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At least 811 records · Page 45

The evolution of Florida thunderstorms on 23 September 1979 as observed by an airborne passive microwave radiometer

The observations made by the aircraft are examined in order to determine sensing parameters for future satellite missions. Minimum brightness temperatures substantially below atmospheric temperatures are revealed in the data. Scattering by an ice layer within the clouds is postulated as the cause. A one-dimensional cloud model initialized with a representative local sounding gives reasonable values for the height and thickness of this ice layer. The model cloud is similar to the observed cloud in both cloud top height and radar reflectivity. A 'mystery' feature observed by the microwave sensors as an area of enhanced scattering, suggesting an updraft core of graupel that in turn is indicative of a convective tower is considered of particular interest. It is noted that this feature was masked in the visible and infrared sensors by the presence of upper-level semitransparent cirrus. The detection of this mystery feature is seen as suggesting that passive microwave sensing of convective areas may provide information regarding the location and/or strength of the more active towers which cannot be detected now with conventional visible or infrared instruments because of a uniform higher-level cloud cover.

Hakkarinen, I. M.↗

The Global Precipitation Measurement (GPM) Mission's Scientific Achievements and Societal Contributions: Reviewing Four Years of Advanced Rain and Snow Observations

Precipitation represents a life-critical energy and hydrologic exchange between the Earth’s atmosphere and its surface. As such, knowledge of where, when, and how much rain and snow falls is essential for scientific research and societal applications. Building on the 17-year success of the Tropical Rainfall Measurement Mission (TRMM), the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO) is the first U.S. National Aeronautical and Space Administration (NASA) satellite mission specifically designed with sensors to observe the structure and intensities of both rain and falling snow. The GPM-CO has proved to be a worthy successor to TRMM, extending and improving high-quality active and passive microwave observations across all times of day. The GPM-CO launched in early 2014, is a joint mission between NASA and the Japanese Aerospace Exploration Agency (JAXA), with sensors that include the NASA-provided GPM Microwave Imager and the JAXA-provided Dual-frequency Precipitation Radar. These sensors were devised with high accuracy standards enabling them to be used as a reference for inter-calibrating a constellation of partner satellite data. These intercalibrated partner satellite retrievals are used with infrared data to produce merged precipitation estimates at temporal scales of 30 minutes and spatial scales of 0.1° x 0.1°. Precipitation estimates from the GPM-CO and partner constellation satellites, provided in near real time and later reprocessed with all ancillary data, are an indispensable source of precipitation data for operational and scientific users. Advances have been made using GPM data, primarily in improving sensor calibration, retrieval algorithms, and ground validation measurements, and used to further our understanding of the characteristics of liquid and frozen precipitation and the science of water and hydrological cycles for climate/weather forecasting. These advances have extended to societal benefits related to water resources, operational numerical weather prediction, hurricane monitoring, prediction, and disaster response, extremes, and disease.

Applications↗

Summary of results and conclusions based on analysis of volume imaging and high spectral resolution lidar data acquired during FIRE phase 1, part 1

The collection of long term global statistics on cloud cover may be most easily accomplished with satellite based observations; however, measurements derived from passive satellite retrieval methods must be calibrated and verified by in situ or ground based remote sensor observations. Verification is not straight forward, however, because the highly variable nature of cloud altitude, morphology, and optical characteristics complicates the scaling of point measurements to satellite footprint sized areas. This is particularly evident for cirrus clouds which may be organized on horizontal scales of 10's of meters to 8 km or more, and have optical depths ranging from less than .003 to greater than 3. Cirrus clouds can strongly influence earths' radiative balance, but, because they are often transmissive, cirrus clouds are difficult to detect and characterize from satellite measurements. Because of its precise ranging capabilities, spatial resolution and sensitivity, lidar observations have played an important role in the detection, depiction, and characterization of cirrus clouds. Some of the characteristics of cirrus clouds are summarized which observed the High Spectral Resolution and Volume Imaging Lidars during the phase 1 IFO and ETO periods.

Grund, Christian J.↗

New accelerometers under development

The commercial viability of the Space Station requires that it provide a micro-g, or submicro-g environment to users. This represents significant improvement over existing systems. Attainment of the lowest micro-g levels requires isolation systems. Passive and active systems have been evaluated. Best performance is achieved using active approaches where accelerometer sensors close feedback loops. Two emerging accelerometer technologies are presented that have promise for meeting performance goals while achieving reductions of package size, weight, and power. The technologies addressed are Honeywell's design concept for an optical cavity locking accelerometer and the recent development of an integrated silicon accelerometer for government applications.

Wald, Jerry↗

Synergistic use of multispectral satellite data for monitoring land surface change

Observations by the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA satellites were used to compute visible and near infrared reflectances and surface temperature, while passive microwave observations at 37 GHz frequency by the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) on board, respectively, the Nimbus-7 and DMSP-F8 satellites were used to compute polarization difference. These observations were analyzed along transects from rainforest to desert over northern Africa for the period 1979-1987, which included an unprecedented drought during 1984 over the Sahel zone. Model simulations were made to understand the interrelationship among multispectral data.

Choudhury, Bhaskar J.↗

A Microwave Technique for Mapping Ice Temperature in the Arctic Seasonal Sea Ice Zone

A technique for deriving ice temperature in the Arctic seasonal sea ice zone from passive microwave radiances has been developed. The algorithm operates on brightness temperatures derived from the Special Sensor Microwave/Imager (SSM/I) and uses ice concentration and type from a previously developed thin ice algorithm to estimate the surface emissivity. Comparisons of the microwave derived temperatures with estimates derived from infrared imagery of the Bering Strait yield a correlation coefficient of 0.93 and an RMS difference of 2.1 K when coastal and cloud contaminated pixels are removed. SSM/I temperatures were also compared with a time series of air temperature observations from Gambell on St. Lawrence Island and from Point Barrow, AK weather stations. These comparisons indicate that the relationship between the air temperature and the ice temperature depends on ice type.

St.Germain, Karen M.↗

Satellite Gravimetry Applied to Drought Monitoring

Near-surface wetness conditions change rapidly with the weather, which limits their usefulness as drought indicators. Deeper stores of water, including root-zone soil wetness and groundwater, portend longer-term weather trends and climate variations, thus they are well suited for quantifying droughts. However, the existing in situ networks for monitoring these variables suffer from significant discontinuities (short records and spatial undersampling), as well as the inherent human and mechanical errors associated with the soil moisture and groundwater observation. Remote sensing is a promising alternative, but standard remote sensors, which measure various wavelengths of light emitted or reflected from Earth's surface and atmosphere, can only directly detect wetness conditions within the first few centimeters of the land s surface. Such sensors include the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) C-band passive microwave measurement system on the National Aeronautic and Space Administration's (NASA) Aqua satellite, and the combined active and passive L-band microwave system currently under development for NASA's planned Soil Moisture Active Passive (SMAP) satellite mission. These instruments are sensitive to water as deep as the top 2 cm and 5 cm of the soil column, respectively, with the specific depth depending on vegetation cover. Thermal infrared (TIR) imaging has been used to infer water stored in the full root zone, with limitations: auxiliary information including soil grain size is required, the TIR temperature versus soil water content curve becomes flat as wetness increases, and dense vegetation and cloud cover impede measurement. Numerical models of land surface hydrology are another potential solution, but the quality of output from such models is limited by errors in the input data and tradeoffs between model realism and computational efficiency. This chapter is divided into eight sections, the next of which describes the theory behind satellite gravimetry. Following that is a summary of the GRACE mission and how hydrological information is gleaned from its gravity products. The fourth section provides examples of hydrological science enabled by GRACE. The fifth and sixth sections list the challenging aspects of GRACE derived hydrology data and how they are being overcome, including the use of data assimilation. The seventh section describes recent progress in applying GRACE for drought monitoring, including the development of new soil moisture and drought indicator products, and that is followed by a discussion of future prospects in satellite gravimetry based drought monitoring.

Rodell, Matthew↗

Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low-Earth orbits. The NASA Short-term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA s Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channel s available from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard METEOSAT-9. This broader suite includes products that discriminate between air mass types associated with synoptic-scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Similarly, researchers at NOAA/NESDIS and CIRA have developed air mass discrimination capabilities using channels available from the current GOES Sounders. Other applications of multispectral composites include combinations of high and low frequency, horizontal and vertically polarized passive microwave brightness temperatures to discriminate tropical cyclone structures and other synoptic-scale features. Many of these capabilities have been transitioned for evaluation and operational use at NWS Weather Forecast Offices and National Centers through collaborations with SPoRT and CIRA. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES-R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar-Orbiting Partnership (S-NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites). At the same time, new image manipulation and display capabilities are available within AWIPS II, the next generation of the NWS forecaster decision support system. This presentation will present a review of SPoRT, CIRA, and NRL collaborations regarding multispectral satellite imagery and articulate an integrated and collaborative path forward with Raytheon AWIPS II development staff for integrating current and future capabilities that support new satellite instrumentation and the AWIPS II decision support system.

Molthan, Andrew L.↗

Current and Future Applications of Multispectral (RGB) Satellite Imagery for Weather Analysis and Forecasting Applications

Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low ]Earth orbits. The NASA Short ]term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA fs Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channels available from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard METEOSAT ]9. This broader suite includes products that discriminate between air mass types associated with synoptic ]scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES ]R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar ]Orbiting Partnership (S ]NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross ]track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites. New applications from VIIRS extend multispectral composites available from MODIS and SEVIRI while adding new capabilities through incorporation of additional CrIS channels or information from the Near Constant Contrast or gDay ]Night Band h, which provides moonlit reflectance from clouds and detection of fires or city lights. This presentation will present a review of SPoRT, CIRA, and NRL collaborations regarding multispectral satellite imagery and recent applications within the operational forecasting environment

Molthan, Andrew L.↗

Lessons Learned During Instrument Testing for the Thermal Infrared Sensor (TIRS)

The Themal InfraRed Sensor (TIRS) instrument, set to launch on the Landsat Data Continuity Mission in 2013, features a passively cooled telescope and IR detectors which are actively cooled by a two stage cryocooler. In order to proceed to the instrument level test campaign, at least one full functional test was required, necessitating a thermal vacuum test to sufficiently cool the detectors and demonstrate performance. This was fairly unique in that this test occurred before the Pre Environmental Review, but yielded significant knowledge gains before the planned instrument level test. During the pre-PER test, numerous discrepancies were found between the model and the actual hardware, which were revealed by poor correlation between model predictions and test data. With the inclusion of pseudo-balance points, the test also provided an opportunity to perform a pre-correlation to test data prior to the instrument level test campaign. Various lessons were learned during this test related to modeling and design of both the flight hardware and the Ground Support Equipment and test setup. The lessons learned in the pre-PER test resulted in a better test setup for the nstrument level test and the completion of the final instrument model correlation in a shorter period of time. Upon completion of the correlation, the flight predictions were generated including the full suite of off-nominal cases, including some new cases defined by the spacecraft. For some of these ·new cases, some components now revealed limit exceedances, in particular for a portion of the hardware that could not be tested due to its size and chamber limitations.. Further lessons were learned during the completion of flight predictions. With a correlated detalled instrument model, significant efforts were made to generate a reduced model suitable for observatory level analyses. This proved a major effort both to generate an appropriate network as well as to convert to the final model to the required format and yielded additional lessons learned. In spite of all the challenges encountered by TIRS, the instrument was successfully delivered to the spacecraft and will soon be tested at observatory level in preparation for a successful mission launch.

Peabody, Hume L.↗

Iodine Satellite

This project is a collaborative effort to mature an iodine propulsion system while reducing risk and increasing fidelity of a technology demonstration mission concept. 1 The FY 2014 tasks include investments leveraged throughout NASA, from multiple mission directorates, as a partnership with NASA Glenn Research Center (GRC), a NASA Marshall Space Flight Center (MSFC) Technology Investment Project, and an Air Force partnership. Propulsion technology is often a critical enabling technology for space missions. NASA is investing in technologies to enable high value missions with very small and low-cost spacecraft, even CubeSats. However, these small spacecraft currently lack any appreciable propulsion capability. CubeSats are typically deployed and drift without any ability to transfer to higher value orbits, perform orbit maintenance, or deorbit. However, the iodine Hall system can allow the spacecraft to transfer into a higher value science orbit. The iodine satellite (iSAT) will be able to achieve a (Delta)V of >500 m/s with <1 kg of solid iodine propellant, which can be stored in an unpressurized benign state prior to launch. The iSAT propulsion system consists of the 200 W Hall thruster, solid iodine propellant tank, a power processing unit, and the necessary valves and tubing to route the iodine vapor. The propulsion system is led by GRC, with critical hardware provided by the Busek Co. The propellant tank begins with solid iodine unpressurized on the ground and in-flight before operations, which is then heated via tank heaters to a temperature at which solid iodine sublimates to iodine vapor. The vapor is then routed through tubing and custom valves to control mass flow to the thruster and cathode assembly. 2 The thruster then ionizes the vapor and accelerates it via magnetic and electrostatic fields, resulting in thrust with a specific impulse >1,300 s. The iSAT spacecraft, illustrated in figure 1, is currently a 12U CubeSat. The spacecraft chassis will be constructed from aluminum with a finish to prevent iodine-driven corrosion. The iSAT spacecraft includes full three-axis control using wheels, magnetic torque rods, inertial management unit, and a suite of sensors and optics. The spacecraft will leverage heat generated by spacecraft components and radiators for a passive thermal control system.

Dankanich, John↗

Towards Physics Guided Optical Flow for Tracking Atmospheric Motion

Atmospheric 3D winds in the horizontal and vertical directions are critical for improving short-range and long-range forecasting. Such advancement in forecasting directly applies to research in a number of areas including convective processes, wildfire plumes and tornado prediction. Atmospheric Motion Vectors (AMVs) provide a passively sensed approach to quantifying horizontal motion and cloud heights, which are typically sourced from geostationary sensors due to the availability of high frequency observations. Recent work has shown that estimating AMVs by tracking individual pixels with dense optical flow is a promising new direction. In this work, we use a state-of-the-art convolutional neural network for optical flow (FlowNetS) in a physics-guided deep learning framework for predicting AMVs in the horizontal direction. The approach is semi-supervised and uses physically informed wind vectors from high-resolution numerical simulations (DYAMOND) for supervised learning followed by fine-tuning though warping and reconstruction of full-disk geostationary images (GOES-16). In the vertical direction, we use labels from the CALIPSO low-earth orbit satellite to predict cloud height from 16-band geostationary images with a neural network. We present results for both tasks on held-out time periods and secondary datasets.

geostationary↗

Towards Physics Guided Optical Flow for Tracking Atmospheric Motion

Observations of atmospheric 3D winds are critical for improving short-range and long-range forecasting. Such advancement in forecasting directly applies to research in a number of areas including convective processes, wildfire plumes and tornado prediction. Atmospheric Motion Vectors (AMVs) provide a passively sensed approach to quantifying horizontal motion and cloud heights, which are typically sourced from geostationary sensors due to the availability of high frequency observations. Recent work has shown that estimating AMVs by tracking individual pixels with dense optical flow is a promising new direction. In this work, we compare state-of-the-art convolutional neural networks for optical flow in a physics-guided deep learning framework for predicting AMVs. The approach is semi-supervised and uses physically informed wind vectors from high-resolution numerical simulations for supervised learning followed by fine-tuning though warping and reconstruction of full-disk geostationary images (GOES-16). In the vertical direction, we use labels from the CALIPSO low-earth orbit satellite to predict cloud height from 16-band geostationary images with a neural network. We present results for both tasks on held-out time periods and secondary datasets.

Geostationary↗

Simulation of microwave brightness temperatures of an evolving hailstorm at SSM/I frequencies

A simulation of the appearance of an intense hailstorm in the passive microwave spectrum is used to characterize the vertical sources of radiation contributing to the microwave brightness temperatures at the top of the atmosphere. The four frequencies studied correspond to those used on the USAF Special Sensor Microwave Imager. The origin and movement of the radiation are described by two vertically resolved radiative structure functions. Consideration is given to problems relating to precipitation retrieval through passive remote sensing.

Mugnai, Alberto↗

Passive microwave soil moisture research

During the four years of the AgRISTARS Program, significant progress was made in quantifying the capabilities of microwave sensors for the remote sensing of soil moisture. In this paper, a discussion is provided of the results of numerous field and aircraft experiments, analysis of spacecraft data, and modeling activities which examined the various noise factors such as roughness and vegetation that affect the interpretability of microwave emission measurements. While determining that a 21-cm wavelength radiometer was the best single sensor for soil moisture research, these studies demonstrated that a multisensor approach will provide more accurate soil moisture information for a wider range of naturally occurring conditions.

Schmugge, T.↗

Intercomparisons between passive and active microwave remote sensing, and hydrological modeling for soil moisture

Soil moisture estimations from a distributed hydrological model and two microwave sensors were compared with ground measurements collected during the MAC-HYDRO'90 experiment. The comparison was done with the purpose of evaluating the performance of the hydrological model and examining the limitations of remote sensing techniques used in soil moisture estimation. An image integration technique was used to integrate and analyze rainfall, soil properties, land cover, topography, and remote sensing imagery. Results indicate that the hydrological model and microwave sensors successfully picked up temporal variations of soil moisture and that the spatial soil moisture pattern may be remotely sensed with reasonable accuracy using existing algorithms.

Wood, E. F.↗

Optoelectronic Sensor System for Guidance in Docking

The Video Guidance Sensor (VGS) system is an optoelectronic sensor that provides automated guidance between two vehicles. In the original intended application, the two vehicles would be spacecraft docking together, but the basic principles of design and operation of the sensor are applicable to aircraft, robots, vehicles, or other objects that may be required to be aligned for docking, assembly, resupply, or precise separation. The system includes a sensor head containing a monochrome charge-coupled- device video camera and pulsed laser diodes mounted on the tracking vehicle, and passive reflective targets on the tracked vehicle. The lasers illuminate the targets, and the resulting video images of the targets are digitized. Then, from the positions of the digitized target images and known geometric relationships among the targets, the relative position and orientation of the vehicles are computed. As described thus far, the VGS system is based on the same principles as those of the system described in "Improved Video Sensor System for Guidance in Docking" (MFS-31150), NASA Tech Briefs, Vol. 21, No. 4 (April 1997), page 9a. However, the two systems differ in the details of design and operation. The VGS system is designed to operate with the target completely visible within a relative-azimuth range of +/-10.5deg and a relative-elevation range of +/-8deg. The VGS acquires and tracks the target within that field of view at any distance from 1.0 to 110 m and at any relative roll, pitch, and/or yaw angle within +/-10deg. The VGS produces sets of distance and relative-orientation data at a repetition rate of 5 Hz. The software of this system also accommodates the simultaneous operation of two sensors for redundancy

Howard, Richard T.↗

Towards a Multisensor Approach to Improve on Current TRMM Retrievals of Clouds and Precipitation

The Tropical Rainfall Measuring Mission (TRMM) was designed to measure tropical rainfall and its variation from a low inclination orbiting satellite. The TRMM payload was carefully chosen to overcome a number of limitations of past satellite observing systems. This payload is predicated on the combination of active and passive observations from the TRMM Precipitation Radar (PR) and TRMM Microwave Imager (TMI) and Visible and Infrared Scanner (VIRS). Our research over the past three years has been devoted to the challenge of developing the most effective way of combining complementary information from these sensors to provide the most consistent estimate of precipitation. We have approached this problem from three directions. The first was to carry out preliminary analysis of passive microwave and infrared data from the TMI and VIRS instruments to understand the character of clear and cloudy skies in the basis defined by polarization and brightness temperature differences. Using this information as a foundation, the properties of two retrieval algorithms were analyzed, one for retrieving ice clouds from VIRS that was developed in parallel with this project and the other for rainfall from the TMI. Finally, the knowledge gleaned from each of these studies, coupled with ancillary data from NWP models and a broadband radiative transfer model, was used to create and algorithm for synthesizing the principal components of the Earth's energy budget from the basic building blocks of the atmosphere, gases, clouds, and precipitation. Principal results from each of these areas of research and their role in the TRMM and climate communities are summarized.

Stephens, Graeme L.↗