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

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Atmospheric temperature, water vapour and liquid water path from two microwave radiometers during MOSAiC

The microwave radiometers HATPRO (Humidity and Temperature Profiler) and MiRAC-P (Microwave Radiometer for Arctic Clouds - Passive) continuously measured radiation emitted from the atmosphere throughout the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition on board the research vessel Polarstern. From the measured brightness temperatures, we have retrieved atmospheric variables using statistical methods in a temporal resolution of 1 s covering October 2019 to October 2020. The integrated water vapour (IWV) is derived individually from both radiometers. In addition, we present the liquid water path (LWP), temperature and absolute humidity profiles from HATPRO. To prove the quality and to estimate uncertainty, the data sets are compared to radiosonde measurements from Polarstern. The comparison shows an extremely good agreement for IWV, with standard deviations of 0.08–0.19 kg m -2 (0.39–1.47 kg m -2 ) in dry (moist) situations. The derived profiles of temperature and humidity denote uncertainties of 0.7–1.8 K and 0.6–0.45 gm -3 in 0–2 km altitude.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Dual Microwave Radiometer Experiment Field Campaign Report

Passive microwave radiometers (MWRs) are the most commonly used and accurate instruments the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Research Facility has to retrieve cloud liquid water path (LWP). The MWR measurements (microwave radiances or brightness temperatures) are often used to derive LWP using climatological constraints, but are frequently also combined with measurements from radar and other instruments for cloud microphysical retrievals. Nominally this latter approach improves the retrieval of LWP and other cloud microphysical quantities (such as effective radius or number concentration), but this also means that when MWR data are poor, other cloud microphysical quantities are also negatively affected. Unfortunately, current MWR data is often contaminated by water on the MWR radome. This water makes a substantial contribution to the measured radiance and typically results in retrievals of cloud liquid water and column water vapor that are biased high. While it is obvious when the contamination by standing water is large (and retrieval biases are large), much of the time it is difficult to know with confidence that there is no contamination. At present there is no attempt to estimate or correct for this source of error, and identification of problems is largely left to users. Typically users are advised to simply throw out all data when the MWR “wet-window” resistance-based sensor indicates water is present, but this sensor is adjusted by hand and is known to be temperamental. In order to address this problem, a pair of ARM microwave radiometers was deployed to the University of Washington (UW) in Seattle, Washington, USA. The radiometers were operated such that one radiometer was scanned under a cover that (nominally) prevents this radiometer radome from gathering water and permits measurements away from zenith; while the other radiometer is operated normally – open or uncovered - with the radome exposed to the sky. The idea is that (1) the covered radiometer data can provide LWP (and water vapor) along the off-zenith slant path and (2) the two sets of measurements can be compared to identify when wet-radome contamination is occurring.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Microwave Radiometer – 3-Channel (MWR3C) Instrument Handbook

The microwave radiometer 3-channel (MWR3C) provides time-series measurements of brightness temperatures from three channels centered at 23.834, 30, and 89 GHz. These three channels are sensitive to the presence of liquid water and precipitable water vapor.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

MWRRETV2 Value-Added Product Report: The Retrieval of Liquid Water Path and Precipitable Water Vapor from Microwave Radiometer – 3-Channel (MWR3C) Data Sets

This report provides a short description of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Microwave Radiometer – 3-Channel (MWR3C) Retrieval (MWRRETV2) Value-Added Product (VAP) algorithm. MWRRETV2 is an updated version of MWRRET, which extends the physical-iterative retrieval of liquid water path (LWP) and precipitable water vapor PWV) to 3-channel microwave radiometers beyond ARM's original standard 2-channel (23-and 31-GHz) systems. The 89-GHz channel in the 3-channel microwave radiometers has approximately three times the sensitivity to liquid water as the 31-GHz channel, thus improving LWP retrieval accuracy when LWP is less than 100 g/m2. We present a general overview of the technique, input parameters, and output products, and describe data quality checks.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Microwave Radiometer Profiler (MWRP) Instrument Handbook

The Microwave Radiometer Profiler (MWRP) provides time-series measurements of brightness temperatures from 12 channels between 22.235 and 58.80 GHz. These channels are sensitive to the presence of liquid water and precipitable water vapor and to the atmospheric temperature and humidity profile.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Microwave Radiometer: Meteorological Temperature Profiler (raw)

The microwave radiometer profiler (MWRP) provides vertical profiles of temperature, humidity, and cloud liquid water content as a function of height or pressure at approximately 5-minute intervals for nearly all weather conditions. The profiles are derived from measurements of absolute microwave radiances (expressed as "brightness temperatures") obtained at 12 frequencies in the range of 22-30 GHz and 51-59 GHz. The data are useful for input to numerical weather forecast models and others that require continuous, high-temporal-resolution profiles. The microwave radiance measurements are useful for testing models of microwave radiation transfer used to derive the profiles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Assessing the accuracy of microwave radiometers and radio acoustic sounding systems for wind energy applications

To assess current remote-sensing capabilities for wind energy applications, a remote-sensing system evaluation study, called XPIA (eXperimental Planetary boundary layer Instrument Assessment), was held in the spring of 2015 at NOAA's Boulder Atmospheric Observatory (BAO) facility. Several remote-sensing platforms were evaluated to determine their suitability for the verification and validation processes used to test the accuracy of numerical weather prediction models. The evaluation of these platforms was performed with respect to well-defined reference systems: the BAO's 300 m tower equipped at six levels (50, 100, 150, 200, 250, and 300 m) with 12 sonic anemometers and six temperature ( T ) and relative humidity (RH) sensors; and approximately 60 radiosonde launches. In this study we first employ these reference measurements to validate temperature profiles retrieved by two co-located microwave radiometers (MWRs) as well as virtual temperature ( T v ) measured by co-located wind profiling radars equipped with radio acoustic sounding systems (RASSs). Results indicate a mean absolute error (MAE) in the temperature retrieved by the microwave radiometers below 1.5 K in the lowest 5?km of the atmosphere and a mean absolute error in the virtual temperature measured by the radio acoustic sounding systems below 0.8 K in the layer of the atmosphere covered by these measurements (up to approximately 1.6-2 km). We also investigated the benefit of the vertical velocity correction applied to the speed of sound before computing the virtual temperature by the radio acoustic sounding systems. We find that using this correction frequently increases the RASS error, and that it should not be routinely applied to all data. Water vapor density (WVD) profiles measured by the MWRs were also compared with similar measurements from the soundings, showing the capability of MWRs to follow the vertical profile measured by the sounding and finding a mean absolute error below 0.5 g m -3 in the lowest 5 km of the atmosphere. However, the relative humidity profiles measured by the microwave radiometer lack the high-resolution details available from radiosonde profiles. Furthermore, an encouraging and significant finding of this study was that the coefficient of determination between the lapse rate measured by the microwave radiometer and the tower measurements over the tower levels between 50 and 300 m ranged from 0.76 to 0.91, proving that these remote-sensing instruments can provide accurate information on atmospheric stability conditions in the lower boundary layer.

17 WIND ENERGY↗
DOE OSTI2024

Microwave Radiometer — 3-Channel (MWR3C) Instrument Handbook

The microwave radiometer – 3-channel (MWR3C, RPG-LWP-U90) deployed by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility provides time-series measurements of brightness temperatures from three channels centered at 23.834, 30, and 89 GHz. These three channels are sensitive to the presence of liquid water and precipitable water vapor.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Microwave radiometer, sun-photometer and GNSS multi-comparison of integrated water vapor in Southwestern Europe

This work presents a comparison of integrated water vapor (IWV) data recorded from microwave radiometer (MWR) and sun-photometer (SP) using global navigation satellite system (GNSS) IWV as reference in five mid-latitude sites of Portugal and Spain (2003–2021). A very high correlation is obtained for both instruments (R2 between 0.94 and 0.98), although, while MWR shows a wet bias, SP exhibits a dry one. In addition, a dependence of mean bias error (MBE) and standard deviation (SD) on IWV has been observed, increasing (larger discrepancies) both indices as IWV increases. The solar zenith angle (SZA) dependence is also studied, finding slightly larger discrepancies for the MWR than for SP in comparison with GNSS for very high values of SZA. Finally, a marked seasonal dependence is observed for SP-GNSS differences, modulated by the IWV dependence explained above. In contrast, the seasonal dependence for MWR is quite weaker than it is for SP. Therefore, in spite of the excellent agreement found among the different instruments, it is recommended that: i) the dependence with IWV be studied and corrected to further increase the performance of the instruments, and ii) metadata be used to filter out situations in which the instrument cannot operate properly.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

ARM Site E36 - CLAMPS 2 Microwave Radiometer / Processed Data

This dataset contains processed data from the CLAMPS 2 Humidity And Temperature PROfiler (HATPRO) Microwave Radiometer and its associated meteorology tower. CLAMPS 2 deployed during fall-winter 2022 (10/3/22-12/27/23) and summer-fall 2023 (6/16/23-10/1/23).

17 WIND ENERGY↗