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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
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NASA NTRS1990

Estimated accuracy of ground-based liquid water measurements during FIRE

Since on goal of the First ISCCP Regional Experiment (FIRE) project is to improve our understanding of the relationships between cloud microphysics and cloud reflectivity, it is important that the accuracy of remote liquid measurements by microwave radiometry be thoroughly understood. The question is particularly relevant since the uncertainty in the absolute value of the radiometric liquid measurement is greatest at low liquid water contents (less than 0.1 mm). However it should be stressed that although uncertainty exists in the absolute value of liquid, it is well known that the observed radiometric signal is proportional to the amount of liquid in the antenna beam. As a result, changes in amounts of liquid are known to greater accuracy than the absolute value, which may contain a bias. Here, an assessment of the liquid measurement accuracy attained at San Nicolas Island (SNI) is presented. The vapor and liquid water data shown were computed from the radiometric brightness temperatures using statistical retrieval algorithms. The retrieval coefficients were derived from the 69 soundings made by Colorado State University during the SNI observations. Sources of error in the vapor and liquid measurements include cross-talk in the retrieval algorithms (not a factor at low liquid contents), uncertainties in the brightness temperature measurement, and uncertainties in the vapor and liquid attenuation coefficients. The relative importance of these errors is discussed. For the retrieval of path-integrated liquid water, the greatest uncertainty is caused by the temperature dependence of the absorption at microwave frequencies. As a result, the accuracy of statistical retrieval of liquid depends to large measure upon how representative the a priori radiosonde data are of the conditions prevailing during the measurements. The microwave radiometer measurements at SNI were supplemented by an infrared (IR) radiometer modified for measurement of cloud-base temperature. Thus, the IR system provides the means to incorporate continuous measurements of the liquid temperature into the retrieval process.

Snider, Jack B.↗
NASA NTRS2008

Uncertainty Analysis of Air Radiation for Lunar Return Shock Layers

By leveraging a new uncertainty markup technique, two risk analysis methods are used to compute the uncertainty of lunar-return shock layer radiation predicted by the High temperature Aerothermodynamic Radiation Algorithm (HARA). The effects of epistemic uncertainty, or uncertainty due to a lack of knowledge, is considered for the following modeling parameters: atomic line oscillator strengths, atomic line Stark broadening widths, atomic photoionization cross sections, negative ion photodetachment cross sections, molecular bands oscillator strengths, and electron impact excitation rates. First, a simplified shock layer problem consisting of two constant-property equilibrium layers is considered. The results of this simplified problem show that the atomic nitrogen oscillator strengths and Stark broadening widths in both the vacuum ultraviolet and infrared spectral regions, along with the negative ion continuum, are the dominant uncertainty contributors. Next, three variable property stagnation-line shock layer cases are analyzed: a typical lunar return case and two Fire II cases. For the near-equilibrium lunar return and Fire 1643-second cases, the resulting uncertainties are very similar to the simplified case. Conversely, the relatively nonequilibrium 1636-second case shows significantly larger influence from electron impact excitation rates of both atoms and molecules. For all cases, the total uncertainty in radiative heat flux to the wall due to epistemic uncertainty in modeling parameters is 30% as opposed to the erroneously-small uncertainty levels (plus or minus 6%) found when treating model parameter uncertainties as aleatory (due to chance) instead of epistemic (due to lack of knowledge).

Kleb, Bil↗
NASA NTRS2009

Integrity of the Plasma Magnetic Nozzle

This report examines the physics governing certain aspects of plasma propellant flow through a magnetic nozzle, specifically the integrity of the interface between the plasma and the nozzle s magnetic field. The injection of 100s of eV plasma into a magnetic flux nozzle that converts thermal energy into directed thrust is fundamental to enabling 10 000s of seconds specific impulse and 10s of kW/kg specific power piloted interplanetary propulsion. An expression for the initial thickness of the interface is derived and found to be approx.10(exp -2) m. An algorithm is reviewed and applied to compare classical resistivity to gradient-driven microturbulent (anomalous) resistivity, in terms of the spatial rate and time integral of resistive interface broadening, which can then be related to the geometry of the nozzle. An algorithm characterizing plasma temperature, density, and velocity dependencies is derived and found to be comparable to classical resistivity at local plasma temperatures of approx. 200 eV. Macroscopic flute-mode instabilities in regions of "adverse magnetic curvature" are discussed; a growth rate formula is derived and found to be one to two e-foldings of the most unstable Rayleigh-Taylor (RT) mode. After establishing the necessity of incorporating the Hall effect into Ohm s law (allowing full Hall current to flow and concomitant plasma rotation), a critical nozzle length expression is derived in which the interface thickness is limited to about 1 ion gyroradius.

Gerwin, Richard A.↗
NASA NTRS2010

Heat Flux and Wall Temperature Estimates for the NASA Langley HIFiRE Direct Connect Rig

An objective of the Hypersonic International Flight Research Experimentation (HIFiRE) Program Flight 2 is to provide validation data for high enthalpy scramjet prediction tools through a single flight test and accompanying ground tests of the HIFiRE Direct Connect Rig (HDCR) tested in the NASA LaRC Arc Heated Scramjet Test Facility (AHSTF). The HDCR is a full-scale, copper heat sink structure designed to simulate the isolator entrance conditions and isolator, pilot, and combustor section of the HIFiRE flight test experiment flowpath and is fully instrumented to assess combustion performance over a range of operating conditions simulating flight from Mach 5.5 to 8.5 and for various fueling schemes. As part of the instrumentation package, temperature and heat flux sensors were provided along the flowpath surface and also imbedded in the structure. The purpose of this paper is to demonstrate that the surface heat flux and wall temperature of the Zirconia coated copper wall can be obtained with a water-cooled heat flux gage and a sub-surface temperature measurement. An algorithm was developed which used these two measurements to reconstruct the surface conditions along the flowpath. Determinations of the surface conditions of the Zirconia coating were conducted for a variety of conditions.

Cuda, Vincent, Jr.↗
NASA NTRS2012

Synegies Between Visible/Near-Infrared Imaging Spectrometry and the Thermal Infrared in an Urban Environment: An Evaluation of the Hyperspectral Infrared Imager (HYSPIRI) Mission

A majority of the human population lives in urban areas and as such, the quality of urban environments is becoming increasingly important to the human population. Furthermore, these areas are major sources of environmental contaminants and sinks of energy and materials. Remote sensing provides an improved understanding of urban areas and their impacts by mapping urban extent, urban composition (vegetation and impervious cover fractions), and urban radiation balance through measures of albedo, emissivity and land surface temperature (LST). Recently, the National Research Council (NRC) completed an assessment of remote sensing needs for the next decade (NRC, 2007), proposing several missions suitable for urban studies, including a visible, near-infrared and shortwave infrared (VSWIR) imaging spectrometer and a multispectral thermal infrared (TIR) instrument called the Hyperspectral Infrared Imagery (HyspIRI). In this talk, we introduce the HyspIRI mission, focusing on potential synergies between VSWIR and TIR data in an urban area. We evaluate potential synergies using an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and MODIS-ASTER (MASTER) image pair acquired over Santa Barbara, United States. AVIRIS data were analyzed at their native spatial resolutions (7.5m VSWIR and 15m TIR), and aggregated 60 m spatial resolution similar to HyspIRI. Surface reflectance was calculated using ACORN and a ground reflectance target to remove atmospheric and sensor artifacts. MASTER data were processed to generate estimates of spectral emissivity and LST using Modtran radiative transfer code and the ASTER Temperature Emissivity Separation algorithm. A spectral library of common urban materials, including urban vegetation, roofs and roads was assembled from combined AVIRIS and field-measured reflectance spectra. LST and emissivity were also retrieved from MASTER and reflectance/emissivity spectra for a subset of urban materials were retrieved from co-located MASTER and AVIRIS pixels. Fractions of Impervious, Soil, Green Vegetation (GV) and Non-photosynthetic Vegetation (NPV), were estimated using Multiple Endmember Spectral Mixture Analysis (MESMA) applied to AVIRIS data at 7.5, 15 and 60 m spatial scales. Surface energy parameters, including albedo, vegetation cover fraction, broadband emissivity and LST were also determined for urban and natural land-cover classes in the region. Fractions were validated using 1m digital photography.

Roberts, Dar A.↗
NASA NTRS2017

Validation of Globsnow-2 Snow Water Equivalent Over Eastern Canada

In Qubec, Eastern Canada, snowmelt runoff contributes more than 30% of the annual energy reserve for hydroelectricity production, and uncertainties in annual maximum snow water equivalent (SWE) over the region are one of the main constraints for improved hydrological forecasting. Current satellite-based methods for mapping SWE over Qubec's main hydropower basins do not meet Hydro-Qubec operational requirements for SWE accuracies with less than 15% error. This paper assesses the accuracy of the GlobSnow-2 (GS-2) SWE product, which combines microwave satellite data and in situ measurements, for hydrological applications in Qubec. GS-2 SWE values for a 30-year period (1980 to 2009) were compared with space- and time-matched values from a comprehensive dataset of in situ SWE measurements (a total of 38,990 observations in Eastern Canada). The root mean square error (RMSE) of the GS-2 SWE product is 94.1+/- 20.3 mm, corresponding to an overall relative percentage error (RPE) of 35.9%. The main sources of uncertainty are wet and deep snow conditions (when SWE is higher than 150 mm), and forest cover type. However, compared to a typical stand-alone brightness temperature channel difference algorithm, the assimilation of surface information in the GS-2 algorithm clearly improves SWE accuracy by reducing the RPE by about 30%. Comparison of trends in annual mean and maximum SWE between surface observations and GS-2 over 1980-2009 showed agreement for increasing trends over southern Qubec, but less agreement on the sign and magnitude of trends over northern Qubec. Extended at a continental scale, the GS-2 SWE trends highlight a strong regional variability.

Snow water equivalent↗
NASA NTRS2019

Evaporation from the Southern Ocean Estimated on the Basis of AIRS Satellite Data

Evaporation plays an important role in the global water and energy cycles and, hence, in climate change. Evaporation over the Southern Ocean, where the Antarctic sea ice coverage has a large annual cycle, is poorly quantified. In this study, daily evaporation is estimated for the Southern Ocean with a sea‐ice‐specific algorithm, using surface temperature and air humidity from National Aeronautics and Space Administration's Atmospheric Infrared Sounder (AIRS), and wind speeds from Modern‐Era Retrospective Analysis for Research and Applications, Version 2 (MERRA‐2), reanalysis during 2003–2016. An uncertainty of 34% was found in the evaporation product. The results indicate that annual evaporation has considerable interannual and regional variability, but with a decreasing trend during the study period over most of the Southern Ocean. There are, however, areas where evaporation has increased, specifically in the Ross Sea in winter and summer, with smaller positive trends in spring and fall. Overall, the changes in the difference between the surface specific humidity and the air specific humidity, and to a much lesser extent in the wind speed, are the main drivers for the changes in evaporation throughout the year. During spring and fall months, changes to the sea ice cover, which alter the surface specific humidity, are the main drivers for the change, but in summer and winter the main driver is the air‐specific humidity. Air masses originating from the Antarctic continent (south) are associated with cold and dry conditions, which increase evaporation, whereas air masses from lower latitudes in the Southern Ocean (north) are associated with warm and moist conditions, decreasing evaporation. Comparisons with other reanalysis evaporation products produce similar trends, although annual averages differ.

Boisvert, Linette↗
NASA NTRSDate not supplied

TPSAS-NF1676L-31179-DND

This presentation will brief the GEWEX Radiation Panel on the progress and results of the GEWEX SRB project during the last year toward production and assessment of the Release 4.0 data set. First, an update is presented regarding SRB Release 4.0 "Integrated Product" that produces consistent with GEWEX projects estimating land and ocean latent and sensible heat fluxes. Changes from the Release 3/3.1 data products to Release 4 are reviewed both for key inputs (such as the ISCCP HXS, the nn-HIRS, Land and Sea surface temperatures) and key algorithm changes. Differences between the old and new input properties are assessed and flux sensitivities to those inputs are summarized. Sample radiative flux data products are presented and compared against the previous version for span of the production run, currently from 1998 through 2012. These fluxes are also compared to surface measurements (i.e., BSRN) and CERES (Clouds and Earth's Radiant Energy System) data products both in terms of bulk statistics and also time series variability. Lastly, the plans for continued processing, archival, assessment and research and will be presented to the panel for discussion and feedback.

Paul W Stackhouse, Jr↗
NASA NTRS2012

The Aquarius Salinity Retrieval Algorithm

The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration [2] converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to molecular oxygen, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind, which is addressed in more detail in section 3. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water [3], [4] and an auxiliary field for the sea surface temperature. In the current processing only v-pol TB are used for this last step.

Meissner, Thomas↗
NASA NTRS1993

Atmospheric parameterization schemes for satellite cloud property retrieval during FIRE IFO 2

Satellite cloud retrieval algorithms generally require atmospheric temperature and humidity profiles to determine such cloud properties as pressure and height. For instance, the CO2 slicing technique called the ratio method requires the calculation of theoretical upwelling radiances both at the surface and a prescribed number (40) of atmospheric levels. This technique has been applied to data from, for example, the High Resolution Infrared Radiometer Sounder (HIRS/2, henceforth HIRS) flown aboard the NOAA series of polar orbiting satellites and the High Resolution Interferometer Sounder (HIS). In this particular study, four NOAA-11 HIRS channels in the 15-micron region are used. The ratio method may be applied to various channel combinations to estimate cloud top heights using channels in the 15-mu m region. Presently, the multispectral, multiresolution (MSMR) scheme uses 4 HIRS channel combination estimates for mid- to high-level cloud pressure retrieval and Advanced Very High Resolution Radiometer (AVHRR) data for low-level (is greater than 700 mb) cloud level retrieval. In order to determine theoretical upwelling radiances, atmospheric temperature and water vapor profiles must be provided as well as profiles of other radiatively important gas absorber constituents such as CO2, O3, and CH4. The assumed temperature and humidity profiles have a large effect on transmittance and radiance profiles, which in turn are used with HIRS data to calculate cloud pressure, and thus cloud height and temperature. For large spatial scale satellite data analysis, atmospheric parameterization schemes for cloud retrieval algorithms are usually based on a gridded product such as that provided by the European Center for Medium Range Weather Forecasting (ECMWF) or the National Meteorological Center (NMC). These global, gridded products prescribe temperature and humidity profiles for a limited number of pressure levels (up to 14) in a vertical atmospheric column. The FIRE IFO 2 experiment provides an opportunity to investigate current atmospheric profile parameterization schemes, compare satellite cloud height results using both gridded products (ECMWF) and high vertical resolution sonde data from the National Weather Service (NWS) and Cross Chain Loran Atmospheric Sounding System (CLASS), and suggest modifications in atmospheric parameterization schemes based on these results.

Titlow, James↗
NASA NTRS2012

Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations

Several L-band microwave radiometer and radar missions have been, or will be, operating in space for land and ocean observations. These include the NASA Aquarius mission and the Soil Moisture Active Passive (SMAP) mission, both of which use combined passive/ active L-band instruments. Aquarius s passive/active L-band microwave sensor has been designed to map the salinity field at the surface of the ocean from space. SMAP s primary objectives are for soil moisture and freeze/thaw detection, but it will operate continuously over the ocean, and hence will have significant potential for ocean surface research. In this innovation, an algorithm has been developed to retrieve simultaneously ocean surface salinity and wind from combined passive/active L-band microwave observations of sea surfaces. The algorithm takes advantage of the differing response of brightness temperatures and radar backscatter to salinity, wind speed, and direction, thus minimizing the least squares error (LSE) measure, which signifies the difference between measurements and model functions of brightness temperatures and radar backscatter. The algorithm uses the conjugate gradient method to search for the local minima of the LSE. Three LSE measures with different measurement combinations have been tested. The first LSE measure uses passive microwave data only with retrieval errors reaching 1 to 2 psu (practical salinity units) for salinity, and 1 to 2 m/s for wind speed. The second LSE measure uses both passive and active microwave data for vertical and horizontal polarizations. The addition of active microwave data significantly improves the retrieval accuracy by about a factor of five. To mitigate the impact of Faraday rotation on satellite observations, the third LSE measure uses measurement combinations invariant under the Faraday rotation. For Aquarius, the expected RMS SSS (sea surface salinity) error will be less than about 0.2 psu for low winds, and increases to 0.3 psu at 25 m/s wind speed for warm waters (25 C). To achieve the required 0.2 psu accuracy, the impact of sea surface roughness (e.g. wind-generated ripples) on the observed brightness temperature has to be corrected to better than one tenth of a degree Kelvin. With this algorithm, the accuracy of retrieved wind speed will be high, varying from a few tenths to 0.6 m/s. The expected direction accuracy is also excellent (less than 10 ) for mid to high winds, but degrades for lower speeds (less than 7 m/s).

Yueh, Simon H.↗
NASA NTRS1981

Remote sensing of soil moisture content over bare field at 1.4 GHz frequency

An algorithm for estimating moisture content of a bare soil from the observed brightness temperature at 1.4 GHz is discussed and applied to a limited data base. The method is based on a radiative transfer model calculation, which has been successfully used in the past to account for many observational results, with some modifications to take into account the effect of surface roughness. Besides the measured brightness temperatures, the three additional inputs required by the method are the effective soil thermodynamic temperature, the precise relation between moisture content and the smooth field brightness temperatures and a pair of parameters related to surface roughness. The procedures of estimating surface roughness parameters and of obtaining moisture content from observed brightness temperature are discussed. The algorithm is applied to observations from truck mounted and airborne radiometers. The estimated moisture contents compare favorably with the observations in the top 2 cm layer.

Wang, J. R.↗
NASA NTRS2016

A New Operational Snow Retrieval Algorithm Applied to Historical AMSR-E Brightness Temperatures

Snow is a key element of the water and energy cycles and the knowledge of spatio-temporal distribution of snow depth and snow water equivalent (SWE) is fundamental for hydrological and climatological applications. SWE and snow depth estimates can be obtained from spaceborne microwave brightness temperatures at global scale and high temporal resolution (daily). In this regard, the data recorded by the Advanced Microwave Scanning Radiometer-Earth Orbiting System (EOS) (AMSR-E) onboard the National Aeronautics and Space Administration's (NASA) AQUA spacecraft have been used to generate operational estimates of SWE and snow depth, complementing estimates generated with other microwave sensors flying on other platforms. In this study, we report the results concerning the development and assessment of a new operational algorithm applied to historical AMSR-E data. The new algorithm here proposed makes use of climatological data, electromagnetic modeling and artificial neural networks for estimating snow depth as well as a spatio-temporal dynamic density scheme to convert snow depth to SWE. The outputs of the new algorithm are compared with those of the current AMSR-E operational algorithm as well as in-situ measurements and other operational snow products, specifically the Canadian Meteorological Center (CMC) and GlobSnow datasets. Our results show that the AMSR-E algorithm here proposed generally performs better than the operational one and addresses some major issues identified in the spatial distribution of snow depth fields associated with the evolution of effective grain size.

passive microwave↗
NASA NTRS1990

Edge detection applied to SST fields

An algorithm designed to detect fronts automatically in satellite-derived sea-surface temperature (SST) fields is presented. The algorithm is operated at different levels to detect and differentiate between false and true edges. For purposes of comparison, the algorithm is applied to a test set of 98 SST images to detect the northern edge of the Gulf Stream. The algorithm successfully detected valid temperature fronts and ignored false edges, and also produced statistics about the temperature fronts that are useful in the subsequent analysis of these fronts. It is assumed that the algorithm performs equally well on other SST fronts such as those associated with rings, the subtropical convergence, or the shelf/slope fronts.

Cayula, Jean-Francois↗
NASA NTRS2019

Seasonal Dependence of SMAP Radiometer-Based Soil Moisture Performance as Observed over Core Validation Sites

The NASA SMAP (Soil Moisture Active Passive) mission provides a global coverage of soil moisture measurements based on its L-band microwave radiometer every 2-3 days at about 40 km resolution. The soil moisture retrieval algorithms model the brightness temperature as a function of soil moisture, surface conditions and vegetation. External data sources inform the algorithms about the surface conditions and vegetation, which enable the retrieval of soil moisture. The inversion process contains uncertainties related to radiometer measurements, forward model assumptions and ancillary data sources. This study focuses on the uncertainties that depend on the seasonal evolution of the surface conditions and vegetation. This study compares the SMAP and core validation site (CVS) soil moisture values over a period of three years to extract the evolution of performance metrics over time. The analysis showed that most CVS that include managed agriculture exhibit significant time-dependent seasonal bias. This bias was linked to seasonal temperature cycle, which is a proxy to several features that can cause seasonally dependent errors in the SMAP product.

core validation site↗
NASA NTRSDate not supplied

Predicting Maximum Temperatures of a Li-ion Battery on a Simulated Flight Profile using a Model-based Prognostics

One of the challenges in using Li-ion packs in aeronautics is their safety, and thermal runaway (TR) is a major concern. The current engineering solutions to prevent a Li-ion pack from a catastrophic TR require additional mass and volume to isolate cells. The excess mass could be reduced by improving detection and, thus, preventing a TR event. One of the possible early warning indicators of a TR is crossing a threshold temperature. We have developed an approach, based on the Unscented Kalman Filter (UKF), to predict the likelihood of reaching the threshold temperature for simulated flight profiles. The current battery prognostics algorithms for aerospace predict state-of-charge (SOC) and end-of-life (EOL) [1]. We extended this two-level algorithm to predict the maximum temperature during discharge. The amount of heat generated in a cell depends on factors such as cell chemistry, cell packaging, total cycles, operating temperature, and abuse history [2]. Our semi-empirical thermal model depends on three phenomenological parameters which account for those factors. In addition, a two-parameter reduced-order model is developed to predict the temperature rise for short bursts of “random-walk” (RW) discharge current sequence, which simulates a flight's current-loading profile. The performance of these models on different datasets and types of current loading will be presented. To predict the maximal temperatures for future cycles we must estimate the evolution of thermal parameters as the batteries age. It is found that the parameters of the 3-parametric thermal model cannot be estimated only from the RW data. To address the issue, we will present two alternative approaches: i) expanding the datasets to include discharge profiles beyond RWs; ii) model reduction to a two-parametric model. The two approaches will be illustrated by an application to the cycling data from a commercial LG 18650 cell. References: 1. M. Daigle, C.S. Kulkarni, End-of-discharge and End-of-life Prediction in Lithium-ion Batteries with Electrochemistry-based Aging Models, in: AIAA Infotech @ Aerospace, American Institute of Aeronautics and Astronautics, San Diego, California, USA, 2016. 2. M. Börner, et. al, Correlation of aging and thermal stability of commercial 18650-type lithium ion batteries, Journal of Power Sources. 342 (2017) 382–392.

Thermal runaway↗
NASA NTRSDate not supplied

Climate Fingerprinting Sounder Product (ClimFiSP) Skin Temperature Trends Analysis

Climate fingerprinting Sounder Product (ClimFiSP) has been developed at NASA Langley Research Center which includes daily skin temperature, surface emissivity, air temperature, H2O, trace gases, and cloud properties on 0.5x0.5 grid. Those properties are derived from IR hyper-spectral radiance measured by AIRS on Aqua and CrIS on SNPP and JPSS series. Global skin temperature trends have been derived using more than 20 years of monthly mean skin temperature data from ClimFiSP. The ClimFiSP algorithm use the spectral fingerprinting methodology that allows a low latency procession of more than two decades long satellite data record. The computational cost can be reduced by more than two orders of magnitude as compared with traditional Level-Level2-Level3 retrieval algorithms. In this presentation the global skin temperature trend from ClimFiSP will be compared with skin temperature trend derived from CLIMCAPS, ERA5, GISTEMP, HadCRUT5, and IASI data products, and the results show that pattern of ClimFiSP global skin temperature trends overall matches well with other datasets. The zonally averaged skin temperature anomaly will also be validated using those datasets. It is expected that ClimFiSP surface temperature data can serve as an important complement for surface-based estimates, especially in the regions where the spatial coverage of the surface-based observations is scarce.

Liqiao Lei↗
NASA NTRS1983

Sea surface temperatures from the Nimbus-7 scanning multichannel microwave radiometer

The algorithm was developed to determine sea surface temperature (SST) from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) data. The SST algorithm has evolved over the last several years. The final version that will be applied to the 1979 SMMR data (more tuning may be needed for later data) is described. Four different stages in the development are reported: Versions I to IV; each version has evolved out of its predecessor either because newly processed data became available or because significant problems were uncovered in earlier versions.

Milman, A. S.↗