Calculation Of Brightness Temperature Research Articles

Brightness temperature calculation of corner reflector on the sea surface and analysis of its jamming on ship recognition in passive millimetre-wave

Corner reflector, as a passive jammer, can generate a large radar cross section (RCS) to interfere with radar for target recognition. However, the impact of corner reflectors on passive millimetre-wave (PMMW) recognition is unclear. In this paper, based on ray tracing, the brightness temperature (TB) of corner reflectors is calculated. Ray tracing paths are used to analyze the impact of the sky, sea surface, and sun on the TB of corner reflectors. The antenna temperature of corner reflectors and their array at different distances is simulated and compared with that of a metal ship to evaluate their jamming performance. Four series of experiments measuring the antenna temperature of corner reflectors and the ship are conducted to verify the jamming performance. The results indicate that the contrast of corner reflectors is much smaller than that of ship target, causing little jamming for PMMW recognition.

Uncertainty in simulated brightness temperature due to sensitivity to atmospheric gas spectroscopic parameters from the centimeter- to submillimeter-wave range

Abstract. Atmospheric radiative transfer models are extensively used in Earth observation to simulate radiative processes occurring in the atmosphere and to provide both upwelling and downwelling synthetic brightness temperatures for ground-based, airborne, and satellite radiometric sensors. For a meaningful comparison between simulated and observed radiances, it is crucial to characterize the uncertainty in such models. The purpose of this work is to quantify the uncertainty in radiative transfer models due to uncertainty in the associated spectroscopic parameters and to compute simulated brightness temperature uncertainties for millimeter- and submillimeter-wave channels of downward-looking satellite radiometric sensors (MicroWave Imager, MWI; Ice Cloud Imager, ICI; MicroWave Sounder, MWS; and Advanced Technology Microwave Sounder, ATMS) as well as upward-looking airborne radiometers (International Submillimetre Airborne Radiometer, ISMAR, and Microwave Airborne Radiometer Scanning System, MARSS). The approach adopted here is firstly to study the sensitivity of brightness temperature calculations to each spectroscopic parameter separately, then to identify the dominant parameters and investigate their uncertainty covariance, and finally to compute the total brightness temperature uncertainty due to the full uncertainty covariance matrix for the identified set of relevant spectroscopic parameters. The approach is applied to a recent version of the Millimeter-wave Propagation Model, taking into account water vapor, oxygen, and ozone spectroscopic parameters, though the approach is general and can be applied to any radiative transfer code. A set of 135 spectroscopic parameters were identified as dominant for the uncertainty in simulated brightness temperatures (26 for water vapor, 109 for oxygen, none for ozone). The uncertainty in simulated brightness temperatures is computed for six climatology conditions (ranging from sub-Arctic winter to tropical) and all instrument channels. Uncertainty is found to be up to few kelvins [K] in the millimeter-wave range, whereas it is considerably lower in the submillimeter-wave range (less than 1 K).

Satellite‐Synoptic Monitoring of Dominant Dust Entering Western Iran

Dust storm in Iran’s western regions has been one of its major environmental problems in recent years, which has not only turned into a yearly phenomenon but is also expanding. This study investigated two events of dominant dust in southwestern Iran using moderate resolution imaging spectroradiometer imagery, Reanalysis Datasets (meteorological fields and atmospheric compositions), in both hot (July 2, 2008) and cold (February 18, 2017) seasons. After radiometric correction and calculation of brightness temperature as well as the reflective and thermal behavior of dust, the research results showed that the detection of dominant dust entering was 0.645 μm (visible red) and 0.858 μm (near‐infrared) in the reflective ranges and 3.959, 8.55, 11.03, and 12.02 µm in the thermal ranges. Synoptically, the lower values for mean sea level pressure from the east Mediterranean along Syria and Iraq to the southwest and Central Asia facilitate a convergence condition in the lower troposphere that induces strong northwesterlies, Shamal winds, over the Middle East toward the Persian Gulf, forming a more expansive aerosol hotspot over southwest Iran. However, on a cold day, high dust events in Arabia and south Iran are related to the ongoing high pressure, which is accompanied by a subtropical jet, following anticyclonic circulation toward southwestern Iran.

Identification of Urban Heat Islands &Its Relationship withVegetation Cover: A Case Study of Colombo & Gampaha Districts in Sri Lanka

Global Warming is a major environmental problem that all kind of organisms has been affected at present. Urban Heat Island (UHI) is one of primary impacts of Global Warming. UHI is a phenomenon that the temperature of urban area is higher than surrounding rural areas or suburban areas. This increasing trend of temperature in urban areas affects many environmental entities such as air quality, water resources, habitats behaviors and climate changes. The most remarkable incident that relate with UHI is the difference of thermal properties of the surfaces. Many countries experience the consequences of Urban Heat Islands in many aspects such as economic, health, social and environmental affects. Thus to mitigate such impacts of UHI, it is very important to identify the main reasons behind this. In this paper UHIs in Colombo, Gampaha Districts and the relationship between UHI and vegetation cover were analyzed based on Landsat 8, 30m resolution data. Land Surface Temperature was derived from Landsat thermal Infrared band through several equations of United State Geological Survay (USGS) guidelines using Arc GIS 10. Conversion of Digital Number (DN) values to Top of Atmosphere (TOA) Radiance, Conversion of TOA Radiance to Satellite Brightness temperature and final calculation of Land Surface Temperature considering land surface emissivity are the steps that had been done for the analysis. Vegetation cover was derived by using vegetation index with the Red and Near Infra Red bands. The result shows that the land high surface temperature directly relates with the urbanized regions where vegetation cover is very less. High temperature difference could be identified that cause to arise the urban heat island effects in Colombo & Gampaha districts. There is a strong linearly negative correlation with correlation coefficient value of -0.742 between land surface temperature and vegetation cover. 78.8 km2 (including water) of total area had been identified as NDVI value less than 0.1. And extent of high temperature area was 74.12 km2 where temperature more than 27oC at 10.22am. The area in temperature range of 25-27 was 464.95km2 and area in NDVI value range 0.1-0.2 was 333.04 km2. 1471.1 km2 was identified as NDVI value between 0.3-0.4 and the area at low temperature was 1529 km2where temperature less than 25oC. According to this results, high temperature at non-vegetated areas and low temperature at vegetated areas could be noted very clearly. This is probably due to the ecological function of vegetation that lay down the surface temperature from high evapotranspiration. Vegetated areas are mostly sensed with surface temperature.Thus research output can be useful for policy-makers and planners of development projects such as Western province Megapolis project as well as for general public to understand the urban heat island effects and importance of vegetation cover to mitigate such impacts.

A Dielectric Mixing Model Accounting for Soil Organic Matter

Core Ideas In the proposed model, the wilting point and porosity are a function of organic matter. In organic‐rich soil, the model improves accuracy of the microwave radiative transfer model. The model is applicable for both portable and satellite soil moisture sensors. Most dielectric mixing models have been developed for mineral soils without extensive consideration of organic matter (OM). In addition, when used for in situ measurement, most of these models focus only on the real part of the effective dielectric constant without the corresponding imaginary part. Organic matter fractions in soils are found globally (57%), with an especially significant amount in the boreal region (17%). Without proper consideration of OM in dielectric mixing models and subsequent microwave radiative transfer modeling, brightness temperature (TB) calculations may be erroneous. This would lead to uncertainties in the estimation of higher level products, such as soil moisture retrievals from portable soil moisture sensors (e.g., time‐domain reflectometers) or passive microwave sensors onboard the Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Advanced Microwave Scanning Radiometer (AMSR2) satellites. We incorporated OM into a dielectric mixing model by adjusting the wilting point and porosity according to the OM content, i.e., the effective soil dielectric constant decreases with higher OM due to a decrease in the fraction of free water and an increase in bound water. With the proposed soil parameters in the dielectric mixing model, high levels of OM increase the TB for a specific soil moisture by decreasing the microwave effective dielectric constant. The simulated TB better reproduced SMAP‐observed TB (11% in RMSE) through the improvement of the effective dielectric constant (40% reduction in RMSE). We anticipate that the application of our approach can improve microwave‐based surface soil moisture retrievals in areas with high OM.

Brightness Temperature Calculation and Uncertainty Propagation for Conical Microwave Blackbody Targets

We discuss the analytical derivation of the absolute brightness temperature uncertainty of a hollow conical blackbody source for radiometer calibration. We introduce a Monte Carlo uncertainty propagation analysis method to quantify uncertainty contributions from nonideal emissivity, physical temperature, and antenna pattern, which are the three major factors contributing to the uncertainty of the brightness temperature radiation from the source. The low reflectance of the hollow conical geometry depends on multiple bounces on the absorber surface. To quantify total brightness temperature over a nonuniform temperature surface, each individual bounce must be considered. We derive a recursive analytical relationship to quantify this multiple-bounce effect as a function of a view angle. The resulting effective blackbody brightness temperature uncertainty is a function of frequency, temperature, antenna pattern, measurement distance, and the measurement environment. We also propagate the uncertainty to the antenna flange of a radiometer viewing the conical blackbody. This includes additional effects, such as spillover, illumination efficiency, and antenna efficiency. We demonstrate the propagation method with an example case. We use fictional input values to investigate the response of the uncertainty to input variables and distance. We find that as the distance between antenna and blackbody increases, the uncertainty due to spillover dominates, but at close distances, the dominant uncertainty contributor is linked to the physical temperature of the absorber.

Identification of Relationship between Urban Heat Islands & Vegetation Cover through Landsat 8: A Case Study of Colombo & Gampaha Districts in Sri Lanka

Global Warming is a major environmental problem that all kind of organisms has been affected at present. Urban Heat Island (UHI) is one of primary impacts of Global Warming. UHI is a phenomenon that the temperature of urban area is higher than surrounding rural areas or suburban areas. This increasing trend of temperature in urban areas affects many environmental entities such as air quality, water resources, habitats behaviors, climate changes. The most remarkable incident that relate with UHI, is the difference of thermal properties of the surfaces. Many countries experience the consequences of Urban Heat Islands in many aspects such as economic, health, social and environmental affects. Thus to mitigate such impacts of UHI, it is very important to identify the main reasons behind this. In this paper UHIs in Colombo, Gampaha Districts and the relationship between UHI and vegetation cover were analyzed based on Landsat 8, 30 m resolution data. Land Surface Temperature was derived from Landsat thermal Infrared band through several equations of United State Geological Surfay (USGS) guidelines using Arc GIS 10. Conversion of Digital Number (DN) values to Top of Atmosphere (TOA) Radiance, Conversion of TOA Radiance to Satellite Brightness temperature and final calculation of Land Surface Temperature considering land surface emissivity are the steps that had been done for the analysis. Vegetation cover was derived by using vegetation index with the Red and Near Infra Red bands. The result shows that the land high surface temperature directly relates with the urbanized regions where vegetation cover is very less. High temperature difference could be identified that cause to arise the urban heat island effects in Colombo & Gampaha districts. There is a strong linearly negative correlation with correlation coefficient value of -0.742 between land surface temperature and vegetation cover. 78.8 km2 (including water) of total area had been identified as NDVI value less than 0.1. And extent of high temperature area was 74.12 km2 where temperature more than 27˚C at 10.22 am. The area in temperature range of 25-27 was 464.95 km2 and area in NDVI value range 0.1-0.2 was 333.04 km2. 1471.1 km2 was identified as NDVI value between 0.3-0.4 and the area at low temperature was 1529 km2 where temperature less than 25˚C. According to this results, high temperature at non-vegetated areas and low temperature at vegetated areas could be noted very clearly. This is probably due to the ecological function of vegetation that lay down the surface temperature from high evapotranspiration. Vegetated areas are mostly sensed with surface temperature. Thus research output can be useful for policy-makers and planners of development projects such as Western province Megapolis project as well as for general public to understand the urban heat island effects and importance of vegetation cover to mitigate such impacts. Keywords: Urban heat island, Vegetation, NDVI, Arc GIS, Landsat, Sri Lanka

Effective surface areas for optimal correlations between surface brightness and air temperatures in an urban environment

We perform correlation analysis between air temperature and surface brightness temperature over the Adelaide Central Business District and the surrounding parklands. The results indicate that three effective surface areas associated with three different mechanisms exist. They are the effective surface area with upward sensible heat transfer to heat up and maintain the air temperature, the effective surface area with downward sensible heat transfer to cool down the air, and the effective surface area related to very localized conditions (e.g., sky-view factors). The three mechanisms occur at different times of the day and result in different air temperature and surface temperature correlations. The first effective surface area exists in the daytime after the surface is heated up by solar radiation and can persist into the night, particularly in urban environments. The second effective area occurs in night-time when the surface has been cooled down sufficiently. The third effective area coexists with the second one and has a weaker correlation between the surface and air temperatures. It was also found that in an urban area, exclusion of roof pixels in the calculation of surface brightness temperature can increase the correlation between the surface and air temperatures in the middle of the night.

Brightness Temperature Calculation of Lunar Crater: Interpretation of Topographic Effect on Microwave Data From Chang'E

In order to quantitatively interpret topographic effect on Chang'E (CE) microwave data, a detailed method to compute brightness temperature (TB) over a lunar crater is proposed, which incorporated the effect of surface tilts. The method improves the effective solar irradiance model of the lunar surface to obtain the temperature profile of the lunar crater. The calculated TB at 37 GHz with the proposed computation method, which is based on three digital elevation models (DEMs) from different sources, are consistent with the observed TB from the CE-2 microwave radiometer. The simulated behavior of TB across crater Hercules reproduces the TB undulation observed by CE in a single swath. TB is significantly affected by the lunar dust of a lunar crater and affected by albedo and emissivity in a lesser degree. Based on the explanation with simplified models, the TB variation over a crater is proved to be significantly affected, through physical temperature, by the crater shape described by DEMs. With the simplified crater model, the amplitude of the TB oscillatory curves is proved to depend on the crater shape.

An improvement in fast radiative transfer calculation of FengYun satellite by Planck weighting correction

A unified regression method to calculate fast transmittance coefficients is used in fast radiative transfer calculation of satellite infrared channel by a convoluted transmittances database from LBL (Line_By_Line) model. Comparison is performed between the fast calculated brightness temperature and LBL calculations for VISSR/FY-2F and IRAS/FY-3B. The examination indicates that STD (Standard Deviation) of fast calculated brightness temperature in window channels are much larger than the values in sounding channels. The lower atmosphere the channel detects, the larger the STD is available. And the largest the STD is less than 0.4 K. In this paper, a discussion is given to the improvement of fast radiative transfer calculation brought about by Planck weighted correction for convoluted channels' transmittances. Analysis shows that overlap between 2350 cm-1 and spectral response filter of the channel is a requirement to the Planck weighted correction. It is shown that STDs of brightness temperature between LBL calculation and fast computation are decreased by 25% after Planck weighted correction. And the improvement is available only for such channels with an overlap between their filter function and 2350 cm-1. Also it is indicated that the improvement from Planck weighted correction could be used not only to the imaging channels that have wide spectral coverage, but also to the sounding channels with very narrow spectral fields.

Sensor-based clear and cloud radiance calculations in the community radiative transfer model

The community radiative transfer model (CRTM) has been implemented for clear and cloudy satellite radiance simulations in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation data assimilation system for global and regional forecasting as well as reanalysis for climate studies. Clear-sky satellite radiances are successfully assimilated, while cloudy radiances need to be assimilated for improving precipitation and severe weather forecasting. However, cloud radiance calculations are much slower than the calculations for clear-sky radiance, and exceed our computational capacity for weather forecasting. In order to make cloud radiance assimilation affordable, cloud optical parameters at the band central wavelength are used in the CRTM (OPTRAN-CRTM) where the optical transmittance (OPTRAN) band model is applied. The approximation implies that only one radiative transfer solution for each band (i.e., channel) is needed, instead of typically more than 10,000 solutions that are required for a detailed line-by-line radiative transfer model (LBLRTM). This paper investigated the accuracy of the approximation and helps us to understand the error source. Two NOAA operational sensors, High Resolution Infrared Radiation Sounder/3 (HIRS/3) and Advanced Microwave Sounding Unit (AMSU), have been chosen for this investigation with both clear and cloudy cases. By comparing the CRTM cloud radiance calculations with the LBLRTM simulations, we found that the CRTM cloud radiance model can achieve accuracy better than 0.4 K for the IR sensor and 0.1 K for the microwave sensor. The results suggest that the CRTM cloud radiance calculations may be adequate to the operational satellite radiance assimilation for numerical forecast model. The accuracy using OPTRAN is much better than using the scaling method (SCALING-CRTM). In clear-sky applications, the scaling of the optical depth derived at nadir for brightness temperature calculation at the other direction may result in an error up to about 7 K for some HIRS/3 channels. Under cloudy conditions, SCALING-CRTM may result in an error of about 3.5 K.

A high‐performance approach for brightness temperature inversion

Brightness temperature inversion is one of the most essential tasks in satellite remote sensing data processing. Accurate calculation of brightness temperature is crucial for many remote sensing applications, such as land surface temperature retrieval, sea surface temperature retrieval, and active fire detection. Due to the huge amount of remote sensing data, performance is also very important for operational use. Major current approaches for brightness temperature inversion are iteration methods, Look‐Up‐Table (LUT) methods, and empirical formula methods. Some of these algorithms can invert brightness temperature efficiently with limited accuracy, while others can invert brightness temperature at high accuracy but have lower performance. It is desirable to develop an algorithm that can make the balance of accuracy and performance more flexible and can invert brightness temperature efficiently even at high accuracy. In this paper, we analyse the advantages and limitations of the current algorithms for brightness temperature inversion, and propose a new approach based on the high‐order approximation of the relationship between band‐averaged radiance and brightness temperature. Our approach has the advantages of high accuracy and flexibility. It can be vectorized easily to exploit the advanced features of current computing platforms and improve performance in operational data processing. For validation and analysis, we have applied this method to brightness temperature inversion of MODIS thermal infrared (TIR) measurements and compared with other algorithms for accuracy and performance. The results demonstrate that our approach can be used for operational data processing more flexibly and efficiently.

The Physical Nature of Polar Broad Absorption Line Quasars

It has been shown based on radio variability arguments that some BALQSOs (broad absorption line quasars) are viewed along the polar axis (o rthogonal to accretion disk) in the recent article of Zhou et a. Thes e arguments are based on the brightness temperature, T(sub b) exceedi ng 10(exp 12) K which leads to the well-known inverse Compton catastr ophe unless the radio jet is relativistic and is viewed along its axi s. In this letter, we expand the Zhou et al sample of polar BALQSOs u sing their techniques applied to SDSS DR5. In the process, we clarify a mistake in their calculation of brightness temperature. The expanded sample of high T(sub b) BALQSOS, has an inordinately large fraction of LoBALQSOs (low ionization BALQSOs). We consider this an important clue to understanding the nature of the polar BALQSOs. This is expec ted in the polar BALQSO analytical/numerical models of Punsly that pr edicted that LoBALQSOs occur when the line of sight is very close to the polar axis, where the outflow density is the highest.

Combined Henyey-Greenstein and Rayleigh phase function

The phase function is an important parameter that affects the distribution of scattered radiation. In Rayleigh scattering, a scatterer is approximated by a dipole, and its phase function is analytically related to the scattering angle. For the Henyey-Greenstein (HG) approximation, the phase function preserves only the correct asymmetry factor (i.e., the first moment), which is essentially important for anisotropic scattering. When the HG function is applied to small particles, it produces a significant error in radiance. In addition, the HG function is applied only for an intensity radiative transfer. We develop a combined HG and Rayleigh (HG-Rayleigh) phase function. The HG phase function plays the role of modulator extending the application of the Rayleigh phase function for small asymmetry scattering. The HG-Rayleigh phase function guarantees the correct asymmetry factor and is valid for a polarization radiative transfer. It approaches the Rayleigh phase function for small particles. Thus the HG-Rayleigh phase function has wider applications for both intensity and polarimetric radiative transfers. For microwave radiative transfer modeling in this study, the largest errors in the brightness temperature calculations for weak asymmetry scattering are generally below 0.02 K by using the HG-Rayleigh phase function. The errors can be much larger, in the 1-3 K range, if the Rayleigh and HG functions are applied separately.

Intercomparison of millimeter-wave radiative transfer models

This study analyzes the performance at millimeter-wave frequencies of five radiative transfer models, i.e., the Eddington second-order approximation with and without /spl delta/-scaling, the Neumann iterative method with and without geometric series approximation, and the Monte Carlo method. Three winter time precipitation profiles are employed. The brightness temperatures calculated by the Monte Carlo method, which considers all scattering angles, are considered as benchmarks in this study. Brightness temperature differences generated by the other models and sources of those differences are examined. In addition, computation speeds of the radiative transfer calculations are also compared. Results show that the required number of quadrature angles to generate brightness temperatures consistent with the Monte Carlo method within 0.5 K varies between two and six. At least second to 15th orders of multiple scattering, depending on the significance of scattering, are required for the Neumann iterative method to represent accurately the inhomogeneous vertical structure of the scattering and absorbing components of precipitating clouds at millimeter-wave frequencies. The /spl delta/-scaling in the Eddington second-order approximation improves brightness temperatures significantly at nadir for cloud profiles that contain snow due to the correction for strong scattering, while it did not make any difference at 53/spl deg/ off-nadir. The computational time comparisons show that the Neumann iterative method generates accurate brightness temperatures with better computational efficiency than the Monte Carlo method for cloud profiles with weak scattering. However, it can consume computational time that is even greater than the Monte Carlo method for some millimeter-wave frequencies and cloud profiles with strong scattering. A geometric series approximation can improve computational efficiency of the Neumann iterative method for those profiles. In view of the ease of introducing scaled parameters into the Eddington second-order approximation, good computational time efficiency, and better than within 2 K accuracy when compared with the Monte Carlo method, we recommend its use for brightness temperature calculations at millimeter-waves in precipitating atmospheres.

Accuracy of ground-based microwave radiometer and balloon-borne measurements during the WVIOP2000 field experiment

We discuss the performances of a set of four microwave water vapor radiometers operating in the 20-30-GHz band during a field experiment, with an emphasis on calibration and achievable accuracy. The field experiment was conducted at the Department of Energy's Atmospheric Radiation Measurement Program's field site in north central Oklahoma, and was focused on clear-sky water vapor measurements by both radiometers and radiosondes. A comparison between two published radiometric tip curve calibration procedures is presented, and these procedures are applied to measurements from two nearly identical instruments placed a few meters apart. Using the instantaneous tip cal method of the Environmental Technology Laboratory, the brightness temperature measurements for the two identical instruments differed by less than 0.2 K over a 24-h period. Results from reference load cryogenic tests and brightness temperature cross comparisons have shown differences within 0.7 K. In addition, we compare radiometric measurements with calculations of brightness temperature based on the Rosenkranz absorption model and radiosonde observations. During the experiment, both Vaisala-type RS80 and RS90 humidity sensors were used. Our comparisons demonstrate the improvements achieved by the new Vaisala RS90 sensors in atmospheric humidity profiling, which reduce or eliminate the "dry bias" problem.

Effects of raindrop size distribution variations on microwave brightness temperature calculation

Many current passive‐microwave rain‐retrieval methods are based on databases built off‐line using cloud models: the models are used to simulate rain events, and radiative transfer calculations produce the associated brightness temperatures. The radiative transfer models depend on, among others, the distribution of hydrometeor sizes. The most popular raindrop size distribution (DSD) used in most models is Marshall and Palmer's [1948]. Improvements were proposed later by Sekhon and Srivastava [1971], Willis and Tattelman [1989], and Feingold and Levin [1986]. Using these DSD models, we study the dependence of forward radiative transfer calculations on the hydrometeor size distribution and quantify the uncertainty due to DSD variability.

Sampling strategies for the comparison of climate model calculated and satellite observed brightness temperatures

Brightness temperatures derived from polar‐orbiting satellites are valuable for the evaluation of global climate models. However, the effect of orbital constraints must be taken into account to ensure valid comparisons. As part of the Atmospheric Model Intercomparison Project II climate model comparisons, this study seeks to evaluate the monthly mean simulated brightness temperature differences of possible model output sampling strategies with respect to the exact satellite sampling and whether they can be practically implemented to provide meaningful comparisons with these satellite observations. We compare various sampling strategies with a proxy satellite data set constructed from model output and actual TIROS operational vertical sounder orbital trajectories, rather than with the observations themselves. To a large extent, this enables isolation of the sampling error from errors caused by deficiencies in the modeled climate processes. Our results suggest that the traditional method of calculating brightness temperatures from monthly mean temperature and moisture profiles yields biases from both nonlinear effects and the removal of the diurnal cycle that may be unacceptable in many applications. However, we also find that a brightness temperature calculation every hour of the simulation provides substantially lower sampling biases provided that there are two or more properly aligned satellites. This is encouraging because it means that for many applications modelers need not accurately mimic actual satellite trajectories in the sampling of their simulations. If only one satellite is available for comparison with simulations, more sophisticated sampling seems necessary. For such circumstances, we introduce a simple procedure that serves as a useful approximation to the rather complex procedure required to sample a model exactly as a polar‐orbiting satellite does the Earth. With all sampling methods, removal of biases associated with cloud cover is problematic and deserves further study.

Upper tropospheric humidity observations from Meteosat compared with short‐term forecast fields

Monthly mean brightness temperature observations from the water vapor channel (WV: 5.7–7.1 μ m) aboard the geostationary weather satellite METEOSAT‐4 are presented for July 1992. The WV channel is sensitive to the atmospheric column water vapor in the upper troposphere above 600 to 500 hPa. The WV channel has been recalibrated with a radiative transfer model using quality controlled radiosondes. The observations are compared with brightness temperature calculations based on short‐term forecast fields (12 and 24 h) of the general circulation model of the European Centre for Medium Range Weather Forecasts (ECMWF). While the model humidity field closely resembles the observed large‐scale distribution it is too moist in the subtropics and slightly too dry in areas associated with the Inter Tropical Convergence Zone (ITCZ). A simple method is suggested that quantifies the moisture bias in the general circulation model by adjusting the model based brightness temperatures.

A Passive Microwave Technique for Estimating Rainfall and Vertical Structure Information from Space. Part I: Algorithm Description

This paper describes a multichannel physical approach for retrieving rainfall and vertical structure information from satellite-based passive microwave observations. The algorithm makes use of statistical inversion techniques based upon theoretically calculated relations between rainfall rates and brightness temperatures. Potential errors introduced into the theoretical calculations by the unknown vertical distribution of hydrometeors are overcome by explicitly accounting for diverse hydrometcor profiles. This is accomplished by allowing for a number of different vertical distributions in the theoretical brightness temperature calculations and requiring consistency between the observed and calculated brightness temperatures. This paper will focus primarily on the theoretical aspects of the retrieval algorithm, which includes a procedure used to account for inhomogeneities of the rainfall within the satellite field of view as well as a detailed description of the algorithm as it is applied over both ocean and land surfaces. The residual error between observed and calculated brightness temperatures is found to be an important quantity in assessing the uniqueness of the solution. At is further found that the residual error is a meaningful quantity that can be used to derive expected accuracies from this retrieval technique. Examples comparing the retrieved results as well as the detailed analysis of the algorithm performance under various circumstances are the subject of a companion paper.