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This paper describes a forward radiative transfer model and retrieval system (FMRS) for the Tropospheric Water and cloud ICE (TWICE) CubeSat instrument. We use the FMRS to simulate radiances for the TWICE's 14 millimeter‐ and submillimeter‐wavelength channels for a tropical atmospheric state produced by a Weather Research and Forecasting model simulation. We also perform simultaneous retrievals of cloud ice particle size, ice water content (IWC), water vapor content (H2O), and temperature from the simulated TWICE radiances using the FMRS. We show that the TWICE instrument is capable of retrieving ice particle size in the range of ~50–1000 μm in mass mean effective diameter with approximately 50% uncertainty. The uncertainties of other retrievals from TWICE are about 1 K for temperature, 50% for IWC, and 20% for H2O., Key Points Cloud ice particle size is an important parameter that determines cloud radiative effect, precipitation, and climate sensitivityA simulation experiment for a CubeSat instrument is conducted to determine the accuracy of ice particle size, humidity, and temperature retrievalsThe results show that the CubeSat instrument is capable of fulfilling the requirements of measuring ice particle size, humidity, and temperature

Results from a cloud-resolving model are systematically compared with a variety of observations, both ground based and satellite, in order to better understand the mean background errors and their correlations. This is a step in the direction of developing a background error covariance matrix for use in cloud data assimilation. Observation sources include the Geostationary Operational Environmental Satellite (GOES), the Atmospheric Emitted Radiance Interferometer (AERI), a microwave radiometer (MWR), radiosonde, and cloud radar. When exploring model biases in temperature, precipitable water vapor, and liquid water path, a warm and moist bias at night and a cool and dry bias during the day are observed. Values for the background decorrelation length of water variables are determined. In addition, a dynamic cloud mask is presented to give more control in the assimilation of cloudy satellite radiances, allowing different cloud types to be excluded from the assimilation as well as establishing values for the maximum residuals to be considered.

The in situ cloud lidar is designed to measure cloud volumes of millions of cubic meters to overcome the sampling limitations of traditional cloud probes in inhomogeneous clouds. This technique sends laser pulses horizontally from an aircraft inside an optically thick cloud and measures the time series of the multiply scattered light with wide field-of-view detectors viewing upward and downward. The extinction in liquid clouds averaged over tens to hundreds of meters and the distance to cloud boundaries can be retrieved from the signal measured by a single-wavelength in situ lidar. This paper describes the design and operation of an in situ cloud lidar. A laser in the aircraft cabin outputs 532-nm wavelength pulses at 10 Hz, which are sent through beam-expanding optics for eye safety. The upward- and downward-viewing detectors use photomultiplier tubes and operate with either daytime (3° half angle; 0.37-nm solar-blocking filter) or nighttime (30°) optics. Example daytime lidar signals in dense cloud have a dynamic range of 1000 after solar background subtraction. Results from a nighttime flight in marine stratus are analyzed in detail. The variations in the lidar signals with aircraft travel are much smoother for the longer photon travel times, indicating that the later times sample volumes hundreds of meters in size. Extinction retrievals for 25-m-radius volumes have high correlation (R2 = 0.84) with Forward Scattering Spectrometer Probe (FSSP)-derived extinction, while the correlation is relatively low (R2 = 0.40) for 200-m volumes due to cloud inhomogeneity. Lidar retrievals of cloud-base and -top height from inside the cloud are consistent with cloud boundaries obtained from aircraft penetrations on ascents and descents.

Three-dimensional radiative transfer calculations are accurate, though computationally expensive, if the spatial distribution of cloud properties is known. The difference between these calculations and those using the much less expensive independent column approximation is called the 3D radiative transfer effect. Assessing the magnitude of this effect in the real atmosphere requires that many realistic cloud fields be obtained, and profiling instruments such as ground-based radars may provide the best long-term observations of cloud structure. Cloud morphology can be inferred from a time series of vertical profiles obtained from profilers by converting time to horizontal distance with an advection velocity, although this restricts variability to two dimensions. This paper assesses the accuracy of estimates of the 3D effect in shallow cumulus clouds when cloud structure is inferred in this way. Large-eddy simulations provide full three-dimensional, time-evolving cloud fields, which are sampled every 10 s to provide a “radar’s eye view” of the same cloud fields. The 3D effect for shortwave surface fluxes is computed for both sets of fields using a broadband Monte Carlo radiative transfer model, and intermediate calculations are made to identify reasons why estimates of the 3D effect differ in these fields. The magnitude of the 3D effect is systematically underestimated in the two-dimensional cloud fields because there are fewer cloud edges that cause the effect, while the random error in hourly estimates is driven by the limited sample observed by the profiling instrument.

The datasets currently being collected at the Atmospheric Radiation Measurement (ARM) program's sites on the islands of Nauru and Manus represent the longest time series of ground-based cloud measurements available in the tropical western Pacific region. In this and a companion paper, a shortwave flux closure study is presented using observations collected at the Nauru site between June 1999 and May 2000. This paper presents frequency of occurrence of nonprecipitating liquid and ice clouds detected by the millimeter wavelength cloud radar (MMCR) and statistics of retrieved microphysical properties. The companion paper presents results from a closure study in which the retrieved cloud properties are input to a radiative transfer model, and the modeled surface fluxes are compared to observations. The liquid cloud properties are retrieved from MMCR and microwave radiometer (MWR) measurements using a Bayesian retrieval technique. Properties of ice phase clouds are retrieved from MMCR measurements usi...

A retrieval method has been developed to directly retrieve statistics of cloud parameters from Geostationary Operational Environmental Satellite (GOES) visible and infrared imager data. This method retrieves cloud parameter probability density functions (PDFs) directly from distributions of multichannel satellite-observed radiances. For example, the joint probability distribution of ice water content and effective radius can be retrieved from a four-dimensional histogram of GOES radiances. A forward radiative transfer model creates a mapping from cloud parameter space to satellite radiance space. The cloud parameter space is described by vertically inhomogeneous liquid and ice cloud layers with variable liquid water path, effective radius, height, and thickness. A Monte Carlo procedure uses the mapping to transform probability density from the observed satellite radiance histogram, or radiance PDF, to a two-dimensional cloud property PDF. An estimate of the uncertainty in the retrieved PDF is cal...

Since three-dimensional (3-D) radiative transfer in cloudy atmospheres is too expensive for large-scale atmospheric models, approximate radiative transfer methods are used. The accuracy of these approximations for a large sample of realistic cloud fields has not been determined. This study examines 150 fields of small marine tropical cumulus to assess the magnitude of 3-D effects on domain average solar fluxes and to evaluate the accuracy of these approximations in actual cumulus fields. The cloud fields are derived from Moderate-Resolution Imaging Spectroradiometer Airborne Simulator (MAS) visible and thermal infrared imagery. Domain average broadband solar fluxes in these fields are simulated with a Monte Carlo radiative transfer model using four radiative transfer methods: full three-dimensional, the independent pixel approximation (IPA), the tilted IPA, and the plane-parallel approximation. The average 3-D radiative effects of these cumulus cloud fields are small, with mean reflected flux errors up to 3 W/m2 for overhead Sun and less than 1 W/m2 for the daytime average. The mean errors for column-absorbed fluxes are less than 0.3 W/m2 for all Sun angles. The small absolute flux errors are a result of the average field having small cloud fraction (10%), low cloud optical depth (4.4), and shallow clouds. Some individual fields have large 3-D absolute reflected flux effects, and the normalized reflected flux errors are significant. The errors correlate well with the cloud fraction; so it may be possible to make corrections to the approximations.

A novel microwave technique for simultaneously retrieving cirrus ice water path (IWP) and characteristic ice particle size is described. The retrieval algorithm exploits radiance measurements made at 150 and 220 GHz by the airborne Millimeter-Wave Imaging Radiometer (MIR). Other MIR channels additionally are used to test for the presence of liquid clouds and precipitation, which otherwise would have a contaminating effect on the retrievals. Forward radiative transfer modeling was used to generate a two-dimensional retrieval table in which brightness-temperature depressions (relative to clear-sky values) for both microwave channels were recorded as functions of IWP and characteristic particle size for gamma distributions of ice particles. Retrieval errors due to particle shape, size distribution, clear-sky water vapor variability, cirrus-cloud altitude variability, and instrument noise were estimated using Monte Carlo analysis. Particle shape uncertainty is believed to be the dominant source of retrieval error. The technique is demonstrated using MIR data recorded on the National Aeronautics and Space Administration ER-2 aircraft during the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment experiment in the tropical western Pacific Ocean in 1993. The retrieval technique with MIR data is suited only to high-IWP clouds with large ice particles, such as thick frontal cirrus and convective anvils. The general methodology, however, is applicable to higher frequencies that have greatly increased sensitivity to thinner cirrus.

Given the substantial radiative effects of cirrus clouds and the need to validate cirrus cloud mass in climate models, it is important to measure the global distribution of cirrus properties with satellite remote sensing. Existing cirrus remote sensing techniques, such as solar reflectance methods, measure cirrus ice water path (IWP) rather indirectly and with limited accuracy. Submillimeter/wave radiometry is an independent method of cirrus remote sensing based on ice particles scattering the upwelling radiance emitted by the lower atmosphere. A new aircraft instrument, the Far Infrared Sensor for Cirrus (FIRSC), is described. The FIRSC employs a Fourier Transform Spectrometer (FTS). which measures the upwelling radiance across the whole submillimeter region (0.1 1.0-mm wavelength). This wide spectral coverage gives high sensitivity to most cirrus particle sizes and allows accurate determination of the characteristic particle size. Radiative transfer modeling is performed to analyze the capabilities of the submillimeter FTS technique. A linear inversion analysis is done to show that cirrus IWP, particle size, and upper-tropospheric temperature and water vapor may be accurately measured, A nonlinear statistical algorithm is developed using a database of 20000 spectra simulated by randomly varying most relevant cirrus and atmospheric parameters. An empirical orthogonal function analysis reduces the 500-point spectrum (20 - 70/cm) to 15 "pseudo-channels" that are then input to a neural network to retrieve cirrus IWP and median particle diameter. A Monte Carlo accuracy study is performed with simulated spectra having realistic noise. The retrieval errors are low for IWP (rms less than a factor of 1.5) and for particle sizes (rins less than 30%) for IWP greater than 5 g/sq m and a wide range of median particle sizes. This detailed modeling indicates that there is good potential to accurately measure cirrus properties with a submillimeter FTS.

The two-dimensional radiative transfer behavior of nine marine stratocumulus clouds observed by cloud radar during the Atlantic Stratocumulus Transition Experiment is examined. The cloud radar resolves the vertical structure to 37.5 m. The method of [Frisch et al., 1995] is used to convert radar reflectivities to extinction fields. Three constructions of the same cloud field help elucidate underlying causes of variability: one is fully two-dimensional, while the other two have vertically uniform extinction fields but possess either a flat cloud top or the original cloud top topography. Two-dimensional solar radiative transfer results are compared with the independent pixel approximation (IPA) result. At the scale of the domain (≈ 7km) the IPA albedo bias is small, even after including vertical structure. Locally, in contrast, the direct solar beam interaction with cloud top geometry competes with radiative smoothing as the dominant radiative process. Power spectral analysis of nadir reflectances is dominated by radiative smoothing for overhead Sun, and side illumination/shadowing of cloud top bumps for low Sun. A method that incorporates direct beam interactions with the cloud geometry, in addition to radiative smoothing, significantly improves correlations of a smoothed IPA radiance field with the 2-D reflectances. In a remote sensing application, optical depth and albedo retrieval biases from plane-parallel theory depend on the spatial scale chosen to emulate a satellite pixel size. For scales less than a few kilometers and with low Sun, cloud top topography can cause large positive optical depth biases even when averaged over the entire domain. A larger spatial scales the negative IPA bias always dominates. Domain-averaged monochromatic albedo retrieval errors remain below 0.005, a relative error of less then 1%.

Vertical profiles of drop size distribution (DSD) parameters are produced from data collected with the National Oceanographic and Atmospheric Administration 915- and 50-MHz Doppler radars at Darwin, Australia, for the 1993–94 monsoon season. An existing algorithm is used to retrieve gamma size distribution parameters from the VHF and UHF Doppler radar spectra. The clear-air mean velocities and spectral widths obtained from the VHF radar are used to fit DSDs accurately to UHF spectra. Uncertainties in retrieved precipitation parameters are estimated from errors in both VHF and UHF spectra. The statistics of the retrieved profiles of DSD parameters are summarized and compared with surface disdrometer data from a site near Darwin. Retrieved vertical profiles of gamma DSDs are input to a microwave radiative transfer model to determine realistic variations in upwelling 10- and 19-GHz brightness temperatures due to uncertainties in drop size distribution. These brightness temperature variations are the...

The scattering properties of cirrus clouds at submillimeter-wave frequencies are analyzed and characterized in this paper. This study lays a theoretical foundation for using radiometric measurements to investigate and monitor cirrus properties from high-flying aircraft or satellite. The significance of this capability is that it would provide data on the global distribution of cloud ice mass that is currently required to validate climate models. At present, these needs remain unmet by existing and planned observational systems. In this study the brightness temperature depression (DTb) of upwelling radiation due to cirrus clouds is simulated at 150, 220, 340, 500, 630, and 880 GHz. The effects of a range of size distributions, eight ice particle shapes, and different atmospheric profiles are modeled. The atmospheric transmission is high enough in the submillimeter windows to allow upper-tropospheric sensing from space, but absorption by water vapor reduces the sensitivity to lower cirrus clouds in a simply predictable manner. It is shown that frequencies above 500 GHz have adequate sensitivity to measure cirrus cloud properties. For these higher frequencies, the DTb is closely proportional to ice water path (IWP) for median mass equivalent sphere diameters (Dme) above 125 mm. The differing sensitivity with frequency allows two channels to determine particle size. A two-channel Bayesian algorithm is developed to assess retrieval accuracy with a Monte Carlo error analysis procedure. Particle shape, size distribution width, and receiver noise are considered as error sources. The rms errors for a nadir view with 630/880 GHz are less than 40% for IWP . 5gm 22 and Dme . 100 mm, while using an oblique viewing angle of 738 results in the same accuracy down to an IWP o f1gm 22 (visible optical depth less than 0.1). The two-channel algorithm and error analysis methods are used to show how submillimeter radiometer and millimeter radar measurements may be combined.

This paper presents the results of polarized microwave radiative transfer modeling of cirrus clouds containing five different particle shoes and 18 Gamma size distributions. Upwelling brightness temperatures for tropical and midlatitude winter atmospheres are simulated at 85.5, 157, 220, and 340 GHz using scattering properties computed with the discrete dipole approximation (described in Part I). The key parameter for the results is the sensitivity (ΔTb/IWP), which relates the modeled brightness temperature depression to the ice water path. It is shown that for the higher frequencies or distributions of larger particles (i.e., in the scattering regime) the sensitivity is nearly independent of cloud temperature and details of the underlying atmosphere. As expected from the single-scattering results, the characteristic particle size has a large effect on the sensitivity, while the distribution width has only a minor effect. The range in sensitivity over the five particle shapes is typically a facto...

A multichannel passive microwave precipitation retrieval algorithm is developed. Bayes theorem is used to combine statistical information from numerical cloud models with forward radiative transfer modeling. Amultivariate lognormal prior probability distribution contains the covariance information about hydrometeor distributions that resolves the nonuniqueness inherent in the inversion process. Hydrometeor profiles are retrieved by maximizing the posterior probability density for each vector of observations. The hydrometeor profile retrievalmethod is tested with data from the Advanced Microwave Precipitation Radiometer (IO, 19, 37, and 85 GHz) of convection over ocean and land in Florida. The CP-2 multiparameter radar data are used to verify theretrieved profiles. The results show that the method can retrieve approximate hydrometeor profiles, with larger errors over land than water. There is considerably greater accuracy in the retrieval of integrated hydrometeor contents than of profiles. Many of the retrieval errors are traced to problems with the cloud model microphysicalinformation, and future improvements to the algorithm are suggested.

We report on the progress of a far-infrared/submillimeter radiometer being developed in Cardiff for the measurement of cirrus clouds. Remote sensing of cirrus clouds is known to be of great importance to the long-term accuracy of current General Circulation Models (GCM) and climate prediction but with greater measurement coverage needed. The instrument reported here is an aircraft deployed, 5 channel fixed band radiometer capable of retrieving cirrus Ice Water Path (IWP) and mean particle diameter (Dme) using a spectral range of between 10 cm-1 and 55 cm-1. The radiometer will capitalise on ongoing measurements from the Fourier transform interferometer based, Far-infrared Sensor for Cirrus (FIRSC), an instrument for which Cardiff has been closely associated. Initial results of channel selection simulations are presented here with comparisons between different combinations of channel frequency and bandwidths, along with the number of channels used and cloud particle shape. Also demonstrated is the effect of instrument noise on retrieval performance which is shown to be the dominant source of retrieval error.

We introduce a low cost, lightweight and compact polarisation sensitive radiometer for the measurement of Cirrus clouds in the submilimeter and far-infrared region (10-50 cm-1). It is widely recognised that enhanced global measurements of cirrus properties are essential to the development of General Circulation and Climate Prediction Models (GCMs) since cirrus clouds have a strong effect on the Earths Global Radiation Budget. We introduce a project currently under development in Cardiff, to design and build a novel instrument suitable for aircraft deployment in order to measure Ice Water Path (IWP) along with cirrus particle size and shape. The radiometer will capitalise on the on going measurements of the NASA led, Fourier Transform interferometer based, Far-Infrared Sensor for Cirrus (FIRSC) instrument for which Cardiff has been closely associated. Data from FIRSC campaigns is being used to select optimum radiometer channels that exhibit good sensitivity to specific cirrus. This new multi-channel radiometer will however have some key advantages over similar spectroscopic instruments for example: portability, increased optical efficiency, a multi-angle field of view and a reduced integration period leading to an improved spatial resolution. The radiometer will benefit from the application of state-of-the-art submm/FIR polariser and solid filter technology currently being developed in Cardiff.

Remote sensing measurements of cirrus clouds are crucial for improving global climate models. Spectral measurements of the far-infrared region provide especially useful information to retrieve cirrus ice water path and particle size properties. Earth radiance spectra of this region have been obtained for a range of cloud conditions using the airborne instrument FIRSC (Far-InfraRed Sensor for Cirrus). The instrument flew on board the high altitude Proteus aircraft in the ARM-FIRE Water Vapor Experiment (AFWEX) during the Nov - Dec 2000 Intensive Operations Period. FIRSC is a Martin-Puplett type Fourier transform spectrometer with two channels covering the ranges 10 - 33 cm -1 and 80 -140 cm -1 at a resolution of 0.1 cm -1 . It has achieved a noise equivalent temperature of approximately 1K at 30 cm -1 using a scan duration of 4 seconds. For the first time this far-infrared data has been compared to data from the thermal IR NAST-I (NPOESS Airborne Sounder Testbed - Interferometer), which was part of the same payload during the AFWEX flights. Retrievals of cirrus ice water path and particle size from the FIRSC data are presented.

[1] We present a new algorithm for retrieving optical depth and liquid water content and effective radius profiles of nonprecipitating liquid water clouds using millimeter wavelength radar reflectivity and dual-channel microwave brightness temperatures. The algorithm is based on Bayes’ theorem of conditional probability and combines prior information on cloud microphysics with the remote sensing observations. Prior probability distribution functions for liquid water clouds were derived from the second, third, and sixth moments of droplet size distributions measured by in situ aircraft probes in shallow tropical cumuli. The algorithm also calculates error bars for each retrieved parameter. To assess the algorithm, we perform retrieval simulations using radar reflectivity and brightness temperatures simulated from tropical cumulus fields calculated by a large eddy simulation model with explicit microphysics. These retrieval simulations show that the Bayesian algorithm has similar magnitude errors to current retrieval methods for liquid water content and liquid water path retrievals but has much smaller errors for effective radius and optical depth. We also perform retrievals on three months of data from the Atmospheric Radiation Measurement (ARM) Program’s site on Nauru in the tropical west Pacific. For nonprecipitating liquid water clouds over Nauru during June–August 1999 we retrieve a mean optical depth of 9.2, mean liquid water content of 0.112 g/m 3 , and mean effective radius of 7.8 mm. The Bayesian method is a flexible approach to cloud profile remote sensing and could be expanded to other sites or cloud types. INDEXTERMS: 3360 Meteorology and Atmospheric Dynamics: Remote sensing; 0320 Atmospheric Composition and Structure: Cloud physics and chemistry; 3394 Meteorology and Atmospheric Dynamics: Instruments and techniques; 3399 Meteorology and Atmospheric Dynamics: General or miscellaneous; KEYWORDS: remote sensing, clouds, radar, microwave radiometer, Bayes

Improved techniques for remote sensing of cirrus are needed to obtain global data for assessing the effect of cirrus in climate change models. Model calculations show that the far infrared/sub-millimeter spectral region is well suited for retrieving cirrus Ice Water Path and particle size parameters. Especially useful cirrus information is obtained at frequencies below 60 cm-1 where single particle scattering dominates over thermal emission for ice particles larger than about 50 micrometer. Earth radiance spectra have been obtained for a range of cloud conditions using an aircraft-based Fourier transform spectrometer. The Far InfraRed Sensor for Cirrus (FIRSC) is a Martin-Puplett interferometer which incorporates a polarizer for the beamsplitter and can be operated in either intensity or linear polarization measurement mode. Two detector channels span 10 to 140 cm-1 with a spectral resolution of 0.1 cm-1; achieving a Noise Equivalent Temperature of approximately 1K at 30 cm-1 in a 4 sec scan. Examples are shown of measured and modeled Earth radiance for a range of cloud conditions from 1998 and 1999 flights.

The lack of a global cirrus cloud database is a major deficiency in validating Global Circulation Models which are the basis for estimating long term climate change. Cirrus clouds being composed of ice particles act to reflect the incoming solar radiation and to block infrared energy radiation loss from the earth. The net effect can be either warming or cooling. The essential data are global distributions of the Ice Water Path (IWP) and effective particle size. We have modeled the outgoing earth radiance spectrum between 8 and 1000 micrometer as a function of IWP and effective particle size. The results are used to estimate cirrus retrieval accuracies for cirrus from far infrared/submm measurements by Fourier transform spectroscopy. We describe the aircraft-based Far Infrared Sensor for Cirrus (FIRSC) instrument which is currently under construction. We also discuss the potential contribution of far infrared/submm measurements for the validation of cirrus products anticipated in the MTPE MODIS program.