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ARM Aerial Facility (AAF) - Unmanned Aircraft Systems, Infrared Thermometer: Sky brightness temperature with QC and lat/log/alt
Mobile radar-radiometer facility for measuring backscattering and brightness temperature of terrain at microwave frequencies
The main goal of this project is to assess and understand how passive microwave brightness temperature values relate to particular hydrometeor types. The hydrometeor types are taken from dual polarization radar hydrometeor identifications in the GPM Validation Network database of matchups between the GPM Microwave Imager (GMI) and dozens of ground radars mostly in the U.S.
L-band brightness temperature (T(sub b)) is one of the key remotely-sensed variables that provides information regarding surface soil moisture conditions. In order to harness the information in T(sub b) observations, a radiative transfer model (RTM) is investigated for eventual inclusion into a data assimilation framework. In this study, T(sub b) estimates from the RTM implemented in the NASA Goddard Earth Observing System (GEOS) were evaluated against the nearly four-year record of daily T(sub b) observations collected by L-band radiometers onboard the Aquarius satellite. Statistics between the modeled and observed T(sub b) were computed over North America as a function of soil hydraulic properties and vegetation types. Overall, statistics showed good agreement between the modeled and observed T(sub b) with a relatively low, domain-average bias (0.79 K (ascending) and -2.79 K (descending)), root mean squared error (11.0 K (ascending) and 11.7 K (descending)), and unbiased root mean squared error (8.14 K (ascending) and 8.28 K (descending)). In terms of soil hydraulic parameters, large porosity and large wilting point both lead to high uncertainty in modeled T(sub b) due to the large variability in dielectric constant and surface roughness used by the RTM. The performance of the RTM as a function of vegetation type suggests better agreement in regions with broadleaf deciduous and needleleaf forests while grassland regions exhibited the worst accuracy amongst the five different vegetation types.
Surface melting is a major component of the Greenland ice sheet (GrIS) surface mass balance, affecting sea level rise through direct runoff and the modulation on ice dynamics and hydrological processes, supraglacially, englacially and subglacially. Passive microwave (PMW) brightness temperature observations are of paramount importance in studying the spatial and temporal evolution of surface melting in view of their long temporal coverage (1979–to date) and high temporal resolution (daily). However, a major limitation of PMW datasets has been the relatively coarse spatial resolution, being historically of the order of tens of kilometres. Here, we use a newly released passive microwave dataset (37 GHz, horizontal polarization) made available through the NASA MeASUREs program to study the spatiotemporal evolution of surface melting over the GrIS at an enhanced spatial resolution of 3.125 Km. We assess the outputs of different detection algorithms through data collected by Automatic Weather Stations (AWS) and the outputs of the MAR regional climate model. We found that surface melting is well captured using a dynamic algorithm based on the outputs of MEMLS model, capable to detect sporadic and persistent melting. Our results indicate that, during the reference period 1979–2019 (1988–2019), surface melting over the GrIS increased in terms of both duration, up to ~4.5 (2.9) days per decade, and extension, up to 6.9 % (3.6 %) of the GrIS surface extent per decade, according to the MEMLS algorithm. Furthermore, the melting season has started up to ~4 (2.5) days earlier and ended ~7 (3.9) days later per decade. We also explored the information content of the enhanced resolution dataset with respect to the one at 25 km and MAR outputs through a semi-variogram approach. We found that the enhanced product is more sensitive to local scale processes, hence confirming the potential interest of this new enhanced product for studying surface melting over Greenland at a higher spatial resolution than the historical products and monitor its impact on sea level rise. This offers the opportunity to improve our understanding of the processes driving melting, to validate modelled melt extent at high resolution and potentially to assimilate this data in climate models.
Surface melting is a major component of the Greenland ice sheet surface mass balance, and it affects sea level rise through direct runoff and the modulation of ice dynamics and hydrological processes, supraglacially, englacially and subglacially. Passive microwave (PMW) brightness temperature observations are of paramount importance in studying the spatial and temporal evolution of surface melting due to their long temporal coverage (1979–present) and high temporal resolution (daily). However, a major limitation of PMW datasets has been the relatively coarse spatial resolution, which has historically been of the order of tens of kilometers. Here, we use a newly released PMW dataset (37 GHz, horizontal polarization) made available through a NASA “Making Earth System Data Records for Use in Research Environments” (MeASUREs) program to study the spatiotemporal evolution of surface melting over the Greenland ice sheet at an enhanced spatial resolution of 3.125 km. We assess the outputs of different detection algorithms using data collected by automatic weather stations (AWSs) and the outputs of the Modèle Atmosphérique Régional (MAR) regional climate model. We found that sporadic melting is well captured using a dynamic algorithm based on the outputs of the Microwave Emission Model of Layered Snowpack (MEMLS), whereas a fixed threshold of 245 K is capable of detecting persistent melt. Our results indicate that, during the reference period from 1979 to 2019 (from 1988 to 2019), surface melting over the ice sheet increased in terms of both duration, up to 4.5 (2.9) d per decade, and extension, up to 6.9 % (3.6 %) of the entire ice sheet surface extent per decade, according to the MEMLS algorithm. Furthermore, the melting season started up to 4.0 (2.5) d earlier and ended 7.0 (3.9) d later per decade. We also explored the information content of the enhanced-resolution dataset with respect to the one at 25 km and MAR outputs using a semi-variogram approach. We found that the enhanced product is more sensitive to local-scale processes, thereby confirming the potential of this new enhanced product for monitoring surface melting over Greenland at a higher spatial resolution than the historical products and for monitoring its impact on sea level rise. This offers the opportunity to improve our understanding of the processes driving melting, to validate modeled melt extent at high resolution and, potentially, to assimilate these data in climate models.
Experimental and theoretical brightness temperature comparisons of lunar surface for different elevation angles of sun and observer
In situ measurements of lunar surface brightness temperatures made as a part of the Apollo Lunar Surface Experiments Package at the Apollo 15 Hadley Rille landing site are reported. Data derived from five thermocouples of the Heat Flow Experiment, which are lying on or just above the surface, are used to examine the thermal properties of the upper 15 cm of the lunar regolith using eclipse and nighttime cool-down temperatures. Application of finite-difference techniques in modeling the lunar soil shows that the thermocouple data are best fit by a model consisting of a low-density and low-thermal conductivity surface layer approximately 2 cm thick overlying a region increasing in conductivity and density with depth. Conductivities on the order of 0.00001 W per cm per deg K are postulated for the upper layer, with conductivity increasing to the order of 0.0001 W per cm per deg K at depths exceeding 20 cm. An increase in mean temperature with depth indicates that the ratio of radiative to conductive transfer at 350 K is 2.7 for at least the upper few centimeters of lunar soil; this value is nearly twice that measured for returned lunar fines.
The relationship between emerging microwave brightness temperatures (T(B)s) and vertically distributed mixtures of liquid and frozen hydrometeors was investigated, using a cloud-radiation model, in order to establish the framework for a hybrid statistical-physical rainfall retrieval algorithm. Although strong relationships were found between the T(B) values and various rain parameters, these correlations are misleading in that the T(B)s are largely controlled by fluctuations in the ice-particle mixing ratios, which in turn are highly correlated to fluctuations in liquid-particle mixing ratios. However, the empirically based T(B)-rain-rate (T(B)-RR) algorithms can still be used as tools for estimating precipitation if the hydrometeor profiles used for T(B)-RR algorithms are not specified in an ad hoc fashion.
In this study, we assimilate Soil Moisture Active Passive (SMAP) mission brightness temperature (Tb) observations into NASA’s Catchment Land Surface Model using an Ensemble Kalman filter to update surface and root-zone soil moisture simulations. Different time series components of the Tb observations are assimilated including anomalies, inter-annual variations, and high-frequency variations. To optimize the weights that the data assimilation (DA) puts on the observations, the ratio between the un-certainties of modeled and observed Tb is approximated using modeled and observed soil moisture uncertainties estimated using triple collocation analysis. Results are compared to a benchmark experiment that mimics the operational SMAP Level-4 algorithm, which assimilates Tb observations using a spatially-constant 4 Kelvin (K) observation uncertainty. All DA experiments exhibit notable skill improvements in most regions. Improvements are greatest for the inter-annual variations in the simulations of both surface and root-zone soil moisture (mean improvements in terms of Pearson correlation (-) are 0.08 and 0.06, respectively). Anomaly simulations improve similarly (0.07), and improvements in the high-frequency variations are only observed for sur-face soil moisture simulations (0.06). Strikingly, however, no notable difference in skill—neither improvement nor deterioration—is observed between the experiments that use optimized observation uncertainty parameters and the 4 K benchmark experiment. We show, analytically, that this may be explained by the presence of large observation operator errors, which have the potential to render post-update uncertainty insensitive to inaccuracies in the Kalman gain.
Water vapor radiometer measurements were made at DSS 43 during an 18 month period. Brightness temperatures at 31 GHz were subjected to a statistical analysis which included correction for the effects of occasional water on the radiometer radome. An exceedance plot was constructed, and the 1 percent exceedance statistics occurs at 120 K. The 5 percent exceedance statistics occurs at 70 K, compared with 75 K in Spain. These values are valid for all of the three month groupings that were studied.
Recent radio interferometer observations of Neptune enable comparisons of the radio brightness temperature (T(sub B)) spectra of all four giant planets. This comparison reveals evidence for fundamental differences in the compositions of Uranus' and Neptune's upper tropospheres, particularly in their ammonia (NH3) and hydrogen sulfide (H2S) mixing ratios, despite those planets' outward similarities. The tropospheric abundances of these constituents yield information about their deep abundances, and ultimately about the formation of the planets from the presolar nebula (Atreya et al.). Figures 1, 2, 3, and 4 show the T(sub B) spectra of Jupiter, Saturn, Uranus, and Neptune, respectively, from 0.1 to tens of cm wavelength. The data shown are collected from many observers. Data for Jupiter, Saturn, and Uranus are those cataloged by de Pater and Massie (1985), plus the Saturn Very Large Array (VLA) data by Grossman et al. Figure 3, Uranus, shows only data acquired since 1973. Before 1973 Uranus' T(sub B) increased steadily as its pole moved into view, causing significant scatter in those data. Neptune data at greater than 1 cm, all taken at the VLA, are collected from de Pater and Richmond, de Pater et al., and Hofstadter. For a variety of reasons, such as susceptibility to source confusion, single-dish data at those wavelengths are much noisier than the more reliable VLA data and have been ignored. Single-dish data by Griffin and Orton shortward of 0.4 cm are shown, along with the Owens Valley Radio Observatory (interferometer) datum at 0.266 cm by Muhleman and Berge. Spectra of Jupiter, Saturn, and Neptune share certain gross characteristics. In each spectrum, T(sub B) at 1.3 cm is approximately 120-140 K, less than approximately 30 K different from that at 0.1 cm. All three spectra show a break in slope at or near 1.3 cm, with T(sub B) increasing fairly rapidly with wavelength longward of 1.3 cm. Visible and IR spectroscopy show that NH3, whose strong inversion spectrum peaks at appropximately 1.3 cm, is an important tropospheric species at Jupiter and Saturn. Its signature on the Jovian radio spectrum is obvious, causing the prominent "hole" at 1.3 cm. At Saturn it is more subdued but is the source of that spectrum's change in slope at 1.3 cm. Radiative transfer models of Jupiter and Saturn with near-solar deep NH3 abundances agree well with the data (e.g., de Pater).
A new method for estimating downwelling shortwave and longwave radiation fluxes in the Arctic from TOVS brightness temperatures has been developed. The method employs a neural network to bypass computationally intensive inverse and for-ward radiative transfer calculations, Results from two drifting ice camps (CEAREX, LeadEx) and from one coastal station show that downwelling fluxes can be estimated with r.m.s. errors of 20 W/sq m for longwave radiation and 35 W/sq m for shortwave radiation. Mean errors are less than 4 W/sq m and are well within the bounds required for many climate process studies.
We present VLBI and Australia Telescope Compact Array images, and derive source frame radio-core brightness temperatures for three prominent, flat-spectrum extragalactic radio sources, notable because they have not been detected as gamma-ray sources with the EGRET instrument.
This paper presents the first experimental evidence that the polarimetric brightness temperatures of sea surfaces are sensitive to ocean wind direction in the incidence angle range of 30 to 50 degrees. Our experimental data were collected by a K-band (19.35 GHz) polarimetric wind radiometer (WINDRAD) mounted on the NASA DC-8 aircraft. A set of aircraft radiometer flights was successfully completed in November 1993. We performed circle flights over National Data Buoy Center (NDBC) moored buoys deployed off the northern California coast, which provided ocean wind measurements. The first WINDRAD flight was made on November 4, 1993. There was clear weather with a wind speed of 12 m/s at 330 degrees around the Pt. Arena buoy. We circled the buoy at three incidence angles, and all data when plotted as functions of azimuth angles show clear modulations of several Kelvin. At 40 degrees incidence angle, there is a 5 Kelvin peak-to-peak signal in the second Stokes parameter Q and the third Stokes parameter U. The Q data maximum is in the upwind direction and U has a 45 degrees phase shift in azimuth as predicted by theory. There is also an up/downwind asymmetry of 2 Kelvin in the Q data, and 1 Kelvin in the U data. At 50 degrees incidence angle, the collected data show very similar wind direction signatures to the SSM/I model function. Additional flights were made on other days under cloudy conditions. Data taken at a wind speed of 8 m/s show that at 40 degrees incidence Q and U have a smaller azimuthal modulation of 3 Kelvin, probably due to the lower wind speed. Additionally, the simultaneously recorded video images of sea surfaces suggested that Q and U data were less sensitive to unpolarized geophysical variations, such as clouds and whitecaps, while the T(v) and T(h) increased by a few Kelvin when the radiometer beam crossed over clouds, or there was a sudden increase of whitecaps in the radiometer footprint. The results of our aircraft flights indicate that passive polarimetric radiometry has a strong potential for global ocean wind speed and direction measurements from space.
This paper presents the first experimental evidence that the polarimetric brightness temperatures of sea surfaces are sensitive to ocean wind direction in the incidence angle range of 30 to 50 degrees.
Data processing of lunar infrared measurements at high spatial and radiometric resolution to obtain brightness temperatures
Lunar surface brightness temperatures derived as part of the Apollo 17 heat flow experiment are reported. Nighttime surface temperatures, calculated from the data provided by two thermocouples suspended about 15 cm above the lunar surface, are used to determine the conductivity profile of the upper 15 cm of regolith at the ALSEP site. The surface reaches a maximum temperature of 384 (plus or minus 6) K at lunar noon and cools to a minimum temperature of 102 (plus or minus 1.5 K) at the end of the lunar night. Conductivities of the order of .000015 W/cm-deg K are postulated for a 2-cm porous surface layer overlying more compact regolith material with conductivities in the range of .0001 to .00015 W/cm-deg K between 2 and 15 cm. A mean surface temperature of 216 (plus or minus 5) K is deduced from the thermocouple data. The 256 K temperature measured by the probe sensors at 130 cm thus indicates that a large mean temperature gradient exists at the Apollo 17 site.