Integrated Cloud Liquid Water Research Articles

Remote sensing of integrated cloud liquid water: Development of algorithms and quality control

Algorithms are developed to infer integrated cloud liquid water path (LWP) over the oceans from spaceborne and ground‐based passive microwave measurements. These algorithms are built from simulated observations, which are calculated with a radiative transfer model applied to a set of about 10,000 atmospheric profiles obtained from the European Centre for Medium‐Range Weather Forecasts forecast model. In this model the liquid water content is computed from a prognostic cloud scheme. A multilinear regression is applied to functions of simulated brightness temperatures (log linear form) and LWP to derive the algorithm coefficients. The retrieval accuracy based on the regression analysis including instrumental noise is 0.0257 and 0.0345 kg m−2 for the DMSP special sensor microwave imager (SSM/I) and the ERSl along‐track scanning radiometer/microwave (ATSR/M), respectively, and 0.0308 kg m−2 for the ground‐based radiometer. It is shown that the log linear form is adequate to transform the nonlinear problem into a quasi‐linear problem for LWP below 0.8 kg m−2. The coherence of the global approach is verified through the validation of total precipitable water (TPW) algorithms developed in a way similar to LWP algorithms. The LWP retrievals from the algorithm for the ground‐based radiometer are in good agreement with retrievals from airborne measurements performed in the vicinity of the radiometer. A coherence test is performed for ATSR/M, benefiting from the coincident infrared images obtained from an infrared radiometer (ATSR/IR) aboard the same platform to select clear‐air areas. Regardless of the slight mean bias of the inferred LWP due to inaccurate calibration, there is no anomalous dependency upon latitude, i.e., upon high water vapor contents in the tropics and strong winds in the high latitudes. The results of the algorithm for SSM/I are compared with a Meteosat cloud classification. When the classification detects the ocean surface, the algorithm systematically retrieves contents close to zero. The retrievals for other classes (i.e., low stratiform clouds, medium clouds) are consistent with the Meteosat data; retrievals in the presence of low stratiform clouds appear more realistic than values provided by some already published algorithms. It is also shown that up to 0.8 kg m−2 the log linear regression approach has a quality of the same order as a variational method, which requires much more computation time.

Microphysical retrievals over stratiform rain using measurements from an airborne dual-wavelength radar-radiometer

The need to understand the complementarity of the radar and radiometer is important not only to the Tropical Rain Measuring Mission (TRMM) program but to a growing number of multi-instrumented airborne experiment that combine single or dual-frequency radars with multichannel radiometers. The method of analysis used in this study begins with the derivation of dual-wavelength radar equations for the estimation of a two-parameter drop size distribution (DSD). Defining a as the set of parameters that characterize snow density, cloud water, water vapor, and features of the melting layer, then to each storm model there will usually correspond a set of range-profiled drop size distributions that are approximate solutions of the radar equations. To test these solutions, a radiative transfer model is used to compute the brightness temperatures for the radiometric frequencies of interest. A storm model or class of storm models is considered optimum if it provides the best reproduction of the radar and radiometer measurements. Tests of the method are made for stratiform rain using simulated storm models as well as measured airborne data. Preliminary results show that the best correspondence between the measured and estimated radar profiles usually can be obtained by using a moderate snow density (0.1-0.2 g/cm/sup -3/), the Maxwell-Garnett mixing formula for partially melted hydrometeors (water matrix with snow inclusions), and low to moderate values of the integrated cloud liquid water (less than 1 kg/m/sup -/2). The storm-model parameters that yield the best reproductions of the measured radar reflectivity factors also provide brightness temperatures at 10 GHz that agree well with the measurements. On the other hand, the correspondence between the measured and modeled values usually worsens in going to the higher frequency channels at 19 and 34 GHz. In searching for possible reasons for the discrepancies, it is found that changes in the DSD parameter /spl mu/, the radar constants, or the path-integrated attenuation can affect the high frequency channels significantly. In particular, parameters that cause only modest increases in the median mass diameter of the snow, and which have a minor effect on the radar returns or the low frequency brightness temperature, can produce a strong cooling of the 31 GHz brightness temperature.

Climatological “models”; of cold air mesocyclones derived from SSM/I data

A major limitation of satellite infrared data used to detect mesocyclones occurring in cold airstreams over datavoid oceanic regions is the inability to document the basic structure of these systems. In this research we use the integrated water vapor (IWV), integrated cloud liquid water (ICLW), precipitation, and surface wind speed information retrieved from the SSM/I (Special Sensor Microwave/Imager) of the DMSP (Defense Meteorological Satellite Program) platform to develop climatological (statistical mean) “models”; of mesocyclone structure and evolution for the southern oceans. Composite analysis of sea level pressures and 500 hPa heights shows that mesocyclones frequently develop in the region between strong synoptic‐scale pressure and height anomalies, and over positive differences in sea‐air temperature. Climatological “models”; (statistical means, standard deviations) of marine atmospheric variables retrieved from the SSM/I indicate that mesocyclones have associated strong horizontal wind shear: highest wind speeds occur in the northwest quadrant and lowest wind speeds in the southeast quadrant of these storms. The composite IWV ranges from low to moderate values (5–15 kg m‐2) that increase from south to north within mesocyclones. Solid precipitation seems to dominate over rain in most of these systems. An estimate of the surface sensible heat flux for one mesocyclone outbreak suggests that surface energy plays an important role in mesoscale cyclogenesis over the oceans.

Effect of Rain on Ground-Based Microwave Radiometric Measurements in the 20–90-GHz Range

A discrete-ordinate radiative transfer algorithm for a multilayered plane-parallel atmosphere was used to evaluate the effect of raindrops on ground-based vertically pointing radiometric measurements in the 20-90- GHz range. The effect of rainfall rate and drop size distribution, the length of the rain column, the scattering phase function, and cloud liquid water content are examined. Errors in the estimation of columnar integrated vapor and liquid water are evaluated as functions of rainfall rate, length of rain column, and integrated cloud liquid water. Brightness temperatures calculated by the model, using a measured atmospheric state and measured raindrop size distributions, agreed with radiometric measurements at 20, 31, and 52 GHz with a standard error of estimate of 4.1, 7.4, and 6.8 K, respectively. Variances of model brightness temperatures calculated using 1-min-average raindrop size distributions over 10-min periods were also correlated with measured brightness temperature variances.

Independent Pixel and Monte Carlo Estimates of Stratocumulus Albedo

Monte Carlo radiative transfer methods are employed here to estimate the plane-parallel albedo bias for marine stratocumulus clouds. This is the bias in estimates of the mesoscale-average albedo, which arises from the assumption that cloud liquid water is uniformly distributed. The authors compare such estimates with those based on a more realistic distribution generated from a fractal model of marine stratocumulus clouds belonging to the class of 'bounded cascade' models. In this model the cloud top and base are fixed, so that all variations in cloud shape are ignored. The model generates random variations in liquid water along a single horizontal direction, forming fractal cloud streets while conserving the total liquid water in the cloud field. The model reproduces the mean, variance, and skewness of the vertically integrated cloud liquid water, as well as its observed wavenumber spectrum, which is approximately a power law. The Monte Carlo method keeps track of the three-dimensional paths solar photons take through the cloud field, using a vectorized implementation of a direct technique. The simplifications in the cloud field studied here allow the computations to be accelerated. The Monte Carlo results are compared to those of the independent pixel approximation, which neglects net horizontal photon transport. Differences between the Monte Carlo and independent pixel estimates of the mesoscale-average albedo are on the order of 1% for conservative scattering, while the plane-parallel bias itself is an order of magnitude larger. As cloud absorption increases, the independent pixel approximation agrees even more closely with the Monte Carlo estimates. This result holds for a wide range of sun angles and aspect ratios. Thus, horizontal photon transport can be safely neglected in estimates of the area-average flux for such cloud models. This result relies on the rapid falloff of the wavenumber spectrum of stratocumulus, which ensures that the smaller-scale variability, where the radiative transfer is more three-dimensional, contributes less to the plane-parallel albedo bias than the larger scales, which are more variable. The lack of significant three-dimensional effects also relies on the assumption of a relatively simple geometry. Even with these assumptions, the independent pixel approximation is accurate only for fluxes averaged over large horizontal areas, many photon mean free paths in diameter, and not for local radiance values, which depend strongly on the interaction between neighboring cloud elements.

Potential Applications of the SSM/I Cloud Liquid Water Parameter to the Estimation of Marine Aircraft Icing

Abstract Images of integrated cloud liquid water derived from the Special Sensor Microwave Imager (SSM/I) aboard the Defense Meteorological Satellite Program polar-orbiting satellite are presented. Examples with infrared and visible images and synoptic charts are shown for the Gulf of Alaska and Bering Sea for March 1992. The SSM/I images often show detailed, low-level cloud circulations not suggested by infrared satellite images. A prototype system for forecasting the potential for aircraft icing, which combines the SSM/I cloud liquid water parameter with numerical model output, is also presented. Where integrated cloud liquid water exceeds a specific threshold, an icing watch region is specified. The top of the icing watch layer is set to the model −20°C level or infrared cloud top, whichever is lower. The base of the icing watch layer is set to the 0°C level from model output. No watch areas are specified where the infrared cloud top temperature is above freezing, regardless of integrated cloud liquid ...

A physical retrieval of cloud liquid water over the global oceans using special sensor microwave/imager (SSM/I) observations

A method of remotely sensing integrated cloud liquid water over the oceans using spaceborne passive measurements from the special sensor microwave/imager (SSM/I) is described. The technique is comprised of a simple physical model that uses the 19.35‐ and 37‐GHz channels of the SSM/I. The most comprehensive validation to date of cloud liquid water estimated from satellites is presented. This is accomplished through a comparison to independent ground‐based microwave radiometer measurements of liquid water on San Nicolas Island, over the North Sea, and on Kwajalein and Saipan Islands in the western Pacific. In areas of marine stratocumulus clouds off the coast of California a further comparison is made to liquid water inferred from advanced very high resolution radiometer (AVHRR) visible reflectance measurements. The results are also compared qualitatively with near‐coincident satellite imagery and with other existing microwave methods in selected regions. These comparisons indicate that the liquid water amounts derived from the simple scheme are consistent with the ground‐based measurements for nonprecipitating cloud systems in the subtropics and middle to high latitudes. The comparison in the tropics, however, was less conclusive. Nevertheless, the retrieval method appears to have general applicability over most areas of the global oceans. An observational measure of the minimum uncertainty in the retrievals is determined in a limited number of known cloud‐free areas, where the liquid water amounts are found to have a low variability of 0.016 kg m−2. A simple sensitivity and error analysis suggests that the liquid water estimates have a theoretical relative error typically ranging from about 25% to near 40% depending on the atmospheric/surface conditions and on the amount of liquid water present in the cloud. For the global oceans as a whole the average cloud liquid water is determined to be about 0.08 kg m−2. The major conclusion of this paper is that reasonably accurate amounts of cloud liquid water can be retrieved from SSM/I observations for nonprecipitating cloud systems, particularly in areas of persistent stratocumulus clouds, with less accurate retrievals in tropical regions.

Satellite observations of a polar low over the Norwegian Sea by special sensor microwave imager, Geosat, and TIROS‐N operational vertical sounder

Many polar lows are generated at the boundary between sea ice and the ocean, in regions of large temperature gradients, where in situ observations are rare or nonexistent. Since satellite observations are frequent in high‐latitude regions, they can be used to detect polar lows and track their propagation and evolution. The Special Sensor Microwave/I mager (SSM/I) providing estimates of surface wind speed, integrated cloud liquid water content, water vapor content, and precipitation size ice‐scattering signal over the ocean; the Geosat radar altimeter measuring surface wind speed and significant wave height; and the TIROS‐N Operational Vertical Sounder (TOVS) allowing the determination of temperature and humidity profiles in the atmosphere have been used in synergy for a specific case which occurred in the Norwegian Sea on January, 23–24 1988. All three instruments show sharp atmospheric gradients associated with the propagation of this low across the ocean, which permit the detection of the polar low at a very early stage and tracking it during its development, propagation, and decay. The wind speed gradients are measured with good qualitative agreement between the altimeter and SSM/I. TOVS retrieved fields prior to the formation of the low confirm the presence of an upper level trough, while during the mature phase baroclinicty can be observed in the 1000–500 hPa geopotential thicknesses. Comparisons between satellite‐retrieved products and analyses of the operational Norwegian limited area model (150‐ and 50‐ km mesh) highlight the importance of satellites for the monitoring of such mesoscale phenomena.

Passive microwave remote sensing of cloud liquid water over land regions

Techniques for cloud liquid water retrieval over land are developed using data from the Special Sensor Microwave/Imager 85.5 GHz (3.5 mm) channels. To minimize the effect of surface emittance variability on the calculations, the surface emittance was estimated with the aid of surface skin temperature retrievals from the Visible Infrared Spin Scan Radiometer in geosynchronous orbit. The high sensitivity of the 85.5 GHz channels to cloud liquid water allows for the estimation of integrated cloud liquid water based on the microwave brightness temperature depression caused by attenuation and emission of microwave radiation at the colder ambient temperature of the cloud. The method assumes nonscattering radiative processes are dominant, therefore only nonprecipitating cloud liquid water is considered. Integrated cloud liquid water retrievals show good qualitative agreement with other available data sources. Numerical error sensitivity analysis show integrated cloud liquid water error estimates of 0.05–0.50 kg m−2 depending on the contrast of cloud over background.

An Eight-Month Sample of Marine Stratocumulus Cloud Fraction, Albedo, and Integrated Liquid Water

As part of the FIRE/Extended Time Observations (ETO) program, extended time observations were made at San Nicolas Island (SNI) from March to October, 1987. Hourly averages of air temperature, relative humidity, wind speed and direction, solar irradiance, and downward longwave irradiance were recorded. The radiation sensors were standard Eppley pyranometers (shortwave) and pyrgeometers (longwave). The SNI data were processed in several ways to deduce properties of the stratocumulus covered marine boundary layer (MBL). For example, from the temperature and humidity the lifting condensation level, which is an estimate of the height of the cloud bottom, can be computed. A combination of longwave irradiance statistics can be used to estimate fractional cloud cover. An analysis technique used to estimate the integrated cloud liquid water content (W) and the cloud albedo from the measured solar irradiance is also described. In this approach, the cloud transmittance is computed by dividing the irradiance measured at some time by a clear sky value obtained at the same hour on a cloudless day. From the transmittance and the zenith angle, values of cloud albedo and W are computed using the radiative transfer parameterizations of Stephens (1978). These analysis algorithms were evaluated with 17 days of simultaneous and colocated mm-wave (20.6 and 31.65 GHz) radiometer measurements of W and lidar ceilometer measurements of cloud fraction and cloudbase height made during the FIRE IFO. The algorithms are then applied to the entire data set to produce a climatology of these cloud properties for the eight month period.