The accuracy of water vapor and cloud liquid determination by dual‐frequency ground‐based microwave radiometry

Westwater, Ed R.

doi:10.1029/rs013i004p00677

Cited by 196 publications

(98 citation statements)

References 25 publications

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“…For this analysis we chose the Rosenkranz98 and the Liebe91 models to illustrate these effects. Since the largest contribution to the liquid and vapor errors is the uncertainty in Tc and Tmr [Westwater, 1978], we evaluate this error here. …”

Section: Physical Versus Statistical Retrieval Methodsmentioning

confidence: 99%

Analysis of integrated cloud liquid and precipitable water vapor retrievals from microwave radiometers during the Surface Heat Budget of the Arctic Ocean project

Westwater¹,

Han²,

Shupe³

et al. 2001

J. Geophys. Res.

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159

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Abstract. We investigated a variety of factors that influence the determination of precipitable water vapor (V) and integrated cloud liquid (L) by dual-channel microwave radiometers (MWRs). These factors include radiometric calibration; dry, water vapor, and liquid absorption coefficients; and physical versus statistical retrieval methods. We then applied the analysis to the MWR that was operated by the Atmospheric Radiation Measurement Program (ARM) during the Surface Heat Budget of the Arctic Ocean project. In the work reported here, MWR data taken from April 1 to July 31, 1998, were analyzed. Data acquired in situ did not always agree with the original MWR liquid retrievals, with MWR estimates at times being too large by perhaps a factor of 2. These differences led us to examine in detail several of the assumptions that go into V and L retrievals. The radiometer was carefully examined and found to be well calibrated with a 0.3 K RMS error. The predicted accuracy in the L retrievals, for this 0.3 K RMS radiometric error and a statistical retrieval, was 25 g m -2 RMS. This accuracy improves to 10%, if we use the improved knowledge of cloud temperature, as can be obtained using radiosondes and cloud radar/lidar measurements. We also studied the degree to which different clear air and cloud liquid models have an effect on V and L retrievals. The most significant changes from the original ARM retrievals were due to the dry opacity and the cloud liquid dielectric model. Although nothing was found in the original ARM data that was grossly incorrect, application of these models reduced the original ARM retrievals by roughly 20 to 30%. The change of clear-air absorption model from the original to a more recent one has little impact on V retrievals except when V is <0.5 cm. with MWR estimates at times being too large by perhaps a factor of 2. These differences led us to examine in detail several of the assumptions that go into V and integrated cloud liquid (L) retrievals. As a preliminary to our analysis, we first outline the steps taken in moisture retrieval. We then examine several contemporary absorption algorithms for both clear and cloudy skies, and then evaluate differences in moisture retrieval using these algorithms. Finally, we apply these algorithms to the SHEBA MWR data and compare both the original and revised retrievals with each other and with aircraft in situ measurements. Retrieval MethodsThe MWR that was operated during SHEBA was one of the operational units from the Atmospheric Radiation Measure-32,019

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Section: Physical Versus Statistical Retrieval Methodsmentioning

confidence: 99%

Analysis of integrated cloud liquid and precipitable water vapor retrievals from microwave radiometers during the Surface Heat Budget of the Arctic Ocean project

Westwater¹,

Han²,

Shupe³

et al. 2001

J. Geophys. Res.

Self Cite

159

152

View full text Add to dashboard Cite

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“…The high accuracy in retrieved LWP and integrated water vapor content (IWV) achieved by two-channel radiometers was demonstrated more than two decades ago [Westwater, 1978]. Together with their simple operation these reasons make microwave radiometers well suited to gather long-term time series needed for atmospheric model evaluation and improvement.…”

Section: Introductionmentioning

confidence: 99%

“…A popular method for deriving LWP from a two-channel microwave radiometer is to use optical thickness (t) instead of brightness temperature [Westwater, 1978;Han and Westwater, 1995] to account for nonlinearities.…”

Section: Regression Techniquesmentioning

confidence: 99%

Accuracy of cloud liquid water path from ground‐based microwave radiometry 1. Dependency on cloud model statistics

2003

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[1] This paper investigates the influence of cloud model statistics on the accuracy of statistical multiple-frequency liquid water path (LWP) retrievals for a ground-based microwave radiometer. Statistical algorithms were developed from a radiosonde data set in which clouds were modeled by using a relative humidity threshold and a modified adiabatic assumption. Evaluation of the algorithms was then performed by applying the algorithms to four data sets in which clouds were generated in different ways (i.e., threshold method, gradient method, and cloud microphysical model). While classical twochannel algorithms, in this case using frequencies at 22.985 and 28.235 GHz, do not show a significant dependency on the cloud model, the inclusion of an additional 50-GHz channel can introduce significant systematic errors. The addition of a 90-GHz frequency to the two-channel algorithm leads to a larger increase in LWP accuracy than in case of the 50-GHz channel and is less sensitive to the choice of cloud model. A drizzle case from the cloud microphysical model shows no significant loss of accuracy for the microwave radiometer algorithms, in contrast to simple cloud radar retrievals of liquid water. In case of rain, however, the results deteriorate when the total liquid water path is larger than 700 g m À2 .INDEX TERMS: 3360 Meteorology and Atmospheric Dynamics: Remote sensing; 3394 Meteorology and Atmospheric Dynamics: Instruments and techniques; 6969 Radio Science: Remote sensing; 1640 Global Change: Remote sensing; 1655 Global Change: Water cycles (1836); KEYWORDS: microwave radiometer, cloud liquid water, sensor synergy, ground-based remote sensing Citation: Löhnert, U., and S. Crewell, Accuracy of cloud liquid water path from ground-based microwave radiometry, 1, Dependency on cloud model statistics,

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“…However, the total column liquid water path, or vertical integral of the third moment, can be retrieved from a passive dualchannel microwave radiometer, in which one channel is more sensitive to integrated water vapor and the other to integrated liquid water [Westwater, 1978]. The inclusion of total liquid water path adds an additional constraint on the DSD, but is still not enough to describe it completely, so other information or assumptions must be included.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian algorithm for the retrieval of liquid water cloud properties from microwave radiometer and millimeter radar data

2002

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[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.

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The accuracy of water vapor and cloud liquid determination by dual‐frequency ground‐based microwave radiometry

Cited by 196 publications

References 25 publications

Analysis of integrated cloud liquid and precipitable water vapor retrievals from microwave radiometers during the Surface Heat Budget of the Arctic Ocean project

Analysis of integrated cloud liquid and precipitable water vapor retrievals from microwave radiometers during the Surface Heat Budget of the Arctic Ocean project

Accuracy of cloud liquid water path from ground‐based microwave radiometry 1. Dependency on cloud model statistics

A Bayesian algorithm for the retrieval of liquid water cloud properties from microwave radiometer and millimeter radar data

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