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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

A proposed tropical rainfall measuring mission (TRMM) satellite

The proposed Tropical Rainfall Measuring Mission (TRMM) satellite (presently in its third year of planning), is described. The TRMM satellite, planned for an operational duration of at least three years beginning in the mid-1990s, is intended to obtain high-quality measurements of tropical precipitation by means of information derived from a quantitative spaceborne radar, a multichannel passive microwave radiometer, and an AVHRR. The satellite's orbit will be low-altitude (320 km), for high resolution, and low-inclination (30 to 35 deg), for making it possible to visit each sampling area twice a day. Radar and passive microwave algorithms and rain-retrieval algorithms to be used in precipitation measurements are discussed together with cloud dynamical models designed to test these algorithms.

Simpson, Joanne↗
NASA NTRS1992

Measurement of the O-18 to O-16 isotope ratio for characterizing oxide surface layers on LDEF samples

The ratio of the density of the oxygen 18 isotope (O-18) to the density of the oxygen 16 isotope (O-16) is a strong function of altitude in the atmosphere because of the stronger gravitational attraction on the heavier isotope. It is proposed that the measurement of this ratio for oxide surface layers on LDEF samples can easily distinguish oxides formed in orbit from contaminative oxides formed during retrieval procedures. Since the satellite altitude is known as a function of time, it may be possible to use the measured ratio to determine the time of formation of oxide layers, the accuracy depending upon the stability of the atmosphere.

Sagalyn, Paul L.↗
NASA NTRS1993

A photon phreak digs the LDEF happening

A year ago at the First Long Duration Exposure Facility (LDEF) Post-Retrieval Symposium, detailed measurements on trunnion sections, as well as results from 'intentional' samples (Co, Ni, In, Ta, and V) and spacecraft parts were reported. For this year's Symposium, some of these findings are re-evaluated in combination with more recent results, to cast a longer perspective on the LDEF experience, and to sketch some promising avenues toward more effective participation in future missions. The LDEF analysis effort has been a superb training exercise, from which lessons learned need to be applied to future missions - right back to the early phases of mission planning.

Smith, Alan R.↗
NASA NTRS2001

System Report for the Optical Properties Monitor (OPM) Experiment

This systems report describes how the Optical Properties Monitor (OPM) experiment was developed. Pertinent design parameters are discussed, along with mission information and system requirements to successfully complete the mission. Environmental testing was performed on the OPM to certify it for spaceflight. This testing included vibration, thermal vacuum, electromagnetic interference and conductance, and toxicity tests. Instrument and monitor subsystem performances, including the reflectometer, vacuum ultraviolet, total integrated scatter, atomic oxygen monitor, irradiance monitor, and molecular contamination monitor during the mission are discussed. The OPM experiment was launched aboard the Space Shuttle on mission STS-81 in January 1997 and transferred to the Mir space station. An extravehicular activity (EVA) was performed in April 1997 to attach the OPM experiment to the outside of the Mir/Shuttle Docking Module for space environment exposure. The OPM conducted in situ measurements of a number of material samples. These data may be found in the OPM Science Report. OPM was retrieved during an EVA in January 1998 and was returned to Earth on board the Space Shuttle on mission STS-89.

Hummer, L.↗
NASA NTRS2006

Online Simulations and Forecasts of the Global Aerosol Distribution in the NASA GEOS-5 Model

We present an analysis of simulations of the global aerosol system in the NASA GEOS-5 transport, radiation, and chemistry model. The model includes representations of all major tropospheric aerosol species, including dust, sea salt, black carbon, particulate organic matter, and sulfates. The aerosols are run online for the period 2000 through 2005 in a simulation driven by assimilated meteorology from the NASA Goddard Data Assimilation System. Aerosol surface mass concentrations are compared with existing long-term surface measurement networks. Aerosol optical thickness is compared with ground-based AERONET sun photometry and space-based retrievals from MODIS, MISR, and OMI. Particular emphasis is placed here on consistent sampling of model and satellite aerosol optical thickness to account for diurnal variations in aerosol optical properties. Additionally, we illustrate the use of this system for providing chemical weather forecasts in support of various NASA and community field missions.

Colarco, Peter↗
NASA NTRSDate not supplied

Empirical Hydrometeor Type Identification from GMI Brightness Temperature Measurements

Brightness temperatures (TB) from GMI and related sensors contain information about the types and amounts of precipitation particles in a column. Approaches like GPROF or machine learning are good for providing precipitation estimates and other quantified information, but it can be difficult to understand why / how a given set of TBs traces to a given retrieval solution. Outlier TBs that are not well-represented in a training sample can lead to dubious solutions. Our goal is to use the scattering signatures at multiple frequencies to determine whether hail is present, or otherwise graupel, or otherwise snow, or otherwise liquid rain without a substantial precipitation ice component. (A hierarchical approach is employed, so a prediction of hail can include the presence of all other categories, but a prediction of snow implies a lack of graupel or hail, and a prediction of liquid rain implies a lack of any detectable precipitation ice.)

Daniel J. Cecil↗
NASA NTRSDate not supplied

Hydrometeor Identification from GMI Radiometer, Trained Using Polarimetric Radar

Brightness temperatures (TB) from GMI and related sensors contain information about the types and amounts of precipitation particles in a column. Approaches like GPROF or machine learning are good for providing precipitation estimates and other quantified information, but it can be difficult to understand why / how a given set of TBs traces to a given retrieval solution. Outlier TBs that are not well-represented in a training sample can lead to dubious solutions. Our goal is to use the scattering signatures at multiple frequencies to determine whether hail is present, or otherwise graupel, or otherwise snow, or otherwise liquid rain without a substantial precipitation ice component. (A hierarchical approach is employed, so a prediction of hail can include the presence of all other categories, but a prediction of snow implies a lack of graupel or hail, and a prediction of liquid rain implies a lack of any detectable precipitation ice.)

Daniel J. Cecil↗
NASA NTRS2004

Use of GOES, SSM/I, TRMM Satellite Measurements Estimating Water Budget Variations in Gulf of Mexico - Caribbean Sea Basins

This study presents results from a multi-satellite/multi-sensor retrieval system designed to obtain the atmospheric water budget over the open ocean. A combination of 3ourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple- algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective m identifying problems in estimating vapor transports from a leaky operational radiosonde network than in verifying the transport estimates determined from the satellite algorithm system Total columnar atmospheric water budget results are presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98,October-98, and January 1999. These results are used to emphasize the changing relationship in E-P, as well as in the varying roles of storage and advection in balancing E-P both on daily and monthly time scales and on localized and basin space scales. Results from the algorithm-to-algorithm intercomparisons are also presented in the context of sensitivity testing to help understand the intrinsic uncertainties in evaluating the water budget terms by an all-satellite algorithm approach.

Smith, Eric A.↗
NASA NTRS2015

On the Feasibility of Monitoring Carbon Monoxide in the Lower Troposphere from a Constellation of Northern Hemisphere Geostationary Satellites (PART 1)

By the end of the current decade, there are plans to deploy several geostationary Earth orbit (GEO) satellite missions for atmospheric composition over North America, East Asia and Europe with additional missions proposed. Together, these present the possibility of a constellation of geostationary platforms to achieve continuous time-resolved high-density observations over continental domains for mapping pollutant sources and variability at diurnal and local scales. In this paper, we use a novel approach to sample a very high global resolution model (GEOS-5 at 7 km horizontal resolution) to produce a dataset of synthetic carbon monoxide pollution observations representative of those potentially obtainable from a GEO satellite constellation with predicted measurement sensitivities based on current remote sensing capabilities. Part 1 of this study focuses on the production of simulated synthetic measurements for air quality OSSEs (Observing System Simulation Experiments). We simulate carbon monoxide nadir retrievals using a technique that provides realistic measurements with very low computational cost. We discuss the sampling methodology: the projection of footprints and areas of regard for geostationary geometries over each of the North America, East Asia and Europe regions; the regression method to simulate measurement sensitivity; and the measurement error simulation. A detailed analysis of the simulated observation sensitivity is performed, and limitations of the method are discussed. We also describe impacts from clouds, showing that the efficiency of an instrument making atmospheric composition measurements on a geostationary platform is dependent on the dominant weather regime over a given region and the pixel size resolution. These results demonstrate the viability of the "instrument simulator" step for an OSSE to assess the performance of a constellation of geostationary satellites for air quality measurements.

GEOS-5↗
NASA NTRS1992

Measured space environmental effects to LDEF during retrieval

On the STS-32 shuttle mission, a space flight experiment provided an understanding of the effects of the space environment on the Long Duration Exposure Facility (LDEF) from rendezvous with the shuttle until removal from the payload bay at the Orbiter Processing Facility (OPF) at KSC. The Interim Operational Contamination Monitor (IOCM) is an attached shuttle payload that has been used on two earlier flights (STS 51C and STS 28) to quantify the contamination deposited during the course of the mission. The IOCM can characterize by direct measurement, the deposition of molecular and particulate contamination during any phase of flight. In addition to these principal measurements, the IOCM actively measures the thermophysical properties of thermal control surfaces by calorimetry, the flux of the ambient atomic oxygen environment, the incident solar flux, and the absolute ambient pressure in the payload bay. The IOCM also provides a structure and sample holders for the exposure of passive material samples to the space environment, e.g. thermal cycling, atomic oxygen, and micrometeoroids and/or orbital debris, etc. One of the more salient results from the STS-32 flight suggests that the LDEF emitted a large number of particulates after berthing into the shuttle. The mission atomic oxygen fluence was also calculated. Although the fluence was low by normal standards, the Kapton passive samples exhibited the onset of erosion. Orbital debris and micrometeoroid impacts also occurred during the retrieval mission. The average perforation diameter was approximately 12.5 microns. The largest perforation diameter was measured at 65 microns.

Maag, Carl R.↗
NASA NTRS1995

Validation of satellite retrievals of cloud microsphysics and liquid water path using observations from FIRE

Cloud effective radii (r(sub e)) and cloud liquid water path (LWP) are derived from ISCCP spatially sampled satellite data and validated with ground-based pyranometer and microwave radiometer measurements taken on San Nicolas Island during the 1987 FIRE IFO. Values of r(sub e) derived from the ISCCP data are also compared to values retrieved by a hybrid method that uses the combination of LWP derived from microwave measurement and optical thickness derived from GOES data. The results show that there is significant variability in cloud properties over a 100 km x 80 km area and that the values at San Nicolas Island are not necessarily representative of the surrounding cloud field. On the other hand, even though there were large spatial variations in optical depth, the r(sub e) values remained relatively constant (with sigma less than or equal to 2-3 microns in most cases) in the marine stratocumulus. Furthermore, values of r(sub e) derived from the upper portion of the cloud generally are representative of the entire stratiform cloud. When LWP values are less than 100 g m(exp -2), then LWP values derived from ISCCP data agree well with those values estimated from ground-based microwave measurements. In most cases LWP differences were less than 20 g m(exp -2). However, when LWP values become large (e.g., greater than or equal to 200 g m(exp -2)), then relative differences may be as large as 50%- 100%. There are two reasons for this discrepancy in the large LWP clouds: (1) larger vertical inhomogeneities in precipitating clouds and (2) sampling errors on days of high spatial variability of cloud optical thicknesses. Variations of r(sub e) in stratiform clouds may indicate drizzle: clouds with droplet sizes larger than 15 microns appear to be associated with drizzling, while those less than 10 microns are indicative of nonprecipitating clouds. Differences in r(sub e) values between the GOES and ISCCP datasets are found to be 0.16 +/- 0.98 micron.

Rossow, W.↗
NASA NTRS2017

Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)

The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The PALS soil moisture was also compared to SMAP and in situ soil moisture at the 36-km scale, which is the SMAP grid size for the standard product. PALS and SMAP soil moistures were found to be very similar owing to the close match of the brightness temperature measurements and the use of a common soil moisture retrieval algorithm. Spatial heterogeneity, which was identified using the high-resolution PALS soil moisture and the intensive ground sampling, also contributed to differences between the soil moisture estimates. In general, discrepancies found between the L-band soil moisture estimates and the 5-cm depth in situ measurements require methodologies to mitigate the impact on their interpretations in soil moisture validation and algorithm development. Specifically, the metrics computed for the SMAP radiometer-based soil moisture product over WGEW will include errors resulting from rainfall, particularly during the monsoon season when the spatial distribution of soil moisture is especially heterogeneous.

SMAPVEX15↗
NASA NTRS2019

Intercomparison of Aerosol Volume Size Distributions Derived from AERONET Ground-Based Remote Sensing and LARGE in Situ Aircraft Profiles During the 2011–2014 DRAGON and DISCOVER-AQ Experiments

Aerosol volume size distribution (VSD) retrievals from the Aerosol Robotic Network (AERONET) aerosol monitoring network were obtained during multiple DRAGON (Distributed Regional Aerosol Gridded Observational Network) campaigns conducted in Maryland, California, Texas and Colorado from 2011 to 2014. These VSD retrievals from the field campaigns were used to make comparisons with near-simultaneous in situ samples from aircraft profiles carried out by the NASA Langley Aerosol Group Experiment (LARGE) team as part of four campaigns comprising the DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) experiments. For coincident (1 h) measurements there were a total of 91 profile-averaged fine-mode size distributions acquired with the LARGE ultra-high sensitivity aerosol spectrometer (UHSAS) instrument matched to 153 AERONET size distributions retrieved from almucantars at 22 different ground sites. These volume size distributions were characterized by two fine-mode parameters, the radius of peak concentration (rpeak_conc) and the VSD fine-mode width (widthpeak_conc). The AERONET retrievals of these VSD fine-mode parameters, derived from ground-based almucantar sun photometer data, represent ambient humidity values while the LARGE aircraft spiral profile retrievals provide dried aerosol (relative humidity; RH< 20 %) values. For the combined multiple campaign dataset, the average difference in rpeak_conc was 0:0330:035 μm (ambient AERONET values were 15.8% larger than dried LARGE values), and the average difference in widthpeak_conc was 0:0420:039 μm (AERONET values were 25.7% larger). For a subset of aircraft data, the LARGE data were adjusted to account for ambient humidification. For these cases, the AERONET–LARGE average differences were smaller, with rpeak_conc differing by 0:0110:019 μm (AERONET values were 5.2% larger) and widthpeak_conc average differences equal to 0:0300:037 μm (AERONET values were 15.8% larger).

Schafer, Joel S.↗
NASA NTRS2016

First Transmitted Hyperspectral Light Measurements and Cloud Properties from Recent Field Campaign Sampling Clouds Under Biomass Burning Aerosol

We present a first view of data collected during a recent field campaign aimed at measuring biomass burning aerosol above clouds from airborne platforms. The NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) field campaign recently concluded its first deployment sampling clouds and overlying aerosol layer from the airborne platform NASA P3. We present results from the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR), in conjunction with the Solar Spectral Flux Radiometers (SSFR). During this deployment, 4STAR sampled transmitted solar light either via direct solar beam measurements and scattered light measurements, enabling the measurement of aerosol optical thickness and the retrieval of information on aerosol particles in addition to overlying cloud properties. We focus on the zenith-viewing scattered light measurements, which are used to retrieve cloud optical thickness, effective radius, and thermodynamic phase of clouds under a biomass burning layer. The biomass burning aerosol layer present above the clouds is the cause of potential bias in retrieved cloud optical depth and effective radius from satellites. We contrast the typical reflection based approach used by satellites to the transmission based approach used by 4STAR during ORACLES for retrieving cloud properties. It is suspected that these differing approaches will yield a change in retrieved properties since light transmitted through clouds is sensitive to a different cloud volume than reflected light at cloud top. We offer a preliminary view of the implications of these differences in sampling volumes to the calculation of cloud radiative effects (CRE).

airborne↗
NASA NTRS2006

Monthly-Diurnal Water Budget Variability Over Gulf of Mexico-Caribbean Sea Basin from Satellite Observations

This study presents results from a multi-satellite/multi-sensor retrieval system design d to obtain the atmospheric water budget over the open ocean. A combination of hourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple-algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective in identifying problems in estimating vapor transports from a "leaky" operational radiosonde network than in verifying the transport estimates determined from the satellite algorithm system. Total columnar atmospheric water budget results are presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98,October-98, and January- 1999. These results are used to emphasize the changing relationship in E-P, as well as in the varying roles of storage and advection in balancing E-P both on daily and monthly time scales and on localized and basin space scales. Results from the algorithm-to-algorithm intercomparisons are also presented in the context of sensitivity testing to help understand the intrinsic uncertainties in evaluating the water budget terms by an all-satellite algorithm approach.

Smith, E. A.↗
NASA NTRS1994

Modeling the bidirectional reflectance distribution function of mixed finite plant canopies and soil

An analytical model of the bidirectional reflectance for optically semi-infinite plant canopies has been extended to describe the reflectance of finite depth canopies contributions from the underlying soil. The model depends on 10 independent parameters describing vegetation and soil optical and structural properties. The model is inverted with a nonlinear minimization routine using directional reflectance data for lawn (leaf area index (LAI) is equal to 9.9), soybeans (LAI, 2.9) and simulated reflectance data (LAI, 1.0) from a numerical bidirectional reflectance distribution function (BRDF) model (Myneni et al., 1988). While the ten-parameter model results in relatively low rms differences for the BRDF, most of the retrieved parameters exhibit poor stability. The most stable parameter was the single-scattering albedo of the vegetation. Canopy albedo could be derived with an accuracy of less than 5% relative error in the visible and less than 1% in the near-infrared. Sensitivity were performed to determine which of the 10 parameters were most important and to assess the effects of Gaussian noise on the parameter retrievals. Out of the 10 parameters, three were identified which described most of the BRDF variability. At low LAI values the most influential parameters were the single-scattering albedos (both soil and vegetation) and LAI, while at higher LAI values (greater than 2.5) these shifted to the two scattering phase function parameters for vegetation and the single-scattering albedo of the vegetation. The three-parameter model, formed by fixing the seven least significant parameters, gave higher rms values but was less sensitive to noise in the BRDF than the full ten-parameter model. A full hemispherical reflectance data set for lawn was then interpolated to yield BRDF values corresponding to advanced very high resolution radiometer (AVHRR) scan geometries collected over a period of nine days. The resulting parameters and BRDFs are similar to those for the full sampling geometry, suggesting that the limited geometry of AVHRR measurements might be used to reliably retrieve BRDF and canopy albedo with this model.

Schluessel, G.↗
NASA NTRSDate not supplied

Test Results for the SEA Ice Crystal Detector (ICD) under SLD Conditions at the NASA IRT

The Science Engineering Associates hot-wire Ice Crystal Detector was tested under Appendix C and Supercooled Large Drop Conditions at the NASA Icing Research Tunnel, with the purpose of comparing the measurements to the tunnel LWC calibration, and to test the performance of the mixed-phase retrievals of the probe. The liquid water content measured by the total water content sensor of the probe agreed well with the tunnel calibration over a wide range of MVDs, not unexpectedly since the tunnel was calibrated with a similar Multiwire hot-wire probe. A scale factor difference of about 7% was attributed to the lack of an efficiency correction for the Ice Crystal Detector at smaller median volume diameters, and typical sample area uncertainties of liquid water content devices. In addition, the simultaneous equations that are used to retrieve liquid and ice water contents were tested under liquid and glaciated conditions. Using constant ice and water efficiencies for each wire, the equations were found to produce a large and false ice water content retrieval in large median volume diameter liquid cases. By applying a liquid efficiency to the liquid water content sensor that varied with median volume diameter, retrievals were improved such that false ice water content was less than ±10% of the total water content out to the 460 μm median volume diameter limit of the testing. The probe was also tested in glaciated conditions by freezing out a small median volume diameter spray. Using constant ice efficiencies for the two sensors provided from aircraft measurements, the retrieved ice water content was about 40% higher than expected for the case presented, likely due to the ice efficiencies that were used from aircraft measurements of natural clouds being too low for the tunnel’s glaciated sprays. Application of ice efficiencies that vary with particle size and potentially other parameters will be explored for future improvement of retrievals.

Air Craft Icing↗
NASA NTRS2021

Test Results for the SEA Ice Crystal Detector (ICD) under SLD Conditions at the NASA IRT

The Science Engineering Associates hot-wire Ice Crystal Detector was tested under Appendix C and Supercooled Large Drop Conditions at the NASA Icing Research Tunnel, with the purpose of comparing the measurements to the tunnel LWC calibration, and to test the performance of the mixed-phase retrievals of the probe. The liquid water content measured by the total water content sensor of the probe agreed well with the tunnel calibration over a wide range of MVDs, not unexpectedly since the tunnel was calibrated with a similar Multiwire hot-wire probe. A scale factor difference of about 7% was attributed to the lack of an efficiency correction for the Ice Crystal Detector at smaller median volume diameters, and typical sample area uncertainties of liquid water content devices. In addition, the simultaneous equations that are used to retrieve liquid and ice water contents were tested under liquid and glaciated conditions. Using constant ice and water efficiencies for each wire, the equations were found to produce a large and false ice water content retrieval in large median volume diameter liquid cases. By applying a liquid efficiency to the liquid water content sensor that varied with median volume diameter, retrievals were improved such that false ice water content was less than ±10% of the total water content out to the 460 μm median volume diameter limit of the testing. The probe was also tested in glaciated conditions by freezing out a small median volume diameter spray. Using constant ice efficiencies for the two sensors provided from aircraft measurements, the retrieved ice water content was about 40% higher than expected for the case presented, likely due to the ice efficiencies that were used from aircraft measurements of natural clouds being too low for the tunnel’s glaciated sprays. Application of ice efficiencies that vary with particle size and potentially other parameters will be explored for future improvement of retrievals.

o Aircraft Icing↗