lidar which was moved to TMF for this comparison, and the Millitech/LaRC microwave radiometer. To assess the performance of these new instruments, a validation/intercomparison campaign was undertaken using established techniques: balloon ozonesondes launched by personnel from the Wallops Flight Facility and from NOAA Geophysical Monitoring for Climate Change (GMCC) (now Climate Monitoring and Diagnostics Laboratory), a NOAA GMCC Dobson spectrophotometer, and a Brewer spectrometer from the Atmospheric Environment Service of Canada, both being used for column as well as Umkehr profile retrievals. All of these instruments were located at TMF and measurements were made as close together in time as possible to minimize atmospheric variability as a factor in the comparisons. Daytime rocket measurements of ozone were made by Wallops Flight Facility personnel using ROCOZ-A instruments launched from San Nicholas Island. The entire campaign was conducted as a blind intercomparison, with the investigators not seeing each others data until all data had been submitted to a referee and archived at the end of the 2-week period (July 20 to August 2, 1989). Satellite data were also obtained from the Stratospheric Aerosol and Gas Experiment (SAGE 2) aboard the Earth Radiation Budget Satellite and the Total Ozone Mapping Spectrometer (TOMS) aboard Nimbus 7. An examination of the data has found excellent agreement among the techniques, especially in the 20- to 40-km range. As expected, there was little atmospheric variability during the intercomparison, allowing for detailed statistical comparisons at a high level of precision. This overview paper summarizes the campaign and provides a 'road map' to subsequent papers in this issue by the individual instrument teams which will present more detailed analysis of the data and conclusions.

Margitan, J. J.↗