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NASA NTRS1973

Effect of increased fuel temperature on emissions of oxides of nitrogen from a gas turbine combustor burning natural gas

An annular gas turbine combustor was tested with heated natural gas fuel to determine the effect of increasing fuel temperature on the formation of oxides of nitrogen. Fuel temperatures ranged from ambient to 800 K (980 F). Combustor pressure was 6 atmospheres and the inlet air temperature ranged from 589 to 894 K (600 to 1150 F). The NOx emission index increased with fuel temperature at a rate of 4 to 9 percent per 100 K (180 F), depending on the inlet air temperature. The rate of increase in NOx was lowest at the highest inlet air temperature tested.

Marchionna, N. R.↗

NASA NTRS1994

Aspects of spatial and temporal aggregation in estimating regional carbon dioxide fluxes from temperate forest soils

We examine the influence of aggregation errors on developing estimates of regional soil-CO2 flux from temperate forests. We find daily soil-CO2 fluxes to be more sensitive to changes in soil temperatures (Q(sub 10) = 3.08) than air temperatures (Q(sub 10) = 1.99). The direct use of mean monthly air temperatures with a daily flux model underestimates regional fluxes by approximately 4%. Temporal aggregation error varies with spatial resolution. Overall, our calibrated modeling approach reduces spatial aggregation error by 9.3% and temporal aggregation error by 15.5%. After minimizing spatial and temporal aggregation errors, mature temperate forest soils are estimated to contribute 12.9 Pg C/yr to the atmosphere as carbon dioxide. Georeferenced model estimates agree well with annual soil-CO2 fluxes measured during chamber studies in mature temperate forest stands around the globe.

Kicklighter, David W.↗

DOE OSTI2022

Influence of gasoline fuel formulation on lean autoignition in a mixed-mode-combustion (deflagration/autoignition) engine

We report stoichiometric spark-ignition engines suffer efficiency penalties due to throttling losses at low loads, a low specific-heat ratio of the stoichiometric working fluid, and limits on compression ratio due to end-gas autoignition leading to undesirable knocking. Mixed-Mode Combustion (MMC) mitigates these shortcomings by using a lean working fluid where a spark-initiated pilot-stabilized deflagrative flame front is followed by controlled end-gas autoignition. This MMC study investigates the effects of initial conditions (intake air temperature, intake pressure, equivalence ratio, and intake oxygen fraction) on autoignition tendency of four gasoline-range fuels with varying properties and composition. The use of fuels with varying octane sensitivity (S) allowed exploring the importance of low-temperature heat release in triggering autoignition. Fuels with high S were less reactive for conditions that promote low-temperature chemistry (operation at high intake air pressure or without N2 dilution). Conversely, an Alkylate fuel with low S showed a greater autoignition resistance at operating conditions that were unfavorable for low-temperature chemistry. Next, the effect of residual gas composition on autoignition tendency of fuels was examined with a chemical-kinetics model. Among the various molecules in the residual gas, nitric oxide (NO) enhanced the low-temperature chemistry and increased the autoignition tendency most significantly. The fuels’ autoignition response to increasing NO amount corroborates the experimental observations. Next, the sequential autoignition of the end-gas was assessed to be less impacted by thermal stratification because of lean mixtures showing relatively less low-temperature chemistry, when compared to stoichiometric mixtures. Next, the effect of changing equivalence ratio on the autoignition was found to be similar for all fuels, regardless of their S. With changing intake air temperature, the response of fuels’ autoignition tendency depended on the dilution level used. At high dilution (i.e. low intake [O2]), fuels’ reactivity increased with increasing intake air temperature. In contrast, for operation without dilution, the autoignition tendency of the low-S Alkylate fuel decreased with increasing intake air temperature, while that of high-S High Cycloalkane fuel still increased with increasing intake air temperature. In conclusion, conventional octane metrics (RON and MON) have utility in assessing the autoignition tendency under lean MMC operation. Moreover, the fuel requirements for MMC align with that of stoichiometric operation: i.e., high RON and high S fuels are desirable for stable non-knocking operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1993

Sensible and latent heat flux estimates in Antarctica

The assumption has been made that the net annual contribution of water by the processes of deposition and sublimation to the Antarctic Ice Sheet is zero. The U.S. Antarctic Program started installing reliable automatic weather stations on the Antarctic Continent in 1980. The initial units were equipped to measure wind speed, wind direction, air pressure, and air temperature. During the 1983-1984 field season in Antarctica, three units were installed that measured a vertical air temperature difference between the nominal heights of 0.5 m and 3.0 m and relative humidity at a nominal height of 3 m. The measurements of the vertical air temperature difference and the relative humidity are the minimum required to estimate the sensible and latent heat fluxes to the air, while not exceeding the available energy requirements for the weather stations. The estimates of the net annual sublimation and deposition on the Ross Ice Shelf amount to 20 to 80 percent of the annual accumulation. We conclude that the assumption that annual sublimation and deposition are zero is not valid under Antarctic conditions.

Stearns, Charles R.↗

DOE OSTI2021

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (°C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a “0” if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the “time warp” period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046–1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503–2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100–103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278–283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1994

Computer modeling of the sensitivity of a laser water vapor sensor to variations in temperature and air speed

Currently, there is disagreement among existing methods of determining atmospheric water vapor concentration at dew-points below -40 C. A major source of error is wall effects which result from the necessity of bringing samples into the instruments. All of these instruments also have response times on the order of seconds. NASA Langley is developing a water vapor sensor which utilizes the absorption of the infrared radiation produced by a diode laser to estimate water vapor concentration. The laser beam is directed through an aircraft window to a retroreflector located on an engine. The reflected beam is detected by an infrared detector located near the laser. To maximize signal to noise, derivative signals are analyzed. By measuring the 2f/DC signal and correcting for ambient temperature, atmospheric pressure and air speed (which results in a Doppler shifting of the laser beam), the water vapor concentration can be retrieved. Since this is an in situ measurement there are no wall effects and measurements can be made at a rate of more than 20 per second. This allows small spatial variations of water vapor to be studied. In order to study the sensitivity of the instrument to variations in temperature and air speed, a computer program which generated the 2f, 3f, 4f, DC and 2f/DC signals of the instrument as a function of temperature, pressure and air speed was written. This model was used to determine the effect of errors in measurement of the temperature and air speed on the measured water vapor concentration. Future studies will quantify the effect of pressure measurement errors, which are expected to be very small. As a result of these studied, a retrieval algorithm has been formulated, and will be applied to data taken during the PEM-West atmospheric science field mission. Spectroscopic studies of the water vapor line used by the instrument will be used to refine this algorithm. To prepare for these studies, several lasers have been studied to determine their output frequency range and power.

Tucker, George F.↗

NASA NTRS2009

Data Assimilation Experiments Using Quality Controlled AIRS Version 5 Temperature Soundings

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains a number of significant improvements over Version 4. Two very significant improvements are described briefly below. 1) The AIRS Science Team Radiative Transfer Algorithm (RTA) has now been upgraded to accurately account for effects of non-local thermodynamic equilibrium on the AIRS observations. This allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval algorithm during both day and night. Following theoretical considerations, tropospheric temperature profile information is obtained almost exclusively from clear column radiances in the 4.3 micron CO2 band in the AIRS Version 5 temperature profile retrieval step. These clear column radiances are a derived product that are indicative of radiances AIRS channels would have seen if the field of view were completely clear. Clear column radiances for all channels are determined using tropospheric sounding 15 micron CO2 observations. This approach allows for the generation of accurate values of clear column radiances and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel clear column radiances. These error estimates are used for quality control of the retrieved products. Based on error estimate thresholds, each temperature profiles is assigned a characteristic pressure, pg, down to which the profile is characterized as good for use for data assimilation purposes. We have conducted forecast impact experiments assimilating AIRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the NASA FVGCM, at a spatial resolution of 0.5 deg by 0.5 deg. Assimilation of Quality Controlled AIRS temperature profiles down to pg resulted in significantly improved forecast skill compared to that obtained from experiments when all data used operationally by NCEP, except for AIRS data, is assimilated. These forecasts were also significantly better than to those obtained when AIRS radiances (rather than temperature profiles) are assimilated, which is the way AIRS data is used operationally by NCEP and ECMWF.

Susskind, Joel↗

NASA NTRS1980

Low-pressure performance of annular, high-pressure (40 atm) high-temperature (2480 K) combustion system

Experimental tests were conducted to develop a combustion system for a 40 atmosphere pressure, 2480 K exhaust gas temperature, turbine cooling facility. The tests were conducted in an existing facility with a maximum pressure capability of 10 atmospheres and where inlet air temperatures as high as 894 K could be attained. Exhaust gas temperatures were as high as 2365 K. Combustion efficiences were about 100 percent over a fuel air ratio range of 0.016 to 0.056. Combustion efficiency decreased at leaner and richer ratios when the inlet air temperature was 589 K. Data are presented that show the effect of fuel air ratio and inlet air temperature on liner metal temperature. Isothermal system pressure loss as a function of diffuser inlet Mach number is also presented. Data included exhaust gas pattern factors; unburned hydrocarbon, carbon monoxide, and oxides of nitrogen emission index values; and smoke numbers.

Wear, J. D.↗

NASA NTRS1939

Correction of Temperatures of Air-Cooled Engine Cylinders for Variation in Engine and Cooling Conditions

Factors are obtained from semiempirical equations for correcting engine-cylinder temperatures for variation in important engine and cooling conditions. The variation of engine temperatures with atmospheric temperature is treated in detail, and correction factors are obtained for various flight and test conditions, such as climb at constant indicated air speed, level flight, ground running, take-off, constant speed of cooling air, and constant mass flow of cooling air. Seven conventional air-cooled engine cylinders enclosed in jackets and cooled by a blower were tested to determine the effect of cooling-air temperature and carburetor-air temperature on cylinder temperatures. The cooling air temperature was varied from approximately 80 degrees F. to 230 degrees F. and the carburetor-air temperature from approximately 40 degrees F. to 160 degrees F. Tests were made over a large range of engine speeds, brake mean effective pressures, and pressure drops across the cylinder. The correction factors obtained experimentally are compared with those obtained from the semiempirical equations and a fair agreement is noted.

Schey, Oscar W↗

DOE OSTI2021

Lawrence Berkley National Laboratory Building 59

The building management system in Building 59 is monitoring and archiving building-level electricity usage, HVAC and lighting system states (e.g., setpoint, temperature, flow rate, pressure), indoor environmental conditions (air temperature, relative humidity, CO2), on-site weather (air temperature, relative humidity), and especially occupant counts as well as other metrics such as Wi-Fi signal. This dataset could support multiple use cases, such as model predictive control and occupant related demand management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Lawrence Berkley National Laboratory Building 59 (Raw)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Lawrence Berkeley National Lab Building 59

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1999

Project ATLANTA (Atlanta Land use Analysis: Temperature and Air Quality): Use of Remote Sensing and Modeling to Analyze How Urban Land Use Change Affects Meteorology and Air Quality Through Time

This paper presents an overview of Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air-quality) which is an investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality. The primary objectives for this research effort are: (1) To investigate and model the relationships between land cover change in the Atlanta metropolitan, and the development of the urban heat island phenomenon through time; (2) To investigate and model the temporal relationships between Atlanta urban growth and land cover change on air quality; and (3) To model the overall effects of urban development on surface energy budget characteristics across the Atlanta urban landscape through time. Our key goal is to derive a better scientific understanding of how land cover changes associated with urbanization in the Atlanta area, principally in transforming forest lands to urban land covers through time, has, and will, effect local and regional climate, surface energy flux, and air quality characteristics. Allied with this goal is the prospect that the results from this research can be applied by urban planners, environmental managers and other decision-makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta area. Multiscaled remote sensing data, particularly high resolution thermal infrared data, are integral to this study for the analysis of thermal energy fluxes across the Atlanta urban landscape.

Quattrochi, Dale A.↗

NASA NTRS1979

Passive microwave applications to snowpack monitoring using satellite data

Nimbus-5 Electrically Scanned Microwave Radiometer data were analyzed for the fall of 1975 and winter and summer of 1976 over the Arctic Coastal Plain of Alaska to determine the applicability of those data to snowpack monitoring. It was found that when the snow depth remained constant at 12.7 cm, the brightness temperatures T sub B varied with air temperature. During April and May the production of ice lenses and layers within the snow, and possibly wet ground beneath the snow contribute to the T sub B variations also. Comparison of March T sub B values of three areas with the same (12.7 cm) snow depth showed that air temperature is the predominant factor controlling the T sub B differences among the three areas, but underlying surface conditions and individual snowpack characteristics are also significant factors.

Hall, D. K.↗

DOE OSTI2025

Artificial light at night outweighs temperature in lengthening urban growing seasons

Plant growing seasons are largely regulated by light and temperature. Cities are increasingly hot (higher air temperature), from the urban heat island effect, and bright (artificial light at night, ALAN). However, the relative effect of heat and light on the timing of plant growth events, called phenology, is unclear, limiting our understanding under climate change and urbanization. Here we used multiple satellite observations of 428 Northern Hemisphere cities from 2014 to 2020 to analyze phenological patterns along a gradient from rural to urban. We found that ALAN increased exponentially toward urban centers, and exerted stronger influence than air temperature in lengthening the urban growing season, especially by delaying its end, although the effects varied across climate zones. Our findings demonstrate that ALAN is a critical driver of vegetation dynamics in cities, one we should consider during urban management and development.

Wang, Lvlv [Wuhan Univ. (China)] (ORCID:0000000347↗

NASA NTRS2006

Integrated Testing of a 4-Bed Molecular Sieve, Air-Cooled Temperature Swing Adsorption Compressor, and Sabatier Engineering Development Unit

Accumulation and subsequent compression of carbon dioxide that is removed from the space cabin are two important processes involved in a closed-loop air revitalization scheme of the International Space Station (ISS). The 4-Bed Molecular Sieve (4BMS) of ISS currently operates in an open loop mode without a compressor. The Sabatier Engineering Development Unit (EDU) processes waste CO2 to provide water to the crew. This paper reports the integrated 4BMS, air-cooled Temperature Swing Adsorption Compressor (TSAC), and Sabatier EDU testing. The TSAC prototype was developed at NASA Ames Research Center (ARC). The 4BMS was modified to a functionally flight-like condition at NASA Marshall Space Flight Center (MSFC). Testing was conducted at MSFC. The paper provides details of the TSAC operation at various CO2 loadings and corresponding performance of the 4BMS and Sabatier.

Knox, James C.↗

NASA NTRS1992

Aerosol optical properties over the midcontinental United States

Solar and sky radiation measurements were analyzed to obtain aerosol properties such as the optical thickness and the size distribution. The measurements were conducted as part of the First International Satellite Land Surface Climatology Project Field Experiment during the second intensive field campaign (IFC) from June 25 to July 14, 1987, and the fifth IFC from July 25 to August 12, 1989, on the Konza Prairie near Manhattan, Kansas. Correlations with climatological and meteorological parameters show that during the period of observations in 1987, two types of air masses dominated the area: an air mass with low optical thickness and low temperature air associated with a northerly breeze, commonly referred to as the continental air, and an air mass with a higher optical thickness and higher temperature air associated with a southerly wind which we call 'Gulf air'. The size distributions show a predominance of the larger size particles in 'Gulf air'. Because of the presence of two contrasting air masses, correlations with parameters such as relative humidity, specific humidity, pressure, temperature, and North Star sky radiance reveal some interesting aspects. In 1989, clear distinctions between continental and Gulf air cannot be made; the reason for this will be discussed.

Halthore, Rangasayi N.↗

NASA NTRS2008

Data Assimilation Experiments using Quality Controlled AIRS Version 5 Temperature Soundings

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AlRS data. Version 5 contains accurate case-by-case error estimates for most derived products, which are also used for quality control. We have conducted forecast impact experiments assimilating AlRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the NASA FVGCM. Assimilation of quality controlled temperature profiles resulted in significantly improved forecast skill in both the Northern Hemisphere and Southern Hemisphere Extra-Tropics, compared to that obtained from analyses obtained when all data used operationally by NCEP except for AlRS data is assimilated. Experiments using different Quality Control thresholds for assimilation of AlRS temperature retrievals showed that a medium quality control threshold performed better than a tighter threshold, which provided better overall sounding accuracy; or a looser threshold, which provided better spatial coverage of accepted soundings. We are conducting more experiments to further optimize this balance of spatial coverage and sounding accuracy from the data assimilation perspective. In all cases, temperature soundings were assimilated well below cloud level in partially cloudy cases. The positive impact of assimilating AlRS derived atmospheric temperatures all but vanished when only AIRS stratospheric temperatures were assimilated. Forecast skill resulting from assimilation of AlRS radiances uncontaminated by clouds, instead of AlRS temperature soundings, was only slightly better than that resulting from assimilation of only stratospheric AlRS temperatures. This reduction in forecast skill is most likely the result of significant loss of tropospheric information when only AIRS radiances unaffected by clouds are used in the data assimilation process.

Susskind, Joel↗