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At least 289 records · Page 16

Toward Physics-informed Neural Networks for 3D Multi-layer Cloud Mask Reconstruction

Three-dimensional (3D) cloud retrievals are critical for understanding their impact on climate and other applications such as aviation safety, weather prediction, and remote sensing. However, obtaining high-resolution and accurate vertical representation of clouds remains unsolved due to the limitations imposed by satellite instrumentation, viewing conditions, and the complexity of cloud dynamics. Cloud masks are essential for comprehending various cloud vertical properties, but deriving accurate 3D cloud masks from 2D satellite imagery data is a challenging task. To tackle these challenges, we introduce a physics-informed loss function for training deep learning models that can extend 2D cloud images into 3D cloud masks. The proposed loss, called CloudMask Loss, is composed of two domain knowledge-informed loss terms: one for evaluating cloud position and thickness, and the other for measuring the number of layers. By combining these loss terms, we improve the trainability of the deep learning models for more accurate and meaningful results. We apply the proposed loss function to different neural networks and demonstrate significant improvements in multi-layer cloud mask reconstruction. Utilizing the same neural network architecture, our proposed loss outperforms standard binary crossentropy loss in terms of multi-layer cloud classification accuracy, number of layers accuracy, and thickness mean absolute error (MAE). The proposed loss function can be readily integrated into various neural network architectures, resulting in substantial performance gains in 3D cloud mask generation.

multi-layer clouds↗

PBL Thermodynamic Characterization and Its Variability From NAST-I During the Wh2yMSIE Field Campaign

The National Airborne Sounder Testbed-Interferometer (NAST‑I) suborbital system (<2.6 km IFOV; 0.25 cm-1 within 645–2700 cm‑1) serves as a spaceborne instrument simulator and pathfinder for future satellite capabilities and airborne science experiments. The NAST‑I measurements are made to advance understanding of science critical for weather, climate, chemistry, and radiation applications. Here we present some groundbreaking capabilities of NAST-I measurements and corresponding geophysical retrievals and their potential benefits toward improved atmospheric state and composition characterizations needed for science applications of particular importance toward enhancing characterization and understanding of the Planetary Boundary Layer (PBL). Initial results of PBL height estimation and thermodynamic characterization and their time evolution from NAST-I measurements during the WH2yMSIE field campaign are presented.

Daniel K Zhou↗

Meteorological image processing applications

Meteorologists at NASA's Goddard Space Flight Center are conducting an extensive program of research in weather and climate related phenomena. This paper focuses on meteorological image processing applications directed toward gaining a detailed understanding of severe weather phenomena. In addition, the paper discusses the ground data handling and image processing systems used at the Goddard Space Flight Center to support severe weather research activities and describes three specific meteorological studies which utilized these facilities.

Bracken, P. A.↗

Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model

The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.

Molthan, Andrew L.↗

Near Real Time Tools for ISS Plasma Science and Engineering Applications

The International Space Station (ISS) program utilizes a plasma environment forecast for estimating electrical charging hazards for crews during extravehicular activity (EVA). The process uses ionospheric electron density (Ne) and temperature (Te) measurements from the ISS Floating Potential Measurement Unit (FPMU) instrument suite with the assumption that the plasma conditions will remain constant for one to fourteen days with a low probability for a space weather event which would significantly change the environment before an EVA. FPMU data is typically not available during EVA's, therefore, the most recent FPMU data available for characterizing the state of the ionosphere during EVA is typically a day or two before the start of an EVA or after the EVA has been completed. Three near real time space weather tools under development for ISS applications are described here including: (a) Ne from ground based ionosonde measurements of foF2 (b) Ne from near real time satellite radio occultation measurements of electron density profiles (c) Ne, Te from a physics based ionosphere model These applications are used to characterize the ISS space plasma environment during EVA periods when FPMU data is not available, monitor for large changes in ionosphere density that could render the ionosphere forecast and plasma hazard assessment invalid, and validate the "persistence of conditions" forecast assumption. In addition, the tools are useful for providing space environment input to science payloads on ISS and anomaly investigations during periods the FPMU is not operating.

Minow, Joseph I.↗

Space Weather Monitoring for ISS Space Environments Engineering and Crew Auroral Observations

The awareness of potentially significant impacts of space weather on spaceand ground ]based technological systems has generated a strong desire in many sectors of government and industry to effectively transform knowledge and understanding of the variable space environment into useful tools and applications for use by those entities responsible for systems that may be vulnerable to space weather impacts. Essentially, effectively transitioning science knowledge to useful applications relevant to space weather has become important. This talk will present proven methodologies that have been demonstrated to be effective, and how in the current environment those can be applied to space weather transition efforts.

Minow, Joseph I.↗

International space technical applications; Proceedings of the Nineteenth Goddard Memorial Symposium, Arlington, VA, March 26, 27, 1981

Topics discussed include industry in space, international Landsat programs, communications, weather and climate, space-based earth science applications, and space-based manufacturing and power generation. Papers are presented on space transportation in the private sector, the role of satellite remote sensing in climatology during the next 20 years, magnetic space-based field measurements, and energy for space applications. An assessment of domestic satellite communication technology is given, as is a forecast of the demand and capacity of U.S. domestic communications satellites.

Adelman, A.↗

Assimilation of GPM-retrieved Ocean Surface Meteorology Data for Two Snowstorm Events during ICE-POP 2018

As a component of the National Aeronautics and Space Administration (NASA) Weather Focus Area and Global Precipitation Measurement (GPM) Ground Validation participation in the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field research and forecast demonstration programs, hourly ocean surface meteorology properties were retrieved from the GPM microwave observations for January – March 2018. In this study, the retrieved ocean surface meteorological products – 2-m temperature, 2-m specific humidity, and 10-m wind speed were assimilated into a regional numerical weather prediction (NWP) framework to explore the application of these observations for two heavy snowfall events during the ICE-POP 2018: 27-28 February, and 7-8 March 2018. The Weather Research and Forecasting (WRF) model and the community Gridpoint Statistical Interpolation (GSI) were used to conduct high resolution simulations and data assimilation experiments. The results indicate that the data assimilation has a large influence on surface thermodynamic and wind fields in the model initial condition for both events. With cycled data assimilation, significantly positive influence of the retrieved surface observation was found for the March case with improved quantitative precipitation forecast and reduced error in temperature forecast. A slightly smaller yet positive impact was also found in the forecast of the February case.

assimilation↗

Results of tests of weathered K5NA closeout material in the MSFC Hot Gas Facility

The application of K5NA over hypolon was investigated. The effects of using K5NA over painted cork surfaces, the effects of weathering on the unpainted K5NA surfaces are determined, and the use of water versus solvent for tooling K5NA in place were compared. It is concluded that: (1) K5NA can be applied to hypalon surfaces; (2) K5NA can be left unpainted; and (3) K5NA can be tested with water or solvent.

Dean, W. G.↗

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

Duda, David P.↗

Real-time applications for remotely sensed lightning observations

Real-time monitoring of lightning activity, including the estimation of the location where the flash strikes the earth, provides a basis for the assessment of the impact of both the lightning hazard and severe weather on daily test and operation schedules. Applications to range meteorology are considered, taking into account the Space Transportation System, the handling of explosive materials, and test operations. Attention is given to details regarding forecasting and nowcasting, a low-cost lightning display system for electrical storm tracking and the support of lightning research activities, two versions of employed software, an example of the storm diagnostics and display products which will be available from the next generation weather radar, and a summary of the evolution of 12 New Mexico thunderstorms.

Goodman, S. J.↗

Visualization and Analysis of Near Real-Time Global Cloud Composites (GCC): Integration in a Geospatial Web Mapping Application

The NASA Langley Satellite ClOud and Radiation Property retrieval System (SatCORPS) team provides tools for retrieving cloud information from operational and research meteorological imager data. LEO and GEO satellite imagers are used for fusing hourly mosaics which create the Global Cloud Composite (GCC). The GCC provides global cloud products with a low latency which can help satisfy the growing needs of the research, modeling and business communities. The Esri ArcGIS system is used to transform the GCC data into Analysis Ready Data (ARD) which can be utilized for a variety of visualization and analysis activities in support of weather diagnoses/forecasting, Earth Sciences remote sensing applications, and disaster management. Additionally, the data is enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services to be consumed via API within a web mapping application. We will present a preview of the new interactive SatCORPS GCC web mapping application and its capabilities in allowing users to access and use GIS data within it.

Web Mapping Application↗

Aerogel Insulation Systems for Space Launch Applications

New developments in materials science in the areas of solution gelation processes and nanotechnology have led to the recent commercial production of aerogels. Concurrent with these advancements has been the development of new approaches to cryogenic thermal insulation systems. For example, thermal and physical characterizations of aerogel beads under cryogenic-vacuum conditions have been performed at the Cryogenics Test Laboratory of the NASA Kennedy Space Center. Aerogel-based insulation system demonstrations have also been conducted to improve performance for space launch applications. Subscale cryopumping experiments show the thermal insulating ability of these fully breathable nanoporous materials. For a properly executed thermal insulation system, these breathable aerogel systems are shown to not cryopump beyond the initial cooldown and thermal stabilization phase. New applications are being developed to augment the thermal protection systems of space launch vehicles, including the Space Shuttle External Tank. These applications include a cold-boundary temperature of 90 K with an ambient air environment in which both weather and flight aerodynamics are important considerations. Another application is a nitrogen-purged environment with a cold-boundary temperature of 20 K where both initial cooldown and launch ascent profiles must be considered. Experimental results and considerations for these flight system applications are discussed.

Fesmire, James E.↗

NASA’s Global Precipitation Measurement Mission: Leveraging Stakeholder Engagement & Applications Activities to Inform Decision-making

The application of satellite precipitation estimates from NASA’s Global Precipitation Measurement (GPM) Mission for decision-making has been a focus for the mission since launch. As a result, GPM data have enabled a range of applications that address societal needs, including water resource management, crop forecasting, ecological monitoring, disaster response, public health, aviation, weather forecasting, and climate modeling, among others. GPM applications activities have continued to focus on user engagement through in person trainings and interviews, workshops, webinars, and educational outreach activities. The goals of these efforts are to synthesize community data needs in order to effectively support and enable decision-making across agencies, academia and the global community. While these efforts have helped the GPM mission establish a large stakeholder community that encompasses federal and state partners, academic institutions, nd private and nonprofit companies, there remains difficulties associated with accessing, processing, and applying the data to support or enable applications. In this article, we present GPM applications strategies and approaches used to enhance the applications value of GPM data, and most importantly, demonstrate how these efforts have and can inform different decision-making contexts. This work also provides a discussion on key lessons learned from the user community and how this information can be utilized to help better support and shape applications approaches for future NASA Earth Science missions.

Satellite precipitation↗

National Airspace System Delay Estimation Using Weather Weighted Traffic Counts

Assessment of National Airspace System performance, which is usually measured in terms of delays resulting from the application of traffic flow management initiatives in response to weather conditions, volume, equipment outages and runway conditions, is needed both for guiding flow control decisions during the day of operations and for post operations analysis. Comparison of the actual delay, resulting from the traffic flow management initiatives, with the expected delay, based on traffic demand and other conditions, provides the assessment of the National Airspace System performance. This paper provides a method for estimating delay using the expected traffic demand and weather. In order to identify the cause of delays, 517 days of National Airspace System delay data reported by the Federal Aviation Administration s Operations Network were analyzed. This analysis shows that weather is the most important causal factor for delays followed by equipment and runway delays. Guided by these results, the concept of weather weighted traffic counts as a measure of system delay is described. Examples are given to show the variation of these counts as a function of time of the day. The various datasets, consisting of aircraft position data, enroute severe weather data, surface wind speed and visibility data, reported delay data and number of aircraft handled by the Centers data, and their sources are described. The procedure for selecting reference days on which traffic was minimally impacted by weather is described. Different traffic demand on each reference day of the week, determined by analysis of 42 days of traffic and delay data, was used as the expected traffic demand for each day of the week. Next, the method for computing the weather weighted traffic counts using the expected traffic demand, derived from reference days, and the expanded regions around severe weather cells is discussed. It is shown via a numerical example that this approach improves the dynamic range of the weather weighted traffic counts considerably. Time histories of these new weather weighted traffic counts are used for synthesizing two statistical features, six histogram features and six time domain features. In addition to these enroute weather features, two surface weather features of number of major airports in the United States with high mean winds and low mean visibility are also described. A least squares procedure for establishing a functional relation between the features, using combinations of these features, and system delays is explored using 36 days of data. Best correlations between the estimated delays using the functional relation and the actual delays provided by the Operations Network are obtained with two different combinations of features: 1) six time domain features of weather weighted traffic counts plus two surface weather features, and 2) six histogram features and mean of weather weighted traffic counts along with the two surface weather features. Correlation coefficient values of 0.73 and 0.83 were found in these two instances.

Chatterji, Gano B.↗

The effect of moonlight on observation of cloud cover at night, and application to cloud climatology

Ten years of nighttime weather observations from the Northern Hemisphere in December were classified according to the illuminance of moonlight or twilight on the cloud tops, and a threshold level of illuminance was determined, above which the clouds are apparently detected adequately. This threshold corresponds to light from a full moon at an elevation angle of 6 deg, light from a partial moon at higher elevation, or twilight from the sun less than 9 deg bvelow the horizon. It permits the use of about 38% of the observations made with the sun below the horizon. The computed diurnal cycles of total cloud cover are altered considerably when this moonlight criterion is imposed. Maximum cloud cover over much of the ocean is now found to be at night or in the morning, whereas computations obtained without benefit of the moonlight criterion, as in our published atlases, showed the time of maximum to be noon or early afternoon in many regions. The diurnal cycles of total cloud cover we obtain are compared with those of the International Satellite Cloud Climatology Project (ISCCP) for a few regions; they are generally in better agreement if the moonlight criterion is imposed on the surface observations. Using the moonlight criterion, we have analyzed 10 years (1982-91) of surface weather observations over land and ocean, worldwide, for total cloud cover and for the frequency of occurrence of clear sky, fog, and precipitation. The global average cloud cover (average of day and night) is about 2% higher if the moonlight criterion is imposed than if all observations are used. The difference is greater in winter than in summer, because of the fewer hours of darkness in summer. The amplitude of the annual cycle of total cloud cover over the Arctic Ocean and at the South Pole is diminished by a few percent when the moonlight criterion is imposed. The average cloud cover for 1982-91 is found to be 55% for Northern Hemisphere land, 53% for Southern Hemisphere land, 66% for Northern Hemisphere ocean, and 70% for Southern Hemisphere ocean, giving a global average of 64%. The global average for daytime is 64.6%; for nighttime 63.3%.

Hahn, Carole J.↗