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For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorge.c1 (ge=general sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. Note that reflectivity in this product is not calibrated.
For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorhi.c1 (hi=high sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. Note that reflectivity in this product is not calibrated.
For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorge.c1 (ge=general sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. Note that reflectivity in this product is not calibrated.
For each of the Ka ARM Zenith Radar (KAZR).a1 datastreams in the CF Radial format, KAZRCFRCOR VAP produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. This is the calibrated KAZRCFRCOR VAP data at level .c1.
For each of the Ka ARM Zenith Radar (KAZR).a1 datastreams in the CF Radial format, KAZRCFRCOR VAP produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. This is the calibrated KAZRCFRCOR VAP data at level .c1.
The Nimbus-4 IRIS data was examined in the spectral region 775 to 1250/cm (8-13 microns) for useful information to determine the sea surface temperature. The high spectral resolution data of IRIS was degraded to low resolution by averaging to simulate a multi-channel radiometer in the window region. These simulated data show that within the region 775-975/cm (12.9-10.25 microns) the brightness temperatures are linearly related to the absorption parameters. Such a linear relationship is observed over cloudy as well as clear regions and over a wide range of latitudes. From this linear relationship it is feasible to correct for the atmospheric attenuation and get the sea surface temperature, accurate to within 1 K, in a cloud free field of view. The information about the cloud cover is taken from the TV pictures and BUV albedo measurements on board the Nimbus-4 satellite.
Preliminary observations at 13.9 GHz of the radar backscatter and microwave emission from the sea were analyzed using data obtained by the radiometer scatterometer on Skylab. Results indicate approximately a square-law relationship between differential scattering coefficient and windspeed at angles of 40 deg to 50 deg, after correction for directional effect, over a range from about 4 up to about 25 meters/sec. The brightness temperature response was also observed, and considerable success was achieved in correcting it for atmospheric attenuation and emission. Measurements were made in June, 1973, over Hurricane Ava off the west coast of Mexico and over relatively calm conditions in the Gulf of Mexico and Caribbean Sea.
Intensity mapping experiments survey the spectrum of diffuse line radiation rather than detect individual objects at high signal-to-noise ratio. Spectral maps of unresolved atomic and molecular line radiation contain three-dimensional information about the density and environments of emitting gas and efficiently probe cosmological volumes out to high redshift. Intensity mapping survey volumes also contain all other sources of radiation at the frequencies of interest. Continuum foregrounds are typically approximately 10(sup 2)-10(Sup 3) times brighter than the cosmological signal. The instrumental response to bright foregrounds will produce new spectral degrees of freedom that are not known in advance, nor necessarily spectrally smooth. The intrinsic spectra of fore-grounds may also not be well known in advance. We describe a general class of quadratic estimators to analyze data from single-dish intensity mapping experiments and determine contaminated spectral modes from the data themselves. The key attribute of foregrounds is not that they are spectrally smooth, but instead that they have fewer bright spectral degrees of freedom than the cosmological signal. Spurious correlations between the signal and foregrounds produce additional bias. Compensation for signal attenuation must estimate and correct this bias. A successful intensity mapping experiment will control instrumental systematics that spread variance into new modes, and it must observe a large enough volume that contaminant modes can be determined independently from the signal on scales of interest.
The relative spectral response (RSR) characterization of the JPSS-1 VIIRS spectral bands has achieved at launch status in the VIIRS Data Analysis Working Group February 2016 Version 2 RSR release. The Version 2 release improves upon the June 2015 Version 1 release by including December 2014 NIST TSIRCUS spectral measurements of VIIRS VisNIR bands in the analysis plus correcting CO2 influence on the band M13 RSR. The T-SIRCUS based characterization is merged with the summer 2014 SpMA based characterization of VisNIR bands (Version 1 release) to yield a fused RSR for these bands, combining the strengths of the T-SIRCUS and the SpMA measurement systems. The M13 RSR is updated by applying a model-based correction to mitigate CO2 attenuation of the SpMA source signal that occurred during M13 spectral measurements. The Version 2 release carries forward the Version 1 RSR for those bands that were not updated (M8-M12, M14-M16AB, I3-I5, DNBMGS). The Version 2 release includes band average (overall detectors and subsamples) RSR plus supporting RSR for each detector and subsample. The at-launch band average RSR have been used to populate Look-Up Tables supporting the sensor data record and environmental data record at-launch science products. Spectral performance metrics show that JPSS-1VIIRS RSR are compliant on specifications with a few minor exceptions. The Version 2 release, which replaces the Version 1 release, is currently available on the password-protected NASA JPSS-1 eRooms under EAR99 control.
NASA Langley Mobile Ozone Lidar (LMOL) has capability to measure the O3 concentration from 0.1 to 8 km. A new method is proposed to retrieve the aerosol backscatter and extinction coefficients from the LMOL attenuated backscatter signals. The LMOL attenuated backscatter data are corrected by the O3 concentration determined by LMOL system. The aerosol extinction coefficients are retrieved by using Fernald-type method. The retrieved aerosol extinction coefficient profiles are compared with the coincident aerosol extinction coefficient profiles provided by overflights of the airborne High Altitude Lidar Observatory (HALO) system during the 2018 LISTOS campaign. Results show the new method has the capability to retrieve aerosol extinction coefficients from 0.1-8 km at night and 0.1-4 km during the day for 5 minute temporal averaging. The profile time series of the retrieved aerosol extinction coefficient are also compared with co-located ceilometer data, showing general agreement with aerosol features and dynamics. The impact of lidar extinction to backscatter ratios on the retrievals is also presented.This new method extends LMOL’s ability to quantitatively determine the vertical distribution of aerosol optical properties. This is expected to contribute to further understanding of the relationship between the ozone and aerosol in the wildfire emissions transport and impact on local air quality during the LISTOS campaign.
This Air Sparge (AS) System Construction Completion, Performance Monitoring, and Long-Term Monitoring (LTM) Report presents activities conducted at the Paint and Oil Locker (POL) (Solid Waste Management Unit [SWMU] 067) and Supply Warehouse #3 (SW3) (SWMU 088) sites located at the Kennedy Space Center (KSC), Florida. Activities include implementation and Year 1 (Quarters [Q] 1 through 4) and Q5 operation, maintenance, and monitoring (OM&M) activities and performance monitoring results for the AS Interim Measure (IM) in the POL Southern Treatment Area, LTM results for the POL Northern Area and SW3, and supplemental direct push technology (DPT) sampling at both sites to support the LTM and performance monitoring programs. The timeframe for activities included in this report extends from August 2019 to August 2022. The scope for these sites currently includes two main components, which are documented within this report: (1) LTM at SW3 and POL Northern Area where an AS system began operation at these sites in May 2009 and June 2013, respectively, and subsequently turned off for both sites in March 2018 (during the previous reporting period); and (2) Active AS operations and performance monitoring in the POL Southern Treatment Area where an AS system was installed and began operation in 2021. The AS IM in the POL Southern Treatment Area was implemented between 2019 and 2021 to treat a chlorinated solvent groundwater plume that resulted from historic operations supporting the National Aeronautics and Space Administration’s (NASA) Space Program. The objective of the AS IM is to remediate groundwater within the treatment zone to support transition to monitored natural attenuation (MNA). The overall Corrective Action objective is to reduce concentrations of trichloroethene (TCE), cis-1,2-dichloroethene (cDCE), trans-1,2- dichloroethene (tDCE), and vinyl chloride (VC) present in groundwater to levels below their respective State of Florida Groundwater Cleanup Target Levels (GCTLs). The AS IM was installed in the POL Southern Treatment Area to target the high concentration plume (HCP), which includes a source zone (SZ) area where TCE was found to exceed 11,000 micrograms per liter (µg/L), and extend to a depth of 30 feet below land surface (bls).
In this paper a sea surface radar echo spectral analysis technique to correct for the rainfall velocity error caused by radar-pointing uncertainty is presented. The correction procedure is quite straightforward when the radar is observing a homogeneous rainfall field. When nonuniform beam filling (NUBF) occurs and attenuating frequencies are used, however, additional steps are necessary in order to correctly estimate the antenna-pointing direction. This new technique relies on the application of the combined frequency-time (CFT) algorithm to correct for uneven attenuation effects on the observed sea surface Doppler spectrum. The performance of this correction technique was evaluated by a Monte Carlo simulation of the Doppler precipitation radar backscatter from high-resolution 3D rain fields (either generated by a cloud resolving numerical model or retrieved from airborne radar measurements). The results show that the antenna-pointing-induced error can, indeed, be reduced by the proposed technique in order to achieve 1 m s(exp -1) accuracy on rainfall vertical velocity estimates.
Micro-pulse lidar (MPL) measurements have been widely used in atmospheric research over the past few decades. However, the MPL afterpulse noise has a large impact on the MPL aerosol measurement in the middle and upper troposphere, and an effective correction method is still lacking. Here, a new afterpulse correction approach is presented by using measurements with low-level optically thick clouds to act as the lids blocking atmospheric signals beyond the clouds completely. Examples are provided to illustrate the effectiveness of this correction method. Using one-year 2014 MPL measurements at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site, the impact of the correction on the aerosol measurements is quantified. The relative error (RE, %) of attenuated backscattering ratio (ABR) without the afterpulse correction is 30% and 190% at the height of 1.00 km and 9.00 km (AGL), and the RE is larger for weaker aerosol signals (ABR<2). The RE of linear depolarization ratio (LDR), which is significantly higher than that of ABR for a given aerosol layer, is highly non-linear above 3.00 km, with a value of 300%-900% for weak aerosols (ABR<2) above 3.00 km. Therefore, the afterpulse correction is critical for the middle and upper tropospheric aerosol observations. We demonstrated that our afterpulse correction can provide reasonable particle depolarization ratio (PDR) to properly identify dust aerosols. The newly developed method can be applied to long-term MPL measurements to support aerosol and mixed-phase/ice cloud interaction study at the NSA site.
Various corrections are needed in order to extract the best value of the measurements from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility’s scanning precipitation radars. The Corrected Moments in Antenna Coordinates (CMAC) Value-Added Product provides an application chain for providing radar moments that are corrected for artifacts such as aliasing, attenuation, multi-trip echoes, and beam blockage. This technical report provides details on the entire process of correcting the ARM scanning precipitation radar data using CMAC. CMAC has been used at multiple ARM sites and ARM Mobile Facility deployments including the Tracking Aerosol Convection Interactions Experiment (TRACER), Cloud, Aerosol, and Complex Terrain Interactions (CACTI), and the Surface Atmosphere Integrated Laboratory (SAIL).
Potential techniques for measuring rainfall rate R and rainwater content W at 9 and 5 GHz are explored. An investigation is made of a previous technique to use the polarization propagation differential phase shift with increasing distance from the radar Phi(H-V) to estimate and remove the effects of specific and polarization differential attenuation from Z(H) and Z(DR), respectively. It is shown that in rain this technique is sensitive to variations in the drop-size distribution. It is confirmed that Phi(H-V) can be used to extend the distance over which useful measurements of Z(H) and Z(DR) can be obtained. While residual errors introduced by attenuation and the 'noise' from the correction scheme itself eclipse the potential of many possible techniques for quantitative rainfall measurements at these frequencies, the attenuation recovery scheme is argued to be adequate for obtaining useful polarization microphysical measurements, particularly above the melting level, even after encounters with rain.
Methods developed at the NASA Lewis Research Center for predicting the noise contributions from various aircraft noise sources were programmed to predict aircraft noise levels either in flight or in ground tests. The noise sources include fan inlet and exhaust, jet, flap (for powered lift), core (combustor), turbine, and airframe. Noise propagation corrections are available for atmospheric attenuation, ground reflections, extra ground attenuation, and shielding. Outputs can include spectra, overall sound pressure level, perceived noise level, tone-weighted perceived noise level, and effective perceived noise level at locations specified by the user. Footprint contour coordinates and approximate footprint areas can also be calculated. Inputs and outputs can be in either System International or U.S. customary units. The subroutines for each noise source and propagation correction are described. A complete listing is given.
From July 21 through August 22, 2025 the Absorption Measurement Inter-Comparison Experiment phase 2 (AMICE2) was conducted at Brookhaven National Laboratory. The experiment included concurrent operation of several filter-based instruments and in situ instruments sampling from a common sample line. The common sample line provided all instruments with either lab-generated aerosols composed of external mixtures of nigrosin, cabojet, and ammonium sulfate, or with ambient aerosol drawn through an external stack. This data set contains measurements from the CAPS PMssa instrument taken as a reference instrument at 532 nm and against which the effectiveness of the filter corrections may be assessed. It also contains attenuation coefficients from all filter-based instruments and filter transmittances in order to permit correction for filter loading, and the SSA and COA to permit corrections for aerosol darkness. Finally, two sets of multiplicative corrections are provided for the AE-33, TAP, and MA-350 instruments: the first one, Corr1, corrects for filter amplification factor and loading, the second one, Corr2, corrects for the aerosol darkness in terms of the natural log of COA.
Aquarius/SAC-D was launched in June 2011 by NASA and CONAE (Argentine space agency). Aquarius includes three L-band (1.4 GHz) radiometers dedicated to measuring sea surface salinity. We report detailed comparisons of Aquarius measurements with radiative transfer model predictions. These comparisons were used as part ofthe initial assessment of Aquarius data. In particular, they were used successfully to estimate the radiometer calibration bias and stability. Further comparisons are being performed to assess the performance of models in the retrieval algorithm for correcting the effect of sources of geophysical "noise" (e.g. the galactic background, atmospheric attenuation and reflected signal from the Sun). Such corrections are critical in bringing the error in retrieved salinity down to the required 0.2 practical salinity unit (psu) on monthly global maps at 150 km by 150 km resolution. The forward models making up the Aquarius simulator have been very useful for preparatory studies in the years leading to Aquarius' launch. The simulator includes various components to compute effects ofthe following processes on the measured signal: 1) emission from Earth surfaces (ocean, land, ice), 2) atmospheric emission and absorption, 3) emission from the Sun, Moon and celestial Sky (directly through the antenna sidelobes or after reflection/scattering at the Earth surface), 4) Faraday rotation, and 5) convolution of the scene by the antenna gain patterns. Since the Aquarius radiometers tum-on in late July 2011, the simulator has been used to perform a first order validation of the data. This included checking the order of magnitude ofthe signal over ocean, land and ice surfaces, checking the relative amplitude of signal at different polarizations, and checking the variation with incidence angle. The comparisons were also used to assess calibration bias and monitor instruments calibration drift. The simulator is also being used in the salinity retrieval. For example, initial assessments of the salinity retrieved from Aquarius data showed degradation in accuracy at locations where glint from the galactic sky background was important. This was traced to an inaccurate correction for the Sky glint. We present comparisons of the simulator prediction to the Aquarius data in order to assess the performances of the models of various physical processes impacting the measurements, such as the effect of sea surface roughness, the impact of the celestial Sky and the Sun emission scattered at the rough ocean surface. We discuss what components of the simulator appear reliable and which ones need improvements. Improved knowledge on the radiative transfer models at L-band will not only lead to better salinity retrieved from Aquarius data, it will also allow be beneficial for SMOS or the upcoming SMAP mission.