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Progress in microwave remote sensing of soil moisture

Significant progress has been made in the application of microwave remote sensing for measuring soil moisture. Both passive and active systems have demonstrated the capability for measuring soil moisture. However, several questions are still unresolved regarding the optimal instrument configuration and other target characteristics, such as roughness and vegetation. In addition, the most likely disciplines for using these data, agriculture and hydrology, do not currently possess adequate models or procedures for using these new data.

Engman, Edwin T.↗

Overview of the NASA TROPICS CubeSat Constellation Mission

Recent technology advances in miniature microwave radiometers that can be hosted on very small satellites has made possible a new class of affordable constellation missions that provide very high revisit rates of tropical cyclones and other severe weather. The Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA as part of the Earth Venture-Instrument (EVI-3)program and is now in development with planned launch readiness in late 2019. The overarching goal for TROPICS is to provide nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones (TCs). TROPICS will provide rapid-refresh microwave measurements (median refresh rate better than 60 minutes for the baseline mission) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm life cycle. TROPICS will comprise a constellation of at least six CubeSats in three low-Earth orbital planes. Each CubeSat will host a high performance radiometer to provide temperature profiles using seven channels near the 118.75 GHz (gigahertz) oxygen absorption line, water vapor profiles using three channels near the 183 GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel at 205 GHz that is more sensitive to precipitation-sized ice particles and low-level moisture. This observing system offers an unprecedented combination of horizontal and temporal resolution in the microwave spectrum to measure environmental and inner-core conditions for TCs on a nearly global scale and is a major leap forward in the temporal resolution of several key parameters needed for assimilation into advanced data assimilation systems capable of utilizing rapid-update radiance or retrieval data. Here, we provide an overview of the mission and an update on current status,with a focus on unique characteristics of the Cubesat system, recent performance simulations on a range of observables to be provided by the constellation, and a summary of science applications.

Passive Microwave↗

Applications of airborne remote sensing in atmospheric sciences research

This paper explores the potential for airborne remote sensing for atmospheric sciences research. Passive and active techniques from the microwave to visible bands are discussed. It is concluded that technology has progressed sufficiently in several areas that the time is right to develop and operate new remote sensing instruments for use by the community of atmospheric scientists as general purpose tools. Promising candidates include Doppler radar and lidar, infrared short range radiometry, and microwave radiometry.

Serafin, R. J.↗

Beaufort/Bering 1979 microwave remote sensing data catalog report, 14-24 March 1979

The airborne microwave remote sending measurements obtained by the Langley Research Center in support of the 1979 Sea-Ice Radar Experiment (SIRE) in the Beaufort and Bering Seas are discussed. The remote sensing objective of SIRE was to define correlations between both active and passive microwave signatures and ice phenomena assocated with practical applications in the Arctic. The instruments used by Langley during SIRE include the stepped frequency microwave radiometer (SFMR), the airborne microwave scatterometer (AMSCAT), the precision radiation thermometer (PRT-5), and metric aerial photography. Remote sensing data are inventoried and cataloged in a user-friendly format. The data catalog is presented as time-history plots when and where data were obtained as well as the sensor configuration.

Hirstein, W. S.↗

A First Approach to Global Runoff Simulation using Satellite Rainfall Estimation

Many hydrological models have been introduced in the hydrological literature to predict runoff but few of these have become common planning or decision-making tools, either because the data requirements are substantial or because the modeling processes are too complicated for operational application. On the other hand, progress in regional or global rainfall-runoff simulation has been constrained by the difficulty of measuring spatiotemporal variability of the primary causative factor, i.e. rainfall fluxes, continuously over space and time. Building on progress in remote sensing technology, researchers have improved the accuracy, coverage, and resolution of rainfall estimates by combining imagery from infrared, passive microwave, and space-borne radar sensors. Motivated by the recent increasing availability of global remote sensing data for estimating precipitation and describing land surface characteristics, this note reports a ballpark assessment of quasi-global runoff computed by incorporating satellite rainfall data and other remote sensing products in a relatively simple rainfall-runoff simulation approach: the Natural Resources Conservation Service (NRCS) runoff Curve Number (CN) method. Using an Antecedent Precipitation Index (API) as a proxy of antecedent moisture conditions, this note estimates time-varying NRCS-CN values determined by the 5-day normalized API. Driven by multi-year (1998-2006) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis, quasi-global runoff was retrospectively simulated with the NRCS-CN method and compared to Global Runoff Data Centre data at global and catchment scales. Results demonstrated the potential for using this simple method when diagnosing runoff values from satellite rainfall for the globe and for medium to large river basins. This work was done with the simple NRCS-CN method as a first-cut approach to understanding the challenges that lie ahead in advancing the satellite-based inference of global runoff. We expect that the successes and limitations revealed in this study will lay the basis for applying more advanced methods to capture the dynamic variability of the global hydrologic process for global runoff monlto~ngin real time. The essential ingredient in this work is the use of global satellite-based rainfall estimation.

Hong, Yang↗

Passive microwave soil moisture research

The AgRISTARS Soil Moisture Project has made significant progress in the quantification of microwave sensor capabilities for soil moisture remote sensing. The 21-cm wavelength has been verified to be the best single channel for radiometric observations of soil moisture. It has also been found that other remote sensing approaches used in conjunction with L-band passive data are more successful than multiple wavelength microwave radiometry in this application. AgRISTARS studies have also improved current understanding of noise factors affecting the interpretability of microwave emission data. The absorption of soil emission by vegetation has been quantified, although this effect is less important than absorption effects for microwave radiometry.

Schmugge, T. J.↗

Assessment of the Impact of Spatial Heterogeneity on Microwave Satellite Soil Moisture Periodic Error

An accurate temporal and spatial characterization of errors is required for the efficient processing, evaluation, and assimilation of remotely-sensed surface soil moisture retrievals. However, empirical evidence exists that passive microwave soil moisture retrievals are prone to periodic artifacts which may complicate their application in data assimilation systems (which commonly treat observational errors as being temporally white). In this paper, the link between such temporally-periodic errors and spatial land surface heterogeneity is examined. Both the synthetic experiment and site-specified cases reveal that, when combined with strong spatial heterogeneity, temporal periodicity in satellite sampling patterns (associated with exact repeat intervals of the polar-orbiting satellites) can lead to spurious high frequency spectral peaks in soil moisture retrievals. In addition, the global distribution of the most prominent and consistent 8-day spectral peak in the Advanced Microwave Scanning Radiometer - Earth Observing System soil moisture retrievals is revealed via a peak detection method. Three spatial heterogeneity indicators - based on microwave brightness temperature, land cover types, and long-term averaged vegetation index - are proposed to characterize the degree to which the variability of land surface is capable of inducing periodic error into satellite-based soil moisture retrievals. Regions demonstrating 8-day periodic errors are generally consistent with those exhibiting relatively higher heterogeneity indicators. This implies a causal relationship between spatial land surface heterogeneity and temporal periodic error in remotely-sensed surface soil moisture retrievals.

Fangni Lei↗

The Norwegian remote sensing experiment (Norsex) in a marginal ice zone

Passive and active microwave measurements from surface based, airborne, and satellite instruments were obtained together with surface observations northwest of Svalbard. Emissivities of different ice patches in the ice edge region over the spectral range from 4.9 to 94 GHz are presented. The combination of a 6.6 GHz microwave radiometer with a 14.6 GHz scatterometer demonstrates the usefulness of an active/passive system in ice classification. A variety of mesoscale features under different meteorological conditions is revealed by a 1.36 GHz synthetic aperture radar. Ice edge location by Nimbus 7 scanning multifrequency microwave radiometer is shown accurate to 10 km when the 37 GHz horizontal polarized channel is used.

Farrelly, B.↗

Airborne passive polarimetric measurements of sea surface anisotropy at 92 GHz

The potential for remote sensing of ocean wave direction using passive polarimetric microwave observations was investigated. A fixed-beam 91.65 GHz polarimetric radiometer was mounted on the NASA DC-8 aircraft during the Tropical Ocean Global Atmosphere/Coupled Ocean Atmosphere Response Experiment (TOGA/COARE January - February 1993). Several experiments were performed during which the DC-8 was flown in constant bank-angle turns at approximately 1.5 km altitude to obtain azimuthal scans of the sea surface at fixed observation angles. Data at 65 deg from nadir are consistent with previous findings using 19 and 37 GHz Special Sensor Microwave Imager (SSM/1) satellite observations and support the claim that a broadband emission mechanism is responsible for the azimuthal brightness signatures. Accordingly, a tilted-facet geometrical optics (GO) model of the surface was developed to investigate emission from deterministic and random striated surfaces. Laboratory measurements of polarimetric emission at 92 GHz from small-amplitude water-waves corroborate this model.

Kunkee, D. B.↗

The Australian National Airborne Field Experiment 2005: Soil Moisture Remote Sensing at 60 Meter Resolution and Up

Spatially-distributed soil moisture observations have applications spanning a wide range of spatial resolutions from the very local needs of individual farmers to the progressively larger areas of interest to weather forecasters, water resource managers, and global climate modelers. To date, the most promising approach for space-based remote sensing of soil moisture makes use of passive microwave emission radiometers at L-band frequencies (1-2 GHz). Several soil moisture-sensing satellites have been proposed in recent years, with the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission scheduled to be launched first in a couple years. While such a microwave-based approach has the advantage of essentially allweather operation, satellite size limits spatial resolution to 10's of km. Whether used at this native resolution or in conjunction with some type of downscaling technique to generate soil moisture estimates on a finer-scale grid, the effects of subpixel spatial variability play a critical role. The soil moisture variability is typically affected by factors such as vegetation, topography, surface roughness, and soil texture. Understanding and these factors is the key to achieving accurate soil moisture retrievals at any scale. Indeed, the ability to compensate for these factors ultimately limits the achievable spatial resolution and/or accuracy of the retrieval. Over the last 20 years, a series of airborne campaigns in the USA have supported the development of algorithms for spaceborne soil moisture retrieval. The most important observations involved imagery from passive microwave radiometers. The early campaigns proved that the retrieval worked for larger and larger footprints, up to satellite-scale footprints. These provided the solid basis for proposing the satellite missions. More recent campaigns have explored other aspects such as retrieval performance through greater amounts of vegetation. All of these campaigns featured extensive ground truth collection over a range of grid spacings, to provide a basis for examining the effects of subpixel variability. However, the native footprint size of the airborne L-band radiometers was always a few hundred meters. During the recently completed (November, 2005) National Airborne Field Experiment (NAFE) campaign in Australia, a compact L-band radiometer was deployed on a small aircraft. This new combination permitted routine observations at native resolutions as high as 60 meters, substantially finer than in previous airborne soil moisture campaigns, as well as satellite footprint areal coverage. The radiometer, the Polarimetric L-band Microwave Radiometer (PLMR) performed extremely well and operations included extensive calibration-related observations. Thus, along with the extensive fine-scale ground truth, the NAFE dataset includes all the ingredients for the first scaling studies involving very-high-native resolution soil moisture observations and the effects of vegetation, roughness, etc. A brief overview of the NAFE will be presented, then examples of the airborne observations with resolutions from 60 m to 1 km will be shown, and early results from scaling studies will be discussed.

Kim, E. J.↗

Electric Field and Lightning Observations in the Core of Category 5 Hurricane Emily

Significant electric fields and lightning activity associated with Hurricane Emily were observed from a NASA high-altitude ER-2 aircraft on July 17, 2005 while this storm developed as a compact but intense category 5 hurricane in the Caribbean south of Cuba. The electrical measurements were acquired as part of the NASA sponsored Tropical Cloud Systems and Processes (TCSP) experiment. In addition to the electrical measurements, the aircraft's remote sensing instrument complement also included active radars, passive microwave, visible and infrared radiometers, and a temperature sounder providing details on the dynamical, microphysical, and environmental structure, characteristics and development of this intense storm. Cloud-to-ground lightning location data from Vaisala's long range lightning detection network were also acquired and displayed in real-time along with electric fields measured at the aircraft. These data and associated display also supported aircraft guidance and vectoring during the mission. During the observing period, flash rates in excess of 3 to 5 flashes per minute, as well as large electric field and field change values were observed as the storm appeared to undergo periods of intensification, especially in the northwest quadrant in the core eyewall regions. This is in contrast to most hurricanes that tend to be characterized by weak electrification and little or no lightning activity except in the outer rain bands. It should be noted that this storm also had significant lightning associated with its rain bands.

Blakeslee, Richard↗

Remote sensing applications in hydrometeorology

Monitoring of precipitation using remote sensing has been carried out successfully over oceans with passive microwave data and over land with visible and infrared data. Further research is necessary to improve accuracy and timeliness of estimations in a variety of rainfall situations. Snowmelt runoff prediction has been demonstrated using satellite snowcover data. Snow depth and wetness measurements are feasible using microwave techniques. The monitoring of ice cover, type, and thickness has been carried out successfully using remote methods. Results from remote sensing evapotranspiration studies have been inconclusive. The remote measurement of evapotranspiration seems to be the most challenging of all applications of remote sensing to hydrometeorology.

Rango, A.↗

Atmospheric limitations to clock synchronization at microwave frequencies

Clock synchronization schemes utilizing microwave signals that pass through the Earth's atmosphere are ultimately limited by our ability to correct for the variable delay imposed by the atmosphere. The atmosphere is non-dispersive at microwave frequencies and imposes a delay of roughly 8 nanosec times the cosecant of the elevation angle. This delay is composed of two parts, the delay due to water vapor molecules (i.e., the wet delay), and the delay due to all other atmospheric constituents (i.e., the dry delay). Water vapor contributes approximately 5 to 10% of the total atmospheric delay but is highly variable, not well mixed, and difficult to estimate from surface air measurements. However, the techniques of passive remote sensing using microwave radiometry can be used to estimate the line of sight delay due to water vapor with potential accuracies of 10 to 20 picosec. The devices that are used are called water vapor radiometers and simply measure the power emitted by the water vapor molecule at the 22.2 GHz spectral line. An additional power measurement is usually included at 31.4 GHz in order to compensate for the effect of liquid water (e.g., clouds). The dry atmosphere is generally in something close to hydrostatic equilibrium and its delay contribution at zenith can be estimated quite well from a simple barometric measurement. At low elevation angles one must compensate for refractive bending and possible variations in the vertical refractivity profile. With care these effects can be estimated with accuracies on the order of 30 picosec down to elevation angles of 10 degree.

Resch, G. M.↗

Remote sensing of soil moisture

The surface emissivity and reflectivity of soil are strong functions of its moisture content. Changes in emissivity, observed by passive microwave techniques (radiometry), and changes in reflectivity, observed by active microwave techniques (radar), can provide information on the moisture content of the 0 to 5 cm surface layer. In addition, the thermal inertia of the surface layer, which can be remotely sensed by observing the diurnal range of surface temperature, is an indicator of soil moisture content. The thermal infrared approach to remote sensing of soil moisture has little utility in the presence of cloud cover, but provides soil moisture data at high spatial resolutions and thermal data which are a potentially useful indicator of crop status. Microwave techniques can penetrate cloud covers. The passive technique has been demonstrated by both aircraft and spacecraft instruments, but spatial resolution is limited by the size of the antenna which can be flown. Active microwave systems offer the possibility of better spatial resolution, but have yet to be demonstrated from aircraft or spacecraft platforms.

Schmugge, T.↗

An integrated approach to the remote sensing of floating ice

Review article on remote sensing applications to glaciology. Ice parameters sensed include: ice cover vs open water, ice thickness, distribution and morphology of ice formations, vertical resolution of ice thickness, ice salinity (percolation and drainage of brine; flushing of ice body with fresh water), first-year ice and multiyear ice, ice growth rate and surface heat flux, divergence of ice packs, snow cover masking ice, behavior of ice shelves, icebergs, lake ice and river ice; time changes. Sensing techniques discussed include: satellite photographic surveys, thermal IR, passive and active microwave studies, microwave radiometry, microwave scatterometry, side-looking radar, and synthetic aperture radar. Remote sensing of large aquatic mammals and operational ice forecasting are also discussed.

Campbell, W. J.↗

The energy balance of wind waves and the remote sensing problem

Measurements of wave growth indicate an energy balance of the wave spectrum governed primarily by input from the atmosphere, nonlinear transfer to shorter and longer waves, and advection. The pronounced spectral peak and sharp low frequency cut-off characteristic of fetch-limited spectra are explained as a self-stabilizing feature of the nonlinear wave-wave interactions. The momentum transferred from the atmosphere to the wind waves accounts for a large part of the wind drag. These findings are relevant for remote microwave sensing of the sea surface by backscatter and passive radiometry methods.

Hasselmann, K.↗

Variations of mesoscale and large-scale sea ice morphology in the 1984 Marginal Ice Zone Experiment as observed by microwave remote sensing

The data acquired during the summer 1984 Marginal Ice Zone Experiment in the Fram Strait-Greenland Sea marginal ice zone, using airborne active and passive microwave sensors and the Nimbus 7 SMMR, were analyzed to compile a sequential description of the mesoscale and large-scale ice morphology variations during the period of June 6 - July 16, 1984. Throughout the experiment, the long ice edge between northwest Svalbard and central Greenland meandered; eddies were repeatedly formed, moved, and disappeared but the ice edge remained within a 100-km-wide zone. The ice pack behind this alternately diffuse and compact edge underwent rapid and pronounced variations in ice concentration over a 200-km-wide zone. The high-resolution ice concentration distributions obtained in the aircraft images agree well with the low-resolution distributions of SMMR images.

Campbell, W. J.↗

Intercalibration of AMSR2 NASA Team 2 Algorithm Sea Ice Concentrations with AMSR-E Slow Rotation Data

Sea ice estimates from AMSR2 are intercalibrated with AMSR-E fields through a two-step process. First, slow rotation 2 r/min AMSR-E data is used to derive regression equations from colocated pairs of AMSR2 and AMSR-E brightness temperatures (Tb s). The regression equations are used to modify AMSR2 Tb s into AMSR-E equivalent Tb s that are then input into the NASA Team 2 (NT2) sea ice concentration algorithm used for the AMSR-E standard products. The regressed Tb s result in changes in sea ice concentration of a few percent compared to using the original un-regressed AMSR2 Tb s. Next, sea ice estimates from the F17 SSMIS sensor are used as a bridge to compare AMSR-E total sea ice extent estimates in 2010 with AMSR2 total sea ice extent estimates in 2013. Based on this comparison, a further adjustment is made to a weather filter threshold used in the NT2 algorithm to minimize the total extent bias between AMSR2 and AMSR-E using a double-differencing approach. The adjustments reduced apparent bias with AMSR-E from 200 000 km2 for the original unmodified AMSR2 Tb s to –700 and 4700 km2 for the Arctic and Antarctic, respectively. These differences are within the range of previous passive microwave sea ice intercalibrations. The adjusted AMSR2 sea ice fields provide a nearly 15-year time series of sea ice change; depending on the lifetime of AMSR2 and possible follow on sensors, AMSR2 has the potential to be part of a multidecadal record of sea ice change.

remote sensing↗