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Estimation of evapotranspiration (ET) is important for monitoring crop water stress and for developing decision support systems for irrigation scheduling. Techniques to estimate ET have been available for many years, while more recently remote sensing data have extended ET into a spatially distributed context. However, remote sensing data cannot be easily used in decision systems if they are not available frequently. For many crops ET estimates are needed at intervals of a week or less, but unfortunately due to cost, weather, and sensor availability constraints, high resolution (< 100 m) remote sensing data are usually available no more frequently than 2 weeks. Since resolution of this problem is unlikely to occur soon, a modeling approach has been developed to extrapolate remotely sensed inputs needed to estimate ET. The approach accomplishes this by combining time-series observations from ground-based radiometers and meteorological instruments with episodic visible, near infrared, and thermal infrared remote sensing image data. The key components of the model are a vegetation density predictor and a diurnal land surface temperature disaggregator, both of which supply needed inputs to a surface energy balance model. To illustrate model implementation, remote sensing and ground-based experimental data were collected for cotton grown in 2003 at Maricopa, Ariz. Spatially distributed cotton canopy densities were forecasted for a 22-day interval using vegetation indices from remote sensing and fractional cover from ground-level photography. Spatially distributed canopy and soil surface temperatures were predicted at 15-min time steps for the same interval by scaling diurnal canopy temperatures according to time of day and vegetative cover. Considering that the predictions span a rapid growth phase of the cotton crop, comparison of spatially projected canopy cover with observed cover were reasonably good, with [R.sup.2]=0.65 and a root-mean-squared error (RMSE) of 0.13. Comparison of predicted temperatures also showed fair agreement with RMSE=2.1[degrees]C. These results show that combining episodic remotely sensed data with continuous ground-based radiometric data are a technically feasible way to forecast spatially distributed input data needed for ET modeling over crops. DOI: 10.1061/(ASCE)IR.1943-4774.0000169 CE Database subject headings: Evapotranspiration; Remote sensing; Temperature effects; Arizona. Author keywords: Evapotranspiration.

The aim of this study was to identify clear air boundaries and to obtain spatial distribution of convective areas associated with the sea breeze over the Iberian Mediterranean zone and the isle of Mallorca, both in Spain. Daytime Advanced Very High Resolution Radiometer (AVHRR) data from National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites were collected for May-October 2004. A cloud detection algorithm was used to identify clouds to derive daytime sea-breeze cloud frequency composites over land. The high-resolution composites aided in identifying the location of five preferential seabreeze convergence zones (SBCZ) in relation to the shape of coastline and orographic effects. Additionally, eight regimes were designated using mean boundary layer wind speed and direction to provide statistics about the effect of prevailing large-scale flows on sea-breeze convection over the five SBCZ. The offshore SW to W and the NW to N regimes were characterized by high cloud frequencies parallel to the coast. Small differences in mean cloud frequency values from morning to afternoon composites were detected with these regimes because sea-breeze fronts tended to form early and persist into the afternoon. Just the opposite occurred under the onshore NE to E and SE to S regimes. It was found that light to moderate ([less than or equal to] 5.1 m [s.sup.-1]) winds aloft result in more clouds at the leading edge of sea breezes. In contrast, strong synoptic-scale (>5.1 m [s.sup.-1]) flows weaken boundary layer convergence. The results from this satellite meteorology study could have practical applications for many people including those that forecast the weather and those that use the forecast for making decisions related to energy use, fishing, recreation, or agriculture activities, as well as for estimating pollution or issuing warnings for heavy rain or flash flooding. DOI: 10.1175/2009JAMC2141.1

Glaciated regions are known to be particularly sensitive to climate change. Historical archives of glacier volume change are important, as they provide context for present-day changes. Although photogrammetric archives exist for many regions, their usefulness is often limited by a lack of contemporary ground control. High quality digital elevation models (DEMs) underpin a range of change analysis activities. This paper presents a cost-effective solution which utilizes Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEMs as control for the scaling and orientation of archival data sets. Instead of relying upon ground-control points, a robust surface matching algorithm is employed to automatically determine the transformation required to register two overlapping DEMs. Through application to the Slakbreen glacier system in Svalbard, Norway, the strategy is assessed by first matching an ASTER DEM to a fixed lidar reference surface. This demonstrates that ASTER DEMs are effectively correct in scale, supporting their use as a control surface. The second stage of the research implements this by matching an aerial photogrammetric DEM to an ASTER reference surface. Resultant volumetric and annual elevation change rates are compared to those derived from lidar data, which are considered in this paper as a truth data set. ASTER-based matching produced a mean annual elevation change rate of -4.12 [ma.sup.-1], compared to a value of -4.11 [ma.sup.-1] derived from the lidar data. In volumetric terms, this equates to a difference of 0.6%. A major advantage of this approach is the near-global coverage offered by ASTER data and the opportunity that this presents for remote glacial change analysis over regional extents. Index Terms--Geodesy, remote sensing, terrain mapping.

The thermal and optical properties of multilayered dental tissue structure, the result of the surface-grown prismless layer on enamel, were evaluated simultaneously using multiparameter fits of photothermal radiometry frequency responses. Tim photothermal field generated in a tooth sample with near-infrared laser excitation was described using a coupled diffuse-photon-density and thermal wave model. The optical (absorption and scattering) coefficients and thermal parameters (spectrally averaged infrared emissivity, thermal diffusivity and conductivity) of each layer, as well as the thickness of the upper prismless enamel layer, were fitted using a multiparameter simplex downhill minimization algorithm. The results show that the proposed tilting approach can increase robustness of the multiparameter estimation of tissue properties in the case of ill-defined multiparameter fits, which are unavoidable in in vivo tissue evaluation. The described method can readily be used for noninvasive in vitro or in two characterization of a wide range of layered biological tissues. of America OCIS codes: 170.1850, 170.7050, 160.4760, 170.5270, 170.6935.

We describe a novel approach developed for the National Polar-Orbiting Operational Environmental Satellite System/Visible Infrared Imaging Radiometer Suite (VIIRS) to retrieve pixel-level mixed-phase cloud optical thicknesses and effective particle sizes using 0.67, 1.6, 2.25, and 3.7 [micro]m bands reflectance/ radiance. This approach utilizes lookup tables of reflectances constructed from radiative transfer simulations and a numerical iterative search method. The capability of this new approach was demonstrated using Moderate Resolution Imaging Spectroradiometer (MODIS) data as proxy to VIIRS. Two proxy scenes, 14 October 2001 over North Platte, Nebraska, during the ninth Cloud Layer Experiment (CLEX-9) and 9 November 2006 over the Great Lakes and Eastern Canada during the Canadian CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations Validation Project (C3VP), were analyzed. The performance of the mixed-phase retrieval algorithm was assessed by comparison with the MODIS retrieval products, airborne in situ observations during CLEX-9 and CloudSat data during C3VP. OCIS codes: 010.1615, 280.1310.

The Remote Sensing Group at the University of Arizona has developed multispectral ground-viewing radiometers that use light-emitting diodes as detectors. This work describes the optical design, electrical design, and laboratory calibration of a three-channel radiometer that operates in the visible and near-infrared region of the spectrum. The optical and electrical design of the radiometer is introduced, and then the calibration and characterization of the radiometer are described. Laboratory measurements include the spectral responsivity for each channel of the radiometer, the temperature dependence of the total responsivity for each channel, system linearity, field of view, and finally, the absolute radiometric calibration. A solar-radiation-based calibration is used to determine the absolute responsivity. OCIS codes: 230.0040, 230.3670, 280.4788, 280.4991.

Combined measurements of diffuse-to-global radiation ratio and global spectral irradiances in the UV are used to derive cosine-corrected UV irradiances and aerosol optical depth (AOD). The diffuse-to-global radiation ratio is used first in the cosine correction of the global irradiance, then to calculate absolutely calibrated direct irradiances. The Beer--Lambert law is applied to derive the UVAOD using independent measurements of the extraterrestrial solar flux. The AOD can be derived with an uncertainty of about 0.03 at 60[degrees] solar zenith angle. The method was applied to measurements obtained with two UV multi-filter rotating shadowband radiometers (UV-MFRSRs) and a MK III Brewer spectrophotometer on the Island of Lampedusa in the Central Mediterranean during two periods of 2002 and 2004. The derived AOD at 318 and 332 nm was compared with UV AOD measured at 318, 320, and 368 nm with different techniques. The retrieved AOD, combining MFRSR and Brewer measurements, is in good agreement with the optical depth derived with the other methods. OCIS codes: 010.1110, 010.5620, 120.0280, 120.6200.

Methods described in the IEEE standards for frequency generator stability can be used to estimate the precision of brightness temperature measurements made by a microwave radiometer. The application of these methods and the inherent assumptions are reviewed. A simple statistic is proposed for use in estimating accuracy drift. Index Terms--Calibration, microwave radiometry, microwave receivers, radiometry, remote sensing.

We focus on inverting the surface temperature (or heat) equation to obtain the surface velocity field in the coastal ocean and compare the results with those from the maximum cross correlation (MCC) technique and with the in situ velocity fields measured by the Rutgers University Coastal Ocean Dynamics Radar (CODAR). When compared with CODAR fields, velocities from the heat equation and MCC have comparable accuracies, but the heat equation technique better resolves the finer scale flow features. We use the results to directly calculate the surface divergence and vorticity. This is possible because we convert the traditionally underdetermined heat inversion problem to an overdetermined one without constraining the velocity field with divergence, vorticity, or energy statements. Because no a priori assumptions are made about the vorticity, it can be calculated directly from the velocity results. The derived vorticity field has typical open-ocean magnitudes (~5 x [10.sup.-5]/s) and exhibits several structures (a warm core ring, Gulf Stream filament, and a diverging flow) consistent with the types of flows required to kinematically deform the sea surface temperature patterns into the observed configurations. Index Terms--Geophysical measurements, HF radar, infrared (IR) imaging, remote sensing, satellite applications, sea coast, sea surface.

We present a detailed analysis of the airborne passive microwave remote-sensing data that were collected at a broad range of microwave bands and at a high spatial resolution during the 2002 and 2003 National Aeronautics and Space Administration Cold Land Processes Experiment (CLPX). An accurate measurement of snowpack properties using passive microwave observations requires the detailed knowledge of the relationship between snowpack geophysical parameters and the upwelling polarimetric brightness signature. The principle microwave instrument used for the CLPX was the polarimetric scanning radiometer (PSR), which provided ~100-m resolution maps of the snow emissivity at all Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) bands during several intensive observation periods over the Colorado Rocky Mountains. The observed conditions included drought, normal snowpack, and spring snowmelt. The PSR and related ground-based observations of snowpack properties made during the 2002 and 2003 CLPX campaigns provide a comprehensive high-resolution passive microwave data set. Results show that the high-resolution PSR data exhibit emissivity modes that are similar to those observed in the historical data sets, and that the empirical relationships between the emissivity and the snow water equivalent (SWE), after the effects of macrovegetation are removed, closely match those found in the past theoretical studies. The use of the 89-GHz channel in the empirical relationships provides improved accuracy under dry snow conditions and a small SWE; however, the variability of the SWE--emissivity relationships increases with an increasing SWE. A summary of the observed relationships between the emissivity spectra of snow and snowpack properties is presented. Comparison of the total water content from the AMSR-E and PSR observations shows that the satellite measurements underestimated the total volume of water storage from airborne observations on the average by a factor of five. Index Terms--Airborne polarimetric scanning radiometer (PSR), beam polarization correction, georegistration, microwave emissivity, passive microwave remote sensing, retrieval algorithm development, snowpack, snow water equivalent (SWE), topography, validation.

A new type of remote-sensing radiometer based upon the Fabry--Perot (FP) interferometric technique has been developed at NASA's Goddard Space Flight Center and tested from both ground and aircraft platforms. The sensor uses direct or reflected sunlight and has channels for measuring the column concentration of carbon dioxide at 1570 nm, oxygen lines sensitive to pressure and temperature at 762 and 768 nm, and water vapor (940 nm). A solid FP etalon is used as a tunable narrow bandpass filter to restrict the measurement to the gas of interest's absorption bands. By adjusting the temperature of the etalon, which changes the index of refraction of its material, the transmission fringes can be brought into nearly exact correspondence with the absorption lines of the particular species. With this alignment between absorption lines and fringes, changes in the amount of a species in the atmosphere strongly affect the amount of light transmitted by the etalon and can be related to gas concentration. The technique is applicable to different chemical species. We have performed simulations and instrument design studies for C[H.sub.4], [sup.13]C[O.sub.2] isotope, and CO detection. Index Terms--Absorbing media, atmospheric measurements, Fabry--Perot (FP) interferometers, optical interferometry, remote sensing.

We present a new compact and automated ground-based microwave mobile radiometer dedicated to the study of middle atmospheric water vapor, which is convenient for measurement, intercomparison, and validation campaigns, particularly in remote places. The instrument detects the [6.sub.16]-[5.sub.23] [H.sub.2]O transition line at 22.235 GHz by means of balanced beam-switching observation of the atmosphere. Tipping curves are performed to estimate the tropospheric opacity. The sky is used as a cold load for calibration, minimizing the use of liquid nitrogen. The main technical issues are caused by the small horn antenna (a beamwidth of ~12[degrees]) inducing large bias when using pencil-beam approximation for the calculation of elevation-dependent parameters. Numerical methods have been developed to include this effect in the data calibration process. Preliminary vertical profiles are retrieved with the Microwave Odin Line Estimation and REtrieval radiative transfer and inversion tool from 25 to 55 km with a vertical resolution of 10-20 km increasing with height, for an integration time of ~12 h and a measurement error of ~15% (~0.8 ppmv). Preliminary comparisons with the spaceborne instrument Aura/Microwave Limb Sounder show a good agreement (~5%) in the 35-55-km altitude range, whereas a negative bias is detected below (up to -30% at 25 km). Index Terms--Atmospheric measurement, calibration, radiometry.

The spaceborne thermal monitoring of the great eruption of Pu'u 'O'o-Kupaianaha in Hawaii (1987 to present) was attempted, integrating high-resolution SWIR-TIR and low-resolution MIR-TIR observations. Data acquired by multispectral payloads ASTER and MODIS onboard spacecraft Terra, and MODIS onboard Aqua, were processed behind real time by the use of computing routines 'MyVOL' and 'MyMOD' based on assessed theory and designed for real-time operations. The process was tested against the 2000-2005 eruptive history, both in geometry and volume dynamics of the lava flow. Here, instant lava effusion rates obtained from approximately 1800 cloud-free (over a total > 3000) day-/nighttime MODIS scenes and 12 cloud-free (over a total of 30) nighttime ASTER scenes are compared with each other and with volcanological ground truth composed of gas (S[O.sub.2])- and electromagnetic potential (very low frequency)-derived eruption rates. Remote-sensed eruption rates are consistent with ground truth from approximately 1 [m.sup.3]/s up to the peak effusion rates of 1.2-1.3 million [m.sup.3]/day observed in 2005. Index Terms--Aqua, ASTER, eruption rate, Hawaii, lava, MODIS, Terra, volcano.

The Clouds and the Earth's Radiant Energy System (CERES) is a program that measures the Earth radiation budget (ERB) from two polar orbiting satellite platforms. CERES radiometers are designed to make stable broadband measurements of scattered solar and emitted thermal radiative flux leaving Earth with an accuracy of 1% or better. Using versatile and programmable scan modes, it is also possible for every CERES instrument to view the Moon on each orbit. However, until now, it has not been possible to derive absolute measurements of lunar irradiance using CERES because the Moon's disk fills only 10% of the telescope field of view. This work presents a method of integrating CERES raster-scan data in order to obtain a measurement of the average scattered solar and emitted thermal radiance from the entire lunar disk. The technique results in excellent agreement between CERES instruments on different satellites as to lunar albedo and emitted thermal flux. The average broadband Moon albedo is measured by CERES at a value of 0.1362 ([+ or -] 2-3%) when normalized to a static lunar phase angle of 7[degrees] using the U.S. Geological Survey lunar irradiance Robotic Lunar Observatory model. The method for the first time also yields very accurate measurements of the thermal irradiance emitted from the Moon. These suggest an average long-wave flux of 977 W[m.sup.-2] ([+ or -] 2-3% at 7[degrees] phase), implying an approximate mean surface temperature of around 92[degrees]C. Statistical analysis on available data suggests that a CERES instrument performing monthly lunar measurements could utilize the Moon as a stability target and reduce calibration drills to 0.3% per decade or less within an instrument's lifetime. Given the success of the technique, a solar calibration system is proposed that will allow precise tracking of an ERB instrument's optical degradation using the Sun. OCIS codes: 040.0040, 280.0280, 010.0280, 040.6808, 120.6085, 350.1270.

The energy transfer integral between radiating rectangular and detecting circular parallel plates having nonideal angular characteristics is solved for modeling the distance dependence of the irradiance signal. The equation derived for the irradiance signal, which is called the modified inverse-square law, depends on the position, shape, size, and angular characteristics of the light source and the detector. We apply the new model equation to the calibration of a spectroradiometer to determine accurately the distance offsets, which fix the positions of the effective receiving apertures of diffusers used in the entrance optics of spectroradiometers. Earlier measurement results, e.g., for solar UV irradiance, may include uncorrected effects and can be corrected reliably as diffuser offsets and other correction factors are determined with the modified inverse-square law. Simplifications of the modified inverse-square law for analyzing the distance offsets and the correction factors are studied. Simplified equations for the diffuser offset analysis may be used without losing the accuracy when the cosine response of the diffuser is reasonably good. However, for diffusers whose angular responsivities deviate much from the cosinusoidal angular responsivity, large approximation errors in the diffuser offset values may appear if the angular effects are not properly taken into account. OCIS codes: 010.1290, 080.0080, 120.5630, 230.1980.

WindSat has systematically collected the first global fully polarimetric passive microwave data over both land and ocean. As the first spaceborne polarimetric microwave radiometer, it was designed to measure ocean surface wind speed and direction by including the third and fourth Stokes parameters, which are mostly related to the asymmetric structures of the ocean surface roughness. Although designed for wind vector retrieval, WindSat data are also collected over land and ice, and this new data has revealed, for the first time, significant land signals in the third and fourth Stokes parameter channels, particularly over Greenland and the Antarctic ice sheets. The third and fourth Stokes parameters show well-defined large azimuth modulations that appear to be correlated with geophysical variations, particularly snow structure, melting, and metamorphism, and have distinct seasonal variation. The polarimetric signatures are relatively weak in the summer and are strongest around spring. This corresponds well with the formation and erosion of the sastrugi in the dry snow zone and snowmelt in the soaked zone. In this paper, we present the full polarimetric signatures obtained from WindSat over Greenland, and use a simple empirical observation model to quantify the azimuthal variations of the signatures in space and time. Index Terms--Greenland ice sheet, ice, polarimetric microwave radiometry, snow, WindSat.

An analytical model and supporting measured data are presented for a preamplified W-band radiometer with a zero-bias detector appropriate for commercial millimeter-wave imaging cameras. Basic radiometer parameters, including RF bandwidth, are computed directly from simple low-frequency measurements and compare well with those obtained from RF measurements. A detailed analytical model shows how radiometer performance depends on internal component parameters, such as low-noise amplifier gain, noise factor, reflection coefficient, detector responsivity, etc. The measurements suggest that performance is sufficient for operation without a Dicke switch or mechanical chopping. A measured noise equivalent temperature difference of 0.45 K was obtained, assuming a single sensor is scanned across a focal plane, forming 32 pixels with 3.125-ms integration time per pixel. This sensitivity is considered sufficient by commercial manufacturers to obtain quality images in low-contrast (e.g., indoor) environments. Index Terms--Direct detection, millimeter-wave imaging, radiometers, W-band sensors.

This paper deals with the potential application of National Oceanic and Atmospheric Administration (NOAA)/ Advanced Very High Resolution Radiometer (AVHRR) data to detect subsurface fire (subsurface hotspots) by proposing an efficient contextual algorithm. Most of the solutions proposed to date are mainly focused on the problem of surface fires, and very few research works have been performed to develop techniques for the subsurface fire problem. Although few algorithms based on the fixed-thresholding approach have been proposed for subsurface hotspot detection, however, for each application, thresholds have to be specifically tuned to cope with unique environmental conditions. The main objective of this paper is to develop an instrument-independent adaptive method by which direct threshold or multithreshold can be avoided. The proposed contextual algorithm is very helpful to monitor subsurface hotspots with operational satellite data, such as the Jharia region of India, without making any region-specific guess in thresholding. Novelty of the proposed work lies in the fact that once the algorithmic model is developed for the particular region of interest after optimizing the model parameters, there is no need to optimize those parameters again for further satellite images. Hence, the developed model can be used for optimized automated detection and monitoring of subsurface hotspots for future images of the particular region of interest. The algorithm is adaptive in nature and uses vegetation index and different NOAA/AVHRR channel's statistics to detect hotspots in the region of interest. The performance of the algorithm is assessed in terms of sensitivity and specificity and compared with other well-known thresholding techniques such as Otsu's thresholding, entropy-based thresholding, and existing contextual algorithm proposed by Flasse and Ceccato. The proposed algorithm is found to give better hotspot detection accuracy with lesser false alarm rate. Index Terms--Contextual algorithm, entropy-based thresholding, image analysis, National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR), Otsu's thresholding, remote sensing, satellite imaging, subsurface hotspot, threshold decoding.

Multifilter rotating shadowband radiometer (MFRSR) calibration values for aerosol optical depth (AOD) retrievals were determined by means of the general method formulated by Forgan [Appl. Opt. 33, 4841 (1994)] at a polluted urban site. The obtained precision is comparable with the classical method, the Langley plot, applied on clean mountaintops distant of pollution sources. The AOD retrieved over Sao Paulo City with both calibration procedures is compared with the Aerosol Robotic Network data. The observed results are similar, and, except for the shortest wavelength (415 nm), the MFRSR's AOD is systematically overestimated by ~0.03. OCIS codes: 010.1100, 010.1290, 280.1100, 280.1120.

A new consistent long-term normalized difference vegetation index (NDVI) time series at a l-[km.sup.2] resolution for Southern Africa that is based on the data from Satellite Pour l'Observation de la Terre VEGETATION (VGT) (1998-2006) and the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (AVHRR) (1985-1998) has been produced for vegetation-dynamics monitoring purposes. This paper presents the evaluation of the newly processed AVHRR data set, as well as the integration of this data set with the VGT archive. First, the AVHRR processing chain and the resulting AVHRR data set have been investigated with respect to calibration accuracy, cloud masking, and atmospheric and geometric correction. Second, different calibration approaches, spectral response (SR) functions, spatial resolutions, overpass times, and geometries of observation for the VGT and AVHRR data sets have been compared for a common observation period. The application of published correction functions accounting for the SR differences for both sensors considerably improved the consistency between both data sets. An [r.sup.2] of 0.85 is obtained between paired samples of the NDVI from the VGT and the newly processed AVHRR archive. After the application of the correction functions, the slope of the regression line between the two NDVI data sets was much closer to the 1:1 line. The performance of the correction functions differed among vegetation types. The largest reduction in the root-mean-square error between the NDVI of both sensors is obtained from areas with higher biomass. Large parts of the remaining variability are suggested to be attributed to the bidirectional reflectance distribution function effects, as demonstrated by the intersensor NDVI time-series variability versus the intrasensor NDVI time-series variability. Index Terms--lmage processing, spectral response function (SRF), time series.

The weekly 0.144[degrees] resolution global vegetation index from the National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS) has a long history, starting late 1981, and has included data derived from Advanced Very High Resolution Radiometer (AVHRR) sensors onboard NOAA-7, -9, -11, -14, -16, -17, and -18 satellites. Even after postlaunch calibration and mathematical smoothing and filtering of the normalized difference vegetation index (NDVI) derived from AVHRR visible and near-infrared channels, the time series of global smoothed NDVI (SMN) still has apparent discontinuities and biases due to sensor degradation, orbital drift [equator crossing time (ECT)], and differences from instrument to instrument in band response functions. To meet the needs of the operational weather and climate modeling and monitoring community for a stable long-term global NDVI data set, we investigated adjustments to substantially reduce the bias of the weekly global SMN series by simple and efficient algorithms that require a minimum number of assumptions about the statistical properties of the interannual global vegetation changes. Of the algorithms tested, we found the adjusted cumulative distribution function (ACDF) method to be a well-balanced approach that effectively eliminated most of the long-term global-scale interannual trend of AVHRR NDV1. Improvements to the global and regional NDVI data stability have been demonstrated by the results of ACDF-adjusted data set evaluated at a global scale, on major land classes, with relevance to satellite ECT, at major continental regions, and at regional drought detection applications. Index Terms--Advanced Very High Resolution Radiometer (AVHRR), land surface, normalized difference vegetation index (NDVI), remote sensing, satellite-based vegetation, vegetation index.

The accuracy and precision are determined of cloud liquid water path (LWP) retrievals from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat-8 using l yr of LWP retrievals from microwave radiometer (MWR) measurements of two CloudNET stations in northern Europe. The MWR retrievals of LWP have a precision that is superior to current satellite remote sensing techniques, which justifies their use as validation data. The Cloud Physical Properties (CPP) algorithm of the Satellite Application Facility on Climate Monitoring (CM-SAF) is used to retrieve LWP from SEVIRI reflectances at 0.6 and 1.6 [micro]m. The results show large differences in the accuracy and precision of LWP retrievals from SEVIRI between summer and winter. During summer, the instantaneous LWP retrievals from SEVIRI agree well with those from the MWRs. The accuracy is better than 5 g [m.sup.-2] and the precision is better than 30 g [m.sup.-2] which is similar to the precision of LWP retrievals from MWR. The added value of the 15-min sampling frequency of Meteosat-8 becomes evident in the validation of the daily median and diurnal variations in LWP retrievals from SEVIRI. The daily median LWP values from SEVIRI and MWR are highly correlated (correlation > 0.95) and have a precision better than 15 g [m.sup.-2]. In addition, SEVIRI and MWR reveal similar diurnal variations in retrieved LWP values. The peak LWP values occur around noon. During winter, SEVIRI generally overestimates the instantaneous LWP values from MWR, the accuracy drops to about 10 g [m.sup.2], and the precision to about 30 g [m.sup.-2]. The most likely reason for these lower accuracies is the shortcoming of CPP, and similar one-dimensional retrieval algorithms, to model inhomogeneous clouds. It is suggested that neglecting cloud inhomogeneities leads to a significant over-estimation of LWP retrievals from SEVIRI over northern Europe during winter.

This paper evaluates the performance of the global precipitation rate retrieval algorithm for the Advanced Microwave Sounding Unit (AMSU) that was described in Part I of this paper. AMSU is in polar orbit on several National Ocean and Atmospheric Administration (NOAA) operational weather satellites. Predicted rms retrieval errors based on a 15-km resolution 0.5-1.0-mm/h MM5 truth were 0.88, 0.83, 1.13, and 3.04 for stratiform, warm rain, ice-free rain, and convective rain, respectively, which were averaged over all view angles ['or land and sea up to 73[degrees] latitude. For MM5 rates of 4-8 mm/h, these rms errors increased to 2.8, 3.4, 3.9, and 4.9 nun/h, respectively. The corresponding rms retrieval accuracies for MM5 hydrometeor water paths between 0.125 and 0.25 mm for rainwater, snow, and graupel were 0.19, 0.10, and 0.22 mm, respectively. The rms retrieval accuracy for the 0.125-0.25-m/s peak vertical wind was 0.08 m/s. Biases are small for cumulative precipitation estimates, although an upward correction factor of 1.37 is derived for convective precipitation rate probability distributions. Differences between these retrievals and those from the conically scanned Advanced Microwave Scanning Radiometer for the Earth Observing System instrument and an alternate NOAA AMSU algorithm are also characterized. Index Terms--Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), Advanced Microwave Sounding Unit (AMSU), microwave precipitation estimation, nficrowave radiative transfer, precipitation.

Shadow-band radiometers in general, and especially the Multi-Filter Rotating Shadow-band Radiometer (MFRSR), are widely used for atmospheric optical depth measurements. The major programs running MFRSR networks in the United States include the Department of Energy Atmospheric Radiation Measurement (ARM) Program, U.S. Department of Agriculture UV-B Monitoring and Research Program, National Oceanic and Atmospheric Administration Surface Radiation (SURFRAD) Network, and NASA Solar Irradiance Research Network (SIRN). We discuss a number of technical issues specific to shadowband radiometers and their impact on the optical depth measurements. These problems include instrument tilt and misalignment, as well as some data processing artifacts. Techniques for data evaluation and automatic detection of some of these problems are described. OCIS codes: 120.4640, 120.5240, 120.5630, 120.0280, 010.1100, 010.1120.

To better understand how terrestrial vegetative ecosystems respond to climate and/or anthropogenic effects, the scientific community is increasingly interested in developing methods of employing satellite data to track changes in land surface phenology (e.g., timing and rate of green-up, amplitude and duration of growing season, and timing and rate of senescence of plant classes). By increasing the inherent resolution of signal extraction procedures while minimizing the effects of cloud cover and prolonged data gaps, such tools can significantly improve land cover classification and land cover change monitoring on multiple scales. This report describes an intuitive approach for tracking the intra-annual details and interannual variability of multiyear time series, employing a sequence of annual high-order polynomial splines (up to the 14th order), stabilized by minimizing model roughness and weighted to fit the upper data envelope to minimize cloud cover bias. The algorithm is tested using multiyear time series for three very different classes of vegetation-stable agriculture, high elevation montane shrubland, and semiarid grassland with high interanuual variability. The results accurately track both short--and long-term land surface phenology and illustrate a robust potential for extracting temporal and spatial detail from a variety of satellite-based multiyear vegetation signals. Index Terms--Advanced Very High Resolution Radiometer (AVHRR), Fourier analysis, harmonic series, multiyear, normalized difference vegetation index (NDVI ), phenology, polynomial lit, signal processing, spline, time series.

The University of Michigan Microwave Geophysics Group participated in the Cold Lands Processes Experiment from February to April 2003 by deploying its Truck Mounted Radiometer System-3 (TMRS-3) to perform temporal monitoring of the snow pack at the local scale observation site (LSOS). The LSOS was located at the Fraser Experimental Forest headquarters in the mountains near Fraser, CO. The small clearing in which the TMRS-3 was deployed was adjacent to tall evergreen trees. To quantify the amount of the downwelling brightness from these trees onto the snow pack, the TMRS-3 periodically observed these trees. Microwave brightness data were collected from the trees every 15 [degrees] from horizontal incidence to 45 [degress] from zenith. Both polarizations were observed for 6.7, 19, and 37 GHz. A rapid decrease in brightness is evident as the radiometers were pointed progressively upward. The next May, an upward-looking hemispherical ('fish-eye') photograph was taken from the center of the clearing, and it reveals a significant sky background through the incomplete canopy. By superimposing Gaussian approximations to the microwave antenna gain pattern of the individual TMRS-3 radiometers onto the photograph, we estimated the amount that the main beams were filled with canopy and with sky. Comparison of the measured data to that expected for a partially filled main beam indicates that the needle-leaf canopy is roughly an isotropic emitter having emissivities at frequencies between 6.7 and 37 GHz of between 0.93 and 0.97 with air temperature as a proxy for tree temperature. Index Terms--Emission, microwave radiometry, snow, vegetation.

An improved Backus--Gilbert resampling scheme is developed and applied on Advanced Microwave Scanning Radiometer-EOS (AMSR-E) brightness temperature swath data. The new resampling scheme has two improvements over the Special Sensor Microwave Imager and AMSR-E resampling schemes currently used to produce standard brightness products. First, the use of a circular Ganssian footprint as the reference footprint achieves near-circular synthesized footprints for all channels. The near-circular synthesized footprints diminish the effect of different orientations of the synthesized elliptical footprints produced by the standard algorithm. Second, a better synthesized footprint spatial resolution for the 6.925- and 10.65-GHz channels in the across scan direction is achieved with a significant reduction in noise level. Oversampling by AMSR-E at these frequencies enables this improvement. Index Terms--Image processing, microwave radiometry.

Sea surface salinity can be remotely measured by means of L-band microwave radiometry. However, the brightness temperature also depends on the sea surface temperature and on the sea state, which is probably today one of the driving factors in the salinity retrieval error budgets of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission and the NASA-Comision Nacional de Actividades Espaciales Aquarius/SAC-D mission. This paper describes the Passive Advanced Unit (PAU) for ocean monitoring. PAU combines in a single instrument three different sensors: an L-band radiometer with digital beamforming (DBF) (PAU-RAD) to measure the brightness temperature of the sea at different incidence angles simultaneously, a global positioning system (GPS) reflectometer [PAU-reflectometer of Global Navigation Satellite Signals (GNSS-R)] also with DBF to measure the sea state from the delay-Doppler maps, and two infrared radiometers to provide sea surface temperature estimates. The key characteristic of this instrument is that both PAU-RAD and the PAU-GNSS/R share completely the RF/IF front-end, and analog-to-digital converters. Since in order to track the GPS-reflected signal, it is not possible to chop the antenna signal as in a Dicke radiometer, a new radiometer topology has been devised which makes uses of two receiving chains and a correlator, which has the additional advantage that both PAU-RAD and PAU-GNSS/R can be operated continuously and simultaneously to perform the sea-state corrections of the brightness temperature. This paper presents the main characteristics of the different PAU subsystems, and analyzes in detail the PAU-radiometer concept. Index Terms--Correlator, Global Navigation Satellite Signals (GNSS), radiometry, reflectometry, sea salinity, sensitivity.

Surface wind vector measurements over the oceans are vital for scientists and forecasters to understand the Earth's global weather and climate. In the last two decades, operational measurements of global ocean wind speeds were obtained from passive microwave radiometers (Special Sensor Microwave/ Imagers); and over this period, full ocean surface wind vector data were obtained from several National Aeronautics and Space Administration and European Space Agency scatterometry missions. However, since SeaSat-A in 1978, there have not been other combined active and passive wind measurements on the same satellite until the launch of Japan Aerospace Exploration Agency's Advanced Earth Observing Satellite-II in 2002. This mission provided a unique data set of coincident measurements between the SeaWinds scatterometer and the Advanced Microwave Scanning Radiometer (AMSR). The AMSR instrument measured linearly polarized brightness temperatures ([T.sub.B]) over the ocean. Although these measurements contained wind direction information, the overlying atmospheric influence obscured this signal and made wind direction retrievals not feasible. However, for radiometer channels between 10 and 37 GHz, a certain linear combination of vertical and horizontal brightness temperatures causes the atmospheric dependence to cancel and surface parameters such as wind speed and direction and sea surface temperature to dominate the resulting signal. In this paper, an empirical relationship between AMSR TB'S (specifically A * [T.sub.BV] - [T.sub.BH]) and surface wind vectors (inferred from SeaWinds' retrievals) is established for three microwave frequencies: 10, 18, and 37 GHz. This newly developed wind vector model function for microwave radiometers can serve as a basis for wind vector retrievals either separately or in combination with active scatterometer measurements. Index Terms--Active and passive microwave, microwave radiometry, ocean surface wind vector, scatterometry.

In this paper, a research version of the Meteorological Service of Canada (MSC) Global Environmental Multiscale (GEM) mesoglobal weather forecasts model is evaluated by comparing the simulated Special Sensor Microwave/Imager brightness temperatures (Tbs) with the observed ones. Several comparisons based on two 15-day periods, one in winter and one in summer, have been done. Results are compared to those obtained for a study conducted on the European Centre for Medium-Range Weather Forecast (ECMWF) model. The overall performance of the GEM model is similar to that of the 2001 version of the ECMWF model. The model appears to simulate with realism the large-scale rainy systems but with frequent mislocations. Moreover, the model has a tendency to produce intense small-scale precipitating areas that are not observed. The occurrence frequency of cloud and rain is overestimated by the model. Finally, these results are encouraging enough to continue investigating the assimilation of Tbs in cloudy and rainy skies at MSC. Index Terms--Forecast-model evaluation, model-to-satellite method, passive-microwave radiometer, Special Sensor Microwave/Imager (SSM/I).

For future remote sensing applications the potential of the millimeter wavelength range for precipitation observations from geostationary orbits is investigated. Therefore, a database consisting of hydrometeor profiles from various mid-latitude precipitation cases over Europe and corresponding simulated brightness temperatures at 18 microwave frequencies was built using the cloud resolving model Meso-NH and the radiative transfer model MicroWave MODel. The information content of the database was investigated by applying simple statistical methods, as well as developing first-order retrieval approaches. The results show that, particularly for snow and graupel, the total column content can be retrieved accurately with relative errors smaller than 25% in dominantly stratiform precipitation cases over land and ocean surfaces. The performance for rain-water path is similar to the one for graupel and snow in light precipitation cases. For the cases with higher precipitation amounts, the relative errors for rain-water path are larger particularly over land. The same behavior can be seen in the surface rain rate retrieval with the difference that the relative errors are doubled in comparison to the rain-water path. Algorithms with reduced number of frequencies show that window channels at higher frequencies are important for the surface rain rate retrieval because these are sensitive to the scattering in the ice phase related to the rain below. For the frozen hydrometeor retrieval, good results can be achieved by retrieval algorithms based only on frequencies at 150 GHz and above which are suitable for geostationary applications due to their reduced demands concerning the antenna size. Index Terms--Hydrometeor, millimeter wave radiometry, remote sensing, retrieval, satellite applications.

This paper presents the results of a simple information content study between the Advanced Microwave Sounding Unit/Microwave Humidity Sounder (AMSU/MHS) and the Advanced Technology Microwave Sounder (ATMS). When a single field of view is considered for both instruments, the AMSU/MHS generally outperforms the ATMS for temperature and moisture information due to its better noise performance. However, when footprint matching is employed to use oversampled ATMS observations, the ATMS consistently shows improvement in temperature and moisture information over the AMSU/MHS. Index Terms--Electromagnetic propagation in absorbing media, geophysical inverse problems, information retrieval, Jacobian matrices, maximum likelihood estimation, microwave measurements, microwave radiometry, remote sensing, satellite applications.