Showing papers on "Radiometer published in 2007"

Daily High-Resolution-Blended Analyses for Sea Surface Temperature

Abstract: Two new high-resolution sea surface temperature (SST) analysis products have been developed using optimum interpolation (OI). The analyses have a spatial grid resolution of 0.25° and a temporal resolution of 1 day. One product uses the Advanced Very High Resolution Radiometer (AVHRR) infrared satellite SST data. The other uses AVHRR and Advanced Microwave Scanning Radiometer (AMSR) on the NASA Earth Observing System satellite SST data. Both products also use in situ data from ships and buoys and include a large-scale adjustment of satellite biases with respect to the in situ data. Because of AMSR’s near-all-weather coverage, there is an increase in OI signal variance when AMSR is added to AVHRR. Thus, two products are needed to avoid an analysis variance jump when AMSR became available in June 2002. For both products, the results show improved spatial and temporal resolution compared to previous weekly 1° OI analyses. The AVHRR-only product uses Pathfinder AVHRR data (currently available from January 1985 to December 2005) and operational AVHRR data for 2006 onward. Pathfinder AVHRR was chosen over operational AVHRR, when available, because Pathfinder agrees better with the in situ data. The AMSR– AVHRR product begins with the start of AMSR data in June 2002. In this product, the primary AVHRR contribution is in regions near land where AMSR is not available. However, in cloud-free regions, use of both infrared and microwave instruments can reduce systematic biases because their error characteristics are independent.

Operational readiness of microwave remote sensing of soil moisture for hydrologic applications

Abstract: Microwave remote sensing of soil moisture has been an active area of research since the 1970s but has yet found little use in operational applications Given recent advances in retrieval algorithms and the approval of a dedicated soil moisture satellite, it is time to re-assess the potential of various satellite systems to provide soil moisture information for hydrologic applications in an operational fashion This paper reviews recent progress made with retrieving surface soil moisture from three types of microwave sensors - radiometers, Synthetic Aperture Radars (SARs), and scatterometers The discussion focuses on the operational readiness of the different techniques, considering requirements that are typical for hydrological applications It is concluded that operational coarse-resolution (25-50 km) soil moisture products can be expected within the next few years from radiometer and scatterometer systems, while scientific and technological breakthroughs are still needed for operational soil moisture retrieval at finer scales (< 1 km) from SAR Also, further research on data assimilation methods is needed to make best use of the coarse-resolution surface soil moisture data provided by radiometer and scatterometer systems in a hydrologic context and to fully assess the value of these data for hydrological predictions

Comparison and assimilation of global soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E) and the Scanning Multichannel Microwave Radiometer (SMMR)

Abstract: [1] Two data sets of satellite surface soil moisture retrievals are first compared and then assimilated into the NASA Catchment land surface model. The first satellite data set is derived from 4 years of X-band (10.7 GHz) passive microwave brightness temperature observations by the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), and the second is from 9 years of C-band (6.6 GHz) brightness temperature observations by the Scanning Multichannel Microwave Radiometer (SMMR). Despite the similarity in the satellite instruments, the retrieved soil moisture data exhibit very large differences in their multiyear means and temporal variability, primarily because they are computed with different retrieval algorithms. The satellite retrievals are also compared to a soil moisture product generated by the NASA Catchment land surface model when driven with surface meteorological data derived from observations. The climatologies of both satellite data sets are different from those of the model products. Prior to assimilation of the satellite retrievals into the land model, satellite-model biases are removed by scaling the satellite retrievals into the land model's climatology through matching of the respective cumulative distribution functions. Validation against in situ data shows that for both data sets the soil moisture fields from the assimilation are superior to either satellite data or model data alone. A global analysis of the innovations (defined as the difference between the observations and the corresponding model values prior to the assimilation update) reveals how changes in model and observations error parameters may enhance filter performance in future experiments.

Hurricane Surface Wind Measurements from an Operational Stepped Frequency Microwave Radiometer

Abstract: For the first time, the NOAA/Aircraft Operations Center (AOC) flew stepped frequency microwave radiometers (SFMRs) on both WP-3D research aircraft for operational hurricane surface wind speed measurement in 2005. An unprecedented number of major hurricanes provided ample data to evaluate both instrument performance and surface wind speed retrieval quality up to 70 m s−1 (Saffir–Simpson category 5). To this end, a new microwave emissivity–wind speed model function based on estimates of near-surface winds in hurricanes by global positioning system (GPS) dropwindsondes is proposed. For practical purposes, utilizing this function removes a previously documented high bias in moderate SFMR-measured wind speeds (10–50 m s−1), and additionally corrects an extreme wind speed (>60 m s−1) underestimate. The AOC operational SFMRs yield retrievals that are precise to within ∼2% at 30 m s−1, which is a factor of 2 improvement over the NOAA Hurricane Research Division’s SFMR, and comparable to the precision fou...

Soil moisture from Operational Meteorological Satellites

Abstract: In recent years, unforeseen advances in monitoring soil moisture from operational satellite platforms have been made, mainly due to improved geophysical retrieval methods. In this study, four recently published soil-moisture datasets are compared with in-situ observations from the REMEDHUS monitoring network located in the semi-arid part of the Duero basin in Spain. The remotely sensed soil-moisture products are retrieved from (1) the Advanced Microwave Scanning Radiometer (AMSR-E), which is a passive microwave sensor on-board NASA’s Aqua satellite, (2) European Remote Sensing satellite (ERS) scatterometer, which is an active microwave sensor on-board the two ERS satellites and (3) visible and thermal images from the METEOSAT satellite. Statistical analysis indicates that three satellite datasets contribute effectively to the monitoring of trends in surface soil-moisture conditions, but not to the estimation of absolute soil-moisture values. These sensors, or rather their successors, will be flown on operational meteorological satellites in the near future. With further improvements in processing techniques, operational meteorological satellites will increasingly deliver high-quality soil-moisture data. This may be of particular interest for hydrogeological studies that investigate long-term processes such as groundwater recharge.

Three-Year Wilkinson Microwave Anisotropy Probe (WMAP)* Observations: Beam Profiles, Data Processing, Radiometer Characterization, and Systematic Error Limits

Abstract: The WMAP satellite has completed 3 years of observations of the cosmic microwave background radiation. The 3yeardataproductsincludeseveralsetsof fullskymapsoftheStokesI,Q,andUparametersinfivefrequencybands, spanning 23Y94 GHz, and supporting items such as beam window functions and noise covariance matrices. The processing used to produce the current sky maps and supporting products represents a significant advancement over the first-year analysis and is described herein. Improvements to the pointing reconstruction, radiometer gain modeling, window function determination, and radiometer spectral noise parameterization are presented. A detailed description of the updated data processing that produces maximum likelihood sky map estimates is presented, along withthemethodsusedtoproducereducedresolutionmapsandcorrespondingnoisecovariancematrices.Finally,two methods used to evaluate the noise of the full resolution sky maps are presented along with several representativeyear-to-yearnulltests,demonstratingthatskymapsproducedfromdatafromdifferentobservationalepochsare consistent. Subject headingg cosmic microwave background — instrumentation: detectors — space vehicles: instruments

Orbital microwave measurement of river discharge and ice status

Abstract: Satellite passive microwave sensors provide global coverage of the Earth's land surface on a near-daily basis without severe interference from cloud cover. Using a strategy first developed for wide-area optical sensors, and in conjunction with even limited ground-based discharge information, such microwave data can be used to estimate river discharge changes, river ice status, and watershed runoff. Water surface area in a river reach increases as flow widens, and any temporally calibrated observation sensitive to changing water area monitors discharge. The sensor spatial resolution is less important than the scene-to-scene calibration and the contrast in upwelling radiance between water and land. We use the Advanced Microwave Scanning Radiometer (AMSR-E) band at 36.5 GHz, descending orbit, horizontal polarization, and the resampled Level-3 daily global data product. The discharge estimator HR is a ratio of calibration-target radiance (expressed as brightness temperature), for a local land parcel unaffected by the river, to measurement-target brightness temperature, for a pixel centered over the river. At midlatitudes, pixel dimensions are approximately 25 km. Because of low emission from water surfaces, HR increases with discharge as in-pixel water area expands. It increases sharply once overbank flow conditions occur. River ice-cover is also detectable. The sensitivity and accuracy of the orbital measurements is tested along U.S. rivers monitored by in situ gaging stations, with favorable results. Other tests demonstrate that for seasonally variable rivers, AMSR-E can provide useful international measurements of daily river discharge even if only fragmentary monthly mean discharge data are available for calibration.

Atmospheric correction algorithm for MERIS above case-2 waters

Abstract: The development and validation of an atmospheric correction algorithm designed for the Medium Resolution Imaging Spectrometer (MERIS) with special emphasis on case-2 waters is described. The algorithm is based on inverse modelling of radiative transfer (RT) calculations using artificial neural network (ANN) techniques. The presented correction scheme is implemented as a direct inversion of spectral top-of-atmosphere (TOA) radiances into spectral remote sensing reflectances at the bottom-of-atmosphere (BOA), with additional output of the aerosol optical thickness (AOT) at four wavelengths for validation purposes. The inversion algorithm was applied to 13 MERIS Level1b data tracks of 2002-2003, covering the optically complex waters of the North and Baltic Sea region. A validation of the retrieved AOTs was performed with coincident in situ automatic sun-sky scanning radiometer measurements of the Aerosol Robotic Network (AERONET) from Helgoland Island located in the German Bight. The accuracy of the derived reflectances was validated with concurrent ship-borne reflectance measurements of the SIMBADA hand-held field radiometer. Compared to the MERIS Level2 standard reflectance product generated by the processor versions 3.55, 4.06 and 6.3, the results of the proposed algorithm show a significant improvement in accuracy, especially in the blue part of the spectrum, where the MERIS Level2 reflectances result in errors up to 122% compared to only 19% with the proposed algorithm. The overall mean errors within the spectral range of 412.5-708.75 nm are calculated to be 46.2% and 18.9% for the MERIS Level2 product and the presented algorithm, respectively.

Initial Results of the Geostationary Synthetic Thinned Array Radiometer (GeoSTAR) Demonstrator Instrument

Abstract: The design, error budget, and preliminary test results of a 50-56-GHz synthetic aperture radiometer demonstration system are presented. The instrument consists of a fixed 24-element array of correlation interferometers and is capable of producing calibrated images with 1deg spatial resolution within a 17deg wide field of view. This system has been built to demonstrate a performance and a design which can be scaled to a much larger geostationary Earth imager. As a baseline, such a system would consist of about 300 elements and would be capable of providing contiguous full hemispheric images of the Earth with 1 K of radiometric precision and 50-km spatial resolution. An error budget is developed around this goal and then tested with the demonstrator system. Errors are categorized as either scaling (i.e., complex gain) or additive (noise and bias) errors. Sensitivity to gain and/or phase error is generally proportional to the magnitude of the expected visibility, which is high only in the shortest baselines of the array, based on model simulations of the Earth as viewed from geostationary Earth orbit. Requirements range from approximately 0.5% and 0.3deg of amplitude and phase uncertainty, respectively, for the closest spacings at the center of the array, to about 4% and 2.5deg for the majority of the array. The latter requirements are demonstrated with our instrument using relatively simple references and antenna models, and by relying on the intrinsic stability and efficiency of the system. The 0.5% requirement (for the short baselines) is met by measuring the detailed spatial response (e.g., on the antenna range) and by using an internal noise diode reference to stabilize the response. This result suggests a hybrid image synthesis algorithm in which long baselines are processed by a fast Fourier transform and the short baselines are processed by a more precise (G-matrix) algorithm which can handle small anomalies among antenna and receiver responses. Visibility biases and other additive errors must be below about 1.5 mK on average, regardless of baseline. The bias requirement is largely met with a phase-shifting scheme applied to the local oscillator distribution of our demonstration system. Low mutual coupling among the horn antennas of our design is also critical to minimize the biases caused by crosstalk of receiver noise. Performance is validated by a three-way comparison between interference fringes measured on the antenna range, solar transit observations, and the system model.

PARASOL in-flight calibration and performance

Abstract: Since 18 December 2004, the PARASOL satellite is a member of the so-called A-train atmospheric orbital observatory, flying together with Aqua, Aura, CALIPSO, CLOUDSAT, and OCO satellites. These satellites combine for the first time a full suite of instruments for observing aerosols and clouds, using passive radiometer complementarily with active lidar and radar sounders. The PARASOL payload is extensively derived from the instrument developed for the POLDER programs that performs measurements of bidirectionality and polarization for a very wide field-of-view and for a visible/near-infrared spectral range. An overview of the results obtained during the commissioning phase and the reevaluation after one year in orbit is presented. In-flight calibration methods are briefly described, and radiometric and geometric performances are both evaluated. All algorithms are based on a panel of methods using mainly natural targets previously developed for POLDER missions and adapted or redeveloped in the PARASOL context. Regarding performances, all mission requirements are met except for band 443 (not recommended for use). After one year in orbit, a perfect geometrical stability was found while a slight decrease of the radiometric sensitivity was observed and corrected through an innovative multitemporal algorithm based on observations of bright and scattered convective clouds. The scientific exploitation of PARASOL has now begun, particularly by coupling these specific observations with other A-train sensor measurements.

A concept for a satellite mission to measure cloud ice water path, ice particle size, and cloud altitude

Abstract: A passive satellite radiometer operating at submillimetre wavelengths can measure cloud ice water path (IWP), ice particle size, and cloud altitude. The paper first discusses the scientific background for such measurements. Formal scientific mission requirements are derived, based on this background and earlier assessments. The paper then presents a comprehensive prototype instrument and mission concept, and demonstrates that it meets the requirements. The instrument is a conically scanning 12-channel radiometer with channels between 183 and 664 GHz, proposed to fly in tandem with one of the Metop satellites. It can measure IWP with a relative accuracy of approximately 20% and a detection threshold of approximately 2 g m−2. The median mass equivalent sphere diameter of the ice particles can be measured with an accuracy of approximately 30 µm, and the median IWP cloud altitude can be measured with an accuracy of approximately 300 m. All the above accuracies are median absolute error values; root mean square error values are approximately twice as high, due to rare outliers.

Multi-instrument comparison of top-of-atmosphere reflected solar radiation

Abstract: Observations from the Clouds and the Earth’s Radiant Energy System (CERES), Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) between 2000 and 2005 are analyzed in order to determine if these data are meeting climate accuracy goals recently established by the climate community. The focus is primarily on top-of-atmosphere (TOA) reflected solar radiances and radiative fluxes. Direct comparisons of nadir radiances from CERES, MODIS, and MISR aboard the Terra satellite reveal that the measurements from these instruments exhibit a year-to-year relative stability of better than 1%, with no systematic change with time. By comparison, the climate requirement for the stability of visible radiometer measurements is 1% decade−1. When tropical ocean monthly anomalies in shortwave (SW) TOA radiative fluxes from CERES on Terra are compared with anomalies in Photosynthetically Active Radiation (PAR) from SeaWiF...

Characterization and calibration of ultraviolet broadband radiometers measuring erythemally weighted irradiance

Abstract: An ultraviolet calibration center has been established in Davos, Switzerland. It provides a laboratory for characterizing the spectral and angular response of broadband radiometers. The absolute calibration of these instruments is performed through the comparison to the reference spectroradiometer qasume. We present what we believe to be a novel calibration methodology that explicitly includes the information of the angular and spectral response functions. From the results of the latest broadband intercomparison campaign, the typical uncertainties of these instruments could be obtained. Most radiometers have an expanded uncertainty of approximately 7%. The angular response introduces an uncertainty of 0.9%-7.2%, depending on the cosine error of the radiometer.

Utility of Radiometric–aerodynamic Temperature Relations for Heat Flux Estimation

Abstract: In many land-surface models using bulk transfer (one-source) approaches, the application of radiometric surface temperature observations in energy flux computations has given mixed results. This is due in part to the non-unique relationship between the so-called aerodynamic temperature, which relates to the efficiency of heat exchange between the land surface and overlying atmosphere, and a surface temperature measurement from a thermal-infrared radiometer, which largely corresponds to a weighted soil and canopy temperature as a function of radiometer viewing angle. A number of studies over the past several years using multi-source canopy models and/or experimental data have developed simplified methods to accommodate radiometric-aerodynamic temperature differences in one-source approaches. A recent investigation related the variability in the radiometric-aerodynamic relation to solar radiation using experimental data from a variety of landscapes, while another used a multi-source canopy model combined with measurements over a wide range in vegetation density to derive a relationship based on leaf area index. In this study, simulations by a detailed multi-source soil-plant-environment model, Cupid, which considers both radiative and turbulent exchanges across the soil-canopy-air interface, are used to explore the radiometric-aerodynamic temperature relations for a semi-arid shrubland ecosystem under a range of leaf area/canopy cover, soil moisture and meteorological conditions. The simulated radiometric-aerodynamic temperatures indicate that, while solar radiation and leaf area both strongly affect the magnitude of this temperature difference, the relationships are non-unique, having significant variability depending on local conditions. These simulations also show that soil-canopy temperature differences are highly correlated with variations in the radiometric-aerodynamic temperature differences, with the slope being primarily a function of leaf area. This result suggests that two-source schemes with reliable estimates of component soil and canopy temperatures and associated resistances may be better able to accommodate variability in the radiometric-aerodynamic relation for a wider range in vegetated canopy cover conditions than is possible with one-source schemes. However, comparisons of sensible heat flux estimates with Cupid using a simplified two-source model and a one-source model accommodating variability in the radiometric-aerodynamic relation based on vegetation density gave similar scatter. On the other hand, with experimental data from the shrubland site, the two-source model generally outperformed the one-source scheme. Clearly, vegetation density/leaf area has a major effect on the radiometric-aerodynamic temperature relation and must be considered in either one-source or two-source formulations. Hence these adjusted one-source models require similar inputs as in two-source approaches, but provide as output only bulk heat fluxes; this is not as useful for monitoring vegetation conditions.

Estimating photosynthetically available radiation at the ocean surface from ADEOS-II global imager data

Abstract: A simple, yet efficient and fairly accurate algorithm is presented to estimate photosynthetically available radiation (PAR) at the ocean surface from Global Imager (GLI) data. The algorithm utilizes plane-parallel radiation-transfer theory and separates the effects of the clear atmosphere and clouds, i.e., the planetary atmosphere is modeled as a clear atmosphere positioned above a cloud layer. PAR is computed as the difference between the incident 400–700 nm solar flux at the top of the atmosphere (known) and the solar flux reflected back to space by the atmosphere and surface (derived from GLI radiance), taking atmospheric absorption into account. Knowledge of pixel composition is not required, eliminating the need for cloud screening and arbitrary assumptions about sub-pixel cloudiness. For each GLI pixel, clear or cloudy, a daily PAR estimate is obtained. Diurnal changes in cloudiness are taken into account statistically, using a regional diurnal albedo climatology based on 5 years of Earth Radiation Budget Satellite (ERBS) data. The algorithm results are verified against other satellite estimates of PAR, the National Centers for Environmental Prediction (NCEP) reanalysis product, and in-situ measurements from fixed buoys. Agreement is generally good between GLI and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) estimates, with root-mean-squared (rms) differences of 7.9 (22%), 4.6 (13%), and 2.7 (8%) Einstein/m2/day on daily, weekly, and monthly time scales, and a bias of only 0.8–0.9 (about 2%) Einstein/m2/day. The rms differences between GLI and Visible and Infrared Spin Scan Radiometer (VISSR) estimates and between GLI and NCEP estimates are smaller and larger, respectively, on monthly time scales, i.e., 3.0 (7%) and 5.0 (14%) Einstein/m2/day, and biases are 1.1 (2%) and −0.2 (−1%) Einstein/m2/day. The comparison with buoy data also shows good agreement, with rms inaccuracies of 10.2 (23%), 6.3 (14%), and 4.5 (10%) Einstein/m2/day on daily, weekly, and monthly time scales, and slightly higher GLI values by about 1.0 (2%) Einstein/m2/day. The good statistical performance makes the algorithm suitable for large-scale studies of aquatic photosynthesis.

Computing Coastal Ocean Surface Currents From Infrared and Ocean Color Satellite Imagery

Abstract: Many previous studies have demonstrated the viability of estimating advective ocean surface currents from sequential infrared satellite imagery using the maximum cross-correlation (MCC) technique when applied to 1.1-km-resolution Advanced Very High Resolution Radiometer (AVHRR) thermal infrared imagery. Applied only to infrared imagery, cloud cover and undesirable viewing conditions (gaps in satellite data and edge-of-scan distortions) limit the spatial and temporal coverage of the resulting velocity fields. In addition, MCC currents are limited to those represented by the displacements of thermal surface patterns, and hence, isothermal flow is not detected by the MCC method. The possibility of supplementing MCC currents derived from thermal AVHRR imagery was examined, with currents calculated from 1.1-km-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) ocean color imagery, which often have spatial patterns complementary to the thermal infrared patterns. Statistical comparisons are carried out between yearlong collections of thermal and ocean color derived MCC velocities for the central California Current. It is found that the image surface patterns and resulting MCC velocities complement one another to reduce the effects of poor viewing conditions and isothermal flow. The two velocity products are found to agree quite well with a mean correlation of 0.74, a mean rms difference of 7.4 cm/s, and a mean bias less than 2 cm/s which is considerably smaller than the established absolute error of the MCC method. Merging the thermal and ocean color MCC velocity fields increases the spatial coverage by approximately 25% for this specific case study

Accuracy of Boundary Layer Temperature Profiles Retrieved With Multifrequency Multiangle Microwave Radiometry

Abstract: The potential of a ground-based microwave temperature profiler to combine full tropospheric profiling with high-resolution profiling of the boundary layer is investigated. For that purpose, statistical retrieval algorithms that incorporate observations from different elevation angles and frequencies are derived from long-term radiosonde data. A simulation study shows the potential to significantly improve the retrieval performance in the lowest kilometer by combining angular information from relatively opaque channels with zenith-only information from more transparent channels. Observations by a state-of-the-art radiometer employed during the International Lindenberg campaign for assessment of humidity and cloud profiling systems and its impact on High-resolution modeling (LAUNCH) in Lindenberg, Germany, are used for an experimental evaluation with observations from a 99-m mast and radiosondes. The comparison not only reveals the high accuracy achieved by combining angular and spectral observations (overall, less than 1 K below 1.5 km), but also emphasizes the need for a realistic description of radiometer noise within the algorithm. The capability of the profiler to observe the height and strength of low-level temperature inversions is highlighted.

Detection of Radio Frequency Interference with the Aquarius Radiometer

Abstract: A radio-frequency interference (RFI) detection algorithm has been developed for the Aquarius microwave radiometer. The algorithm compares individual brightness temperature samples with a local mean obtained from neighboring samples. If the sample under test significantly deviates from the local mean, then it is assumed to be corrupted by RFI. The algorithm has several adjustable parameters to optimize RFI detection. The performance of the algorithm has been characterized as a function of these parameters using a new form of RFI ldquoground truthrdquo that is based on the kurtosis of the amplitude distribution of the predetected voltages of a radiometer. Ground-based radiometric data obtained from the JPL-PALS campaign were used to assess the performance of the algorithm. False-alarm rates and the dependence of false alarms on worst case naturally occurring brightness temperature variations on orbit are determined as functions of the adjustable parameters of the algorithm.

1D-VAR Retrieval of Temperature and Humidity Profiles From a Ground-Based Microwave Radiometer

Abstract: A variational method to retrieve profiles of temperature, humidity, and cloud is described, which combines observations from a 12-channel microwave radiometer, an infrared radiometer, and surface sensors with background from shortrange numerical weather prediction (NWP) forecasts in an optimal way, accounting for their error characteristics. An analysis is presented of the error budget of the background and observations, including radiometric, modeling, and representativeness errors. Observation errors of some moisture channels are found to be dominated by representativeness, due to their sensitivity to atmospheric variability on smaller scales than the NWP model grid, whereas channels providing information on temperature in the lowest 1 km are dominated by instrument noise. Profiles of temperature and a novel total water control variable are retrieved from synthetic data using Newtonian iteration. An error analysis shows that these are expected to improve mesoscale NWP, retrieving temperature and humidity profiles up to 4 km with uncertainties of 1 K and 40% and 2.8 and 1.8 degrees of freedom for signal, respectively, albeit with poor vertical resolution. A cloud classification scheme is introduced to address convergence problems and better constrain the retrievals. This Bayesian retrieval method can be extended to incorporate observations from other instruments to form a basis for future integrated profiling systems.

Temperature-resolved infrared spectral emissivity of SiC and Pt-10Rh for temperatures up to 900°C

Abstract: This article reports the first comprehensive results obtained from a fully functional, recently established infrared spectral-emissivity measurement facility at the National Institute of Standards and Technology (NIST). First, sample surface temperatures are obtained with a radiometer using actual emittance values from a newly designed sphere reflectometer and a comparison between the radiometer temperatures and contact thermometry results is presented. Spectral emissivity measurements are made by comparison of the sample spectral radiance to that of a reference blackbody at a similar (but not identical) temperature. Initial materials selected for measurement are potential candidates for use as spectral emissivity standards or are of particular technical interest. Temperature-resolved measurements of the spectral directional emissivity of SiC and Pt–10Rh are performed in the spectral range of 2–20 μm, over a temperature range from 300 to 900°C at normal incidence. Further, a careful study of the uncertainty components of this measurement is presented.

Satellite Microwave Remote Sensing of Boreal and Arctic Soil Temperatures From AMSR-E

Abstract: Methods are developed and evaluated to retrieve surface soil temperature information for the advanced microwave scanning radiometer on earth observing system for seven boreal forest and Arctic tundra biophysical monitoring sites across Alaska and Northern Canada. A multiple-band iterative radiative transfer process-based method producing dynamic vegetation and snow cover correction quantities and an empirical multiple regression method using several frequencies are employed. The seasonal pattern of microwave emission and relative accuracy of the soil temperature retrievals are influenced strongly by landscape properties, including the presence of open water, vegetation type and seasonal phenology, snow cover, and freeze-thaw transitions. The retrieval of soil temperature is similar for the two methods with an overall root-mean-square error of 3.1-3.9 K during summer thawed conditions, with a larger error occurring in winter during periods of dynamic snow cover and freeze-thaw state. These results indicate that at high latitudes, the influence of the atmosphere may be less important than that of surface conditions in determining the relative accuracy of the estimated soil temperature. Impacts of surface conditions on surface emissivity, observed brightness temperature, and estimated soil temperature are discussed.

A new satellite retrieval method for precipitable water vapor over land and ocean

Abstract: [1] A fundamentally new method is presented for retrieving precipitable water vapor (PWV) using observations from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) satellite instrument. Unlike all existing passive satellite methods, the new technique is applicable both day and night, over ocean and land surfaces, and with little sensitivity to clouds. The method relies on a simple but accurate parameterization for AMSR-E polarization-difference signals at 18.7 and 23.8 GHz. Over land, validation is based on comparisons with the SuomiNet network of ground-based GPS receivers. With quality control measures applied, RMS retrieval errors over land are limited to approximately six mm with a linear correlation coefficient of 0.89. Differences with the operational AMSR-E oceanic PWV product are typically less than two mm. Products based on the new method should prove valuable in weather and climate research.

Analysis of Radiosonde and Ground-Based Remotely Sensed PWV Data from the 2004 North Slope of Alaska Arctic Winter Radiometric Experiment

Abstract: During 9 March–9 April 2004, the North Slope of Alaska Arctic Winter Radiometric Experiment was conducted at the Atmospheric Radiation Measurement Program’s (ARM) “Great White” field site near Barrow, Alaska. The major goals of the experiment were to compare microwave and millimeter wavelength radiometers and to develop forward models in radiative transfer, all with a focus on cold (temperature from 0° to 40°C) and dry [precipitable water vapor (PWV) 0.5 cm] conditions. To supplement the remote sensors, several radiosonde packages were deployed: Vaisala RS90 launched at the ARM Duplex and at the Great White and Sippican VIZ-B2 operated by the NWS. In addition, eight dual-radiosonde launches were conducted at the Duplex with Vaisala RS90 and Sippican GPS Mark II, the latter one modified to include a chilled mirror humidity sensor. Temperature comparisons showed a nighttime bias between VIZ-B2 and RS90, which reached 3.5°C at 30 hPa. Relative humidity comparisons indicated better than 5% average agreement between the RS90 and the chilled mirror. A bias of about 20% for the upper troposphere was found in the VIZ-B2 and the Mark II measurements relative to both RS90 and the chilled mirror. Comparisons in PWV were made between a microwave radiometer, a microwave profiler, a global positioning system receiver, and the radiosonde types. An RMS agreement of 0.033 cm was found between the radiometer and the profiler and better than 0.058 cm between the radiometers and GPS. RS90 showed a daytime dry bias on PWV of about 0.02 cm.

Relative impact of polar‐orbiting and geostationary satellite radiances in the Aladin/France numerical weather prediction system

Abstract: For its short-range forecasts over Western Europe, Meteo-France runs the limited-area model ALADIN operationally with four daily analyses obtained with a 3D-Var data assimilation system. This system includes, among other observation types, radiances from AMSU-A, AMSU-B, HIRS and SEVIRI radiometers. SEVIRI is on board the geostationary platform Meteosat-8 and provides continuous observations in space and in time over the region of interest at several wavelengths, while the others, which are on board polar-orbiting satellites, have poorer temporal and horizontal resolutions but a better spectral resolution than SEVIRI. Observing System Experiments (OSEs) have been performed with the operational 3D-Var to assess the impact of such satellite data on analyses and on forecasts. DFS (Degrees of Freedom for Signal) have been computed and have shown the complementarity between WV channels from the different radiometers. In the operational version of the 3D-Var, DFS values show that analyses are strongly controlled by SEVIRI data in the mid to high troposphere. This is consistent with the large number of assimilated SEVIRI radiances. HIRS and AMSU-B WV data would provide more information if SEVIRI data were not assimilated and if ATOVS data were used with a higher density. However, using ATOVS data with a higher horizontal resolution makes the analyses more dependent on these data, and it does not appear to be beneficial in this particular context, probably because of a non-optimal bias correction. In that case however, the individual impact of each pixel decreases because of the horizontal correlation lengths of the structure functions. Forecast scores and predicted precipitation patterns display the positive impact of SEVIRI data.

Vertical distribution and optical properties of aerosols observed over Japan during the Atmospheric Brown Clouds–East Asia Regional Experiment 2005

Abstract: [1] Lidar and sky radiometer systems at Sapporo, Toyama, and Nagasaki, Japan, observed the vertical distributions and optical properties of (nonspherical) dust and spherical aerosol particles from March to May 2005 as part of the Atmospheric Brown Clouds–East Asia Regional Experiment 2005 (ABC-EAREX2005). Sky radiometer observations suggest that single scattering albedo at Nagasaki was smaller than that at Toyama and Sapporo. Relationships between the single scattering albedo and Angstrom exponent suggest that aerosol particles observed at Toyama in March differed from those observed in April and May. In contrast, at Nagasaki, there was no obvious difference in aerosol particles among the 3 months. Aerosol optical thicknesses observed by the sky radiometer resemble the aerosol optical thicknesses observed by lidar and simulated by the Chemical Weather Forecasting System (CFORS) model. A new parameter that describes the aerosol vertical distribution, Hm, is the modified scale height of the extinction coefficient. Hm can be used as an index of the vertical aerosol extent even if the detailed structure of the vertical profile cannot be shown. Hm observed by lidar was consistent with Hm simulated by the CFORS. Relationships between the aerosol optical thickness and Hm obtained by lidar measurements and CFORS simulations suggest that dust aerosol particles are generally transported over Japan at higher altitudes than are spherical aerosol particles.

Modeling Sun Glitter at L-Band for Sea Surface Salinity Remote Sensing With SMOS

Abstract: Since the sun is an extremely strong radiation source at L-band, accounting for sun glint over the ocean, i.e., solar radiation reflected by the sea surface toward downward-looking radiometers, raises a significant challenge for the remote sensing of sea surface salinity. This paper describes a dedicated physical model for sun glint at L-band frequencies and provides quantitative and qualitative estimates of the sun glint contamination impinging the antenna of the Microwave Imaging Radiometer with Aperture Synthesis interferometer onboard the future European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. The sun brightness temperature expected during the mission period is first estimated from past solar flux data with an expected range of to about . Numerical simulations of the predicted illumination of the SMOS antenna by solar radiation scattered by the rough sea surface are then performed at key dates of the seasonal cycle using different asymptotic scattering models and several representative surface conditions. Although the center of the sun's glitter pattern will never be located within the useful part of SMOS' synthesized field of view, the expected contamination due to roughness scattering will range between 0 K and about 500 K, depending on the target position, the season period, the roughness state at the target, and the level of solar activity at the time of measurements. In particular, we find the sun glint contamination to be more intense when SMOS will probe ocean surfaces in the Southern Hemisphere, reaching maxima in descending passes with highest values expected at dates around winter solstices.

Development of a Chinese land data assimilation system: its progress and prospects

Abstract: The Objective of land data assimilation is to merge multi-source observations into the dynamics of land surface model for improving the estimation of land surface states. We have developed a land data assimilation system for China's land territory. In this system, the Common Land Model and Simple Biosphere Model 2 are used to simulate land surface processes. The radiative transfer models of thawed and frozen soil, snow, lake, and vegetations are used as observation operators to transfer model predictions into estimated brightness temperatures. A Monte-Carlo sequential filter, the ensemble Kalman filter, is implemented as data assimilation method to integrate modeling and observation. The system is capable of assimilating passive microwave remotely sensed data such as special sensor microwave imager (SSM I), TRMM microwave imager (TMI), and advanced microwave scanning radiometer enhanced for EOS (AMSRE) and the conventional in situ measurements of soil and snow. A spatiotemporally consistent assim...