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NASA NTRS2020

Harnessing Big Data to Support the Conservation and Rehabilitation of Mangrove Forests Globally

Mangrove forests are found on sheltered coastlines in tropical, subtropical, and some warm temperate regions. These forests support unique biodiversity and provide a range of benefits to coastal communities, but as a result of large-scale conversion for aquaculture, agriculture, and urbanization, mangroves are considered increasingly threatened ecosystems. Scientific advances have led to accurate and comprehensive global datasets on mangrove extent, structure, and condition, and these can support evaluation of ecosystem services and stimulate greater conservation and rehabilitation efforts. To increase the utility and uptake of these products, in this Perspective we provide an overview of these recent and forthcoming global datasets and explore the challenges of translating these new analyses into policy action and on-the-ground conservation. We describe a new platform for visualizing and disseminating these datasets to the global science community, non-governmental organizations, government officials, and rehabilitation practitioners and highlight future directions and collaborations to increase the uptake and impact of large-scale mangrove research.

mangrove↗

NASA NTRS2020

Spurious Signal in SMAP Fourth Stokes Parameter

The radiometer on the NASA Soil Moisture Active/Passive (SMAP) mission is a fully polarimetric instrument that operates at L-band in the spectrum window at 1400-1427 MHz protected for passive use only. A unique feature of the radiometer is the fully digital back-end which permits direct computation of the third and fourth Stokes parameters: the real and imaginary part of the correlation of signal at horizontal and vertical polarizations, respectively. In particular, the SMAP conical scanning geometry provides the opportunity to look at the global distribution of the fourth Stokes parameter, TA4, at constant incidence angle (40°). A striking feature of TA4 is the existence of a strong (±10 K) spurious signal at coastlines. This article provides examples of the spikes and an explanation of the cause. Simulations have shown that the spurious signal is associated with antenna imperfections, such as cross polarization coupling and phase mismatch between polarizations.

radiometry↗

NASA NTRS2021

GRACE Fast Mascons from Spherical Harmonics and a Regularization Design Trade Study

Mass concentration (mascon) solutions have become a prominent medium for investigating time-variable gravity recovered by GRACE and GRACE Follow-On. While GRACE Level-2 spherical harmonic products require various post-processing techniques to eliminate correlated noise, mascon formulations employ spatial regularization strategies during the estimation step to improve signal recovery. However, mascon estimation has traditionally required large computing resources and GRACE Level-1B processing capabilities. In this study, we show that a typical mascon estimation system can be reformulated to allow for the estimation of regularized mascons from Level-2 spherical harmonics. Provided that spherical harmonic solution covariances are available, the computed mascons will be mathematically equivalent to similar mascons estimated from Level-1B observations. This method is computationally efficient, better leverages GRACE spherical harmonics than past methods, and matches the performance of typical mascon solutions without locking scientists into pre-determined regularization designs. We develop a proof-of-concept solution using ITSG-Grace2018 and compare results with traditional mascons from JPL and NASA GSFC. We then assess the effects of spherical harmonic truncation and use of regularization correlations on basin signal recovery. We find that spherical expansions to degree and order 60 provide the minimum expansion necessary to study most basins, while larger expansions help further localize signals. We also find that diagonal regularizations (i.e., regularizations that do not contain inter-mascon correlations) are adversely affected by leakage, especially across boundaries such as coastlines where signals are not highly correlated, whereas including inter-mascon correlations and regional boundaries in the regularization greatly improves signal recovery.

M. J. Croteau↗

NASA NTRS2019

Measuring Metapopulation Characteristics of the Southeastern Beach Mouse on Kennedy Space Center using a Dynamic Habitat Occupancy Approach

The Cape Canaveral Barrier Island Complex (CCBIC) represents the largest (72 km) continuous coastal habitat supporting the core population of the threatened southeastern beach mouse (Peromyscus polionotus niveiventris) in Florida. Despite protection throughout the subspecies’ remaining range, storm activity during the past two decades has de-stabilized coastal dune and coastal strand habitat required for beach mouse survival. Our long-term goal is to provide information to the management process to ensure a sustainable population on the CCBIC in light of sea-level rise, extreme storm events, and continued land development supporting the multi-user spaceport.Because beach mice populations are affected by storms (hurricanes, tropical storms, nor’easters), it is important to understand the species-habitat relations during periods with and without storm impacts. Conventional wisdom is that coastal dune and coastal strand are the preferred habitats, but coastal scrub habitat may be important because it is less affected by storm impacts (e.g., overwash, escarpment, sand deposition, etc.) and thus may serve as a refugia. In addition, genetic studies have shown some evidence for reduced dispersal between regions on CCBIC (Kalkvik et al., 2012; Zimmerman et al., 2015). We compared site occupancy dynamics for coastal dune, coastal strand, and coastal scrub habitat over three quarters (seasons) and determined the pattern of spatial correlation in habitat occupancy dynamics for locations at a range of distances in coastal dune, coastal strand, and coastal scrub habitats along the Kennedy Space Center (KSC) coastline (Figures1 and 2). Although habitat occupancy is very useful for understanding species-habitat relationships,in its simplest form it ignores differences in abundance between sites. Because information on abundance may inform management efforts and provide knowledge regarding status of the population, we tested measuring abundance state based on the number of detections in tracking tubes. Small mammal populations often fluctuate in a cyclic manner over time. These fluctuations make populations more susceptible to extinction and make trend detection more difficult. Efficient methods of measuring abundance across time and space are needed for monitoring trends.The purpose of this project was to:1.Estimate southeastern beach mouse habitat occupancy parameters in coastal dune, coastal strand, and coastal scrub habitats using a combination of tracking tubes and traps; 2.Model the spatial relationships of the effect of habitat (coastal dune, coastal strand, and coastal scrub) on parameters as a function of distance; and 3.Compare the reliability and efficiency of our survey methods and evaluate the potential to develop an abundance index.

Eric Douglas Stolen↗

NASA NTRS2021

NASA-NOAA Feasibility Report

The western stock of Steller sea lions and the Aleutian stock of harbor seals both experienced dramatic declines in abundance during the past few decades, particularly in the central and western Aleutian Islands. Both stocks have continued to decline in recent years, thus are a high priority for routine monitoring. NOAA’s Marine Mammal laboratory (MML) has conducted aerial surveys of marine mammals throughout coastal Alaska to monitor trends in population abundance and distribution for more than 20 years. These surveys have typically been conducted from a twinengine aircraft, such as a DHC-6 Twin Otter, operated by NOAA pilots and crewmembers. Aerial surveys in the Aleutian Islands present significant challenges and higher risks due to their remoteness, rugged terrain, and extreme weather. To evaluate the feasibility of transitioning from manned to unmanned aerial surveys in this region, thereby reducing risks to NOAA personnel and high-value aircraft, we propose to conduct test survey flights in the Near Islands of Alaska using a medium-sized, fixed-wing UAV (NASA’s SIERRA-B aircraft) with a nadir-aimed imaging payload. Survey flights are planned to be conducted during daylight hours on days with VFR conditions and less than ~20 knot winds at altitudes of 800-1200 feet. Survey imagery, including thermal video and high-resolution color photos, would be collected at known Steller sea lion and harbor seal sites along the coastlines of Shemya, Nizki, Alaid, Agattu, and Attu Islands. The planning team will request approval and support from the US Air Force to conduct this project at Eareckson Air Station (Shemya Island, AK) during the month of September 2022 when weather conditions in the western Aleutian Islands are expected to be optimal.

NOAA↗

NASA NTRSDate not supplied

Regional Variations in the Diurnal Cycle of Tropical Precipitation as Represented by IMERG, ERA5, and Spaceborne Ku Radar

The diurnal cycle of precipitation is highly regional and is typically a product of multiple competing effects that can be highly localized. The diurnal cycle in high precipitation regions such as the Amazon and the Maritime Continent are of particular interest, especially due to the complex coastal effects which take place over the Maritime Continent. The high spatial and temporal resolution provided by the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) dataset, is used in this study to examine the fine-scale features of the diurnal cycle in these regions. Using an 18-year (2000 – 2018) record of IMERG precipitation observations, diurnal and semidiurnal phase and amplitude are calculated using a fast Fourier transform (FFT) method on precipitation averaged for each half-hour of the day at 0.1°x0.1° spatial resolution. We first introduce an objective method of identifying locations where the diurnal signals are robust and strong. Clear patterns of precipitation phase propagation with distance from shore are shown over both regions, with the diurnal phase and amplitude exhibiting a strong dependence on the distance from the coastline. Semidiurnal cycles are generally weaker than the diurnal cycle except in some isolated locations. Similar analysis is also conducted on the ERA5 reanalysis data in order to evaluate the model’s representation of the precipitation diurnal cycle. The model captures the broad scale patterns of diurnal variability but does not capture all the fine scale patterns nor the exact timing that is observed by IMERG. Comparisons are also made to a long record Ku radar dataset created by combining Tropical Rainfall Measuring Mission (TRMM) and GPM observations, thus providing an additional point of comparison for the timing of the ERA5 precipitation peak, since the timing precipitation can be different, even in between observational datasets.

L J Hayden↗

NASA NTRS2021

Increases in Future AR Count and Size: Overview of 2 the ARTMIP Tier 2 CMIP5/6 Experiment

The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi-model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA-2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design. Plain Language Summary: Atmospheric rivers (ARs) are a type of weather pattern known to be important for moving water vapor from the warm, moist tropics to the cool, dry polar regions; when they reach midlatitudes in the winter time, they are commonly associated with heavy precipitation. Recent studies that assess the impacts of global climate change on ARs tend to agree that there will be more ARs in a warmer climate, and that ARs will tend to be more extreme. However, it has been increasingly recognized by the AR research community that these results may depend on the method used to identify ARs and the choice of climate model. This study reports results from a controlled experiment, involving an international research community, that aims to show how different AR identification methods and climate models might impact our scientific understanding of ARs in the future. This experiment shows that there will likely be more ARs in the future, and that ARs will generally have a larger spatial footprint. This experiment also shows that uncertainty in these results are large, with the uncertainty from AR identification methods outweighing that of climate models. Future efforts to better understand the physics of ARs may help us reduce this uncertainty.

T A OBrien↗

NASA NTRS2022

An Overview of ARTMIP’s Tier 2 Reanalysis Intercomparison: Uncertainty in the Detection of Atmospheric Rivers and their Associated Precipitation

Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags--binary fields indicating the presence or absence of atmospheric rivers--of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six-hourly tags in the Japanese 55-year Reanalysis (JRA-55). Due to a higher climatological mean for integrated water vapor transport in MERRA-2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. The fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.

ARTMIP↗

NASA NTRS2022

Evaluating Uncertainty and Modes of Variability for Antarctic Atmospheric Rivers

Antarctic atmospheric rivers (ARs) are driven by their synoptic environments and lead to profound and varying impacts along the coastlines and over the continent. The definition and detection of ARs over Antarctica accounts for large uncertainty in AR metrics, and consequently, impacts quantification. We find that Antarctic-specific detection tools consistently capture the AR footprint inland over ice sheets, whereas most global detection tools do not. Large-scale synoptic environments and associated ARs, however, are broadly consistent across detection tools. Using data from the Atmospheric River Tracking Method Intercomparison Project and global reanalyses, we quantify the uncertainty in Antarctic AR metrics and evaluate large-scale environments in the context of decadal and interannual modes of variability. The Antarctic western hemisphere has stronger connections to both decadal and interannual modes of variability compared to East Antarctica, and the Indian Ocean Dipole’s influence on Antarctic ARs is stronger while in phase with El Nino Southern Oscillation.

Antarctic↗

NASA NTRSDate not supplied

Florida Water Resources: Assessing Coastal Resiliency Across Florida's Aquatic Preserves Response To Hurricane Forces

Intensifying weather events, sea level rise, and extensive coastal development in Southwestern Florida are escalating the need for Florida’s mangrove conservation. These mangroves are imperative for coastline stabilization, habitat provision for native species, and water quality management. Our partner, the Florida Department of Environmental Protection (FDEP), Office of Resilience and Coastal Protection is tasked with monitoring and conserving the Charlotte Harbor, Estero Bay, Rookery Bay, and Pinellas County Aquatic Preserves. We developed the Growth, Resilience, and Optical Vegetation Evaluator (GROVE) Google Earth Engine toolset for partners to determine mangrove forest extent through time, analyze mangrove forest health, and collect several water quality parameters within the preserves from January 2002–August 2022. The toolset provides easily accessible data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager 2 (OLI-2), and the Shuttle Radar Topography Mission (SRTM). Using training datasets of known mangrove forest locations, we also established a machine learning approach to create mangrove extent maps. Maps from all four preserves indicated migration of mangrove forests inland as the greatest areas of change were transitional zones. Additionally, normalized difference vegetation index (NDVI), normalized difference turbidity index (NDTI), and chlorophyll-a maps were generated for the partners. This project provides decision makers with a useful tool for understanding temporal changes in Florida’s aquatic preserves, identifying areas of ecological stress, and providing actionable data to make informed plans for mangrove preservation.

Samuel Perrello↗

NASA NTRS2022

Florida Water Resources: Assessing Coastal Resiliency Across Florida's Aquatic Preserves in Response to Hurricane Forces

Remote sensing↗

NASA NTRSDate not supplied

VISUALIZING INTERANNUAL TO DECADAL COASTAL VARIABILITY NEAR VULNERABLE NASA INFRASTRUCTURE UTILIZING VIDEOS PRODUCED FROM REMOTELY SENSED DATA AT CAPE CANAVERAL, FL AND WALLOPS ISLAND, VA

Coastlines represent an interesting convolution of intense anthropogenic development superimposed onto morphologies that are among the most dynamic on the planet. Two of NASA’s critical facilities are particularly vulnerable to coastal change, Kennedy Space Center, Cape Canaveral, FL and Wallops Flight Facility, Wallops Island, VA. With continuing global sea level rise and increasing storminess coastal vulnerabilities at these facilities will only be exacerbated. These launch centers a subject to multiple coastal hazards including, flooding, episodic coastal erosion, saltwater intrusion, and coastal morphological changes. Although rapid change is readily observed during large storms or hurricanes, long term annual to decadal coastal change is much harder to visualize and conceptualize. The authors use videos developed from remotely sensed data to enhance conceptualization of coastal processes for planning and management stakeholders at these NASA facilities. Near or better than decadal coastal imagery has been available through high altitude photogrammetry efforts since the 1930’s. A significant amount of additional imagery was acquired through other federal, state, and local government agencies such as the USGS, NOAA, State DOT, and local Assessors Offices providing annual and inter annual images at spatial resolutions of 10cm – 1m. With the advent of GIS systems these images could be rectified and then layered to better understand change through time using a multitude of visual base shoreline proxies. With the increased awareness and use of video editing software the rectified images can be used to create videos. These videos can then be used to conceptualize a multitude of coastal processes including: performance of coastal restoration efforts, rapid change in sedimentation rates due to storms or other geomorphic processes, loss of protective barrier islands as sea level rises and lower sedimentation rates occur. The videos are also useful as a tool for verification and comparison to coastal models and provide an easy to understand educational resource for stakeholder engagement at these NASA centers, and other vulnerable coastal populations.

Richard A. MacKenzie III↗

NASA NTRS2023

Electrification Within Wintertime Stratiform Regions Sampled During the 2020/2022 NASA IMPACTS Field Campaign

Two nor'easter events—sampled during the NASA Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign—were examined to characterize the microphysics in relation to the underlying electrification processes within wintertime stratiform regions. A theoretical model was developed to determine whether accretion or diffusion growth regimes were preferential during periods of greatest electrification. Model simulation with electrification parameterization was used to provide supplemental context to the physical processes of in-cloud microphysics and electrification. The strongest electric fields (i.e., ∼80 V m −1 at 20 km) during the 2020 NASA IMPACTS deployment was associated with large non-rimed ice crystals colliding with each other. During the 29–30 January 2022 science flight, the NASA P-3 microphysical probe data demonstrated that non-inductive charging was possible off the coastline of Cape Cod, Massachusetts. Later in the science flight, when the NASA P-3 and ER-2 were coordinating with each other, measured electric fields consistently were less than 8 V m −1 and electrification was subdued owing to reduced concentrations of graupel and large ice hydrometeors. Altogether, the in-situ observations provide evidence for the non-riming collisional charging mechanism and demonstrates that graupel and supercooled liquid water may not be necessary for weak electrification within wintertime stratiform regions. Model output from simulation of both events suggested that the main synoptic snowbands were associated with elevated hydrometeor snow charge density and electric fields.

snowfall↗

NASA NTRS2023

Maldives Climate II: Evaluating the Potential Impacts of Sea Level Rise on Human Development and Coastal Infrastructure

The Republic of the Maldives is a low-lying island nation in the Indian Ocean which has experienced rapid urbanization, landcover changes, and sea level rise over recent years. The growth of tourism, coastal erosion, and urbanization have all driven land reclamation efforts across many islands. As in-situ landcover change monitoring has proven difficult across the vast archipelago, the NASA DEVELOP team collaborated with the Maldives Ministry of Environment, Climate Change, and Technology; USAID; and the U.S. Department of State, to utilize Earth observations to predict sea level rise impacts on coastal infrastructure. The team used a supervised classification algorithm within Google Earth Engine to create land use maps and time series analyses of nine islands and atolls using imagery from Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, Sentinel-2 Multispectral Instrument, and PlanetScope, covering a combined period of 2000 through 2023. Additionally, the team projected coastal inundation with a modified deterministic Bathtub model utilizing elevation data from CoastalDEM and 2050-2100 Shared Socioeconomic Pathway scenarios identified in the NASA Sea Level Rise Projection Tool. The team found that islands undergoing urban growth experienced a 23% decrease in vegetation between 2014 and 2022. Furthermore, the model predicted that 51–57% of the study area’s-built environment has a chance of inundation by 2100 under the low and high sea level scenarios. These analyses demonstrate how remote sensing can be used to both track land use changes over time and project how coastlines will be affected by sea level rise.

remote sensing↗

NASA NTRS2023

Spatial and Temporal Characterization of Cyanobacteria Blooms in the Mississippi Sound and Their Relationship to the Bonnet Carré Spillway Openings

During the spring and summer of 2019, an unprecedented cyanobacterial harmful algal bloom (cyanoHAB) was responsible for beach advisories on 25 beaches along the Mississippi Sound for over 3 months. Due to the preceding heavy rainfall and flooding within the Mississippi River watershed, for the first time in history, the Bonnet Carré Spillway (BCS) opened twice in one year during 2019. The coastal cyanoHAB coincided with the second BCS opening. The main objectives of this study were: (1) to investigate the potential for using the National Aeronautics and Space Administration (NASA) ocean color standard Cyanobacteria Index (CIcyano) algorithm to characterize the spatial and temporal extent of the 2019 cyanoHAB; (2) to couple the CIcyano data with river discharge, salinity, and modeled-wind data to study the conditions leading to the cyanoHAB and factors aiding the advection and persistence of the bloom within the Mississippi Sound, including a possible relationship to the BCS; (3) to further investigate the relationship with the BCS by repeating the methods using data from 2018, which was a year when the BCS was opened but no evidence of cyanoHABs was reported along the Mississippi coast. Weekly means and monthly frequency CIcyano images, river discharge, salinity, and modeled-wind data from February to September of 2018 and 2019 were analyzed, which coincide with three BCS openings. In March 2018, a cyanobacteria bloom was observed within Lake Pontchartrain coinciding with the BCS opening; however, the month-long bloom was contained to the lake. Two distinct cyanoHABs were observed in 2019 and both blooms were advected into the Mississippi Sound, and likely contributed to the 3-month-long beach water advisories of 2019 along the Mississippi coastline. From March to mid-July 2019, salinity at stations within the Mississippi Sound was consistently near zero indicating high levels of freshwater. During that time, winds were predominantly northwestward, preventing the BCS waters from flushing into the Mississippi Shelf and resulting in BCS waters remaining longer within the estuarine lakes and Mississippi Sound. Although the BCS had an undeniable impact on the presence of the coastal cyanoHAB of 2019, other variables including wind direction, water flow, mixing, and persistence of freshwater within the Sound can determine the intensity and extent of the cyanoHABs. Coupling in situ phytoplankton information from freshwater water bodies to the marine continuum along with water flow, wind data, and satellite imagery could help identify cyanoHABs at early stages and forecast their trajectory and potential impacts on coastal areas.

Bonnet Carré Spillway↗

NASA NTRS2023

Invasion in the Niger Delta: Remote Sensing of Mangrove Conversion to Invasive Nypa fruticans from 2015-2020

Invasive species are a leading threat to biodiversity worldwide. Nypa palm ( Nypa fruticans ) has emerged as the predominant invasive species in the Niger Delta region of Nigeria. While endemic mangroves have high rates of carbon sequestration, stabilize coastlines, and protect biodiversity, Nypa does not provide these services outside its native region of Southeast Asia. Oil exploration and urbanization in this region also exacerbates mangrove loss and Nypa spread. As Nypa is difficult to distinguish from endemic mangrove species in remotely sensed data, estimates of mangrove and ecosystem services losses in Nigeria are highly uncertain. Here, we analyze multisensor satellite data with machine learning to quantify the rapid expansion of Nypa from 2015-2020 in Nigeria. Using Landsat imagery and random forest classification, we quantify total potential Nypa extent in Nigeria in 2019. We then produced a Nypa extent map using iterative combinations of Sentinel-1 SAR, Sentinel-2 MSI, and ALOS PALSAR. Random forest classifications using SAR data from ALOS and Sentinel-1 were best suited for mapping Nypa extent with similar accuracies (78% and 75% respectively). Based on data availability and accuracy, we focused our change analysis on Sentinel-1 SAR. Our results show ~28,000 ha of mangroves were converted to Nypa in Nigeria by 2020 and covered a larger extent than endemic mangroves, compounding the effect of the existing degradation and deforestation in the region. We also compared forest height and complexity estimates from GEDI (Global Ecosystem Dynamics Investigation) LiDAR to further distinguish between endemic mangroves and Nypa in three dimensions. Nypa structural variability, measured by top-of-canopy height, vegetation cover, plant area index, and foliage height diversity, was lower than that of mangroves. At current rates of Nypa expansion, the entire area of study would be invaded by Nypa by 2028, with potentially detrimental consequences to the ecosystem services provided by mangroves.

GEE↗

NASA NTRSDate not supplied

On-Orbit Performance of the NOAA-21 Advanced Technology Microwave Sounder (ATMS)

The Advanced Technology Microwave Sounder (ATMS) instrument provides sounding measurements of Earth’s atmosphere to collect temperature and water vapor data for NOAA’s Joint Polar Satellite System (JPSS) program. ATMS is a total-power passive microwave radiometer with 22 channels spanning a frequency range from 22 to 183 GHz. A general description of the ATMS instrument is detailed in [1]. Three ATMS units are currently on-orbit. The Suomi National Polar-orbiting Partnership (SNPP) unit was launched in 2011 and the NOAA-20 (previously JPSS-1) unit was launch in 2017. Both SNPP and NOAA-20 ATMS units are currently operational and the data is used for numerical weather prediction (NWP) models. The NOAA-21 (formerly JPSS-2) ATMS unit was launched on November 10, 2022 from Vandenberg Space Force Base in California [2]. The ATMS instrument began generating radiance data on November 21, 2022. At the time of this abstract NOAA-21 ATMS is currently completing on-orbit commissioning and checkout activities; it is expected that the commissioning activities will be complete by the IGARSS 2023 conference. This paper will focus on the on-orbit performance of the NOAA-21 ATMS instrument based on measurements and activities from the commissioning period. Comparisons will be made to specifications and to expected performance based on pre-launch test activities. Pre-launch JPSS-2 (NOAA-21) ATMS performance is detailed in [4]. Additionally, the NOAA-21 performance will be compared to the on-orbit performance of the SNPP and NOAA-21 ATMS units. The post-launch performance of SNPP ATMS is detailed in [1][5][6][7]. The post-launch performance of NOAA-20 ATMS is detailed in [5][7][8]. On-orbit performance is evaluated through data collects from nominal mission operations as well as specific post-launch tests and spacecraft maneuvers. Nominal mission operations can be used to evaluate parameters such as instrument thermal stability, Noise Equivalent Delta Temperature (NEDT)/radiometric sensitivity, geolocation, inter-channel noise correlation, striping, and radiometric bias and stability. Shortly after instrument activation, the instrument thermal stability as measured from onboard temperature sensors is evaluated to demonstrate stable and steady-state behavior. Methods for computing NEDT are described in [9][10][11]. Passive geolocation measurements are performed using the coastline inflection point (CIP) method, described in [8][12]. The striping index, used as a metric to quantify striping, is the ratio of along-track variance to cross-track variance of the observed brightness temperature [4][8][14]. Inter-channel noise correlation has been previously reported for SNPP and NOAA-20 [1][8]. Dedicated post-launch tests and spacecraft maneuvers are utilized during the commissioning phase for further evaluation of on-orbit instrument performance. These activities provide information on the optimal space view selection, noise power spectral density (PSD), gain stability, scan bias, interference from onboard transmitters, reflector emissivity, active geolocation, and radiometric bias and stability detection methods. The optimal space view selection is used to determine which of ATMS space view sectors is preferred for minimizing contamination of the space view [1]. Point and stare testing is used to generate noise PSD and gain stability information, as described in [1][8]. Spacecraft roll and pitch maneuvers allow the ATMS to view different zones, including deep space, and the data can be used to provide information on scan biases and antenna sidelobe contamination [1][8]. The pitch maneuver can also be used to assess interference from onboard Ka-band transmitters and reflector emissivity [8]. Active geolocation is evaluated as a method for geolocation, described in [15].

Edward Kim↗

NASA NTRSDate not supplied

Creating Regional and Seasonal Climatologies of Marine and Dusty Marine Aerosol Lidar Ratios using MODIS AOD Constrained Retrievals and GOCART Model Simulations

The CALIPSO aerosol algorithms currently assign one lidar ratio (LR) value globally for each of the seven tropospheric aerosol types. In this study, MODIS total column aerosol optical depths (AODs) are used to constrain collocated CALIOP backscatter profiles in a Fernald inversion that infers aerosol LRs for CALIOP-classified marine and dusty marine aerosols. The GOCART aerosol model is leveraged to estimate the sea salt volume fractions (SSVFs) that are collocated with the CALIOP+MODIS LR retrievals. An inverse empirical relationship is found between the SSVFs and LRs (i.e., smaller SSVFs and larger LRs near coastlines, but the opposite in the remote oceans). This SSVF/LR relationship is applied to create regional and seasonal hybrid (i.e., retrieval & model-assisted) climatological LR maps so as to develop more robust LR selections for marine and dusty marine aerosols in the CALIPSO algorithms. These analyses also provide critical LR information for the next generation of spaceborne elastic backscatter lidars.

Travis D. Toth↗