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NASA NTRS2019

Surface Emissivity Impacts on GOES-R Series Multi-Spectral Imagery Applications

Value-added imagery products from the GOES-R series Advanced Baseline Imager are used to identify features of interest for operational forecasters, including: blowing dust, smoke, volcanic ash, cloud cover, atmospheric moisture, biomass fires and snow cover. These features each have a specific spectral signal that algorithms are designed to detect, but those signals are not always unique to just a single feature. Sometimes, the surface can mimic the spectral signal associated with an atmospheric feature of interest, creating a false alarm in a value-added product which negatively impacts interpretation of that product. This case study focuses on one such situation where areas of desert in the southwestern United States mimic the positive value associated with low clouds in the Brightness Temperature Difference (BTD) between the 10.35 μm and 3.9 μm channels, producing a false alarm. In order to characterize these “false alarm” areas, this study uses the cloud-cleared background product from the Cooperative Institute for Research in the Atmosphere (CIRA) to create a dataset of the cloud-free surface. Previous results have shown that cloud-cleared backgrounds of the 10.35 μm-3.9 μm BTD have successfully identified areas of positive BTDs in the cloud-free environment, proving that it is a property of the surface emissivity and a true “false alarm”. This study builds on that previous research to further characterize the seasonality of the “false-alarm” regions and to catalogue how they impact interpretation of multi-spectral imagery products from the GOES-R series ABI, especially the Nighttime Microphysics RGB created by NASA Short-term Prediction Research and Transition (SPoRT) Center.

Burke, Angela↗
NASA NTRS2020

The AERONET Version 3 Aerosol Retrieval Algorithm, Associated Uncertainties and Comparisons to Version 2

The Aerosol Robotic Network (AERONET) Version 3 (V3) aerosol retrieval algorithm is described, which is based on the Version 2 (V2) algorithm with numerous updates. Comparisons of V3 aerosol retrievals to those of V2 are presented, along with a new approach to estimate uncertainties in many of the retrieved aerosol parameters. Changes in the V3 aerosol retrieval algorithm include (1) a new polarized radiative transfer code (RTC), which replaced the scalar RTC of V2, (2) detailed characterization of gas absorption by adding NO2 and H2O to specify total gas absorption in the atmospheric column, specification of vertical profiles of all the atmospheric species, (3) new bidirectional reflectance distribution function (BRDF) parameters for land sites adopted from the MODIS BRDF/Albedo product, (4) a new version of the extraterrestrial solar flux spectrum, and (5) a new temperature correction procedure of both direct Sun and sky radiance measurements. The potential effect of each change in V3 on single scattering albedo (SSA) retrievals was analyzed. The operational almucantar retrievals of V2 versus V3 were compared for four AERONET sites: GSFC, Mezaira, Mongu, and Kanpur. Analysis showed very good agreement in retrieved parameters of the size distributions. Comparisons of SSA retrievals for dust aerosols (Mezaira) showed a good agreement in 440 nm SSA, while for longer wavelengths V3 SSAs are systematically higher than those of V2, with the largest mean difference at 675 nm due to cumulative effects of both extraterrestrial solar flux and BRDF changes. For non-dust aerosols, the largest SSA deviation is at 675 nm due to differences in extraterrestrial solar flux spectrums used in each version. Further, the SSA 675 nm mean differences are very different for weakly (GSFC) and strongly (Mongu) absorbing aerosols, which is explained by the lower sensitivity to a bias in aerosol scattering optical depth by less absorbing aerosols. A new hybrid (HYB) sky radiance measurement scan is introduced and discussed. The HYB combines features of scans in two different planes to maximize the range of scattering angles and achieve scan symmetry, thereby allowing for cloud screening and spatial averaging, which is an advantage over the principal plane scan that lacks robust symmetry. We show that due to an extended range of scattering angles, HYB SSA retrievals for dust aerosols exhibit smaller variability with solar zenith angles (SZAs) than those of almucantar (ALM), which allows extension of HYB SSA retrievals to SZAs less than 50∘ to as small as 25∘. The comparison of SSA retrievals from closely time-matched HYB and ALM scans in the 50 to 75∘ SZA range showed good agreement with the differences below ∼0.005. We also present an approach to estimate retrieval uncertainties which utilizes the variability in retrieved parameters generated by perturbing both measurements and auxiliary input parameters as a proxy for retrieval uncertainty. The perturbations in measurements and auxiliary inputs are assumed as estimated biases in aerosol optical depth (AOD), radiometric calibration of sky radiances combined with solar spectral irradiance, and surface reflectance. For each set of Level 2 Sun/sky radiometer observations, 27 inputs corresponding to 27 combinations of biases were produced and separately inverted to generate the following statistics of the inversion results: average, standard deviation, minimum and maximum values. From these statistics, standard deviation (labeled U27) is used as a proxy for estimated uncertainty, and a lookup table (LUT) approach was implemented to reduce the computational time. The U27 climatological LUT was generated from the entire AERONET almucantar (1993–2018) and hybrid (2014–2018) scan databases by binning U27s in AOD (440 nm), Angström exponent (AE, 440–870 nm), and SSA (440, 675, 870, 1020 nm). Using this LUT approach, the uncertainty estimates U27 for each individual V3 Level 2 retrieval can be obtained by interpolation using the corresponding measured and inverted combination of AOD, AE, and SSA.

Aliaksandr Siniuk↗
NASA NTRSDate not supplied

Open-source Numerical Modeling of Solidification Cracking Susceptibility: Application to Refractory Alloy Systems

Introduction. Alloys such as aluminum, nickel-base, and austenitic stainless steels are susceptible to solidification cracking during welding and 3D printing. Compositional optimization is one method used to effectively mitigate solidification cracking of those alloy systems. With the surge in hypersonic and in-space propulsion activities, refractory metals (Nb, Mo, Ta, W, and Re) and their alloy derivatives are increasing in importance due to their extreme high melting point and retention of high-temperature strength; however, their chemistry was most typically optimized to promote ductility during mechanical operations such as drawing and forming. Welding of such alloys has been a challenge due to a number of issues including solidification cracking, atmospheric contamination (O, C, and N), as well as a shift in ductile-to-brittle transition to higher temperature following grain growth induced by welding. Compositional optimization of refractory alloys for solidification cracking resistance in particular is desirable as their usage increases with the advent of advanced manufacturing methods such as 3D printing. This work evaluates the effect of compositional variation in refractory metal systems on the solidification cracking susceptibility with the goals of optimizing existing alloys and joining process techniques, and formulating new alloys with increased solidification cracking resistance. Experimental Procedures. A python code was developed in a Jupyter notebook environment (Michael and Sowards, 2023) to facilitate the calculation of crack susceptibility index proposed by Kou (2015). Composition is entered as a single point, or as a 1-D or 2-D array. The notebook calls pycalphad (Otis and Liu, 2017 and Bocklund et al, 2020) to calculate the evolution of fraction solid as a function of temperature (under either Scheil or equilibrium assumptions) and then evaluates steepness of the fraction solid curve near the terminal stage of solidification to predict solidification cracking resistance. Open source thermodynamic databases available at online repositories are used (van de Walle). The process is setup in an automated fashion to generate plots that show variation in solidification cracking susceptibility according to composition on 1-D line plots or 2-D contour plots. The Jupyter notebook and crack susceptibility algorithm was also integrated with a widely used commercial CALPHAD code for validation and alloy exploration. Results and Discussion. The crack susceptibility model was first validated against a series of refractory alloy compositions evaluated in past work which utilized a specialized Varestraint test built inside a vacuum chamber environment (Lessman and Gold, 1971). The alloys tested in the Varestraint apparatus included T-111 (Ta-8W-2Hf), ASTAR-811C (Ta-8W-1Re-0.7Hf-0.025C), FS-85 (Nb-27Ta-10W-1Zr), T-222 (Ta-9.6W-2.4Hf-0.01C), Ta-10W, B-66 (Nb-5Mo-5V-1Zr), and SCb-291 (Nb-10W-10Ta). The initial test of the model showed a strong correlation with empirical Varestraint data, i.e., a Spearman rank correlation between model predictions and hot cracking measurements was observed to be greater than 0.8. Following the validation, a set of refractory metal binary mixtures was investigated to evaluate sensitivity of Nb, Mo, W, and Ta to C, N, and O content. A series of plots were produced that suggest ppmw ranges of C, N, and O where solidification cracking increases significantly and reaches a maximum. Also comparative ranking of each primary refractory metal to each interstitial was produced. For example C produces greater cracking response in Mo whereas O produces greater cracking response in Ta and Nb. Such compositional values have utility in setting limits on pickup of these interstitial elements during welding and printing rather than using a one-size-fits-all approach. Furthermore, the results have use in determining additive powder recycling requirements, which is especially pertinent for refractory metal powders due to their high cost compared to conventional alloys. Another application created thousands of hypothetical alloys within the nominal specified composition range of two widely used refractory alloys C103 (Nb-10Hf-1Ti) and TZM (Mo-0.5Ti-0.1Zr). The cracking index was calculated for the alloys and results were fed into machine learning regression techniques including Multiple Linear Regression, Ridge Regression, and Lasso Regression to determine relative potency each alloying element had on computed solidification cracking index. A series of linear equations were produced that relate composition of C103 and TZM to solidification cracking index. The crack susceptibility of C103 for example is described by an equation of the form: cracking index ~ O + 0.667*C + 0.635*N + 0.00037*Ta – 0.0008*Hf (in wt.%) From that equation, it is clear that O has strong propensity to induce solidification cracking. Interestingly, Hf is shown to reduce calculated cracking response. Finally, realizing the potential of this method to discover new refractory alloy formulations across the period table that have low solidification cracking sensitivity, the code was applied to new untested alloy systems including W-Zr-C, W-Ta-C, and others. Conclusions. In summary, an open source numerical method has been developed using Python code to calculate Kou’s crack susceptibility index. The method was applied to refractory metals which are inherently difficult to study from a weldability testing standpoint since inert shielding gas is not sufficient and welding is typically done in vacuum, especially in light of findings presented here where oxygen has profound influence on solidification cracking. This work revealed the effect of compositional variations on a series of refractory metals and showed the framework defined here will be useful in 1) the development of new alloys that have improved weldability and 3D printability, 2) placing compositional limits on existing alloys, and 3) ensuring adequate controls of manufacturing processes such as 3D printing where powder reuse is critical. Keywords. pycalphad; Python; refractory metals; solidification cracking. References. B. Bocklund et. al. (2020) http://doi.org/10.5281/zenodo.3630657. S. Kou. (2015) https://doi.org/10.1016/j.actamat.2015.01.034. G.G. Lessmann and R.E. Gold. Welding Journal, issue 1, pp. 1-s – 8-s (1971). F.N. Michael and J.W. Sowards. NASA/TM-20230002218 (2023). R. Otis and Z.-K. Liu. (2017) http://doi.org/10.5334/jors.140. A. Van de Wallle et. al. (2018) https://doi.org/10.1016/j.calphad.2018.04.003.

pycalphad↗
NASA NTRS2003

Computational And Experimental Studies Of Three-Dimensional Flame Spread Over Liquid Fuel Pools

Schiller, Ross, and Sirignano (1996) studied ignition and flame spread above liquid fuels initially below the flashpoint temperature by using a two-dimensional computational fluid dynamics code that solves the coupled equations of both the gas and the liquid phases. Pulsating flame spread was attributed to the establishment of a gas-phase recirculation cell that forms just ahead of the flame leading edge because of the opposing effect of buoyancy-driven flow in the gas phase and the thermocapillary-driven flow in the liquid phase. Schiller and Sirignano (1996) extended the same study to include flame spread with forced opposed flow in the gas phase. A transitional flow velocity was found above which an originally uniform spreading flame pulsates. The same type of gas-phase recirculation cell caused by the combination of forced opposed flow, buoyancy-driven flow, and thermocapillary-driven concurrent flow was responsible for the pulsating flame spread. Ross and Miller (1998) and Miller and Ross (1998) performed experimental work that corroborates the computational findings of Schiller, Ross, and Sirignano (1996) and Schiller and Sirignano (1996). Cai, Liu, and Sirignano (2002) developed a more comprehensive three-dimensional model and computer code for the flame spread problem. Many improvements in modeling and numerical algorithms were incorporated in the three-dimensional model. Pools of finite width and length were studied in air channels of prescribed height and width. Significant three-dimensional effects around and along the pool edge were observed. The same three-dimensional code is used to study the detailed effects of pool depth, pool width, opposed air flow velocity, and different levels of air oxygen concentration (Cai, Liu, and Sirignano, 2003). Significant three-dimensional effects showing an unsteady wavy flame front for cases of wide pool width are found for the first time in computation, after being noted previously by experimental observers (Ross and Miller, 1999). Regions of uniform and pulsating flame spread are mapped for the flow conditions of pool depth, opposed flow velocity, initial pool temperature, and air oxygen concentration under both normal and microgravity conditions. Details can be found in Cai et al. (2002, 2003). Experimental results recently performed at NASA Glenn of flame spread across a wide, shallow pool as a function of liquid temperature are also presented here.

Ross, Howard D.↗
NASA NTRS1992

A technique for measuring vertically and horizontally polarized microwave brightness temperatures using electronic polarization-basis rotation

This technique for electronically rotating the polarization basis of an orthogonal-linear polarization radiometer is based on the measurement of the first three feedhorn Stokes parameters, along with the subsequent transformation of this measured Stokes vector into a rotated coordinate frame. The technique requires an accurate measurement of the cross-correlation between the two orthogonal feedhorn modes, for which an innovative polarized calibration load was developed. The experimental portion of this investigation consisted of a proof of concept demonstration of the technique of electronic polarization basis rotation (EPBR) using a ground based 90-GHz dual orthogonal-linear polarization radiometer. Practical calibration algorithms for ground-, aircraft-, and space-based instruments were identified and tested. The theoretical effort consisted of radiative transfer modeling using the planar-stratified numerical model described in Gasiewski and Staelin (1990).

Gasiewski, Albin J.↗
NASA NTRS1981

Observation of sea ice properties with the Nimbus-7 SMMR

Techniques for treating Nimbus-7 scanning multispectral microwave radiometer (SMMR) data to retrieve information on sea ice parameters are discussed. The SMMR produces information on ice concentration, temperature, multiyear ice fraction, thin ice fraction, difference between thin and thick ice temperatures, and atmospheric opacity. Sea ice emissivities as determined from ground truth and Nimbus-7 SMMR observations are provided, noting the necessity to further characterize the values with a larger data base. It was found that longest wavelengths displayed the largest contrast between open water and sea. Ice emissivity polarization differences are no more than 0.15 at any wavelength, while water polarizations are never less than 0.52. Ice emissivity increases directly with wavelength, and water emissivity increases inversely. Algorithmic representations of SMMR data to retrieve sea ice parameters are described.

Cavalieri, D. J.↗
NASA NTRS1983

Satellite remote sensing of meteorological parameters

Recent advances in remote atmospheric sensing are briefly reviewed, with particular attention given to vertical temperature and humidity profiles, cloud structure, and wind. Present capabilities and projections of future improvements in accuracy and resolution are given for the Microwave Sounding Unit, High Resolution Infrared Sounder, Defence Meteorological Satellite Project, and VISSR Atmospheric Sounder. It is noted that future sounding systems will require (1) high spectral resolution; (2) multispectral observations of the atmosphere and the surface in order to correct for most of the geophysical processes contaminating the outgoing radiance; and (3) a control algorithm capable of using information from multispectral channels to identify those parameters that have errors larger than a specified value.

Chahine, M. T.↗
NASA NTRS2002

Using Clustering to Establish Climate Regimes from PCM Output

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Oglesby, Robert↗
NASA NTRS2013

An Approach to Detect and Mitigate Ice Particle Accretion in Aircraft Engine Compression Systems

The accretion of ice in the compression system of commercial gas turbine engines operating in high ice water content conditions is a safety issue being studied by the aviation sector. While most of the research focuses on the underlying physics of ice accretion and the meteorological conditions in which accretion can occur, a systems-level perspective on the topic lends itself to potential near-term operational improvements. This work focuses on developing an accurate and reliable algorithm for detecting the accretion of ice in the low pressure compressor of a generic 40,000 lbf thrust class engine. The algorithm uses only the two shaft speed sensors and works regardless of engine age, operating condition, and power level. In a 10,000-case Monte Carlo simulation, the detection approach was found to have excellent capability at determining ice accretion from sensor noise with detection occurring when ice blocks an average of 6.8 percent of the low pressure compressor area. Finally, an initial study highlights a potential mitigation strategy that uses the existing engine actuators to raise the temperature in the low pressure compressor in an effort to reduce the rate at which ice accretes.

May, Ryan D.↗
NASA NTRS1988

Relations between VAS physical retrievals and their first guess input

The Smith (1983) physical retrieval algorithm, which is designed to yield mesoscale soundings through a blending of first-guess limited fine mesh-derived profiles with VISSR Atmospheric Sounder (VAS) detected radiance data by means of an inversion of the radiative transfer equation, yields retrievals that may be better related to ground truth data than the guess profiles at some levels. At other levels, the first-guess profiles were slightly superior to the retrievals. Correlation functions related to the window and midtropospheric temperature channels indicate that magnitudes and orientations of retrieval gradients were intermediate to those of the guess data and brightness temperatures.

Beven, John L.↗
NASA NTRS1995

The Atmospheric Data Acquisition And Interpolation Process For Center-TRACON Automation System

The Center-TRACON Automation System (CTAS), an advanced new air traffic automation program, requires knowledge of spatial and temporal atmospheric conditions such as the wind speed and direction, the temperature and the pressure in order to accurately predict aircraft trajectories. Real-time atmospheric data is available in a grid format so that CTAS must interpolate between the grid points to estimate the atmospheric parameter values. The atmospheric data grid is generally not in the same coordinate system as that used by CTAS so that coordinate conversions are required. Both the interpolation and coordinate conversion processes can introduce errors into the atmospheric data and reduce interpolation accuracy. More accurate algorithms may be computationally expensive or may require a prohibitively large amount of data storage capacity so that trade-offs must be made between accuracy and the available computational and data storage resources. The atmospheric data acquisition and processing employed by CTAS will be outlined in this report. The effects of atmospheric data processing on CTAS trajectory prediction will also be analyzed, and several examples of the trajectory prediction process will be given.

Jardin, M. R.↗
NASA NTRSDate not supplied

Comparing Tropopause-Penetrating Convection Identifications Derived from NEXRAD and GOES over the Contiguous United States

Overshooting cloud tops (OTs) are a result of powerful updrafts that rapidly transport air from the troposphere to the lower stratosphere. Aside from the well-known relationships between strong updrafts and severe weather, the boundaries of updrafts, including the OT, are turbulent, which leads to irreversible mixing of air between the stratosphere and troposphere, altering the composition of both layers. In order to better understand the impact of OTs, knowing precisely when and where they occur is vital. Within the last decade remote-sensing observations from satellites and radars have been used to identify OTs, but the results thus far have not been entirely consistent due to challenges with accurately identifying OTs with these sensor datasets. This study compares OTs identified using NEXRAD reflectivity data from the GridRad dataset with an approach that uses GOES infrared (IR) data. The GridRad method estimates the altitude of echo tops directly from the radar pointing geometry, merging a combination of radars that enables products every 5 mins, with 2 km spatial and 1 km vertical grid spacing. The GOES satellite method uses spatial patterns in tropopause-relative IR brightness temperature to derive an OT likelihood. The study region covers a large part of the contiguous United States during selected active convection dates in 2017 and includes data from GOES-13/16. A large sample of OTs observed by NEXRAD and GOES-13/16 satellites are analyzed to better understand NEXRAD and IR observations of OTs, quantify agreement between the OT detection methods, and demonstrate how the 4x increase in spatial resolution from GOES-13 to GOES-16 impacts OT algorithm detection performance. The results show that for nearly time-matched scenes, with many severe storms, GOES-13 and -16 detection accuracy is quite comparable; however, some missed detections are attributed to poorer GOES-13 image resolution. It was found that GOES-13 OT regions are ~2 K warmer than GOES-16 on average, but such differences exceed 5 K for the most intense OT regions. It is found that false GOES IR-based detections are unavoidable, given that cold cloud pixels significantly colder than the tropopause from nearby or recently decayed OTs can persist within anvils for 15 minutes or more.

John W. Cooney↗
NASA NTRSDate not supplied

Initial Exploratory Study of the Impacts of Climate Change on Air Traffic Operations

Climate change is already happening and is projected to accelerate in the future. It will persist for the foreseeable future, even with optimistic projections of technological advances and behavior changes. It will make aviation more and more challenging over time. Among other things, it is expected to cause increased severe weather, more extreme temperatures, and rising sea levels that constrain when, where, and how aircraft can fly. NASA has many prior, ongoing, and upcoming efforts towards mitigating the impacts of aviation on climate change. There is also a need to perform a comprehensive investigation of the reverse: that is, the impacts of climate change on aviation. This is an initial exploratory study on this topic utilizing the NAS Digital Twin—composed of the ATM TestBed simulation platform and NAS Digital Twin airspace management algorithms—to run NAS-wide simulations with Convective Weather Avoidance Model polygons at different avoidance thresholds to emulate the increase in severe weather that could manifest due to climate change. It was found that air traffic management may be able to limit the impact of climate change in terms of delay and fuel burn. However, increased severe weather due to climate change can make separation—particularly, aircraft-to-weather separation—more challenging by reducing available airspace and constraining the solution space. Challenging situations were identified and corresponding potential solutions were proposed towards ensuring air traffic operations continue to be robust and resilient to the impacts of increased severe weather due to climate change.

climate change, weather, air traffic operations↗
NASA NTRS1978

The simultaneous inference of stratospheric trace gases with overlapping spectral signatures using limb sounding radiometry

An inversion algorithm has been developed to simultaneously infer the concentrations of two gases with overlapping spectral signatures using limb emission measurements. The algorithm is efficient and provides a solution in two or three iterations. It has been applied in a simulation study to the inference of stratospheric NO2-H2O and HNO3-CF2Cl2. Existing satellite instrumentation was the basis for errors used in the calculations. It is estimated that concentrations of all four gases can be determined with errors of about 20 percent. This assumes an estimated 1980 CF2Cl2 level. Also, other error sources due to contaminant gas, aerosol emission, and the temperature profile must be included to obtain a better estimate of experimental accuracies.

Russell, J. M., III↗
NASA NTRS1983

Satellite microwave radiances correlated with radar rain rates over land

The characteristics of upwelling microwave radiation from raindrops as measured by satellite sensors are examined. The scanning multichannel microwave radiometers on board the Nimbus 7 and Seasat satellites have the capability of quantifying the perpendicularly polarized antenna temperatures at 37, 21, 18, 10.7, and 6.6 GHz. The instruments scan the earth at a constant 50 deg angle to the surface with a footprint that varies from 20-70 km. Radar rainfall measurements have an accuracy of within 60 percent, whereas a series of test measurements using SMMR data in comparison with radar data for rainfall in the same areas showed that the microwave data depicted rainfall rates with less than 1.55 mm/h error. Details of the rainfall rate algorithms used to treat the satellite microwave data are provided, noting that the identification of rainfall rates is dependent on quantifying the amount the upwelling radiance is reduced due to rainfall.

Spencer, R. W.↗
NASA NTRS1986

Engineering description of the ascent/descent bet product

The Ascent/Descent output product is produced in the OPIP routine from three files which constitute its input. One of these, OPIP.IN, contains mission specific parameters. Meteorological data, such as atmospheric wind velocities, temperatures, and density, are obtained from the second file, the Corrected Meteorological Data File (METDATA). The third file is the TRJATTDATA file which contains the time-tagged state vectors that combine trajectory information from the Best Estimate of Trajectory (BET) filter, LBRET5, and Best Estimate of Attitude (BEA) derived from IMU telemetry. Each term in the two output data files (BETDATA and the Navigation Block, or NAVBLK) are defined. The description of the BETDATA file includes an outline of the algorithm used to calculate each term. To facilitate describing the algorithms, a nomenclature is defined. The description of the nomenclature includes a definition of the coordinate systems used. The NAVBLK file contains navigation input parameters. Each term in NAVBLK is defined and its source is listed. The production of NAVBLK requires only two computational algorithms. These two algorithms, which compute the terms DELTA and RSUBO, are described. Finally, the distribution of data in the NAVBLK records is listed.

Seacord, A. W., II↗
NASA NTRS2004

Seasonal Surface Spectral Emissivity Derived from Terra MODIS Data

The CERES (Clouds and the Earth's Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties form various images to produce a combined global radiation and cloud property data set. In this paper, simultaneous data from Terra MODIS (Moderate Resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 11.0, and 12.0 m are used to derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of clear sky temperature in each channel determined by scene classification during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7- m radiances. A set of simultaneous equations is then solved to derive the emissivities. Global monthly emissivity maps are derived from Terra MODIS data while numerical weather analyses provide soundings for correcting the observed radiances for atmospheric absorption. These maps are used by CERES and other cloud retrieval algorithms.

Sun-Mack, Sunny↗
NASA NTRS2017

AMSR2 Soil Moisture Product Validation

The Advanced Microwave Scanning Radiometer 2 (AMSR2) is part of the Global Change Observation Mission-Water (GCOM-W) mission. AMSR2 fills the void left by the loss of the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) after almost 10 years. Both missions provide brightness temperature observations that are used to retrieve soil moisture. Merging AMSR-E and AMSR2 will help build a consistent long-term dataset. Before tackling the integration of AMSR-E and AMSR2 it is necessary to conduct a thorough validation and assessment of the AMSR2 soil moisture products. This study focuses on validation of the AMSR2 soil moisture products by comparison with in situ reference data from a set of core validation sites. Three products that rely on different algorithms were evaluated; the JAXA Soil Moisture Algorithm (JAXA), the Land Parameter Retrieval Model (LPRM), and the Single Channel Algorithm (SCA). Results indicate that overall the SCA has the best performance based upon the metrics considered.

microwave↗