ALBERT

Description: It is our hope that the "Landsat Legacy" story will appeal to a broader audience than just those who use Landsat data on a regular basis. In an era when ready access to images and data from Earth-observing satellites is routine, it is hard to believe that only a few decades ago this was not the case. As the world's first digital land-observing satellite program, Landsat missions laid the foundation for modern space-based Earth observation and blazed the trail in the new field of quantitative remote sensing.

Description: A steep decline in archiving could make large tree-ring datasets irrelevant. But increased spatiotemporal coverage, the addition of novel parameters at sub-annual resolution, and integration with other in situ and remote Earth observations will elevate tree-ring data as an essential component of global-change research.

Description: The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing dataset that ranges from the 1980's to the present. Over the years, several efforts have been made on the calibration of the different instruments to establish a consistent land surface reflectance time-series and to augment the AVHRR data record with data from other sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS). In this paper, we present a summary of all the corrections applied to the AVHRR Surface Reflectance and NDVI Version 4 Product, developed in the framework of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) program. These corrections result from assessment of the geo-location, improvement of the cloud masking and calibration monitoring. Additionally, we evaluate the performance of the surface reflectance over the AERONET sites by a cross-comparison with MODIS, which is an already validated product, and evaluation of a downstream Leaf Area Index (LAI) product. We demonstrate the utility of this long time-series by estimating the winter wheat yield over the USA. The methods developed by [1] and [2] are applied to both the MODIS and AVHRR data. Comparison of the results from both sensors during the MODIS-era shows the consistency of the dataset with similar errors of 10%. When applying the methods to AVHRR historical data from the 1980's, the results have errors equivalent to those derived from MODIS.

Description: The research frontiers of radiative transfer (RT) in coupled atmosphere-ocean systems are explored to enable new science and specifically to support the upcoming Plankton, Aerosol, Cloud ocean Ecosystem (PACE) satellite mission. Given (i) the multitude of atmospheric and oceanic constituents at any given moment that each exhibits a large variety of physical and chemical properties and (ii) the diversity of light-matter interactions (scattering, absorption, and emission), tackling all outstanding RT aspects related to interpreting and/or simulating light reflected by atmosphere-ocean systems becomes impossible. Instead, we focus on both theoretical and experimental studies of RT topics important to the science threshold and goal questions of the PACE mission and the measurement capabilities of its instruments. We differentiate between (a) forward (FWD) RT studies that focus mainly on sensitivity to influencing variables and/or simulating data sets, and (b) inverse (INV) RT studies that also involve the retrieval of atmosphere and ocean parameters. Our topics cover (1) the ocean (i.e., water body): absorption and elastic/inelastic scattering by pure water (FWD RT) and models for scattering and absorption by particulates (FWD RT and INV RT); (2) the air-water interface: variations in ocean surface refractive index (INV RT) and in whitecap reflectance (INV RT); (3) the atmosphere: polarimetric and/or hyperspectral remote sensing of aerosols (INV RT) and of gases (FWD RT); and (4) atmosphere-ocean systems: benchmark comparisons, impact of the Earth's sphericity and adjacency effects on space-borne observations, and scattering in the ultraviolet regime (FWD RT). We provide for each topic a summary of past relevant (heritage) work, followed by a discussion (for unresolved questions) and RT updates.

Description: These maps are an analysis of the Thomas Fire that occurred in California during December 2017. Using a variety of NASA Earth science data from five National Aeronautics and Space Administration (NASA) sources (including four Earth Observing System Data and Information System Distributed Active Archive Centers and NASA Fire Information for Resource Management System), as well as ancillary data from Ventura County, Santa Barbara County, and the Department of Homeland Security, this analysis sought to identify forest fire risk zones, create a fire occurrence density map, examine the vegetation and subsequent burn scar, capture the affected parcels, and capture the affected vegetation.

Description: An extreme biomass-burning event occurred in Indonesia from September through October 2015 due to severe drought conditions, partially caused by a major El Nino event, thereby allowing for significant burning of peatland that had been previously drained. This event had the highest sustained aerosol optical depths (AOD) ever monitored by the global Aerosol Robotic Network (AERONET). The newly developed AERONET Version 3 algorithms retain high AOD at the longer wavelengths when associated with high Angstrom Exponents (AEs), which thereby allowed for measurements of AOD at 675 nanometers as high as approximately 7, the upper limit of Sun photometry. Measured AEs at the highest monitored AOD levels were subsequently utilized to estimate instantaneous values of AOD at 550 nanometers in the range of 11 to 13, well beyond the upper measurement limit. Additionally, retrievals of complex refractive indices, size distributions, and single scattering albedos (SSA) were obtained at much higher AOD levels than possible from almucantar scans due to the ability to perform retrievals at smaller solar zenith angles with new hybrid sky radiance scans. For retrievals made at the highest AOD levels the fine mode volume median radii were approximately 0.25 to 0.30 microns, which are very large particles for biomass burning. Very high SSA values (approximately 0.975 from 440 to 1020 nanometers) are consistent with the domination by smoldering combustion of peat burning. Estimates of the percentage peat contribution to total biomass burning aerosol based on retrieved SSA and laboratory measured peat SSA were approximately 80-85 percent, in excellent agreement with independent estimates.

Description: The lack of a standardized database of eddy covariance observations has been an obstacle for data-driven estimation of terrestrial carbon dioxide fluxes in Asia. In this study, we developed such a standardized database using 54 sites from various databases by applying consistent postprocessing for data-driven estimation of gross primary productivity (GPP) and net ecosystem carbon dioxide exchange (NEE). Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. Site-level evaluation of the estimated carbon dioxide fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8 days are reproduced (e.g., r (exp 2) =0.73 and 0.42 for 8 day GPP and NEE). Evaluation of spatially estimated GPP with Global Ozone Monitoring Experiment 2 sensor-based Sun-induced chlorophyll fluorescence shows that monthly GPP variations at subcontinental scale were reproduced by SVR (r (exp 2)=1.00, 0.94, 0.91, and 0.89 for Siberia, East Asia, South Asia, and Southeast Asia, respectively). Evaluation of spatially estimated NEE with net atmosphere-land carbon dioxide fluxes of Greenhouse Gases Observing Satellite (GOSAT) Level 4A product shows that monthly variations of these data were consistent in Siberia and East Asia; meanwhile, inconsistency was found in South Asia and Southeast Asia. Furthermore, differences in the land carbon dioxide fluxes from SVR-NEE and GOSAT Level 4A were partially explained by accounting for the differences in the definition of land carbon dioxide fluxes. These data-driven estimates can provide a new opportunity to assess carbon dioxide fluxes in Asia and evaluate and constrain terrestrial ecosystem models.

Description: This analysis is a follow-on to the Thomas Fire analysis presented by Ross Bagwell ("Fire Analysis of the Thomas Fire Using NASA DATA in a GIS"). The Thomas fire and heavy rains a month later led to the historic flooding. The maps tell the story using NASA Earth Observing System data in concert with Santa Barbara County data.

Description: Cloud droplet number concentration (Nd) is an important parameter of liquid clouds and is crucial to understanding aerosol-cloud interactions. It couples boundary layer aerosol composition, size and concentration with cloud reflectivity. It affects cloud evolution, precipitation, radiative forcing, global climate and, through observation, can be used to partially monitor the first indirect effect. With its unique combination of multi-wavelength, multi-angle, total and polarized reflectance measurements, the Research Scanning Polarimeter (RSP) retrieves Nd with relatively few assumptions. The approach involves measuring cloud optical thickness, mean droplet extinction cross-section and cloud physical thickness. Polarimetric observations are capable of measuring the effective variance, or width, of the droplet size distribution. Estimating cloud geometrical thickness is also an important component of the polarimetric Nd retrieval, which is accomplished using polarimetric measurements in a water vapor absorption band to retrieve the amount of in-cloud water vapor and relating this to physical thickness. We highlight the unique abilities and quantify uncertainties of the polarimetric approach. We validate the approach using observational data from the North Atlantic and Marine Ecosystems Study (NAAMES). NAAMES targets specific phases in the seasonal phytoplankton lifecycle and ocean-atmosphere linkages. This study provides an excellent opportunity for the RSP to evaluate its approach of sensing Nd over a range of concentrations and cloud types with in situ measurements from a Cloud Droplet Probe (CDP). The RSP and CDP, along with an array of other instruments, are flown on the NASA C-130 aircraft, which flies in situ and remote sensing legs in sequence. Cloud base heights retrieved by the RSP compare well with those derived in situ (R=0.83) and by a ceilometer aboard the R.V. Atlantis (R=0.79). Comparing geometric mean values from 12 science flights throughout the NAAMES-1 and NAAMES-2 campaigns, we find a strong correlation between Nd retrieved by the RSP and CDP (R=0.96). A linear least squares fit has a slope of 0.92 and an intercept of 0.3 cm3. Uncertainty in this comparison can be attributed to cloud 3D effects, nonlinear liquid water profiles, multilayered clouds, measurement uncertainty, variation in spatial and temporal sampling, and assumptions used within the method. Radiometric uncertainties of the RSP measurements lead to biases on derived optical thickness and cloud physical thickness, but these biases largely cancel out when deriving Nd for most conditions and geometries. We find that a polarimetric approach to sensing Nd is viable and the RSP is capable of accurately retrieving Nd for a variety of cloud types and meteorological conditions.

Description: An evapotranspiration (ET) ensemble composed of 36 land surface model (LSM) experiments and four diagnostic datasets (GLEAM, ALEXI, MOD16, and FLUXNET) is used to investigate uncertainties in ET estimate over five climate regions in West Africa. Diagnostic ET datasets show lower uncertainty estimates and smaller seasonal variations than the LSM-based ET values, particularly in the humid climate regions. Overall, the impact of the choice of LSMs and meteorological forcing datasets on the modeled ET rates increases from north to south. The LSM formulations and parameters have the largest impact on ET in humid regions, contributing to 90% of the ET uncertainty estimates. Precipitation contributes to the ET uncertainty primarily in arid regions. The LSM-based ET estimates are sensitive to the uncertainty of net radiation in arid region and precipitation in humid region. This study serves as support for better determining water availability for agriculture and livelihoods in Africa with earth observations and land surface models.

Description: We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Description: On 27 August 2013, during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys field mission, NASA's ER2 research aircraft encountered a region of enhanced water vapor, extending over a depth of approximately 2 km and a minimum areal extent of 20,000 km(exp 2) in the stratosphere (375 K to 415 K potential temperature), south of the Great Lakes (42N, 90W). Water vapor mixing ratios in this plume, measured by the Harvard Water Vapor instrument, constitute the highest values recorded in situ at these potential temperatures and latitudes. An analysis of geostationary satellite imagery in combination with trajectory calculations links this water vapor enhancement to its source, a deep tropopausepenetrating convective storm system that developed over Minnesota 20 h prior to the aircraft plume encounter. High resolution, groundbased radar data reveal that this system was composed of multiple individual storms, each with convective turrets that extended to a maximum of ~4 km above the tropopause level for several hours. In situ water vapor data show that this storm system irreversibly delivered between 6.6 kt and 13.5 kt of water to the stratosphere. This constitutes a 2025% increase in water vapor abundance in a column extending from 115 hP to 70 hPa over the plume area. Both in situ and satellite climatologies show a high frequency of localized water vapor enhancements over the central U.S. in summer, suggesting that deep convection can contribute to the stratospheric water budget over this region and season.

Description: A deeper understanding of how clouds will respond to a warming climate is one of the outstanding challenges in climate science. Uncertainties in the response of clouds, and particularly shallow clouds, have been identified as the dominant source of the discrepancy in model estimates of equilibrium climate sensitivity. As the community gains a deeper understanding of the many processes involved, there is a growing appreciation of the critical role played by fluctuations in water vapor and the coupling of water vapor and atmospheric circulations. Reduction of uncertainties in cloud-climate feedbacks and convection initiation as well as improved understanding of processes governing these effects will result from profiling of water vapor in the lower troposphere with improved accuracy and vertical resolution compared to existing airborne and space-based measurements. This paper highlights new technologies and improved measurement approaches for measuring lower tropospheric water vapor and their expected added value to current observations. Those include differential absorption lidar and radar, microwave occultation between low-Earth orbiters, and hyperspectral microwave remote sensing. Each methodology is briefly explained, and measurement capabilities as well as the current technological readiness for aircraft and satellite implementation are specified. Potential synergies between the technologies are discussed, actual examples hereof are given, and future perspectives are explored. Based on technical maturity and the foreseen near-mid-term development path of the various discussed measurement approaches, we find that improved measurements of water vapor throughout the troposphere would greatly benefit from the combination of differential absorption lidar focusing on the lower troposphere with passive remote sensors constraining the upper-tropospheric humidity.

Description: NASA Earth Science and Aeronautics researchers have been involved in development and use of High Altitude Long Endurance (HALE) unmanned aircraft systems (UAS) since the 1990's. The NASA Environmental Research Aircraft Sensor and Technology Program (ERAST) demonstrated the promise of HALE aircraft for providing observations while also proving the importance of triple-redundant avionics to improve system reliability for large unmanned aircraft. Early efforts to develop an operational HALE capability for earth observations languished for nearly two decades owing to insufficient solar panel efficiency, battery power density, and light-weight, yet strong, materials. During this time NASA researchers focused on using the Global Hawk to demonstrate the utility of providing diurnal measurements over severe storms (ie. HS3) and to track stratospheric water vapor transport (ATTREX). Recent significant commercial investments are now leading to the realization of a long-held goal of week- to month-long sustained observations and measurements from the stratosphere. In addition to a historical review of NASA use and interest in HALE aircraft, this paper will present current concepts for exploiting current and planned HALE aircraft capabilities including in situ characterization of atmospheric composition and dynamics as well as imagery collection. NASA researchers anticipate HALE will provide a useful means to test smallsat instruments and components. Observations from HALE-based instruments might also provide useful gap-filler observations to flagship satellite missions where the repeat time doesn't allow for measurements of quickly changing phenomenon. HALE will likely also provide measurements and communications relay to facilitate other aircraft in multi-aircraft campaigns. We will also report on progress towards a NASA-funded flight test planned for summer 2019 of a solar-electric vehicle designed to carry 7kg (15lbs) for 30 days at 20km altitude.

Description: In this work, we use the Clouds and the Earths Radiant Energy System (CERES) FluxByCloudTyp data product, which calculates TOA shortwave and longwave fluxes for cloud categories defined by cloud optical depth () and cloud top pressure (), to evaluate the HadGEM2-A model with a simulator. The CERES Flux-by-cloud type simulator is comprised of a cloud generator that produces subcolumns with profiles of binary cloud fraction, a cloud property simulator that determines the (,) cloud type for each subcolumn, and a radiative transfer model that calculates TOA fluxes. The identification of duplicate atmospheric profiles reduces the number of radiative transfer calculations required by approximately 97.6%. In the Southern Great Plains region in JFD (January, February, and December) 2008, the simulator shows that simulated cloud tops are higher in altitude than observed, but also have higher values of OLR than observed, leading to a compensating error that results in an average value of OLR that is close to observed. When the simulator is applied to the Southeast Pacific stratocumulus region in JJA 2008, the simulated cloud tops are primarily low in altitude; however, the clouds tend to be less numerous, and have higher optical depths than are observed. In addition to the increase in albedo that comes from having too many clouds with higher optical depth, the HadGEM2-A albedo is higher than observed for those cloud types that occur most frequently. The simulator is also applied to the entire 60 N 60 S region, and it is found that there are fewer clouds than observed for most cloud types, but there are also higher albedos for most cloud types, which represents a compensating error in terms of the shortwave radiative budget.

Description: The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure high-resolution atmospheric profiles of ozone. The accurate characterization of these lidars is necessary to determine the uniformity of the network calibration. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission and the Front Range Air Pollution and Photochemistry xperiment (FRAPP) to measure ozone variations from the boundary layer to the top of the troposphere. This study presents the analysis of the intercomparison between the TROPOZ, TOPAZ, and LMOL lidars, along with comparisons between the lidars and other in situ ozone instruments including ozonesondes and a P-3B airborne chemiluminescence sensor. The TOLNet lidars measured vertical ozone structures with an accuracy generally better than 15 % within the troposphere. Larger differences occur at some individual altitudes in both the near-field and far-field range of the lidar systems, largely as expected. In terms of column average, the TOLNet lidars measured ozone with an accuracy better than 5 % for both the intercomparison between the lidars and between the lidars and other instruments. These results indicate that these three TOLNet lidars are suitable for use in air quality, satellite validation, and ozone modeling efforts.

Description: Nearly all proglacial water discharge from the Greenland Ice Sheet is routed englacially, from the surface to the bed, via moulins. Identification of moulins in high-resolution imagery is a frequent topic of study, but the processes controlling how and where moulins form remain poorly understood. We seek to leverage information gained from the development of a physical model of moulin formation, remotely sensed ice-sheet data products, and an analytic model of ice-flow perturbations to develop a predictive stochastic model of moulin distribution across Greenland. Here we present initial results from the physical model of moulin formation and characterize the sensitivity of moulin geometry to a range of model parameters. This parameterization of moulin formation is the first step in developing a stochastic model that will be a predictive, computationally efficient representation of the englacial hydrologic system.

Description: The NASA PACE project, in conjunction with the IOCCG, EUMETSAT, and JAXA, have initiated an Aquatic Primary Productivity working group, with the aim to develop community consensus on multiple methods for measuring aquatic primary productivity used for satellite validation and model synthesis. A workshop to commence the working group efforts was held December 05-07, 2018 at the University Space Research Association headquarters in Columbia, MD U.S.A., bringing together 26 active researchers from 16 institutions. The group discussed the primary differences, nuances, scales, uncertainties, definitions, and best practices for measurements of primary productivity derived from in situ/on-deck/laboratory radio/stable isotope incubations, dissolved oxygen concentrations (from incubations or autonomous platforms such as floats or gliders), oxygen-argon ratios, triple oxygen isotope, natural fluorescence, and FRRF/ETR/kinetic analysis. These discussions highlighted the necessity to move the community forward towards the establishment of climate-quality primary productivity measurements that follow uniform protocols, which is imperative to ensure that existing and future measurements can be compared, assimilated, and their uncertainties determined for model development and validation. The specific deliverable resulting from of this activity will be a protocol document, published in coordination with the IOCCG. This presentation will discuss the findings of the meeting, and address future activities of the working group.

Description: Previous studies have quantified the expansion of gold mining-related forest loss (Espejo et al., 2018; Asner et al., 2017; Swenson et al., 2011) in the Madre de Dios region of Peru. This study uses Spectral Mixture Analysis (SMA) in a cloud-computing platform to map general forest loss within and outside key land tenure areas in this region. Landsat 7 Enhanced Thematic Mapper plus (ETM+) and Landsat 8 Operational Land Imager (OLI) Surface Reflectance data were utilized spanning 2013 and 2018 and spectral unmixing was performed to identify patterns of forest loss for each year. Planet Scope and RapidEye imagery were used to conduct an accuracy assessment and to identify potential drivers.

Description: No abstract available

Description: As part of the Southeast United States-based Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), and collinear with part of the Southeast Atmosphere Study, the University of Wisconsin High Spectral Resolution Lidar system was deployed to the University of Alabama from 19 June to 4 November 2013. With a collocated Aerosol Robotic Network (AERONET) sun photometer, a nearby Chemical Speciation Network (PM2.5) measurement station, and near daily ozonesonde releases for the August-September SEAC4RS campaign, the site allowed the regions first comprehensive diurnal monitoring of aerosol particle vertical structure. A 532nm lidar ratio of 55 sr provided good closure between aerosol backscatter and AERONET (aerosol optical thickness, AOT). A principle component analysis was performed to identify key modes of variability in aerosol backscatter. ''Fair weather'' days exhibited classic planetary boundary layer structure of a mixed layer accounting for approx. 50% of AOT and an entrainment zone providing another 25%. An additional 5-15% of variance is gained from the lower free troposphere from either convective detrainment or frequent intrusions of western United States biomass burning smoke. Generally, aerosol particles were contained below the 0 C level, a common level of stability in convective regimes. However, occasional strong injections of smoke to the upper troposphere were also observed, accounting for the remaining 10-15% variability in AOT. Examples of these common modes of variability in frontal and convective regimes are presented, demonstrating why AOT often has only a weak relationship to surface PM2.5 concentration.

Description: No abstract available

Description: AVHRR data record is well alive and continue to improve and be used by a large land user community.Most of the improvement are due to the overlapping with MODIS Aqua, Terra.We recommend operating missions as long as possible to enable overlap of at least a few years (especially for applications).

Description: Balloon-borne frostpoint measurements have shown a high frequency of supersaturation near the tropical tropopause, and this has been attributed to forced ascent associated with wavemotions as well as diabatic heating. Long-term profile statistics are typically presented on altitude, pressure or potential temperature surfaces. For example, at Costa Rica long-term mean values of CFH RH at 16.8 km, the mean annual height of the tropopause, range from less than 60 percent in July to over 90% in October. While a plot of the annual cycle vs height shows relatively high humidities in the upper troposphere and especially so as one approaches the tropopause, the overall picture is one of subsaturation. A very different picture emerges,however, if the analysis is done in height relative to the tropopause. Here the long-term average of RH at the tropopause is 94 percent or greater throughout the year. We discuss this paradoxical result in the context of dynamical and cloud processes occurring near the tropical tropopause.

Description: No abstract available

Description: Stratospheric ozone concentrations have begun to show early signs of recovery following the implementation of the Montreal Protocol and its amendments as well as in response to decreasing upper-stratospheric temperatures. Secular trends in stratospheric ozone are modulated by considerable interannual variability and systematic changes in transport patterns that are expected under increasing concentrations of greenhouse gases, especially in the lower stratosphere. These factors necessitate the continued close monitoring of stratospheric ozone in upcoming decades, with a special focus on the lower stratosphere.As highly resolved data sets combining a plethora of observations with model simulations atmospheric reanalyses are, in principle, well suited for the task. All major reanalyses generate ozone output. However, significant spurious discontinuities that arise from step changes in the observing systems prevent a straightforward analysis of ozone trends and long-term variability. Building on our recent work, in this presentation we will demonstrate that trend detection is nonetheless possible using the ozone record from NASA's MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2) reanalysis bias-corrected using a chemistry model simulation as a transfer function. Next, we will outline several strategies to reduce artificial discontinuities in the ozone record in future NASA reanalyses. This discussion will be illustrated by an example of joint assimilation of bias-corrected ozone profiles from the Microwave Limb Sounder (MLS) on the Aura satellite (2004 to present) and the Ozone Mapping Profiler Suite Limb Profiler (OMPS-LP) sensors that are expected to operate on future NOAA platforms.

Description: In July and August 2014, NASA conducted an airborne lidar campaign based out of Fort Wainwright,Fairbanks, Alaska, in support of Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) algorithm development. The survey targeted Alaskan glaciers and icefields and sea ice in the Arctic Ocean during the summer melt season. Ultimately, the mission, MABEL Alaska 2014, including checkout and transit flights, conducted 11 science flights, for a total of over 50 flight hours over glaciers, icefields, and sea ice.

Description: This work is using the newly available NASA SMAP soil moisture measurement data to evaluate its impact on the atmospheric dust emissions. Dust is an important component of atmospheric aerosols, which affects both climate and air quality. In this work, we focused on semi-desert regions, where dust emissions show seasonal variations due to soil moisture changes, i.e. in Sahel of Africa. We first identified three Aerosol Robotic Network (AERONET) sites in the Sahel (IER_Cinzana, Banizoumbou, and Zinder_Airport). We then utilized measurements of aerosol optical depth (AOD), fine mode fraction, size distribution, and single-scattering albedo and its wave-length dependence to select dust plumes from the available measurements We matched the latitude and longitude of the AERONET station to the corresponding SMAP data cell in the years 2015 and 2016, and calculated their correlation coefficient. Additionally, we looked at the correlation coefficient with a three-day and a five-day shift to check the impact of soil moisture on dust plumes with some time delay. Due to the arid nature of Banizoumbou and Zinder_Airport, no correlation was found to exist between local soil moisture and dust aerosol load. While IER_Cinzana had soil moisture levels above the satellite threshold of 0.02cm3/cm3, R-value approaching zero indicated no presence of a correlation. On the other hand, Ilorin demonstrated a significant negative correlation between aerosol optical depth and soil moisture. When isolating the analysis to Ilorin's dry season, a negative correlation of -0.593 was the largest dust-isolated R-value recorded, suggesting that soil moisture is driven the dust emission in this semi-desert region during transitional season.

Description: Waterways of the Sacramento San Joaquin Delta have recently become infested with invasive aquatic weeds such as floating water hyacinth (Eichhoria crassipes) and water primrose (Ludwigia peploides). These invasive plants cause many negative impacts, including, but not limited to: the blocking of waterways for commercial shipping and boating; clogging of irrigation screens, pumps and canals; and degradation of biological habitat through shading. Zhang et al. (1997, Ecological Applications, 7(3), 1039-1053) used NASA Landsat satellite imagery together with field calibration measurements to map physical and biological processes within marshlands of the San Francisco Bay. Live green biomass (LGB) and related variables were correlated with a simple vegetation index ratio of red and near infra-red bands from Landsat images. More recently, the percent (water area) cover of water hyacinth plotted against estimated LGB of emergent aquatic vegetation in the Delta from September 2014 Landsat imagery showed a 80% overall accuracy. For the past two years, we have partnered with the U. S. Department of Agriculture (USDA) and the Department of Plant Sciences, University of California at Davis to conduct new validation surveys of water hyacinth and water primrose coverage and LGB in Delta waterways. A plan is underway to transfer decision support tools developed at NASA's Ames Research Center based on Landsat satellite images to improve Delta-wide integrated management of floating aquatic weeds, while reducing chemical control costs. The main end-user for this application project will be the Division of Boating and Waterways (DBW) of the California Department of Parks and Recreation, who has the responsibility for chemical control of water hyacinth in the Delta.

Description: This Synthetic Aperture Radar (SAR) handbook of applied methods for forest monitoring and biomass estimation has been developed by SERVIR in collaboration with SilvaCarbon to address pressing needs in the development of operational forest monitoring services. Despite the existence of SAR technology with all-weather capability for over 30 years, the applied use of this technology for operational purposes has proven difficult. This handbook seeks to provide understandable, easy-to-assimilate technical material to remote sensing specialists that may not have expertise on SAR but are interested in leveraging SAR technology in the forestry sector.

Description: Like a peninsula into the Southern Ocean, the vast Patagonia desert in the southern tip of South America is exposed to extreme winds. Dust blown from this region has important impacts thousands of kilometers away, but these impacts are very difficult to assess. Questions such as the sources of dust found in snow in East Antarctica as well as the provenance of nutrients in the Southern Ocean remain unanswered. While the Patagonia desert is the likely source of dust, there is a dearth of observational records of dust activity from this desert. This study fills the gap in observations by providing a record of 50 years of surface and satellite observations of the largest and most active dust source in Patagonia: lake Colhu Huapi. The seasonality, frequency and periods of major dust activity are identified from meteorological records at a station located 100km downwind from the lake. Collocated satellite observations confirmed the major periods of dust activity in the last 30 years. This dataset provides information on how to interpret records of recent dust found in East Antarctica snow as well as help to understand the CO2 cycle in the Southern Ocean.

Description: Integrated multi-sensor assessment is proposed as a novel approach to advance satellite precipitation validation in order to provide users and algorithm developers with an assessment adequately coping with the varying performances of merged satellite precipitation estimates. Gridded precipitation rates retrieved from space sensors with quasi-global coverage feed numerous applications ranging from water budget studies to forecasting natural hazards caused by extreme events. Characterizing the error structure of satellite precipitation products is recognized as a major issue for the usefulness of these estimates. The Global Precipitation Measurement (GPM) mission aims at unifying precipitation measurements from a constellation of low-earth orbiting (LEO) sensors with various capabilities to detect, classify and quantify precipitation. They are used in combination with geostationary observations to provide gridded precipitation accumulations. The GPM Core Observatory satellite serves as a calibration reference for consistent precipitation retrieval algorithms across the constellation. The propagation of QPE uncertainty from LEO active/passive microwave (PMW) precipitation estimates to gridded QPE is addressed in this study, by focusing on the impact of precipitation typology on QPE from the Level-2 GPM Core Observatory Dual-frequency Precipitation Radar (DPR) to the Microwave Imager (GMI) to Level-3 IMERG precipitation over the Conterminous U.S. A high-resolution surface precipitation used as a consistent reference across scales is derived from the ground radar-based Multi-Radar/Multi-Sensor. While the error structure of the DPR, GMI and subsequent IMERG is complex because of the interaction of various error factors, systematic biases related to precipitation typology are consistently quantified across products. These biases display similar features across Level-2 and Level-3, highlighting the need to better resolve precipitation typology from space and the room for improvement in global-scale precipitation estimates. The integrated analysis and framework proposed herein applies more generally to precipitation estimates from sensors and error sources affecting low-earth orbiting satellites and derived gridded products.

Description: No abstract available

Description: No abstract available

Description: The objective of this project is to quantify changes of mangrove extent in Madagascar and Nigeria from 2015-2018. Both countries contain a significant portion of the worlds mangroves, and which are known to be deforested and degraded due to natural and anthropogenic factors. Change is estimated using multi-date Landsat-8 OLI data and cloud computational techniques. Findings show that mangroves in both countries have exhibited areal loss during the study period, but loss varies across space. Understanding the rate and magnitude of mangrove change can aid in identifying priority areas for forest regenerations, and can help construct sustainable management practices for the future.

Description: No abstract available

Description: No abstract available

Description: The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument on-board the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft. The S-NPP launched in October 2011 and it has been collecting valuable Earth science data with VIIRS and four other instruments for more than five years. The VIIRS Characterization Support Team (VCST) of the National Aeronautics and Space Administration (NASA) Science Investigator-led Processing Systems (SIPS) is designed to support the VIIRS sensor pre-launch geometric and radiometric characterization and to access on-orbit long-term Level-1B (L1B) calibration and performance. This paper reviews the VIIRS thermal emissive bands (TEB), covering wavelengths from 3.7 to 12.0 m, L1B radiometric calibration algorithms and presents the calibration uncertainty methodology which will be implanted in the L1B processing software. Discussions will be focused on the key uncertainty parameters and the application in L1B.

Description: Background (what): SI (International System of Units)-traceable Microwave Radiometer calibration; Motivation (why): NWP (Numerical Weather Prediction), FCDR (Fundamental Climate Data Record); Technology (how): NIST (National Inst. of Standards and Technology) blackbody target for ; Standards: Status & Future Plans. Development of a National Standard for Microwave Brightness Temperature (TB) at NIST.

Description: This chapter summarizes ocean color science data product requirements for the Plankton, Aerosol, Cloud,ocean Ecosystem (PACE) mission's Ocean Color Instrument (OCI) and observatory. NASA HQ delivered Level-1 science data product requirements to the PACE Project, which encompass data products to be produced and their associated uncertainties. These products and uncertainties ultimately determine the spectral nature of OCI and the performance requirements assigned to OCI and the observatory. This chapter ultimately serves to provide context for the remainder of this volume, which describes tools developed that allocate these uncertainties into their components, including allowable OCI systematic and random uncertainties, observatory geo location uncertainties, and geophysical model uncertainties.

Description: No abstract available

Description: Operating and maintaining a large multi-tenant ecosystem in the cloud requires scalable solutions to unique technical and process challenges. The Cloud Computing model grants significant permissions to development teams that traditionally were reserved for Data-Center Administrators and Supply-Chain Managers. Earthdata Cloud has worked to re-cast traditional data-center management into a sensible cloud-first model. This talk discusses some of our challenges, solutions, and way ahead.

Description: Cumulus is a scalable, extensible cloud-based archive system which is capable of ingesting, archiving, and distributing data from both existing on-prem sources and new cloud-native missions. As we have built and evolved the system with contributions from seven NASA EOSDIS organizations, we have learned several lessons about how to build a robust, broadly-applicable, microservices-based cloud system for geospatial data which we will share in this talk.

Description: Mineral dust is an integral component in the Earth system that interacts with the system's many other components involving the energy, water, and carbon cycles. Dust also degrades air quality and adversely affects human health. These interactions and impacts are not contained in regions nearby dust sources, but can reach very far because of the long-range transport on intercontinental and global scales. Satellite's routine sampling and extensive coverage in time and space makes it an ideal platform to follow the dust from sources to sinks and assess its impacts along the long journey. Dust particles are unique in their coarse size and irregular shape, which makes it feasible to distinguish them from other aerosol particles using remote sensing techniques. This talk will provide an overview of what we have learned from analyzing advanced satellite remote sensing measurements during the EOS-era supplemented by in situ observations and model simulations, including dust source characterization, seasonal and interannual variability, trans-Pacific and trans-Atlantic transport and deposition, and dust influences on the radiation budget, air quality, and ecosystems. The talk will also discuss challenges and opportunities to further improve the dust characterization and assessment of the impacts via remote sensing techniques.

Description: Temperature is a primary determining factor for plant growth and development so providing an appropriate temperature input is critically important for developing growth models. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA (US Dept. of Agriculture)-sponsored area-wide project including NASA Ames Research Center and State of California Department of Boating and Waterways, uses modeling to assess invasive aquatic plant impacts on ecosystem services in the Delta. Availability of continuous records for monitored temperature is limited and particularly in the case of water temperature the distribution of monitoring is inadequate. This work quantitatively defines the influence of air and water temperature in determining dominant growth rate processes for important floating aquatic invasive plants in the Delta. Since these plants function with portions submerged and above water we wanted to understand the relationship between root zone and shoot zone temperature and ability to use a single temperature inputs in DRAAWP models. Water Hyacinth and Primrose were gown in multiple controlled environment chamber studies with various combinations of root zone and shoot zone temperatures. Long-term growth studies provided integrated response of biomass accumulation and distribution within the canopy. Short-term gas exchange studies provide a time scale for responsiveness to temperature and a short-term study approach to evaluate temperature responses at various stages of canopy development.

Description: The NASA Goddard Earth Sciences Data and Information Services Center archives tens of thousands of Earth Observation (EO) parameters for land, atmosphere, and ocean. To facilitate GIS users to easily find, visualize, obtain, and analyze these EO data through, we developed an ArcGIS infrastructure with the Server, image services, Portal, and AOL. We will show how this capability supports broad GIS applications. Use cases including water management and air quality analyses will be demonstrated.

Description: We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Description: 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 NASAs 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 NASAs GV team to verify GPM level-2 precipitation products in rain and snow. We describe the tools and analysis framework used to confirm that NASAs Level-1 science requirements for GPM are met by the GPM Core Observatory. Examples of routine validation activities related to verification of Integrated Multi-satellitE Retrievals for GPM (IMERG) products for two different regions of the globe (Korea and the U.S.) are provided, and a brief analysis related to IMERG performance in the extreme rainfall event associated with Hurricane Florence is discussed.

Description: The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

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Description: Talks presented by Dr. Ralph Kahn at the 16th AeroCom and 5th AeroSat Workshops, held October 9-13, 2017 in Helsinki, Finland.

Description: NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of twelveNASA Earth Observing System (EOS) data centers that process, archive, document, and distributedata from Earth science missions and related projects. The GES DISC hosts a wide range ofremotely-sensed and model data and provides reliable and robust data access and services to usersworldwide. This presentation, focusing on hydrological land surface data, provides a summary tablefor the hydrological data holdings, along with discussions of recent updates to data and data services.

Description: Volcanic lava flows and/or the gas eruptions are the most common characteristics that can be remotely monitored with satellite technology in the global perspective and on different timescales. Atmospheric Sulfur Dioxide (SO2), one of the most abundant gases from volcanic eruptions apart from atmospheric common gases Carbon Dioxide and water vapor, can be directly detected by space-based sensors on satellites. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of the 12 Distributed Active Archive Centers (DAACs) within NASA's Earth Observing System Data and Information System (EOSDIS), which archives SO2 data sets from the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) in 1978, till the ongoing Ozone Monitoring Instrument (OMI) on NASA's EOS-Aura satellite, the Ozone Mapping Profiler Suite (OMPS) Nadir Mapper (NM) on both the Suomi National Polar-Orbiting Partnership (Suomi-NPP or SNPP) and the Joint Polar-orbiting Satellite System-1 (JPSS-1) satellites, into the future JPSS missions. In addition to the standard OMI/Aura and OMPS/S-NPP SO2 products, SO2 products created under the charter of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) project, are also archived at GES DISC, through which NASA enacts to expand understanding the Earth system using consistent data records. The Land Processes Distributed Active Archive Center (LP DAAC) is another EOSDIS's DAAC that provides land data products and operates as a partnership with the U.S. Geological Survey (USGS). The LP DAAC has been archiving the satellite imagery from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard NASA's EOS-Terra satellite, a high spatial resolution (15 meters) and 14 band multispectral instrument. The ASTER imagery is one of the land products contributing to the application for monitoring hot spots and land terrain changes caused by volcanic eruption events. The data potential in GES DISC and LP DAAC to monitor volcanic sources of SO2 and the influence of wind fields on the gas plume spread will be demonstrated with the most recent 2018 May-July Kilauea Volcano eruption.

Description: Crafting a great user experience is hard. Crafting a great user experience for Earth science applications is fraught with challenges. From the variability in metadata to the experience profile of various users the possible permutations of use cases introduce layer upon layer of complexities that must be designed against. In this session, the Earthdata Search team would like to highlight lessons learned over the lifespan of the application the good, the bad, and the ugly.

Description: The Gravity Recovery and Climate Experiment - Follow-On (GRACE-FO) Mission is a NASA directed mission to continue the goals of the original GRACE mission and provide continuity for the GRACE data set. The GRACE-FO mission is the result of an international cooperation to develop a concept and approach that minimizes cost and risk and maximizes the probability of success through limited changes to the original GRACE system design. The result is a system architecture in which maintenance of heritage is paramount, including heritage derived through the partnership with the German Research Centre for Geosciences (GFZ) in Germany. As a secondary goal, GRACE-FO will carry a Laser Ranging Interferometer (LRI) as a technology demonstration, which will provide laser interferometry measurements of inter-satellite range, complementary to the K/Ka-Band microwave link to demonstrate laser-ranging technology in support of future GRACE-like missions. Another secondary objective is the continuation of GRACE radio occultation measurements.

Description: This presentation provides mission operations status for the Earth Observing System (EOS) Aqua satellite for the past six-months (December 2018 through May 2019). It only contains information that is of interest to the International Earth Science Constellation (ESC) Mission Operations Working Group (MOWG) member missions. It will be presented at the bi-annual MOWG Meeting in Toulouse, France on Wednesday, June 5, 2019. These meetings have been occurring twice a year since the MOWG was formed in 2003.

Description: No abstract available

Description: Interannual climate variability patterns associated with the El Nio-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 20152016 El Nio event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Nio-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (1481% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.528% higher during years with El Nio events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p 〈 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p 〈 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.

Description: The ObseRvations of Aerosols above Clouds and their interactions (ORACLES) project is making a series of field deployments to the southeastern Atlantic with NASA ER-2 and P3 aircraft to acquire both detailed remote sensing observations and in situ measurements of the aerosols and clouds in that region. This area is home to one of the largest low-level cloud decks on Earth that is seasonally affected by vast plumes of smoke from biomass burning, which in effect provides a natural experiment testing the radiative and microphysical interactions between the smoke and the clouds. The downward solar radiation at the surface, or cloud top, is always reduced by the presence of smoke. However, whether the amount of sunlight reflected back out to space is increased, or decreased by the presence of smoke is sensitively dependent on the brightness of the clouds and the fraction of light that the smoke absorbs each time light hits a smoke particle. In this study we use data from the Research Scanning Polarimeter, an along track scanning instrument, that provides measurements of the Stokes parameters I, Q and U at 410, 470, 555, 670, 865, 960, 1590, 1880 and 2260 nm at 150 viewing angles over a range of +/- 60 from nadir for each contiguous sub-aircraft pixel (~ 300 m in size). A retrieval algorithm is applied to the data acquired with a table look up technique, similar to that of the operational POLDER algorithm, to provide a first guess of the complex refractive index, optical depth and size distribution of the smoke particles together with cloud droplet size and optical depth. A subsequent iterative fitting procedure, where the fact that the doubling/adding method allows the construction of the Green's function for the radiative transfer equation, is used to obtain an efficient and statistically optimal estimate of the aerosol and cloud retrieval parameters. These retrieval parameters are evaluated against in situ observations, when available, and the optical depth and intensive lidar variables that are measured by the High Spectral Resolution Lidar 2. Finally, the aerosol and cloud retrievals are used to evaluate the variations in top of the atmosphere, surface/cloud top shortwave radiative forcing and atmospheric absorption that are caused by variations in the smoke and clouds.

Description: This paper describes the current ground-based calibration results of Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Suomi National Polar orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS), and Sentinel-2A Multispectral Instrument (MSI), using an automated suite of instruments located at Railroad Valley, Nevada, USA. The period of this study is 2012 to 2016 for MODIS, VIIRS, and ETM+, 2013 to 2016 for OLI, and 2015 to 2016 for MSI. The current results show that all sensors agree with the Radiometric Calibration Test Site (RadCaTS) to within +/-5% in the solar-reflective regime, except for one band on VIIRS that is within +/-6%. In the case of ETM+ and OLI, the agreement is within +/-3%, and, in the case of MODIS, the agreement is within +/-3.5%. MSI agrees with RadCaTS to within +/-4.5% in all applicable bands.

Description: We derive water vapor column abundances and aerosol properties from Mars Science Laboratory (MSL) ChemCam passive mode observations of scattered sky light. This paper covers the methodology and initial results for water vapor and also provides preliminary results for aerosols. The data set presented here includes the results of 113 observations spanning from Mars Year 31 L(s) = 291 deg (March 30, 2013) to Mars Year 33 L(s) = 127 deg (March 24, 2016). Each ChemCam passive sky observation acquires spectra at two different elevation angles. We fit these spectra with a discrete-ordinates multiple scattering radiative transfer model, using the correlated-k approximation for gas absorption bands. The retrieval proceeds by first fitting the continuum of the ratio of the two elevation angles to solve for aerosol properties, and then fitting the continuum-removed ratio to solve for gas abundances. The final step of the retrieval makes use of the observed CO 2 absorptions and the known CO 2 abundance to correct the retrieved water vapor abundance for the effects of the vertical distribution of scattering aerosols and to derive an aerosol scale height parameter. Our water vapor results give water vapor column abundance with a precision of +/-0.6 precipitable microns and systematic errors no larger than +/-0.3 precipitable microns, assuming uniform vertical mixing. The ChemCam-retrieved water abundances show, with only a few exceptions, the same seasonal behavior and the same timing of seasonal minima and maxima as the TES, CRISM, and REMS-H data sets that we compare them to. However ChemCam-retrieved water abundances are generally lower than zonal and regional scale from-orbit water vapor data, while at the same time being significantly larger than pre-dawn REMS-H abundances. Pending further analysis of REMS-H volume mixing ratio uncertainties, the differences between ChemCam and REMS-H pre-dawn mixing ratios appear to be much too large to be explained by large scale circulations and thus they tend to support the hypothesis of substantial diurnal interactions of water vapor with the surface. Our preliminary aerosol results, meanwhile, show the expected seasonal pattern in dust particle size but also indicate a surprising interannual increase in water-ice cloud opacities.

Description: Since the 1960s, satellites have been looking down at the Earth to monitor weather patterns and track severe storms, observe how our land surface is changing and responding to hydrometerological extremes, and even to sense how the Earth's crust is deforming from earthquakes and volcanoes. Space and airborne platforms can provide unique views of the disaster lifecycle, informing pre-event mitigation and preparedness, emergency response following an event, and monitoring longer-term recovery. These remotely-sensed data, products and models can provide a global perspective to see beyond administrative boundaries, reach remote places where in situ observations are di cult or non-existent, and provide the necessary context and situational awareness to aid in disaster response. So how do these platforms work? Instruments aboard satellites use different portions of the electromagnetic spectrum to passively or actively observe energy across a range of wavelengths, which can be turned into meaningful data on geophysical, atmospheric, and hydrological variables. e US has had a broad range of Earth observation (EO) platforms delivering open data for scientific research and societal benefits for decades. e Landsat programme, a joint initiative between the US Geological Survey (USGS) and NASA, has the world's longest continuous collection of space-based satellite imagery of the Earth, extending from 1972 to present. e Landsat satellites provide visible, near infrared, and thermal data that are used to support emergency response and disaster relief by mapping changes in water during floods, and dramatic land surface changes, including those resulting from landslides, wild res, severe weather, volcanic plumes, and dust storms.

Description: No abstract available

Description: No abstract available

Description: This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP) observations. Neural network (NN) and physically-based SMAP soil moisture retrievals were assimilated into the National Aeronautics and Space Administration (NASA) Catchment model over the contiguous United States for April 2015 to March 2017. By construction, the NN retrievals are consistent with the global climatology of the Catchment model soil moisture. Assimilating the NN retrievals without further bias correction improved the surface and root zone correlations against in situ measurements from 14 SMAP core validation sites (CVS) by 0.12 and 0.16, respectively, over the model-only skill, and reduced the surface and root zone unbiased root-mean-square error (ubRMSE) by 0.005 m(exp 3) m(exp 3) and 0.001 m(exp 3) m(exp 3), respectively. The assimilation reduced the average absolute surface bias against the CVS measurements by 0.009 m(exp 3) m(exp 3), but increased the root zone bias by 0.014 m(exp 3) m(exp 3). Assimilating the NN retrievals after a localized bias correction yielded slightly lower surface correlation and ubRMSE improvements, but generally the skill differences were small. The assimilation of the physically-based SMAP Level-2 passive soil moisture retrievals using a global bias correction yielded similar skill improvements, as did the direct assimilation of locally bias-corrected SMAP brightness temperatures within the SMAP Level-4 soil moisture algorithm. The results show that global bias correction methods may be able to extract more independent information from SMAP observations compared to local bias correction methods, but without accurate quality control and observation error characterization they are also more vulnerable to adverse effects from retrieval errors related to uncertainties in the retrieval inputs and algorithm. Furthermore, the results show that using global bias correction approaches without a simultaneous re-calibration of the land model processes can lead to skill degradation in other land surface variables.

Description: Disturbances, both natural and anthropogenic, are critical determinants of forest structure, function, and distribution. The vulnerability of forests to potential changes in disturbance rates remains largely unknown. Here, we developed a framework for quantifying and mapping the vulnerability of forests to changes in disturbance rates. By comparing recent estimates of observed forest disturbance rates over a sample of contiguous US forests to modeled rates of disturbance resulting in forest loss, a novel index of vulnerability, Disturbance Distance, was produced. Sample results indicate that 20% of current US forestland could be lost if disturbance rates were to double, with southwestern forests showing highest vulnerability. Under a future climate scenario, the majority of US forests showed capabilities of withstanding higher rates of disturbance then under the current climate scenario, which may buffer some impacts of intensified forest disturbance.

Description: The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) satellite uses its 14 reflective solar bands to passively collect solar radiant energy reflected off the Earth. The Level 1 product is the geolocated and radiometrically calibrated top-of- the-atmosphere solar reflectance. The absolute radiometric uncertainty associated with this product includes contributions from the noise associated with measured detector digital counts and the radiometric calibration bias. Here, we provide a detailed algorithm for calculating the estimated standard deviation of the retrieved top-of-the-atmosphere spectral solar radiation reflectance.

Description: Uncertainties in input land cover estimates contribute to a significant bias in modeled above ground biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

Description: The diurnal variation of tropical ice clouds has been well observed and examined in terms of the occurring frequency and total mass but rarely from the viewpoint of ice microphysical parameters. It accounts for a large portion of uncertainties in evaluating ice cloud's role on global radiation and hydrological budgets. Owing to the advantage of precession orbit design and paired polarized observations at a high-frequency microwave band that is particularly sensitive to ice particle microphysical properties, three years of polarimetric difference (PD) measurements using the 166 GHz channel of Global Precipitation Measurement Microwave Imager (GPM-GMI) are compiled to reveal a strong diurnal cycle over tropical land (30degS-30deg N) with peak amplitude varying up to 38%. Since the PD signal is dominantly determined by ice crystal size, shape, and orientation, the diurnal cycle observed by GMI can be used to infer changes in ice crystal properties. Moreover, PD change is found to lead the diurnal changes of ice cloud occurring frequency and total ice mass by about 2 hours, which strongly implies that understanding ice microphysics is critical to predict, infer, and model ice cloud evolution and precipitation processes.

Description: Active cloud observations from A-Trains CloudSat and CALIPSO satellites offer new opportunities to examine the vertical structure of hydrometeor layers. We use the 2B CLDCLASSLIDAR merged CloudSat-CALIPSO product to examine global aspects of hydrometeor vertical stratification. We group the data into major Cloud Vertical Structure (CVS) classes based on our interpretation of how clouds in three standard atmospheric layers overlap, and provide their global frequency of occurrence. We contrast CVS occurrences between daytime and nighttime, identify ocean and land differences, and examine their seasonal and geographical variations for the dominant CVS classes. In order to evaluate CVS role in the radiation budget, we estimate radiative effects and contributions of the various CVS classes at the solar and thermal infrared part of the spectrum. We also investigate the consistency between passive and active views of clouds by providing the CVS breakdowns of MODIS cloud regimes for spatiotemporally coincident MODIS-Aqua and CloudSat-CALIPSO daytime observations. This analysis is expanded for a more in-depth look at the most heterogeneous of the MODIS regimes, and ultimately confirms previous interpretations of the nature of cloud regimes that did not have the benefit of collocated active observations.

Description: This work presents a state-of-the art methodology for constructing snow water equivalent (SWE) reanalysis. The method is comprised of two main components: (1) a coupled land surface model and snow depletion curve model, which is used to generate an ensemble of predictions of SWE and snow cover area for a given set of (uncertain) inputs, and (2) a reanalysis step, which updates estimation variables to be consistent with the satellite observed depletion of the fractional snow cover time series. This method was applied over the Sierra Nevada (USA) based on the assimilation of remotely sensed fractional snow covered area data from the Landsat 5-8 record (1985-2016). The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlation greater than 0.95 compared with in situ SWE observations. The method (fully Bayesian), resolution (daily, 90-meter), temporal extent (31 years), and accuracy provide a unique dataset for investigating snow processes. This presentation illustrates how the reanalysis dataset was used to provide a basic accounting of the stored snowpack water in the Sierra Nevada over the last 31 years and ultimately improve real-time streamflow predictions.

Description: Agricultural stakeholders need more credible information on which to base adaptation and mitigation policy decisions. In order to provide this, we must improve the rigor of agricultural modelling. Ensemble approaches can be used to address scale issues and integrated teams can overcome disciplinary silos. The AgMIP Coordinated Global and Regional Assessments of Climate Change and Food Security (CGRA) has the goal to link agricultural systems models using common protocols and scenarios to significantly improve understanding of climate effects on crops, livestock and livelihoods across multiple scales. The AgMIP CGRA assessment brings together experts in climate, crop, livestock, economics, and food security to develop Protocols to guide the process throughout the assessment. Scenarios are designed to consistently combine elements of intertwined storylines of future society including, socioeconomic development, greenhouse gas concentrations, and specific pathways of agricultural sector development. Through these approaches, AgMIP partners around the world are providing an evidence base for their stakeholders as they make decisions and investments.

Description: For the purposes of interpreting active (radar) and passive (radiometer) microwave and millimeter wave remote sensing data, we have constructed a consistent radiative transfer modeling framework to simulate the responses for arbitrary sensors with differing sensing geometries and hardware configurations. As part of this work, we have implemented a recent method for calculating the electromagnetic properties of individual ice crystals and snow flakes. These calculations will allow us to exploit polarized remote sensing observations to discriminate different particles types and elucidate dynamics of cloud and precipitating systems.

Description: No abstract available

Description: NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) is a virtual system that provides near real-time EOS data and imagery to meet the needs of scientists and application users interested in monitoring a wide variety of natural and man-made phenomena in near real-time. Over the last year: near real-time data and imagery from MOPITT, MISR, OMPS and VIIRS (Land and Atmosphere), the Fire Information for Resource Management System (FIRMS) has been updated and LANCE has begun the process of integrating the Global NRT flood, and Black Marble products. In addition, following the AMSU-A2 instrument anomaly in September 2016, AIRS-only products have replaced the NRT level 2 AIRS+AMSU products. This presentation provides a brief overview of LANCE, describes the new products that are recently available and contains a preview of what to expect in LANCE over the coming year.

Description: Collect Earth Online (CEO) is a free and open online implementation of the FAO Collect Earth system for collaboratively collecting environmental data through the visual interpretation of Earth observation imagery. The primary collection mechanism in CEO is human interpretation of land surface characteristics in imagery served via Web Map Services (WMS). However, interpreters may not have enough contextual information to classify samples by only viewing the imagery served via WMS, be they high resolution or otherwise. To assist in the interpretation and collection processes in CEO, SERVIR, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries, developed the GeoDash system, an embedded and critical component of CEO. GeoDash leverages Google Earth Engine (GEE) by allowing users to set up custom browser-based widgets that pull from GEE's massive public data catalog. These widgets can be quick looks of other satellite imagery, time series graphs of environmental variables, and statistics panels of the same. Users can customize widgets with any of GEE's image collections, such as the historical Landsat collection with data available since the 1970s, select date ranges, image stretch parameters, graph characteristics, and create custom layouts, all on-the-fly to support plot interpretation in CEO. This presentation focuses on the implementation and potential applications, including the back-end links to GEE and the user interface with custom widget building. GeoDash takes large data volumes and condenses them into meaningful, relevant information for interpreters. While designed initially with national and global forest resource assessments in mind, the system will complement disaster assessments, agriculture management, project monitoring and evaluation, and more.

Description: No abstract available

Description: The biodiversity, ecosystem services and climate variability of the Antarctic continent, and the Southern Ocean are major components of the whole Earth system. Antarctic ecosystems are driven more strongly by the physical environment than many other marine and terrestrial ecosystems. As a consequence, to understand ecological functioning, cross-disciplinary studies are especially important in Antarctic research. The conceptual study presented here is based on a workshop initiated by the Research Programme Antarctic Thresholds - Ecosystem Resilience and Adaption of the Scientific Committee on Antarctic Research, which focused on challenges in identifying and applying cross-disciplinary approaches in the Antarctic. Novel ideas, and first steps in their implementation, were clustered into eight themes, ranging from scale problems, risk maps, organism and ecosystem responses to multiple environmental changes, to evolutionary processes. Scaling models and data across different spatial and temporal scales were identified as an overarching challenge. Approaches to bridge gaps in the research programmes included multi-disciplinary monitoring, linking biomolecular findings and simulated physical environments, as well as integrative ecological modelling. New strategies in academic education are proposed. The results of advanced cross-disciplinary approaches can contribute significantly to our knowledge of ecosystem functioning, the consequences of climate change, and to global assessments that ultimately benefit humankind.

Description: This study seeks to help better understand aerosol-cloud interactions by examining statistical relationships between aerosol properties and nearby low-altitude cloudiness using satellite data. The analysis of a global dataset of MODIS (Moderate Resolution Imaging Spectroradiometer) observations reveals that the positive correlation between cloudiness and aerosol optical depth (AOD) reported in earlier studies is strong throughout the globe and during both winter and summer. Typically, AOD is 30-50 higher on cloudier-than-average days than on less cloudy days. A combination of satellite observations and MERRA-2 global reanalysis data reveals that the correlation between cloud cover and AOD is strong for all aerosol types considered: sulfate, dust, carbon, and sea salt. The observations also indicate that in the presence of nearby clouds, aerosol size distributions tend to shift toward smaller particles over large regions of the Earth. This is consistent with a greater cloud-related increase in the AOD of fine mode than of coarse mode particles. The greater increase in fine mode AOD implies that the cloudiness-AOD correlation does not come predominantly from cloud detection uncertainties. Additionally, the results show that aerosol particle size increases near clouds even in regions where it decreases with increasing cloudiness. This suggests that the decrease with cloudiness comes mainly from changes in large-scale environment, rather than from clouds increasing the number or the size of fine mode aerosols. Finally, combining different aerosol retrieval algorithms demonstrated that quality assessment flags based on local variability can help identifying when the observed aerosol populations are affected by surrounding clouds.

Description: No abstract available

Description: Fires have influenced atmospheric composition and climate since the rise of vascular plants, and satellite data has shown the overall global extent of fires. Our knowledge of historic fire emissions has progressively improved over the past decades due mostly to the development of new proxies and the improvement of fire models. Currently there is a suite of proxies including sedimentary charcoal records, measurements of fire-emitted trace gases and black carbon stored in ice and firn, and visibility observations. These proxies provide opportunities to extrapolate emissions estimates based on satellite data starting in 1997, but each proxy has strengths and weaknesses regarding, for example, the spatial and temporal extents over which they are representative. We developed a new historic biomass burning emissions dataset starting in 1750 that merges the satellite record with several existing proxies, and uses the average of six models from the Fire Model Intercomparison Project (FireMIP) protocol to estimate emissions when the available proxies had limited coverage. According to our approach, global biomass burning emissions were relatively constant with 10-year averages varying between 1.8 and 2.3 petagrams of carbon per year. Carbon emissions increased only slightly over the full time period and peaked during the 1990's after which they decreased gradually. There is substantial uncertainty in these estimates and patterns varied depending on choices regarding data representation, especially on regional scales. The observed pattern in fire carbon emissions is for a large part driven by African fires, which accounted for 58 percent of global fire carbon emissions. African fire emissions declined since about 1950 due to conversion of savanna to cropland, and this decrease is partially compensated for by increasing emissions in deforestation zones of South America and Asia. These global fire emissions estimates are mostly suited for global analyses and will be used in the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations.

Description: The spaceborne AVHRR sensors have provided a data record approaching 40 years, which is a crucial asset for studying the long-term trends of aerosol properties on both a global and regional basis. However, due to the limitations on its channels and information content, aerosol optical depth (AOD) data from AVHRR over land are still largely lacking. In this paper, we describe a new physics-based algorithm to retrieve global aerosol properties over both land and ocean from AVHRR for the first time. The over-land algorithm is an extension of our SeaWiFSMODIS Deep Blue algorithm, while a simplified version of the Satellite Ocean Aerosol Retrieval (SOAR) algorithm is used over ocean. We compare the retrieved AVHRR AOD values with those from MODIS collection 6 aerosol products on a daily and seasonal basis, and find in general good agreement between the two. For the satellites with equatorial crossing times within two hours of solar noon, the spatial coverage of the AVHRR aerosol product is comparable to that of MODIS, except over very bright arid regions (such as the Sahara and deserts in the Arabian Peninsula), where the underlying surface reflectance at 630 nm reaches the critical surface reflectance. Based upon comparisons of the AVHRR AOD against the AERONET data, the preliminary results indicate that the expected error is around +/-(0.03+15%) over ocean and +/-(0.05+25%) over land for this first version of the AVHRR aerosol products. Consequently, these new AVHRR aerosol products can contribute important building blocks for constructing a consistent long-term data record for climate studies.

Description: No abstract available

Description: The Langley mobile ozone lidar (LMOL) is a mobile ground-based ozone lidar system that consists of a pulsed UV laser producing two UV wavelengths of 286 and 291 nm with energy of approximately 0.2 mJ/pulse 0.2 mJ/pulse and repetition rate of 1 kHz. The 527 nm pump laser is also transmitted for aerosol measurements. The receiver consists of a 40 cm parabolic telescope, which is used for both backscattered analog and photon counting. The lidar is very compact and highly mobile. This demonstrates the utility of very small lidar systems eventually leading to space-based ozone lidars. The lidar has been validated by numerous ozonesonde launches and has provided ozone curtain profiles from ground to approximately 4 km in support of air quality field missions.

Description: Accurate characterization of the Earth's radiant energy is critical for many climate monitoring and weather forecasting applications. For example, groups at the NASA Langley Research Center rely on stable visible- and infrared-channel calibrations in order to understand the temporal/spatial distribution of hazardous storms, as determined from an automated overshooting convective top detection algorithm. Therefore, in order to facilitate reliable, climate-quality retrievals, it is important that consistent calibration coefficients across satellite platforms are made available to the remote sensing community, and that calibration anomalies are recognized and mitigated. One such anomaly is the infrared imager brightness temperature (BT) drift that occurs for some Geostationary Earth Orbit satellite (GEOsat) instruments near local midnight. Currently the Global Space-Based Inter-Calibration System (GSICS) community uses the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) sensor as a common reference to uniformly calibrate GEOsat IR imagers. However, the combination of IASI, which has a 21:30 local equator crossing time (LECT), and hyperspectral Atmospheric Infrared Sounder (AIRS; 01:30 LECT) observations are unable to completely resolve the GEOsat midnight BT bias. The precessing orbit of the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS), however, allows sampling of all local hours every 46 days. Thus, VIRS has the capability to quantify the BT midnight effect observed in concurrent GEOsat imagers. First, the VIRS IR measurements are evaluated for long-term temporal stability between 2002 and 2012 by inter-calibrating with Aqua-MODIS. Second, the VIRS IR measurements are assessed for diurnal stability by inter-calibrating with Meteosat-9 (Met-9), a spin-stabilized GEOsat imager that does not manifest any diurnal dependency. In this case, the Met-9 IR imager is first adjusted with the official GSICS calibration coefficients. Then VIRS is used as a diurnal calibration reference transfer to produce hourly corrections of GEOsat IR imager BT. For the 9 three-axis stabilized GEO imagers concurrent with VIRS, the midnight effect increased the BT on average by 0.5 K (11 microns) and 0.4 K (12 microns), with a peak at approx.01:00 local time. As expected, the spin-stabilized GEOsats revealed a smaller diurnal temperature cycle (mostly 〈 0.2 K) with inconsistent peak hours.

Description: No abstract available

Description: EPIC (Earth Polychromatic Imaging Camera) is a 10-channel spectroradiometer onboard DSCOVR (Deep Space Climate Observatory) spacecraft. In addition to the near-infrared (NIR, 780 nm) and the 'red' (680 nm) channels, EPIC also has the O2 A-band (764+/-0.2 nm) and B-band (687.75+/-0.2 nm). The EPIC Normalized Difference Vegetation Index (NDVI) is defined as the difference between NIR and 'red' channels normalized to their sum. However, the use of the O2 B-band instead of the 'red' channel mitigates the effect of atmosphere on remote sensing of surface reflectance because O2 reduces contribution from the radiation scattered by the atmosphere. Applying the radiative transfer theory and the spectral invariant approximation to EPIC observations, the paper provides supportive arguments for using the O2 band instead of the red channel for monitoring vegetation dynamics. Our results suggest that the use of the O2 B-band enhances the sensitivity of the top-of-atmosphere NDVI to the presence of vegetation.

Description: CAR (Cloud Absorption Radiometer) is a multi-angular and multi-spectral airborne radiometer instrument, whose radiometric and geometric characteristics are well calibrated and adjusted before and after each flight campaign. CAR was built by NASA (National Aeronautics and Space Administration) in 1984. On 16 May 2008, a CAR flight campaign took place over the well-known calibration and validation site of Railroad Valley in Nevada (38.504 deg N, 115.692 deg W).The campaign coincided with the overpasses of several key EO (Earth Observation) satellites such as Landsat-7, Envisat and Terra. Thus, there are nearly simultaneous measurements from these satellites and the CAR airborne sensor over the same calibration site. The CAR spectral bands are close to those of most EO satellites. CAR has the ability to cover the whole range of azimuth view angles and a variety of zenith angles depending on altitude and, as a consequence, the biases seen between satellite and CAR measurements due to both unmatched spectral bands and unmatched angles can be significantly reduced. A comparison is presented here between CARs land surface reflectance (BRF or Bidirectional Reflectance Factor) with those derived from Terra/MODIS (MOD09 and MAIAC), Terra/MISR, Envisat/MERIS and Landsat-7. In this study, we utilized CAR data from low altitude flights (approx. 180 m above the surface) in order to minimize the effects of the atmosphere on these measurements and then obtain a valuable ground-truth data set of surface reflectance. Furthermore, this study shows that differences between measurements caused by surface heterogeneity can be tolerated, thanks to the high homogeneity of the study site on the one hand, and on the other hand, to the spatial sampling and the large number of CAR samples. These results demonstrate that satellite BRF measurements over this site are in good agreement with CAR with variable biases across different spectral bands. This is most likely due to residual aerosol effects in the EO derived reflectances.

Description: To better understand the life-essential cycles and processes of our planet and to further develop remote sensing (RS) technology, there is an increasing need for models that simulate the radiative budget (RB) and RS acquisitions of urban and natural landscapes using physical approaches and considering the three-dimensional (3-D) architecture of Earth surfaces. Discrete anisotropic radiative transfer (DART) is one of the most comprehensive physically based 3-D models of Earth-atmosphere radiative transfer, covering the spectral domain from ultraviolet to thermal infrared wavelengths. It simulates the optical 3-DRB and optical signals of proximal, aerial, and satellite imaging spectrometers and laser scanners, for any urban and/or natural landscapes and for any experimental and instrumental configurations. It is freely available for research and teaching activities. In this paper, we briefly introduce DART theory and present recent advances in simulated sensors (LiDAR and cameras with finite field of view) and modeling mechanisms (atmosphere, specular reflectance with polarization and chlorophyll fluorescence). A case study demonstrating a novel application of DART to investigate urban landscapes is also presented.

Description: The Moderate Resolution Imaging Spectroradiometer (MODIS) is currently flying on NASA's Earth Observing System Terra and Aqua satellites, launched in 1999 and 2002, respectively. MODIS reflective solar bands in the visible wavelength range are known to be sensitive to polarized light based on prelaunch polarization sensitivity tests. After about five years of on-orbit operations, it was discovered that the polarization sensitivity at short wavelengths had shown a noticeable increase. In this paper, we examine the impact of polarization on measured top-of-atmosphere (TOA) reflectance based on MODIS Collection-6 L1B over pseudo invariant desert sites. The standard polarization correction equation is used in combination with simulated at-sensor radiances using the second simulation of a satellite signal in the Solar Spectrum, Vector Radiative Transfer Code (6SV). We ignore the polarization contribution from the surface and a ratio approach is used for both 6SV-derived in put parameters and observed TOA reflectance. Results indicate that significant gain corrections up to 25% are required near the end of scan for the 412 and 443 nm bands. The polarization correction reduces the seasonal fluctuations in reflectance trends and mirror side ratios from 30% and 12% to 10% and 5%, respectively, for the two bands. Comparison of the effectiveness of the polarization correction with the results from the NASA Ocean Biology Processing Group shows a good agreement in the corrected reflectance trending results and their seasonal fluctuations.

Description: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) updates NASA's previous satellite era (1980 - onward) reanalysis system to include additional observations and improvements to the Goddard Earth Observing System, Version 5 (GEOS-5) Earth system model. As a major step towards a full Integrated Earth Systems Analysis (IESA), in addition to meteorological observations, MERRA-2 now includes assimilation of aerosol optical depth (AOD) from various ground- and space-based remote sensing platforms. Here, in the first of a pair of studies, we document the MERRA-2 aerosol assimilation, including a description of the prognostic model (GEOS-5 coupled to the GOCART aerosol module), aerosol emissions, and the quality control of ingested observations. We provide initial validation and evaluation of the analyzed AOD fields using independent observations from ground, aircraft, and shipborne instruments. We demonstrate the positive impact of the AOD assimilation on simulated aerosols by comparing MERRA-2 aerosol fields to an identical control simulation that does not include AOD assimilation. Having shown the AOD evaluation, we take a first look at aerosol-climate interactions by examining the shortwave, clear-sky aerosol direct radiative effect. In our companion paper, we evaluate and validate available MERRA-2 aerosol properties not directly impacted by the AOD assimilation (e.g. aerosol vertical distribution and absorption). Importantly, while highlighting the skill of the MERRA-2 aerosol assimilation products, both studies point out caveats that must be considered when using this new reanalysis product for future studies of aerosols and their interactions with weather and climate.

Description: Black carbon (BC) concentrations observed in 22 snowpits sampled in the northwest sector of the Greenland ice sheet in April 2014 have allowed us to identify a strong and widespread BC aerosol deposition event, which was dated to have accumulated in the pits from two snow storms between 27 July and 2 August 2013. This event comprises a significant portion (57 on average across all pits) of total BC deposition over 10 months (July 2013 to April 2014). Here we link this deposition event to forest fires burning in Canada during summer 2013 using modeling and remote sensing tools. Aerosols were detected by both the Cloud-Aerosol Lidar with Orthogonal Polarization (on board CALIPSO) and Moderate Resolution Imaging Spectroradiometer (Aqua) instruments during transport between Canada and Greenland. We use high-resolution regional chemical transport modeling (WRF-Chem) combined with high-resolution fire emissions (FINNv1.5) to study aerosol emissions, transport, and deposition during this event. The model captures the timing of the BC deposition event and shows that fires in Canada were the main source of deposited BC. However, the model underpredicts BC deposition compared to measurements at all sites by a factor of 2100. Underprediction of modeled BC deposition originates from uncertainties in fire emissions and model treatment of wet removal of aerosols. Improvements in model descriptions of precipitation scavenging and emissions from wildfires are needed to correctly predict deposition, which is critical for determining the climate impacts of aerosols that originate from fires.

Description: A coherent bistatic vegetation scattering model, based on a Monte Carlo simulation, is being developed to simulate polarimetric bi-static reflectometry at VHF/UHF-bands (240-270 MHz). The model is aimed to assess the value of geostationary satellite signals of opportunity to enable estimation of the Earth's biomass and root-zone soil moisture. An expression for bistatic scattering from a vegetation canopy is derived for the practical case of a ground-based/low altitude platforms with passive receivers overlooking vegetation. Using analytical wave theory in conjunction with distorted Born approximation (DBA), the transmit and receive antennas effects (i.e., polarization, orientation, height, etc.) are explicitly accounted for. Both the coherency nature of the model (joint phase and amplitude information) and the explicit account of system parameters (antenna, altitude, polarization, etc) enable one to perform various beamforming techniques to evaluate realistic deployment configurations. In this paper, several test scenarios will be presented and the results will be evaluated for feasibility for future biomass and root-zone soil moisture application using geostationary communication satellite signals of opportunity at low frequencies.

Description: Remotely sensing the water status of plant canopies remains a long term goal of remote sensing research. Established approaches involve measurements in the thermal infrared and the 900-2000nm reflective infrared. Less popular UV-visible-NIR techniques presumably deserve research attention, because photochemical changes linked to plant water status manifest spectral light scattering and absorption changes. Here we monitored the visible and NIR light reflected from the leaf interior as well as the leaf transmittance as the relative water content of corn (Zeamays L.) leaves decreased. Our results highlight the importance of both scattering effects and effects due to absorption by leaf pigments.

Description: Radio Frequency Interference (RFI) Mitigation at Goddard Geophysical and Astronomical Observatory (GGAO) has been addressed in three different ways by NASA's Space Geodesy Project (SGP); masks, blockers, and filters. All of these techniques will be employed at the GGAO, to mitigate the RFI consequences to the Very Long Baseline Interferometer.