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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

NANT Site - Microwave Radiometer Thermodynamic Retrievals TROPoe / Derived Data

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by NOAA Physical Sciences Laboratory on Nantucket Island for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

17 WIND ENERGY↗
DOE OSTI2025

NOAA PSL Microwave Radiometer Block Island / Thermodynamic retrievals TROPoe

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by NOAA Physical Sciences Laboratory on the Block Island for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

17 WIND ENERGY↗
NASA NTRS1992

The Split Window Microwave Radiometer (SWMR) for hurricane wind speed measurement from space

The monitoring of hurricanes demands considerable resources each year by the National Oceanic and Atmospheric Administration. Even with the extensive use of satellite and airborne probing of those storms, there is still much uncertainty involved in predicting landfall for timely evacuation of people subject to the threat. The concept of the Split Window Microwave Radiometer (SWMR) is to add an additional capability of remotely measuring surface winds to hopefully improve prediction capabilities or at least define the severity of the storm while it is far from land. Some of the present science and observational needs are addressed in this report as are remote sensing limitations which impact the design of a minimal system which can be launched into low earth orbit by a low cost launch system. This study has concluded that wind speed and rain rate maps of hurricanes can be generated with an X-Band radiometer system with an antenna whose aperture is 2 m on a side.

Swift, Calvin T.↗
NASA NTRS1980

Microwave radiometer measurements of soil moisture content

A unique set of radiometer measurements is presented, recorded during a 1000-h day and night monitoring of irrigated fields from fully saturated to completely dry. Radiometer measurements were recorded at 2.8-cm (X-band) and 21.4-cm (L-band) wavelengths for a range of incident angles from nadir to 50 deg. Soil moisture and soil temperature profile measurements were recorded to a depth of 15 cm. The test site was located in east-central Texas on a clay soil (Miller clay). Three bare-surface plots were used, each having a distinctly different surface roughness. Vegetated plots were also measured. The data quantify the sensitivity of microwave radiometer measurements to soil moisture variations, the effect of surface roughness on the measurement, and the influence of surface vegetation.

Newton, R. W.↗
NASA NTRS1988

Synthetic aperture microwave radiometer

Realizing the full potential of microwave remote sensing from space requires putting relatively large antennas in orbit. Research is being conducted to develop synthetic aperture antennas to reduce the physical collecting area required of sensors in space, and to possibly open the door to new applications of microwave remote sensing. The technique under investigation involves using a correlation interferometer with multiple baselines. The Microwave Sensors and Data Collection Branch has been engaged in research to develop this technique for applications to remote sensing of soil moisture from space. Soil moisture is important for agricultural applications and for understanding the global hydrologic cycle. An aircraft prototype of an instrument suitable for making such measurements was developed. This is an L-band radiometer called ESTAR which is hoped will become part of the Earth Observing System (EOS). ESTAR is a hybrid instrument which uses both real aperture antennas (long sticks to obtain resolution in the along-track dimension) and aperture synthesis (correlation between sticks to obtain resolution in the cross track dimension). The hybrid was chosen as a compromise to increase the sensitivity (T) of the instrument.

Levine, D. M.↗
NASA NTRS2000

A Preview of AMSR: Airborne C-band Microwave Radiometer (ACMR) Observations from SGP99

Although L-band is generally considered ideal for passive microwave sensing of soil moisture, near-future satellite observing systems such as Advanced Mechanically Scanned Radiometer (AMSR) will provide C-band data for several years before any L-band data might become available. The Southern Great Plains'99 (SGP99) Experiment was designed to generate C-band observations suitable for testing and refinement of AMSR-era soil moisture retrieval algorithms. C-band data collected using the Airborne C-band Microwave Radiometer (ACMR), a new high-accuracy NASA/GSFC instrument, clearly demonstrated a strong response to a 9-day drydown event as well as to differences between the northern (cooler & wetter) and southern (warmer & dryer) areas covered by the P-3 flights. For example, the H-polarized brightness temperatures observed during the first three days of the drydown increased up to 50 K in the northern areas. These observations represent a preview of what we can expect from AMSR, albeit at 3-km spatial resolution vs. approximately 60 km for AMSR. Initial results of soil-vegetation microwave modeling will also be presented to estimate the relative contributions of soil physical temperature, canopy physical temperature, soil moisture, and canopy moisture. Significant radio-frequency interference (RFI) was evident during the experiment, and amelioration strategies will be discussed. The net effect of RFI (an upward bias in brightnesses) when averaged over an AMSR footprint is expected to be more subtle.

Kim, Edward↗
NASA NTRS1984

Comparison of sea surface wind speed fields by SEASAT radar altimeter, scatterometer and scanning multichannel microwave radiometer with an emphasis on the Southern Ocean

The SEASAT altimeter (ALT), scatterometer (SASS), and scanning microwave multichannel radiometer (SMMR) measured sea surface wind speed. During the satellite lifetime from June to October 1978, the Austral winter, the highest wind speeds were recorded in the Southern Ocean. Three-month, monthly, and three-day surface wind speed fields deduced from the three Seasat wind speed sensors are compared. The monthly and three-day fields show a pronounced mesoscale (1000 km) variability in wind speed. At all space and time scales analyzed, differences of 40% are found in the magnitude of the wind speed features, with the ALT consistently yielding the lowest wind speed and the SMMR the highest.

Mognard, N. M.↗
NASA NTRS1992

ESTAR - A synthetic aperture microwave radiometer for measuring soil moisture

The measurement of soil moisture from space requires putting relatively large microwave antennas in orbit. Aperture synthesis, an interferometric technique for reducing the antenna aperture needed in space, offers the potential for a practical means of meeting these requirements. An aircraft prototype, electronically steered thinned array L-band radiometer (ESTAR), has been built to develop this concept and to demonstrate its suitability for the measurement of soil moisture. Recent flights over the Walnut Gulch Watershed in Arizona show good agreement with ground truth and with measurements with the Pushbroom Microwave Radiometer (PBMR).

Le Vine, D. M.↗
NASA NTRS1981

The Effect of Sea-Surface Sun Glitter on Microwave Radiometer Measurements

A relatively simple model for the microwave brightness temperature of sea surface Sun glitter is presented. The model is an accurate closeform approximation for the fourfold Sun glitter integral. The model computations indicate that Sun glitter contamination of on orbit radiometer measurements is appreciable over a large swath area. For winds near 20 m/s, Sun glitter affects the retrieval of environmental parameters for Sun angles as large as 20 to 25 deg. The model predicted biases in retrieved wind speed and sea surface temperature due to neglecting Sun glitter are consistent with those experimentally observed in SEASAT SMMR retrievals. A least squares retrieval algorithm that uses a combined sea and Sun model function shows the potential of retrieving accurate environmental parameters in the presence of Sun glitter so long as the Sun angles and wind speed are above 5 deg and 2 m/s, respectively.

Wentz, F. J.↗
NASA NTRS1999

A TRMM Microwave Radiometer Rain Rate Estimation Method with Convective and Stratiform Discrimination

Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer brightness temperature data in the 85 GHz channel (T85) reveal distinct local minima (T85min) in a regional map containing a Mesoscale Convective System (MCS). This is because of relatively small footprint size (approximately 5.5 km) and strong extinction properties in this channel of the TMI. A map of surface rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85(sub min), produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we infer empirically from TMI data the presence of three different kinds of thunderstorms or Cbs. These Cbs are classified as young, mature, and decaying types, and are assumed to have a scale of about 20 km on the average. Two parameters are used to classify these three kinds of Cbs based on the T85 data: a) the magnitude of scattering depression deduced from local T85(sub min) and b) the mean horizontal gradient of T85 around such minima. Knowing the category of a given Cb, we can estimate the rain rate associated with it. Such estimation is done with the help of relationships linking T85min to rain rate in each Cb type. Similarly, a weak background rain rate in all the areas where T85 is less than 260 K is deduced with another relationship linking T85 to rain rate. In our rain retrieval model, this background rain constitutes stratiform rain where the Cbs are absent. Initially, these relationships are optimized or tuned utilizing the PR and TMI data of a few MCS events. After such tuning, the model is applied to independent MCS cases. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (>= 20 mm/hr) rain rates are retrieved satisfactorily. Accuracy in the estimates of the light, moderate, and intense rain areas and the mean rain rates associated with such areas in these independent MCS cases is on the average about 15 %. Taking advantage of this ability of our retrieval method, one could derive the latent heat input into the atmosphere over the 760 km wide swath of the TMI radiometer in the tropics.

Prabhakara, C.↗
NASA NTRS2000

TRMM Microwave Radiometer Rain Rate Estimation Method with Convective and Stratiform Discrimination

Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer brightness temperature data in the 85 GHz channel (T85) reveal distinct local minima (T85min) in a regional map containing a Mesoscale Convective System (MCS). A map of surface rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85min, produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we have developed a TMI algorithm to retrieve convective and stratiform rain. In this algorithm, two parameters are used to classify three kinds of thunderstorms (Cbs) based on the T85 data: a) the magnitude of scattering depression deduced from local T85mi, and b) the mean horizontal gradient of T85 around such minima. Initially, the algorithm is optimized or tuned utilizing the PR and TMI data of a few MCS events. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (greater than or equal to 20 mm/hr) rain rates are retrieved on the average with an accuracy of about 15%. Taking advantage of this ability of our retrieval method, one could derive the latent heat input into the atmosphere over the 760 km wide swath of the TMI radiometer in the tropics.

Prabhakara, Cuddapah↗
NASA NTRS2008

Wind Retrievals under Rain for Passive Satellite Microwave Radiometers and its Applications to Hurricane Tracking

We have developed an algorithm that retrieves wind speed under rain using C-hand and X-band channels of passive microwave satellite radiometers. The spectral difference of the brightness temperature signals due to wind or rain allows to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. We &ve trained a statistical algorithm that applies under hurricane conditions and is able to measure wind speeds in hurricanes to an estimated accuracy of about 2 m/s. We have also developed a global algorithm, that is less accurate but can be applied under all conditions. Its estimated accuracy is between 2 and 5 mls, depending on wind speed and rain rate. We also extend the wind speed region in our model for the wind induced sea surface emissivity from currently 20 m/s to 40 mls. The data indicate that the signal starts to saturate above 30 mls. Finally, we make an assessment of the performance of wind direction retrievals from polarimetric radiometers as function of wind speed and rain rate

Meissner, Thomas↗