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Validation of lidar and satellite remote sensing

Validation of observations is an important part of any remote sensing program. With respect to aerosols this is exceedingly difficult because each technique typically measures a different aerosol parameter. Correlative sensors, therefore, must be capable of measuring the same parameter over the same size range or include enough measurements to properly characterize the aerosol, possibly with the assistance of models. In any correlative measurement program, simultaneity in space and time is required. This can be less restrictive during periods of atmospheric stability. The discussion is presented which is focused on the validation programs developed for NASA's Stratospheric Aerosol Measurement (SAM II), and the Stratospheric Aerosol and Gas Experiments I and II (SAGE I and II). To date these were limited to the stratosphere. Since satellite sensors are capable of providing near-global and long-term observations, periodic correlative observations over various global locations and seasons are required for assuring that data quality is unchanged, or for understanding any changes observed.

Mccormick, M. P.↗

SEDS1 mission software verification using a signal simulator

The first flight of the Small Expendable Deployer System (SEDS1) is scheduled as the secondary payload of a Delta II in late 1992. The objective of the SEDS1 mission is to collect data to validate the concept of tethered satellite systems and to verify computer simulations used to predict their behavior. A series of tests will be performed to exercise the software modules which make up the Mission Software of the SEDS Data System. These tests will be performed by using a SEDS Signal Simulator to generate signals which will simulate the inputs normally produced by sensors and circuits in the SEDS system. The SEDS Signal Simulator will be used in the debugging and in the formal verification of the SEDS1 Mission Software. The Simulator will not only emulate normal flight conditions but also exercise all modules written to handle anticipated anomalous flight conditions, conditions that would be difficult to reproduce and control with actual SEDS hardware. The simulator will help to expedite software development and to increase the confidence of the users of the Mission Software. With little modification, the Simulator should be useful in the software development of future SEDS flights.

Pierson, William E.↗

Neural Network-Based Sensor Validation for Turboshaft Engines

Sensor failure detection, isolation, and accommodation using a neural network approach is described. An auto-associative neural network is configured to perform dimensionality reduction on the sensor measurement vector and provide estimated sensor values. The sensor validation scheme is applied in a simulation of the T700 turboshaft engine in closed loop operation. Performance is evaluated based on the ability to detect faults correctly and maintain stable and responsive engine operation. The set of sensor outputs used for engine control forms the network input vector. Analytical redundancy is verified by training networks of successively smaller bottleneck layer sizes. Training data generation and strategy are discussed. The engine maintained stable behavior in the presence of sensor hard failures. With proper selection of fault determination thresholds, stability was maintained in the presence of sensor soft failures.

Moller, James C.↗

Satellite-Derived Dynamics of Southern Ocean Sea Ice

Antarctic ERS-2, RADARSAT Synthetic Aperture Radar and ERS-1/2 Scatterometer images were analyzed with SMMI radiometer image time-series data to investigate seasonal variability in satellite-tracked sea-ice dynamics in the Southern Ocean during 1992. Supporting field data were acquired during 'in-situ' experiments including the winter 1992 Ice Station Weddell and Winter Weddell Gyre studies. A variety of surface measurements were made during these experiments including Argos-buoy deployment and GPS drift measurements. These are used in conjunction with International Program for Antarctic Buoys drift trajectories for ice-motion tracking validation. Comparisons between gridded Special Sensor Microwave Imager (SSMI) ice-motion vectors and European Center for Medium Range Weather Forecasts/National Centers for Environmental Prediction (ECMWF/NCEP) analyses indicate that large-scale drift is forced predominantly by the long-term mean, large-scale synoptic pressure field. Only sub-daily SAR sea-ice tracking can capture high-frequency fluctuations, driven by polar lows or tidal forcing. In these cases, sea-ice drift can respond rapidly to changes in forcing on semi-diurnal time scales depending on the location with respect to the coastline. Seasonality of ice drift, particularly in the Weddell and Ross Seas, is linked to ice extent and compactness, and internal ice stresses transmitted through the pack ice from the coast. Three-monthly seasonal climatologies are presented of austral winter of ice drift in the Southern Ocean. The large Weddell and Ross Sea gyres are clearly resolved along with key seasonal and spatial attributes of their cyclonic circulation. Regional time series of ice dynamics parameters are used to illustrate correlations with meteorological forcing. Persistent divergence such as that occurring in the Ronne-Filchner polynya system results in large fractions of new ice. Similarly, convergence zones produce large fractions of deformed ice and characterize the dynamics of regions where perennial ice is observed. High shear strains also help delineate the axis of the Antarctic divergence in many places in the ice cover. In these regions, the separation between the coastal 'east wind drift'and ACC-dominated drift regimes is characterized by zonally extended regions of intense shear.

Drinkwater, Mark R.↗

TRMM Science Highlights and Status of Precipitation Estimates on Monthly and Finder Time Scales

The Tropical Rainfall Measuring Mission (TRMM) has completed three years in orbit. A summary of research highlights will be presented focusing on application of TRMM data to topics ranging from climate analysis, through improving forecasts, to microphysical research. Monthly surface rainfall estimates over the ocean based on different instruments on TRMM currently differ by 20%. The difference is not surprising considering the different type of observations available for the first time from TRMM with both the passive and active microwave sensors. Resolving this difference will strengthen the validity and utility of ocean rainfall estimates and is the topic of ongoing research utilizing various facets of the TRMM validation and field experiment programs. The TRMM rainfall estimates are intercompared among themselves and with other estimates, including those of the standard, monthly Global Precipitation Climatology Project (GPCP) analysis. The GPCP analysis agrees roughly in magnitude with the passive microwave-based TRMM estimates which is not surprising considering GPCP over-ocean estimates are based on passive microwave observations. A three year TRMM rainfall climatology is presented based on the TRMM merged product, including anomaly fields related to the changing ENSO situation during the mission. Results of merging TRMM, other passive microwave observations, and geosynchronous infrared rainfall estimates into a global, tropical 3-hour time resolution analysis will also be described.

Adler, Robert↗

TRMM: Science Highlights and Status of Precipitation Estimates on Monthly and Finer Time Scales

The Tropical Rainfall Measuring Mission (TRMM) has completed three years in orbit. A summary of research highlights will be presented focusing on application of TRMM data to topics ranging from climate analysis, through improving forecasts, to microphysical research. Monthly surface rainfall estimates Over the ocean based on different instruments on TRMM currently differ by 20%. The difference is not surprising considering the different type of observations available for the first time from TRMM with both the passive and active microwave sensors. Resolving this difference will strengthen the validity and utility of ocean rainfall estimates and is the topic of ongoing research utilizing various facets of the TRMM validation and field experiment programs. The TRMM rainfall estimates are intercompared among themselves and with other estimates, including those of the standard, monthly Global Precipitation Climatology Project (GPCP) analysis. The GPCP analysis agrees roughly in magnitude with the passive microwave-based TRMM estimates which is not surprising considering GPCP over-ocean estimates are based on passive microwave observations. A three-year TRMM rainfall climatology is presented based on the TRMM merged product, including anomaly fields related to the changing ENSO situation during the mission. Results of merging TRMM, other passive microwave observations, and geosynchronous infrared rainfall estimates into a global, tropical 3-hour time resolution analysis will also be described.

Adler, Robert↗

Performance of Landsat-8 and Sentinel-2 Surface Reflectance Products for River Remote Sensing Retrievals of Chlorophyll-A and Turbidity

Rivers and other freshwater systems play a crucial role in ecosystems, industry, transportation and agriculture. Despite the more than 40 years of inland water observations made possible by optical remote sensing, a standardized reflectance product for inland waters is yet forthcoming. The aim of this work is to compare the standard USGS land surface reflectance product to two Landsat-8 and Sentinel-2 aquatic remote sensing reflectance products over the Amazon, Columbia and Mississippi rivers. Landsat-8 reflectance products from all three routines are then evaluated for their comparative performance in retrieving chlorophyll-a and turbidity in reference to shipborne, underway in situ validation measurements. The land surface product shows the best agreement (4 percent Mean Absolute Percent Difference) with field measurements of radiometry collected on the Amazon River and generates 36 percent higher reflectance values in the visible bands compared to aquatic methods (ACOLITE (Atmospheric Correction for OLI (Operational Land Imager) 'lite') and SeaDAS (Sea-viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System)) with larger differences between land and aquatic products observed in Sentinel-2 (0.01 per steraradian) compared to Landsat-8 (0.001 per steraradian). Choice of atmospheric correction routine can bias Landsat-8 retrievals of chlorophyll-a and turbidity by as much as 59 percent and 35 percent respectively. Using a more restrictive time window for matching in situ and satellite imagery can reduce differences by 5–31 percent depending on correction technique. This work highlights the challenges of satellite retrievals over rivers and underscores the need for future optical and biogeochemical research aimed at improving our understanding of the absorbing and scattering properties of river water and their relationships to remote sensing reflectance.

Landsat-8↗

Generation of Merged Radar-Lidar Data Products during the IMPACTS 2020 Field Campaign

A novel, composite lidar and radar data products was created using lidar and radar data products generated from the NASA ER-2 aircraft during the NASA IMPACTS 2020 field campaign. This product is intended to supplement the raw data sources, tease out additional aspects of the mechanisms underpinning wintertime cyclones, and enhance our understanding of microphysical properties in sensor overlap regions. Initial combined products focused on generating normalized fields of ER-2 based radar and lidar data to provide a more comprehensive visualization of storm structure (precipitation bands, cloud tops, melting levels, etc.) Ongoing work has focused on developing a combined radar-lidar reflectivity product and deriving hydrometeor particle properties (type, orientation, etc.) using ER-2-based depolarization data. To validate these hydrometeor properties, we leverage coincident overpasses of the high-altitude ER-2 aircraft with the suite of cloud particle probes on the in-situ P-3 aircraft during coincident flight overpasses. This work aims to provide vital information to help IMPACTS achieve its mission goal of improving microphysical properties retrievals from airborne and spaceborne platforms for these high-impact winter storm events.

Stephen D Nicholls↗

An Evaluation of the Liquid Cloud Droplet Effective Radius Derived from MODIS, Airborne Remote Sensing, and in Situ Measurements from CAMP2Ex

The cloud drop effective radius (Re) of the drop size distribution derived from passive satellite sensors is a key variable used in climate research. Validation of these satellite products has often taken place under stratiform cloud conditions that favor the assumption of cloud horizontal homogeneity used by the retrieval techniques. However, many studies have noted concerns with respect to significant biases in retrieved Re arising from cloud heterogeneity, for example, in cumulus cloud fields. Here, we examine data collected during the 2019 “Cloud, Aerosol and Monsoon Processes Philippines Experiment” (CAMP2Ex), which, in part, targeted the objective of providing the first detailed evaluation of Re retrieved across multiple platforms and techniques in a cumulus and congestus cloud region. Our evaluation consists of cross-comparisons of Re between the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, the Research Scanning Polarimeter (RSP) onboard the NASA P-3 aircraft, and in situ measurements from both the NASA P-3 and Learjet aircraft that are all taken in close spatiotemporal proximity to the same cloud fields. A particular advantage of our approach lies in the capability of the RSP to retrieve Re using a bi-spectral MODIS approach and a polarimetric approach, which allows for the evaluation of bi-spectral and polarimetric Re retrievals from an airborne perspective using the same samples. Averaged over all P-3 flight segments examined here for warm clouds, the RSP polarimetric method, the in situ method, and the bias-adjusted MODIS method of Fu et al. (2019) show a comparable median (mean ± standard deviation) for the Re samples of 9.6 (10.2 ± 4.0) µm, 11.0 (13.6 ± 11.3) µm, and 10.4 (10.8 ± 3.8) µm, respectively. These values are far lower than the values of 15.1 (16.2 ± 5.5) µm and 17.2 (17.7 ± 5.7) µm from the bi-spectral retrievals of RSP and MODIS, respectively. Similar results are observed when Re is segregated by cloud-top height and in detailed case studies. The clouds sampled during CAMP2Ex consist of mostly small (mean transect length ∼ 1.4 km) and low clouds (mean cloud-top height ∼ 1 km), which had more numerous small clouds than the trade wind cumuli sampled in past field campaigns such as Rain in Shallow Cumulus over the Ocean (RICO) and the Indian Ocean Experiment (INDOEX). The overestimates of Re from the RSP bi-spectral technique compared with the polarimetric technique increased as cloud size and cloud optical depth decreased. Drizzle, cloud-top bumpiness, and solar zenith angle, however, are not closely correlated with the overestimate of bi-spectral Re. For shallow clouds that dominated the liquid cloud cover for the CAMP2Ex region and period, we show that 3-D radiative transfer and cloud heterogeneity, particularly for the optically thin and small clouds, appear to be the leading cause of the large positive biases in bi-spectral retrievals. Because this bias varies with the underlying structure of the cloud field, caution continues to be warranted in studies that use bi-spectral Re retrievals in cumulus cloud fields.

Cloud microphysics↗

Mapping National Forest Aboveground Biomass in Mexico by Integrating GEDI, Sentinel‐1 and Sentinel‐2 Data

Accurate mapping of forest aboveground biomass density (AGBD) is required to better understand the role of forests in the global carbon cycle and to support international policies for climate change mitigation and adaptation. Mexico is one of the countries having great potential for the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (or UN-REDD program) and there is a growing demand for unbiased Monitoring Reporting Verification systems at a national level. As an effort under NASA’s Carbon Monitoring System (CMS) program, we developed a machine learning model using multi-stream remote sensing measurements as well as topographic data to create a high spatial resolution AGBD map (~100 m) over Mexico (circa 2020). The remote sensing data includes Global Ecosystem Dynamic Investigation (GEDI) lidar, Sentinel 1 Synthetic-Aperture Radar (SAR), and Sentinel-2 multispectral imagery (MSI). GEDI onboard the International Space Station provides unprecedented forest structure and AGBD sampling datasets for model training and validation practices. Our analysis indicates that the developed random forest model can capture 63 % of the spatial variation (RMSE = 33.7 Mg/ha) of AGBD of Mexican forests. We find that shortwave infrared bands of Sentinel-2 MSI and topographical variables from elevation data are the most important variables in the developed AGBD model. Our study highlights methodological opportunities in synergistic uses of multiple sensors for large-scale forest AGBD mapping and shows potential for retrospective analysis and operational monitoring of forest AGBD and its dynamics.

Taejin Park↗

Validation of the first LiDAR wind resource assessment buoy system offshore the Northeast United States

The US offshore wind industry is maturing with several projects in various stages of development. These projects require site wind and environmental data before and during operation. Conventional techniques such as fixed-bottom meteorological towers present economical and permitting challenges for the US. Floating Light Detection and Ranging (LiDAR) buoys offer significant advantages including reduced costs, less permitting, and reusability. This paper presents the validation of the first floating LiDAR buoy in Northeast US waters. The buoy, named DeepCLiDAR, includes a LiDAR, ecological monitoring sensors, and metocean sensors. A three-phase LiDAR validation plan was executed, and its results are presented. The objective of the validation plan was to verify the accuracy of measurements made by the LiDAR buoy in wave environments against an unmoving reference wind measurement. Due to a lack of reference met masts, the use of a LiDAR on land as a baseline reference was implemented for validation. Comparison to a reference LiDAR instead of a traditional meteorological tower was a unique approach required in the Northeast US waters due to the absence of a reference fixed-bottom meteorological tower in the region at the time of this study. The testing included a comparison of wind speed measurements made by the buoy deployed 15 km offshore from the mainland and a land-based reference LiDAR located on a nearby island. This paper presents the methodology and results of this program, which indicate favorable agreement. This was the first such validation program in the Northeast USA which is now seeing rapid development of offshore wind.

17 WIND ENERGY↗

Thermo-Hydro-Mechanical Modeling of Brine Migration in a Heated Borehole Test in Bedded Salt

Abstract This research paper focuses on the thermo-hydro-mechanical (THM) modeling of brine migration in a heated borehole test conducted as part of the ongoing Brine Availability Test in Salt (BATS) at the Waste Isolation Pilot Plant (WIPP) in New Mexico. It is a component of the international collaboration project DECOVALEX-2023 (DEvelopment of COupled models and their VALidation against EXperiments), which aims to understand the THM processes governing brine flow in heated rock salt repositories through collaborative analysis by multiple research teams. Using the TOUGH–FLAC simulator, THM simulations were performed and compared with data from the BATS phase 1a. This experiment involved two identical horizontal-borehole arrays, one heated and one serving as a control, both equipped with sensor arrays. Analysis of measurements revealed water flow rate surges during heater power transitions, with the highest jump observed during cooling. Acoustic emission activity exhibited distinct patterns in response to heater power changes, suggesting that damage to rock salt is particularly pronounced during the cooling phase. The THM simulations successfully captured these phenomena, highlighting the significance of thermal effects, brine migration, and mechanical behavior in predicting brine availability in heated and damaged rock salt. Our modeling also revealed the critical interplay between heating and cooling-induced damage and its influence on flow properties, particularly affecting brine inflow estimation. Notably, we found that cooling-induced brine inflow spikes result from increased permeability due to tensile dilatancy. These findings have important implications for the development of robust containment strategies and enhance our understanding of the complex processes involved in repository performance.

58 GEOSCIENCES↗

Datasets of Faults in Variable Air Volume Terminal Units in a Multi-Zone Commercial Building

Faults in HVAC systems can decrease system efficiency and equipment lifespan, leading to 5%–30% of energy consumption being wasted in commercial buildings. We identified two common faults in HVAC variable air volume systems: a stuck damper fault in the variable air volume terminal unit and a discharge airflow sensor fault. We conducted three sets of damper stuck tests and two sets of airflow sensor tests, each including a fault-free scenario and scenarios with varying levels of faults, over one day. The faults were implemented in Oak Ridge National Laboratory’s two-story Flexible Research Platform building to generate a high-quality, well-controlled dataset covering fault-induced and fault-free scenarios. The test building, fault test scenarios, and data validation are described here. The open-source dataset includes 1 min intervals of weather and building data on the presence and absence of building faults. This dataset can be used to analyze the effects of HVAC system faults on system operation and indoor building conditions, and to develop or evaluate a fault detection and diagnosis algorithm.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Advances in Rotational Seismic Measurements

Rotational motion is increasingly understood to be a significant part of seismic wave motion. Rotations can be important in earthquake strong motion and in Induced Seismicity Monitoring. Rotational seismic data can also enable shear selectivity and improve wavefield sampling for vertical geophones in 3D surveys, among other applications. However, sensor technology has been a limiting factor to date. The US Department of Energy (DOE) and Applied Technology Associates (ATA) are funding a multi-year project that is now entering Phase 2 to develop and deploy a new generation of rotational sensors for validation of rotational seismic applications. Initial focus is on induced seismicity monitoring, particularly for Enhanced Geothermal Systems (EGS) with fracturing. The sensors employ Magnetohydrodynamic (MHD) principles with broadband response, improved noise floors, robustness, and repeatability. This paper presents a summary of Phase 1 results and Phase 2 status.

58 GEOSCIENCES↗

Ubiquitous Nuclear Threat Detection Final Report, Harvey Mudd College Engineering Clinic

The Lawrence Livermore National Labs clinic team was asked to design a repeatable, portable procedure that would incentivize participants to carry detectors that form a radiation sensor network along repeated paths, to precisely known locations and past known radioactive sources. To achieve these goals, the team designed day-long and week-long data collection procedures in the form of puzzle hunt events. The team also created an Android app in order to support this measurement campaign and foster engagement. A ground truth collection method was constructed and validated through repeated use. Information concerning effective deployment of the data-collection procedure was gathered for future iterations. Over the course of procedural testing, 6 de 17 HMC students participated and collected 250 hours of data. 3 deployments of the procedure were conducted in each semester. A total of 63 students participated and collected 300 hours of data over the year. Deployment 1: 16 students, Deployment 2: 17 students, Deployment 3: 8 users, ~18 active hours, Deployment 4: 4 students, ~10 active hours, and Deployment 5: 18 students, ~40 active hours.

42 ENGINEERING↗

POD-based constrained sensor placement and field reconstruction from noisy wind measurements: A perturbation study

Sensor placement at the extrema of Proper Orthogonal Decomposition (POD) is efficient and leads to accurate reconstruction of the wind field from a limited number of measure- ments. In this paper we extend this approach of sensor placement and take into account measurement errors and detect possible malfunctioning sensors. We use the 48 hourly spa- tial wind field simulation data sets simulated using the Weather Research an Forecasting (WRF) model applied to the Maine Bay to evaluate the performances of our methods. Specifically, we use an exclusion disk strategy to distribute sensors when the extrema of POD modes are close. It turns out that this strategy can also reduce the error of recon- struction from noise measurements. Also, by a cross-validation technique, we successfully locate the malfunctioning sensors.

54 ENVIRONMENTAL SCIENCES↗

Ensemble-Based Assimilation of Aerosol Observations in GEOS-5

MERRA-2 is the latest Aerosol Reanalysis produced at NASA's Global Modeling Assimilation Office (GMAO) from 1979 to present. This reanalysis is based on a version of the GEOS-5 model radiatively coupled to GOCART aerosols and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from AVHRR over ocean, MODIS sensors on both Terra and Aqua satellites, MISR over bright surfaces and AERONET data. In order to assimilate lidar profiles of aerosols, we are updating the aerosol component of our assimilation system to an Ensemble Kalman Filter (EnKF) type of scheme using ensembles generated routinely by the meteorological assimilation. Following the work performed with the first NASA's aerosol reanalysis (MERRAero), we first validate the vertical structure of MERRA-2 aerosol assimilated fields using CALIOP data over regions of particular interest during 2008.

LDE↗

Ultraviolet Satellite Measurements of Volcanic Ash

Ultraviolet (UV) remote sensing of volcanic ash and other absorbing aerosols from space began with the launch of the first Total Ozone Mapping Spectrometer (TOMS) instrument in 1978. Subsequent UV satellite missions (TOMS, GOME, SCIAMACHY, OMI, GOME-2, OMPS) have extended UV ash measurements to the present, generating a unique multidecadal record. A UV Aerosol Index (UVAI) based on two near-UV wavelengths, equally applicable to multispectral (TOMS, DSCOVR) or hyperspectral (GOME, SCIAMACHY, OMI, GOME-2, OMPS) instruments, has been used to derive a unique absorbing aerosol climatology across multiple UV satellite missions. Advantages of UV ash measurements relative to infrared (IR) techniques include the ability to detect ash at any altitude (assuming no clouds), above clouds, and over bright surfaces, where visible and IR techniques may fail. Disadvantages include the daytime-only restriction and nonspecificity to silicate ash, since UV measurements are sensitive to any UV-absorbing aerosol, including smoke, desert dust, and pollution. However, simultaneous retrieval of sulfur dioxide (SO2) abundance and UVAI provides robust discrimination of volcanic clouds. Although the UVAI is only semiquantitative, it has proved successful at detecting and tracking volcanic ash clouds from many volcanic eruptions since 1978. NASA A-Train measurements since 2006 (eg, CALIOP) have provided much improved constraints on volcanic ash altitude, and also permit identification of aerosol type through sensor synergy. Quantitative UV retrievals of ash optical depth, effective particle size, and ash column mass are possible and require assumptions of ash refractive index, particle size distribution, and ash layer altitude. The lack of extensive ash refractive index data in the UV-visible and the effects of ash particle shape on retrievals introduce significant uncertainty in the retrieved parameters, although limited validation against IR ash retrievals has been successful. In this contribution, we review UV ash detection and retrieval techniques and provide examples of volcanic eruptions detected in the approx. 37 year data record.

Multidecadal record↗