Microwave Signatures Research Articles

Comparison of Pr-doped Ca 122 and Ca 112 Pnictides by Low-field Microwave Absorption Spectroscopy

ABSTRACTPraseodymium doped CaFe2As2 (122 structure) and CaFeAs2 (112 structure) are characterized by modulated Low Magnetic Field Microwave Absorption (LFMA) spectroscopy. In both (Pr,Ca)122 and (Pr,Ca)112 structures, a strong hysteretic LFMA is found, with a TcH of ∼30 K and ∼26 K, respectively. However, in (Pr,Ca)122, measurements also show an unusual Narrow Peak (NP) LFMA signal appearing at higher temperatures, above the lower TcH superconducting state until a TcNP of 49 K. We associate this NP LFMA with interfacial superconductivity, which has been found previously by highly anisotropic magnetization measurements. Furthermore, the absence of NP in (Pr,Ca)112 correlates with the absence of an interfacial phase. These results give useful information about the microwave signature of interfacial superconductivity present in the (Pr,Ca)122 system, and may form a roadmap towards a stabilized high temperature superconducting phase in pnictides.

Detecting snowfall over land by satellite high‐frequency microwave observations: The lack of scattering signature and a statistical approach

AbstractIt has been long believed that the dominant microwave signature of snowfall over land is the brightness temperature decrease caused by ice scattering. However, our analysis of multiyear satellite data revealed that on most of occasions, brightness temperatures are rather higher under snowfall than nonsnowfall conditions, likely due to the emission by cloud liquid water. This brightness temperature increase masks the scattering signature and complicates the snowfall detection problem. In this study, we propose a statistical method for snowfall detection, which is developed by using CloudSat radar to train high‐frequency passive microwave observations. To capture the major variations of the brightness temperatures and reduce the dimensionality of independent variables, the detection algorithm is designed to use the information contained in the first three principal components resulted from Empirical Orthogonal Function (EOF) analysis, which capture ~99% of the total variances of brightness temperatures. Given a multichannel microwave observation, the algorithm first transforms the brightness temperature vector into EOF space and then retrieves a probability of snowfall by using the CloudSat radar‐trained look‐up table. Validation has been carried out by case studies and averaged horizontal snowfall fraction maps. The result indicated that the algorithm has clear skills in identifying snowfall areas even over mountainous regions.

Field Observations During the Ninth Microwave Water and Energy Balance Experiment (MicroWEX-9): from March 24, 2010 through January 6, 2011

The goal of MicroWEX-9 was to conduct a season-long experiment that incorporated passive microwave observations as well as Light Detection and Ranging (LiDAR) observations for a growing season of elephant grass. The variety of sensors would allow for further understanding of the land-atmosphere interactions during the growing season, and their effect on observed passive microwave signatures at 6.7 GHz and 1.4 GHz, as well as LiDAR scans. This 72-page fact sheet was written by Tara Bongiovanni, Pang-Wei Liu, Karthik Nagarajan, Robert Terwilleger, Alejandro Monsivais-Huertero, Jasmeet Judge, Juan Fernandez-Diaz, Daniel Preston, Tyler Cheney, Jason Motsinger, and published by the UF Department of Agricultural and Biological Engineering, January 2013.
 http://edis.ifas.ufl.edu/ae494

Regional Variability within Global-Scale Relations between Passive Microwave Signatures and Raining Clouds over the Tropical Oceans

AbstractEmpirical orthogonal function (EOF) analysis of radiance vectors associated with emission and scattering indices for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) has been performed to examine the regional variability in relations between brightness temperature and rain rate over portions of the tropical oceans known to exhibit regional differences due to different thermodynamic environments and different large-scale forcing. The TMI indices and rain rates used in this study are the products of the Goddard profiling algorithm (GPROF), version 6. The EOF framework reduces the nine-dimensional space of the brightness temperatures and their polarizations to just two dimensions associated with the EOF coefficients. Vertical profiles of reflectivity from the TRMM precipitation radar (PR) are used to show that the statistically obtained EOFs represent bulk physical characteristics of raining clouds. Hence, EOF analysis provides an efficient framework for diagnosing regional differences in cloud structures that affect brightness temperature–rain-rate relations. The EOF framework revealed fundamental differences in the behavior of TMI surface rain-rate retrievals versus retrievals that are based on the PR aboard the TRMM satellite. In EOF space, TMI rain rates were bimodally distributed, with one mode indicating higher rain rates with greater high-density ice and rainwater content in the cloud and the other mode being consistent with moderately heavy warm rain from shallow convection. In contrast, the PR rain-rate distribution showed high rain rates being assigned over a much greater diversity of cloud structures. The manifold of EOF space constructively shows that, of the regions examined here, the tropical northwestern Pacific Ocean region produces the greatest occurrence of particularly strong cumulonimbus clouds.

Passive microwave remote sensing of the historic February 2010 snowstorms in the Middle Atlantic region of the USA

AbstractThe snowfall in the Baltimore/Washington metropolitan area during the winter of 2009/2010 was unprecedented and caused serious snow‐related disruptions. In February 2010, snowfall totals approached 2 m, and because maximum temperatures were consistently below normal, snow remained on the ground the entire month. One of the biggest contributing factors to the unusually severe winter weather in 2009/2010, throughout much of the middle latitudes, was the Arctic Oscillation. Unusually high pressure at high latitudes and low pressure at middle latitudes forced a persistent exchange of mass from north to south. In this investigation, a concerted effort was made to link remotely sensed falling snow observations to remotely sensed snow cover and snowpack observations in the Baltimore/Washington area. Specifically, the Advanced Microwave Scanning Radiometer onboard the Aqua satellite was used to assess snow water equivalent, and the Advanced Microwave Sounding Unit‐B and Microwave Humidity Sounder were employed to detect falling snow. Advanced Microwave Scanning Radiometer passive microwave signatures in this study are related to both snow on the ground and surface ice layers. In regard to falling snow, signatures indicative of snowfall can be observed in high frequency brightness temperatures of Advanced Microwave Sounding Unit‐B and Microwave Humidity Sounder. Indeed, retrievals show an increase in snow water equivalent after the detection of falling snow. Yet, this work also shows that falling snow intensity and/or the presence of liquid water clouds impacts the ability to reliably detect snow water equivalent. Moreover, changes in the condition of the snowpack, especially in the surface features, negatively affect retrieval performance. Copyright © 2011. This article is a U.S. Government work and is in the public domain in the USA.

Detection of oyster habitat in tidal flats using multi-frequency polarimetric SAR data

Exposed oyster reefs in tidal flats have complex and rough surfaces because of their unique surface texture, which are quite distinct from the surrounding mud or sand flats. Here we investigate the microwave signatures, backscattered from naturally distributed oyster reefs in tidal flats, utilizing the polarimetric analysis techniques to fully polarimetric RADARSAT-2 (C-band) and ALOS PALSAR (L-band) data. The study areas include the tidal flats around Jebu Island and Hampyung Bay on the west coast of the Korean peninsula. We analyzed the microwave scattering mechanisms associated with oyster reefs and surrounding areas using the polarimetric target decomposition theorem and quantitatively measu ρ HHVV red target depolarization effects (the cross-polarized ratio (HV/VV), the co-polarized correlation coefficient ( ρ HHVV), and the co-polarized phase difference between HH and VV). On the basis of a large increase in the cross-polarized backscattering (HV) in the C-band SAR data, one can observe strong volume (or multiple) scattering and depolarization effects over oyster reefs areas, whereas only surface scattering was dominant in most parts of the background tidal areas. In oyster reefs, the proportion of volume scattering and the cross-polarized ratio were greater than 0.7 and −8 dB, respectively. These scattering characteristics were also verified from in-situ measurements in the field using a ground-based polarimetric scatterometer system. However, almost no difference was observed between the scattering signatures of oyster reefs and background mudflat areas from L-band data, which have a considerably longer wavelength than C-band. The study clearly suggests that multi-frequency (C- and L-band) polarimetric SAR systems can be used to detect the naturally distributed oyster reefs in tidal flats.

Evaluation of passive microwave brightness temperature simulations and snow water equivalent retrievals through a winter season

Plot-scale brightness temperature (T B) measurements at 6.9, 19, 37, and 89 GHz were acquired in forest, open, and lake environments near Churchill, Manitoba, Canada with mobile sled-based microwave radiometers during the 2009–2010 winter season. Detailed physical snow measurements within the radiometer footprints were made to relate the microwave signatures to the seasonal evolution of the snowpack, and provide inputs for model simulations with the Helsinki University of Technology (HUT) snow emission model. Large differences in depth, density, and grain size were observed between the three land cover types. Plot-scale simulations with the HUT model showed a wide range in simulation accuracy between sites and frequencies. In general, model performance degraded when the effective grain size exceeded 2 mm and/or there was an ice lens present in the pack. HUT model performance improved when simulations were run regionally at the satellite scale (using three proportional land cover tiles: open, forest, and lake) and compared to Advanced Microwave Scanning Radiometer (AMSR-E) measurements. Root mean square error (RMSE) values ranged from approximately 4 to 16 K depending on the frequency, polarization, and land cover composition of the grid cell. Snow water equivalent (SWE) retrievals produced using forward T B simulations with the HUT model in combination with AMSR-E measurements produced RMSE values below 25 mm for the intensive study area. Retrieval errors exceeded 50 mm when the scheme was applied regionally.

Estimating flooded area and mean water level using active and passive microwaves: the example of Paraná River Delta floodplain

Abstract. This paper describes a procedure to estimate both the fraction of flooded area and the mean water level in vegetated river floodplains by using a synergy of active and passive microwave signatures. In particular, C band Envisat ASAR in Wide Swath mode and AMSR-E at X, Ku and Ka band, are used. The method, which is an extension of previously developed algorithms based on passive data, exploits also model simulations of vegetation emissivity. The procedure is applied to a long flood event which occurred in the Paraná River Delta from December 2009 to April 2010. Obtained results are consistent with in situ measurements of river water level.

High radar-backscatter regions on Antarctic sea-ice and their relation to sea-ice and snow properties and meteorological conditions

The temporal and spatial variability of sea-ice radar signatures in the Southern Ocean during late winter, spring and early summer from QuikSCAT data is presented. We observe a circumpolar and broad band of sea-ice close to the marginal ice zone that is characterized by very high radar backscatter. This feature is explained through detailed in situ observations of snow and sea-ice properties as well as in relation to meteorological conditions, which were derived from US National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis data. Our results indicate that high backscatter regions are caused by metamorphous snow, which forms through re-freezing after short-term melt events. This process is connected with the episodic passes of low-pressure systems entraining warmer air from the north. South of the Antarctic Circumpolar Trough, sea-ice is not affected by this influence and shows spatially homogenous microwave signatures with low backscatter.

Convective cloud discrimination using multi-frequency microwave signatures of the AMSR-E sensor: evaluation over the Tibetan Plateau

Multi-frequency passive microwave remote sensing affords a unique opportunity to understand various phenomena; low-frequency microwaves penetrate clouds and are able to observe Earth surface conditions (∼6–18 GHz), while the higher frequencies are strongly impacted by prevailing atmospheric conditions. By using these relationships, an atmospheric opacity index (AOI) using Advanced Microwave Scanning Radiometer on Earth Observing Satellite (AMSR-E) multi-frequency data is proposed. This index utilizes four AMSR-E frequencies spanning both high- and low-microwave frequency. This AOI can be used to discriminate cloudy atmosphere from clear-sky conditions. This index shows good agreement with current cloud indices. In this research, it is compared against the Moderate Imaging Spectroradiometer (MODIS) and the Geostationary Operational Environmental Satellite 9th series (GOES-9) atmosphere products. It offers the possibility of detecting convective clouds at all times (day and night) due to the advantage of the independence of the microwave sensors on the Sun for illumination.

Typical Patterns of Microwave Signatures and Vertical Profiles of Precipitation in the Midlatitudes from TRMM Data

AbstractRepresentative patterns from multichannel microwave brightness temperature Tb in the midlatitude oceanic region, observed by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), are studied during precipitation events detected by the TRMM precipitation radar (PR) for three summer and winter seasons using empirical orthogonal function (EOF) analysis. The first three patterns are interpreted as rain liquid water, solid particles, and rain type based on the frequency distributions of vertical profiles of the radar reflectivity factor and the heights of the storm top, cloud top, and freezing level. The first EOF (EOF1) correlates with the near-surface rain rate. While the eigenvector for the 85.5-GHz channel is less significant for EOF1 variability in summer, those in all channels contribute equally to the variability in winter. This difference suggests that summer precipitation is caused by additional solid particles formed in developing precipitation systems. The second EOF (EOF2) represents the number of solid particles and also corresponds to the near-surface rain rate. This result suggests an increase of solid particles with the development of precipitation systems. EOF2 varies largely by echo-top height in summer and by echo-top height and freezing height in winter. The positive component score has double Tb peaks. Dividing the score into two patterns according to these peaks reveals highly developed precipitation systems, such as convective rainbands and frontal systems, and weak precipitation with shallow systems caused by cold outbreaks in the winter case. The negative component score also shows shallow and weak precipitation systems with warm rain. The third EOF (EOF3) is related to rain type. Vertical profiles show a significant bright band with a small height difference between the echo top and freezing level for negative EOF3, while positive EOF3 has no bright band with a high echo top relative to the freezing height. The results indicate that stratiform and convective precipitation systems can be characterized by EOF3.

Semi-automated feature-tracking of East Antarctic sea ice from Envisat ASAR imagery

While feature tracking of sea ice using cross-correlation methods on pairs of satellite Synthetic Aperture Radar (SAR) images has been extensively carried out in the Arctic, this is not the case in the Antarctic. This is due to the dynamic nature of Antarctic pack ice, its microwave signature, the tendency for SAR swath paths to be poorly aligned with the often narrow sea ice zone around the continent and inadequate satellite sampling. A semi-automated system, known as IPADS (IMCORR [IMageCORRelation] Processing, Analysis and Display System), has been developed to map fast ice and pack ice in Antarctica using multiple pairs of SAR images. The software processing pipeline uses overlapping image pairs which are geocoded and roughly registered using only data contained in the image headers. Next, fast ice maps are rapidly generated using zero motion features located within ocean regions. This also provides precise image registration. Finally, the same image pairs are re-examined for pack ice motion in a slower off-line batch process. The pack and fast ice are identified using a cluster-based search method which compares both location and motion information. Each image pair generates a NetCDF file which adds to a growing database of Antarctic sea ice motion and ice roughness. Five image-pair examples are presented to illustrate the methods used as well as their strengths and limitations. Substantial pack ice motion can often be detected in the marginal ice zone on SAR images only a few days apart.

Understanding three-dimensional effects in polarized observations with the ground-based ADMIRARI radiometer during the CHUVA campaign

[1] Measurements of down‐welling microwave radiation from raining clouds performed with the Advanced Microwave Radiometer for Rain Identification (ADMIRARI) radiometer at 10.7–21–36.5 GHz during the Global Precipitation Measurement Ground Validation “Cloud processes of the main precipitation systems in Brazil: A contribution to cloud resolving modeling and to the Global Precipitation Measurement” (CHUVA) campaign held in Brazil in March 2010 represent a unique test bed for understanding three‐dimensional (3D) effects in microwave radiative transfer processes. While the necessity of accounting for geometric effects is trivial given the slant observation geometry (ADMIRARI was pointing at a fixed 30° elevation angle), the polarization signal (i.e., the difference between the vertical and horizontal brightness temperatures) shows ubiquitousness of positive values both at 21.0 and 36.5 GHz in coincidence with high brightness temperatures. This signature is a genuine and unique microwave signature of radiation side leakage which cannot be explained in a 1D radiative transfer frame but necessitates the inclusion of three‐dimensional scattering effects. We demonstrate these effects and interdependencies by analyzing two campaign case studies and by exploiting a sophisticated 3D radiative transfer suited for dichroic media like precipitating clouds.

Cassini SAR, radiometry, scatterometry and altimetry observations of Titan’s dune fields

Large expanses of linear dunes cover Titan’s equatorial regions. As the Cassini mission continues, more dune fields are becoming unveiled and examined by the microwave radar in all its modes of operation (SAR, radiometry, scatterometry, altimetry) and with an increasing variety of observational geometries. In this paper, we report on Cassini’s radar instrument observations of the dune fields mapped through May 2009 and present our key findings in terms of Titan’s geology and climate. We estimate that dune fields cover ∼12.5% of Titan’s surface, which corresponds to an area of ∼10 million km 2, roughly the area of the United States. If dune sand-sized particles are mainly composed of solid organics as suggested by VIMS observations (Cassini Visual and Infrared Mapping Spectrometer) and atmospheric modeling and supported by radiometry data, dune fields are the largest known organic reservoir on Titan. Dune regions are, with the exception of the polar lakes and seas, the least reflective and most emissive features on this moon. Interestingly, we also find a latitudinal dependence in the dune field microwave properties: up to a latitude of ∼11°, dune fields tend to become less emissive and brighter as one moves northward. Above ∼11° this trend is reversed. The microwave signatures of the dune regions are thought to be primarily controlled by the interdune proportion (relative to that of the dune), roughness and degree of sand cover. In agreement with radiometry and scatterometry observations, SAR images suggest that the fraction of interdunes increases northward up to a latitude of ∼14°. In general, scattering from the subsurface (volume scattering and surface scattering from buried interfaces) makes interdunal regions brighter than the dunes. The observed latitudinal trend may therefore also be partially caused by a gradual thinning of the interdunal sand cover or surrounding sand sheets to the north, thus allowing wave penetration in the underlying substrate. Altimetry measurements over dunes have highlighted a region located in the Fensal dune field (∼5° latitude) where the icy bedrock of Titan is likely exposed within smooth interdune areas. The hemispherical assymetry of dune field properties may point to a general reduction in the availability of sediments and/or an increase in the ground humidity toward the north, which could be related to Titan’s asymmetric seasonal polar insolation. Alternatively, it may indicate that either the wind pattern or the topography is less favorable for dune formation in Titan’s northern tropics.

Comparison of Satellite Precipitation Products with Rain Gauge Data for the Khumb Region, Nepal Himalayas

Rain gauge data for the period of 1998–2004 from the Syangboche Automated Weather Station (S-AWS) site in the Nepal Himalayas were compared with multi-satellite precipitation products for the period of 2003–2005, employing several retrieval algorithms: the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), the Climate Prediction Center (CPC) morphing algorithm (CMORPH), the Precipitation Estimation from Remote Sensing Information using an artificial neural network (PERSIANN), and the Global Satellite Mapping of Precipitation (GSMaP). All the products, except GSMaP, showed an increase in precipitation during the summer monsoon, in agreement with S-AWS. However, PERSIANN showed large differences with the observed values in winter and CMORPH had a tendency to overestimate precipitation in the pre- and post-monsoon seasons relative to S-AWS/TMPA. Summer monsoon precipitation showed an increase in the evening and mid-night in all products except GSMaP, but the local-time peak in PERSIANN lagged compared to that of S-AWS by several hours, and the peak in other products was ahead of that in S-AWS by several hours. All products except for PERSIANN showed an increase in precipitation during the morning. The differences among the products may reflect microwave signatures from convection, the sun-synchronous satellite orbit, and infrared-merging processes. A verification of rain detection by GSMaP revealed good scores over global land areas except for the Tibetan Plateau (including the present study area) due to insufficient resolution for rain/no-rain classification. The peak local-time distribution of precipitation showed a relationship with the topography in the order of precipitation radar (strongest relationship), microwave radiometer, and infrared products.

In search of water vapor on Jupiter: Laboratory measurements of the microwave properties of water vapor under simulated jovian conditions

Detection and measurement of atmospheric water vapor in the deep jovian atmosphere using microwave radiometry has been discussed extensively by Janssen et al. (Janssen, M.A., Hofstadter, M.D., Gulkis, S., Ingersoll, A.P., Allison, M., Bolton, S.J., Levin, S.M., Kamp, L.W. [2005]. Icarus 173 (2), 447–453.) and de Pater et al. (de Pater, I., Deboer, D., Marley, M., Freedman, R., Young, R. [2005]. Icarus 173 (2), 425–447). The NASA Juno mission will include a six-channel microwave radiometer system (MWR) operating in the 1.3–50cm wavelength range in order to retrieve water vapor abundances from the microwave signature of Jupiter (see, e.g., Matousek, S. [2005]. The Juno new frontiers mission. Tech. Rep. IAC-05-A3.2.A.04, California Institute of Technology). In order to accurately interpret data from such observations, nearly 2000 laboratory measurements of the microwave opacity of H2O vapor in a H2/He atmosphere have been conducted in the 5–21cm wavelength range (1.4–6GHz) at pressures from 30 mbars to 101 bars and at temperatures from 330 to 525K. The mole fraction of H2O (at maximum pressure) ranged from 0.19% to 3.6% with some additional measurements of pure H2O. These results have enabled development of the first model for the opacity of gaseous H2O in a H2/He atmosphere under jovian conditions developed from actual laboratory data. The new model is based on a terrestrial model of Rosenkranz et al. (Rosenkranz, P.W. [1998]. Radio Science 33, 919–928), with substantial modifications to reflect the effects of jovian conditions. The new model for water vapor opacity dramatically outperforms previous models and will provide reliable results for temperatures from 300 to 525K, at pressures up to 100 bars and at frequencies up to 6GHz. These results will significantly reduce the uncertainties in the retrieval of jovian atmospheric water vapor abundances from the microwave radiometric measurements from the upcoming NASA Juno mission, as well as provide a clearer understanding of the role deep atmospheric water vapor may play in the decimeter-wavelength spectrum of Saturn.

Physical, dielectric, and C band microwave scattering properties of first‐year sea ice during advanced melt

This paper investigates the influence of solar heating and intermittent cloud cover on the physical and dielectric properties of naturally snow‐free, warm (>−2°), first‐year sea ice (FYI) in the southeastern margin of the Beaufort Sea during advanced melt. A simple three‐layer physical model describing the surface is introduced and copolarized C band microwave signatures are simulated using a multilayer scattering model forced with four sets of measured surface parameters. Modeled backscatter signatures are compared to coincident surface‐based C band scatterometer signatures in order to elucidate the signature controlling properties of the ice. Results show that 50 MHz impedance probe dielectric measurements of desalinated upper ice layers exhibit statistically significant diurnal variations due to the link between solar forcing and the availability of free water in brine‐free upper ice layers. Enhanced downwelling longwave radiation to the surface from low‐level stratus clouds is positively linearly associated (r = 0.709) with volumetric moisture mv detected in upper ice layers. Model results show that desalinated upper ice layers contribute volume scattering from smooth, snow‐free FYI under the observed surface mv range. Sustained cloud‐free periods result in the formation of a 0.5–2.5 cm granular surface layer, composed of 5.2 mm ice grains, which enhances backscatter under relatively dry conditions. Sensitivity analyses show that layer thickness plays a significant role in scattering due to the increased number density of inclusions which act as discrete scatterers, and sufficient energy may penetrate to, and scatter from, the saline columnar ice layer under relatively dry conditions only (mv < 2%).

Normalized radar cross section of the sea for backscatter: 2. Modulation by internal waves

We report measurements of microwave surface signatures of internal waves with dual‐polarized, coherent, X band radars mounted on three ships and an airplane. In shipboard measurements in the South China Sea, internal waves generally increased the backscattering cross section near the peaks of the internal waves with little detectable decrease afterward. The peak of the cross‐section signature shifted its location relative to the internal wave crest depending on the maximum strain rate of the internal wave. We show that a similar shift is produced in the modulation of short‐gravity waves by internal waves. We suggest that this modulation of “intermediate‐scale” waves causes small‐scale radar scatterers to maximize at this location. In shipboard measurements off the New Jersey coast, the range resolution of the radar was sufficiently small to allow us to detect significant modulation of gravity waves on the order of 15–30 m long by the internal waves. At the high incidence angles of the shipboard measurements, the cross section for horizontally polarized transmit and receive signals, σo(HH), regularly exceeded that for vertically polarized transmit and receive signals, σo(VV), near the internal wave crest by 5–10 dB. At the more moderate incidence angles observed from the aircraft, maximum values of σo(HH) and σo(VV) are more nearly equal, with σo(HH) often being comparable to σo(VV) and only occasionally exceeding it. These observations suggest that roughness due to breaking short‐gravity waves plays a significant role in producing microwave signatures of internal waves, even at moderate incidence angles where it competes with the modulation of wind‐generated waves. The intensity of modulation of the cross section caused by internal waves observed from the plane depended little on the direction of observation. Internal wave surface signatures from the aircraft became less visible with increasing wind speed, being very difficult to observe at 9 m/s.

An EOF‐based comparison and evaluation of simulated passive microwave signatures to observations over tropical oceans

Bayesian algorithms are a common method of retrieving cloud properties from a set of observed passive microwave brightness temperature (TB) measurements. In practice, such methods often use predefined databases from cloud‐resolving models to perform the retrieval. Successful performance in these types of Bayesian retrievals is greatly affected by the similarity of TBs between observed and predefined databases. Here empirical orthogonal function (EOF) analysis methods were used to illustrate the importance of predefined simulation databases on the ability to retrieve known regional variability in cloud structures across different parts of the tropical oceans and to provide insight on the relative impact of environmental conditions to limitations in cloud model microphysical parameterizations in retrieving different types of cloud structures. The spatial distributions of EOF coefficients in EOF space showed that there were both underrepresentation and overrepresentation between manifolds of the predefined and observed databases. Moreover, there was poor alignment in the frequency distribution between observed and simulated clouds structures. Additionally, the ability to retrieve known regional variability in convective cloud structure was dependent on the environmental conditions used to generate the simulated data set more so than limitations in the model microphysical parameterizations. The opposite was true for stratiform rain, as the dominant EOF patterns of the radiation indices for the predefined databases exhibit overproduction of large‐sized high‐density ice‐phase hydrometeors for a given rain content in comparison to the observations. Improvements to microphysical parameterization schemes appear to be necessary to produce radiance index vectors that are consistent with observations.

The Varying Response of Microwave Signatures to Different Types of Overland Rainfall Found over the Korean Peninsula

Abstract The Tropical Rainfall Measuring Mission (TRMM) precipitation radar and ground rain measurements were used to investigate the performance of the TRMM Microwave Imager (TMI) land algorithm. In particular, data from a dense network of rain gauges being operated over the Korean Peninsula were utilized. To retrieve information related to the rainfall rate over land, the TRMM land algorithm relies mainly on brightness temperature TB depression at vertically polarized 85(V) GHz because of scattering by ice particles. It refers to the relationships between 85(V)-GHz TBs and rain rates in its predefined database. By comparing the TMI rain rates with the surface rain gauge and TRMM radar measurements, it was found that there are a variety of relationships between 85(V)-GHz TBs and rainfall rates resulting from the various types of precipitating clouds. The TMI land algorithm, therefore, could not resolve some raining clouds such as warm clouds as well as cold clouds having small amounts of ice particles above the rain layer. The rainfall amounts for those missed rain events are significant. As a result, rain rates produced by the land algorithm show systematic biases, which are a function of raining cloud types. Meanwhile, it is found that the 37-GHz TMI channels contain additional information on surface rain; the uncertainties in retrieving rain rates from TBs at TMI frequencies can be reduced up to 11% if all polarized 37- and 85-GHz TBs are used as predictors.