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NASA NTRS2010

Use of Quality Controlled AIRS Temperature Soundings to Improve Forecast Skill

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. Also included are the clear column radiances used to derive these products which are representative of the radiances AIRS would have seen if there were no clouds in the field of view. All products also have error estimates. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20 percent, in cases with up to 90 percent effective cloud cover. The products are designed for data assimilation purposes for the improvement of numerical weather prediction, as well as for the study of climate and meteorological processes. With regard to data assimilation, one can use either the products themselves or the clear column radiances from which the products were derived. The AIRS Version 5 retrieval algorithm is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates for retrieved quantities and clear column radiances, and the use of these error estimates for Quality Control. The temperature profile error estimates are used to determine a case-by-case characteristic pressure pbest, down to which the profile is considered acceptable for data assimilation purposes. The characteristic pressure p(sub best) is determined by comparing the case dependent error estimate (delta)T(p) to the threshold values (Delta)T(p). The AIRS Version 5 data set provides error estimates of T(p) at all levels, and also profile dependent values of pbest based on use of a Standard profile dependent threshold (Delta)T(p). These Standard thresholds were designed as a compromise between optimal use for data assimilation purposes, which requires highest accuracy (tighter Quality Control), and climate purposes, which requires more spatial coverage (looser Quality Control). Subsequent research using Version 5 sounding and error estimates showed that tighter Quality Control performs better for data assimilation proposes, while looser Quality Control better spatial coverage) performs better for climate purposes. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 degree latitude x 0.67 degree longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates (delta)T(p) were used as the uncertainty for each measurement in the data assimilation process.

Susskind, Joel↗

NASA NTRS2010

Improving Forecast Skill by Assimilation of AIRS Temperature Soundings

Susskind, Joel↗

NASA NTRS2012

Global Assessment of Land Surface Temperature From Geostationary Satellites and Model Estimates

Land surface (or 'skin') temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research we compare two global and independent data sets: (i) LST retrievals from five geostationary satellites generated at the NASA Langley Research Center (LaRC) and (ii) LST estimates from the quasi-operational NASA GEOS-5 global modeling and assimilation system. The objective is to thoroughly understand both data sets and their systematic differences in preparation for the assimilation of the LaRC LST retrievals into GEOS-5. As expected, mean differences (MD) and root-mean-square differences (RMSD) between modeled and retrieved LST vary tremendously by region and time of day. Typical (absolute) MD values range from 1-3 K in Northern Hemisphere mid-latitude regions to near 10 K in regions where modeled clouds are unrealistic, for example in north-eastern Argentina, Uruguay, Paraguay, and southern Brazil. Typically, model estimates of LST are higher than satellite retrievals during the night and lower during the day. RMSD values range from 1-3 K during the night to 2-5 K during the day, but are larger over the 50-120 W longitude band where the LST retrievals are derived from the FY2E platform

Reichle, Rolf H.↗

NASA NTRS1999

Cardiopulmonary baroreceptor control of muscle sympathetic nerve activity in heat-stressed humans

Whole body heating decreases central venous pressure (CVP) while increasing muscle sympathetic nerve activity (MSNA). In normothermia, similar decreases in CVP elevate MSNA, presumably via cardiopulmonary baroreceptor unloading. The purpose of this project was to identify whether increases in MSNA during whole body heating could be attributed to cardiopulmonary baroreceptor unloading coincident with the thermal challenge. Seven subjects were exposed to whole body heating while sublingual temperature, skin blood flow, heart rate, arterial blood pressure, and MSNA were monitored. During the heat stress, 15 ml/kg warmed saline was infused intravenously over 7-10 min to increase CVP and load the cardiopulmonary baroreceptors. We reported previously that this amount of saline was sufficient to return CVP to pre-heat stress levels. Whole body heating increased MSNA from 25 +/- 3 to 39 +/- 3 bursts/min (P < 0. 05). Central blood volume expansion via rapid saline infusion did not significantly decrease MSNA (44 +/- 4 bursts/min, P > 0.05 relative to heat stress period) and did not alter mean arterial blood pressure (MAP) or pulse pressure. To identify whether arterial baroreceptor loading decreases MSNA during heat stress, in a separate protocol MAP was elevated via steady-state infusion of phenylephrine during whole body heating. Increasing MAP from 82 +/- 3 to 93 +/- 4 mmHg (P < 0.05) caused MSNA to decrease from 36 +/- 3 to 15 +/- 4 bursts/min (P < 0.05). These data suggest that cardiopulmonary baroreceptor unloading during passive heating is not the primary mechanism resulting in elevations in MSNA. Moreover, arterial baroreceptors remain capable of modulating MSNA during heat stress.

NASA Discipline Cardiopulmonary↗

NASA NTRS1993

AVHRR Surface Temperature and Narrow-Band Albedo Comparison with Ground Measurements for the Greenland Ice Sheet

An ice-surface temperature retrieval algorithm for the Greenland ice sheet was developed using NOAA 11 thermal radiances from channels 4 and 5. Temperature, pressure and humidity profiles, cloud observations and skin temperatures from the Swiss Federal Institute of Technology (ETH) camp, located at the equilibrium line altitude at 49 deg17 min W, 69 deg 34 min N, were used in the LOWTRAN 7 model. Through a statistical analysis of daily clear sky profiles, the coefficients that correct for the atmospheric effects were determined for the ETH-Camp field season (May to August). Surface temperatures retrieved by this method were then compared against the in situ observations with a maximum difference of 0.6 K. The NOAA 11 narrow-band planetary albedo values for channels 1 and 2 were calculated using pre-launch calibration coefficients. Scattering and absorption by the atmosphere were modelled with LOWTRAN 7. Then, narrow-band albedo values for the AVHRR visible and near infrared channels were compared with in situ high resolution spectral reflectance measurements. In the visible band (580-680 nm), AVHRR-derived narrow-band albedo and the in situ measurements corrected with radiative transfer model LOWTRAN 7 showed a difference of less than 2%. For the near infrared channel (725-1100 nm) the difference between the measured and modelled narrow-band albedo was 14%. These discrepancies could be either the result of inaccurate aerosol scattering modelling (lack of the in situ observation), or the result of sensor drift due to degradation.

Haefliger, M.↗

NASA NTRS2008

Radiative Transfer and Retrievals in EOF Domain

The Infrared Atmospheric Sounding Interferometer (IASI) is a hyperspectral sensor with 8461 spectral channels and a nominal spectral resolution of 0.25 cm(sup -1). It is computationally intensive to perform radiative transfer calculations and inversions using all these channels. We will present a Principal Component-based Radiative Transfer Model (PCRTM) and a retrieval algorithm which perform all the necessary calculations in EOF domain. Since the EOFs are orthogonal to each other, only about 100 principal components are needed to represent the information content of the 8461 channels. The PCRTM provides the EOF coefficients and associated derivatives with respect to atmospheric and surface parameters needed by the inversion algorithm. The inversion algorithm is based on a non-linear Levenberg-Marquardt method with climatology covariance and a priori information as constraints. The retrieved parameters include atmospheric temperature, moisture and ozone profiles, cloud parameters, surface skin temperature, and surface emissivities. To make the retrieval system even more compact and stable. The atmospheric vertical profiles are compressed into the EOF space as well. The surface emissivities are also compressed into EOF space.

Liu, Xu↗

NASA NTRSDate not supplied

A Radiometric Consistent Spectral Fingerprinting Algorithm for Continuity Products of Hyperspectral Sounders

A radiometric consistent climate fingerprinting methodology has been developed to derive long-term temperature, water vapor, cloud, trace gases, and surface skin temperature anomaly time series from the hyper-spectral sounder measurements of multiple platforms. The spectral fingerprinting methodology requires the use of radiative kernels that are radiometrically consistent with observations. Radiative kernels are built using space-time averaged Jacobians that are physically retrieved from observations under all sky conditions. The physical retrieval algorithm uses the Principal Component based Radiative Transfer Model (PCRTM) for the forward simulation. The incorporation of multiple scattering simulation in PCRTM allows the direct radiative relationship between single field-of-view (FOV) radiance observations and corresponding thermal dynamic variables including cloud properties to be established. Therefore, radiance ?closure? can be achieved under all-sky conditions by the fingerprinting scheme. This methodology has been used to derive climate anomalies from the space-time averaged spectra of AIRS/AMSU and CrIS/ATMS. The use of a consistent fingerprinting scheme provides an effective mean of generating continuity product by merging observations from different platforms and therefore facilitating the long-term climate trend study.

Wan Wu↗

NASA NTRSDate not supplied

A New, Efficient, and Consistent Method for Generating Climate Data Record from Operational Hyperspectral Sounder Instruments on AQUA, S-NPP and NOAA 20

Operational IR sounders such AIRS on NASA Aqua, CrIS on S-NPP and on NOAA 20 satellites provide high quality hyperspectral measurements for weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of level-2 products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. We have developed a Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It can provide fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

Xu Liu↗

NASA NTRSDate not supplied

Climate Data Record Derived from Hyperspectral Sounders on AQUA, S-NPP and NOAA 20

Climate products are typically derived by performing spatial and temporal averaging of level-2 products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. We have developed a Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. It eliminates or reduces the errors due to inconsistent L2 algorithms. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

climate data record↗

NASA NTRSDate not supplied

Generating Essential Climate Variables from Multiple Satellite Hyperspectral Remote Sensors

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. There are two shortcomings of this approach. First, it is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Secondly, differences in level-2 retrieval algorithms can lead to errors in the fused multi-satellite data. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to data collected from Atmospheric Infrared Sounder (AIRS) on Aqua satellite and Cross-track Infrared Sounder (CrIS) on SNPP and NOAA20 and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Atmosphere Observing System (AOS).

Xu Liu↗

NASA NTRSDate not supplied

Deriving Essential Climate Variable Data from Multiple Satellite Remote Sensors Using a Consistent Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms can lead to errors in the climate products when fusing data from different satellite sensors. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS) data and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Aerosol and Cloud, Convection and Precipitation (ACCP).

Xu Liu↗

NASA NTRSDate not supplied

A Spectral Fingerprinting Method for Deriving Consistent Climate Data Records from Multiple Satellite IR Sounders

Deriving Climate Data Records (CDRs) from multiple IR sounders such AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C requires from current operational products are challenging due to different radiative transfer models and retireavl algorithms used for processing level 2 data. We developed a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm, which uses a single set of radiative kernels a robust spectral fingerprinting method to performs retrievals using spatiotemporally averaged L1 hyperspectral radiances directly. The ClimFiSP algorithm provides accurate data fusion CDR products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. We plan to add IASI to the CDR data set in the future. The ClimFiSP is being transitioned to NASA GES DISC data center for public access.

Xu Liu↗

NASA NTRS2009

Comparison of Anomalies and Trends of OLR as Observed by CERES and Computed from Geophysical Parameters Derived from Analysis of AIRS/AMSU Data

Anomalies and trends of outgoing longwave radiation (OLR) serve as important indicators of climate change. Several satellite based instruments currently provide information related to OLR. CERES, on board the EOS Aqua and Terra satellites, contains broad band radiometers that measure total flux and short-wave flux, from which OLR is determined. AIRS is a high spectral resolution IR sounder on EOS Aqua that measures IR radiances covering most of the spectral interval 650 cm-1 to 2670 cm-1. These observations enable the determination of detailed information about atmospheric temperature, moisture, and ozone profiles, as well as surface skin temperatures and cloud parameters. The AIRS OLR product is the total flux over the spectral interval 2 cm-1 to2750 cm-1 computed for the surface and atmospheric state determined from AIRS observations. We compared spatial anomalies and trends of OLR, over the seven year period September 2002 through August 2009, as observed by CERES and computed using Version 5 AIRS products. These two sets of OLR anomalies and trends, obtained in very different ways, agree with each other almost perfectly in essentially every detail. This important finding shows that a very stable high spectral infra-red sounder such as AIRS corroborates the anomalies and trends of OLR obtained from CERES. More significantly, anomalies and trends of the individual geophysical parameters derived from AIRS explain the detailed causes of the anomalies and trends of CERES OLR. Both sets of results show that global mean OLR has been decreasing at a rate of 0.12 W/m2/yr over the seven year time period under study. Both also confirm that the primary cause of this is due to changes in the tropics, in which OLR has been decreasing at a rate of 0.27 W/m2/yr. AIRS products show that the decrease of tropical OLR is a result of increasing tropical atmospheric water vapor and cloud cover over the time period studied, which in turn is responding to a very strong E1 Nino/ La Nina cycle. Equatorial ocean temperatures between 160E and 120W cooled considerably during this time period, with corresponding local decreases in mid-tropospheric humidity and cloud cover, resulting in increases in local OLR. This was more than compensated by substantial increases in water vapor and cloud cover elsewhere in the tropics, resulting in a net decrease in tropical OLR.

Susskind, Joel↗

NASA NTRS2010

AIRS Products Confirm and Explain Recent Negative Trends of OLR as Observed by CERES

Anomalies and trends of OLR serve as important indicators of climate change. Several satellite based instruments currently provide information related to OLR. CERES, on board the EOS Aqua and Terra satellites, contains broad band radiometers that measure total flux and short-wave flux, from which OLR is determined. AIRS is a high spectral resolution IR sounder on EOS Aqua that measures IR radiances covering most of the spectral interval 650/cm to 2670/cm. These observations enable the determination of detailed information about atmospheric temperature, moisture, and ozone profiles, as well as surface skin temperatures and cloud parameters. The AIRS OLR product is the total flux over the spectral interval 2/cm to 2750/cm computed for the surface and atmospheric state determined from AIRS observations. We compared spatial anomalies and trends of OLR, over the seven year period September 2002 through August 2009, as observed by CERES and computed using Version-5 AIRS products. These two sets of OLR anomalies and trends, obtained in very different ways, agree with each other almost perfectly in essentially every detail. This important finding shows that a very stable high spectral infra-red sounder such as AIRS corroborates the anomalies and trends of OLR obtained from CERES. More significantly, anomalies and trends of the individual geophysical parameters derived from AIRS explain the detailed causes of the anomalies and trends of CERES OLR. Both sets of results show that global mean OLR has been decreasing at a rate of 0.12 W/sq m/yr over the seven year time period under study. Both also confirm that the primary cause of this is due to changes in the tropics, in which OLR has been decreasing at a rate of 0.27 W/sq m/yr. AIRS products show that the decrease of tropical OLR is a result of increasing tropical atmospheric water vapor and cloud cover over that time period studied, which in turn is responding to a very strong La Nina; a event starting in late 2007. Equatorial ocean temperatures between 160 E and 120 W cooled considerably during this time period, with corresponding local decreases in mid-tropospheric humidity and cloud cover, resulting in increases in local OLR. This was more than compensated by substantial increases in water vapor and cloud cover elsewhere in the tropics, resulting in a net decrease in tropical OLR. The AIRS Version-5 products currently extend through December 2009. An El Nino event began in late 2009. AIRS products show that tropical OLR began to increase at that time, and there was a corresponding reversal of sign of tropical cloud and water vapor anomalies.

Susskind, Joel↗

NASA NTRS2012

Assess Calibration Consistency of MODIS and AVHRR Thermal Infrared Bands Using SNO Observations Corrected for Atmospheric Effects

Monitoring environmental changes from space requires extremely well-calibrated observations to achieve the necessary high accuracy and stability. The calibration differences between the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High Resolution Radiometer (AVHRR) thermal bands provide a valuable quality assessment of the instrument performance. This letter compares the calibration differences between the Aqua MODIS and NOAA-18 AVHRR bands at 11.0 and 12.0 /Lm using simultaneous nadir overpass observations obtained in nearly parallel orbits. Impacts due to the relative spectral-response differences between the two sensors are estimated by MODTRAN simulations with real-time atmospheric profiles of temperature, water vapor, atmospheric pressure and ozone, and surface skin temperatures. Results show that the temperature difference after the removal of atmospheric impacts is within 0.30 K (or 0.40% in radiance) across the effective calibration range (or the 1l.0 l'm band/channel. For the 12.0 pm band, the differences are OAO K (or 0.50%) at the typical radiance and up to 0.70 K (or 0.90%) close to the maximum radiance, indicating an excellent calibration consistency between MODIS and AVHRR for both bands.

Wu, Aisheng↗

NASA NTRSDate not supplied

Evaluation of Climate Fingerprinting Sounder Product (ClimFiSP) Air Temperature and H2O Trends

Climate fingerprinting Sounder Product (ClimFiSP) provides gridded (0.5x0.5) daily skin temperature, surface emissivity, air temperature, water vapor, trace gases, and cloud properties, which derived from IR hyper-spectral radiance measured by AIRS on Aqua and CrIS on SNPP and JPSS series. In this work, the ClimFiSP daily air temperature and H2O were retrieved on 98 pressure levels by applying the spectral fingerprint algorithm on 0.5x0.5 gridded daily mean radiances from Climate Hyperspectral Infrared Radiance Product (CHIRP). CHIRP is a stable climate-quality radiance time series spanning AIRS and CrIS. The air temperature and H2O monthly data and trends were calculated from the more than two decades long CHIRP AIRS data. Troposphere warming and stratosphere cooling can be seen in both ClimFiSP and ERA5 air temperature data. The ClimFiSP air temperature trends are also compared with the MW sounding air temperature trends to validate the ClimFiSP air temperature results. The H2O trends on upper troposphere are evaluated by comparing with the ERA5 H2O trends, and results show a reasonable agreement with two sets of results. The ClimFiSP algorithm provides a unique and fast way to retrieve the spatial-temporal change in climate variables from the corresponding change in radiances, gridded at the same spatial-temporal scale. This greatly facilitates the procession of long-term climate data records.

ClimFiSP↗

NASA NTRS1977

Liquid-cooled bra for cancer detection

Garment cools entire breast area uniformly, improving sensitivity of thermographic techniques. Flow and temperature of coolant are controlled by system which also monitors skin temperature.

Williams, B. A.↗

NASA NTRS1939

A Preliminary Study of the Prevention of Ice on Aircraft by the Use of Engine-exhaust Heat

An investigation was made in the N.A.C.A. ice tunnel at air temperatures from 20 degrees to 28 degrees Fahrenheit and at a velocity of 80 miles per hour to determine whether ice formations on a model wing could be prevented by the use of the heat from the engine-exhaust gas. Various spanwise duct systems were tested in a 6-foot-chord N.A.C.A. 23012 wing model. The formation of ice over the entire wing chord was prevented by the direct heating of the forward 10 percent of the wing by hot air, which was passed through leading-edge ducts. Under dry conditions, enough heat to maintain the temperature of the forward 10 percent of the wing at about 200 degrees Fahrenheit above that of the ambient air was required for the prevention of ice formation. The air temperature in the ducts that was necessary to produce these skin temperatures varied from 360 degrees to 834 degrees Fahrenheit; the corresponding air velocities in the duct were 152 and 45 feet per second. Ice formations at the leading edge were locally prevented by air that passed over the interior of the wing surface at a velocity of 30 feet per second and a temperature of 122 degrees Fahrenheit.

Rodert, Lewis A↗