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J. Vivekanandan, J. Turk, and V. N. Bringi

Abstract

Microwave emission emerging from a precipitating cloud top and lying in a radiometer's field of view represents the culmination of a complex interaction between emitted microwave radiation and its ongoing extinction through overlapping regions of liquid, melting phase, and ice. The encounter with the ice region represents the final interaction between the upwelling microwave radiation and the cloud constituents. Hence, an ice phase characterization perhaps represents a more inherently retrievable property from a combination of scattering-based channels above 37 GHz than the underlying rainfall. Model computations of top-of-atmospheric microwave brightness temperatures TB from layers of precipitation-sized ice of variable bulk density and ice water content (IWC) are presented. The 85-GHz TB is shown to depend essentially on the ice optical thickness, while the possibility of using the 37- and 85-GHz brightness temperature difference ΔTB to estimate the integrated ice water path (IWP) is investigated. The results demonstrate the potential usefulness of using scattering-based channels to characterize the ice phase and suggest a top-down methodology for retrieval of cloud vertical structure and precipitation estimation from multifrequency passive microwave measurements.

Radiative transfer model results using the multiparameter radar data initialization from the Cooperative Huntsville Meteorological Experiment (COHMEX) in northern Alabama are also presented. The vertical behavior of the simulated multifrequency TB, albedo, and extinction is presented along with the associated multiparameter radar measurements during the cloud lifecycle. Ice water path values estimated from the radar measurements are compared with the above theoretical computations for the corresponding TB values and show agreement for values of IWP less than 1 kg m−1. Above this, assumptions in the form of the ice-size distribution fail to adequately characterize the ice scattering process. Brightness temperature TB warming effects due to the inclusion of a cloud liquid water profile are shown to be especially significant at 85 GHz during later stages of cloud evolution.

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J. Turk, F. S. Marzano, and A. Mugnai

Abstract

Based on the fundamental relationship involving the interaction of microwave radiation with precipitation, microwave-based satellite precipitation estimates hold the most promise for quantitative rain estimation from space. At present, the low-resolution channels onboard the DMSP Special Sensor Microwave Imager (SSM/I) are sampled with a spatial resolution several times larger than the scale at which rainfall is generated in typical convective rainbands. Aircraft-based instruments can provide views of the detailed microwave radiometric characteristics of precipitating clouds.

In this manuscript, the authors present coincident finescale (1–3-km resolution) collocated aircraft radiometric and aircraft precipitation radar measurements collected during the 1993 Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment in the western Pacific Ocean. By intentionally degrading the resolution of the aircraft datasets from their native resolution to that of current and future spaceborne sensors, the impact of sensor resolution upon a combined radiometer–radar vertical profiling rain-retrieval algorithm (developed and utilized for the Precipitation Intercomparison Program 2) was examined. Retrieved values of the columnar graupel content were more influenced by the addition of the radar profile than was the columnar rain content. The retrieved values of columnar graupel were also significantly smaller than previously published results for land-based rainfall. The results show that the general trend of the rain structure is maintained but finescale details are lost once the observations are reduced to resolutions of 15 km.

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J. Vivekanandan, J. Turk, G. L. Stephens, and V. N. Bringi

Abstract

Theoretical calculations of the upwelling microwave radiances from clouds containing layers of rain, ice, and a melting region were performed at frequencies of 18, 37, and 92 GHz. These frequencies coincide with high-resolution microwave radiometer measurements taken aboard the NASA ER-2 high-altitude aircraft during the summer 1936 COHMEX (Cooperative Huntsville Meteorological Experiment) in Alabama. For purposes of brightness temperature computations, the storms were modeled with rain, melting phase, and ice layers. The melting phase region was composed of water-coated ice spheres defined by a “melt index” in terms of the volume fraction of water. Single scatter albedo, scattering, and extinction coefficients were computed at the above frequencies as a function of the rain rate and melt index. In addition, multiparameter radar observations of the storm were mapped into a cartesian space and averaged over regions comparable to the radiometer footprint. Vertical profiles of these data under the ER-2 flight path were constructed to reveal quantitative estimates of regions of rain, melting, and ice phases, and also to retrieve a two-parameter exponential size distribution. This information was used to compute extinction coefficients and Mie phase matrices for each layer of specified microphysical characteristics. Upwelling multifrequency brightness temperatures were computed using plane-parallel radiative transfer modeling, and compared with those observed by the ER-2 airborne radiometers.

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J. Turk, J. Vivekanandan, T. Lee, P. Durkee, and K. Nielsen

Abstract

Recent deployments of the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellites (GOES-8 and -9) include full-time 3.9-μm imaging capabilities. This shortwave (near infrared) channel has been available at 3.7 μm on the Advanced Very High Resolution Radiometer (AVHRR) instrument aboard the NOAA polar-orbiting satellite systems. In this spectral region, daytime satellite-observed radiances include contributions from both the reflected solar radiation and the emitted thermal emission. In particular, typical stratus and fog clouds posess near-infrared emissivities less than unity, which requires special processing to account for the angular dependence of the solar reflection. In this paper, a side-by-side comparison of time-coincident GOES- and AVHRR-derived near-infrared cloud reflectance is carried out in order to demonstrate the capability of GOES-8 and -9 in both identifying and characterizing the microphysics of stratus and fog clouds during the daytime.

The authors first present the mathematical formalism and then apply the technique to extract the near-infrared reflectances from GOES-8 and -9 data. The technique is applicable for operational usage and requires a lookup table to account for the continuously changing sun-satellite viewing geometry. Near-infrared cloud reflectances are extracted from coincident GOES-9 and AVHRR data from both NOAA-14 and -12 for different times of day and are verified against theoretical reflectances derived from radiative transfer theory and previously published results. A retrieval of the cloud drop size distribution effective radius is demonstrated on satellite data along coastal California during the summer of 1996.

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Thomas F. Lee, Francis J. Turk, Jeffrey Hawkins, and Kim Richardson

Abstract

Images of the 85-GHz frequency from the Special Sensor Microwave Imager (SSM/I) aboard the Defense Meteorological Satellite Program (DMSP) spacecraft are routinely viewed by forecasters for tropical cyclone analyses. These images are valued because of their ability to observe tropical cyclone structure and to locate center positions. Images of lower-frequency SSM/I channels, such as 37 GHz, have poor quality due to the coarse spatial resolution, and therefore 85 GHz has become the de facto analysis standard. However, the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in 1997, has much better spatial resolution for all channels than the SSM/I. Although originally designed to investigate precipitation for climate research, real-time images are now sent into tropical cyclone forecast offices, and posted to Web pages of the Naval Research Laboratory and the Fleet Numerical Meteorology and Oceanography Center, both in Monterey, California. TMI images of 37 GHz have a number of properties that make them useful complements to images of 85 GHz. They have the capacity to detect low-level circulation centers, which are sometimes unseen at 85 GHz. Also, because the 37-GHz channel generally senses atmospheric layers much nearer to the surface than 85 GHz, parallax error is less, allowing more accurate fixes. This paper presents several case studies comparing the two TMI frequencies and offers some forecasting guidelines for when to use each.

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V. Chandrasekar, Y. Golestani, J. Turk, and V. N. Bringi

Abstract

Two-dimensional PMS precipitation probes mounted with horizontal optical axis have been previously used to study the shapes of hydrometeors such as raindrops and graupel. Fourier and moment descriptors have been applied to such images for the purposes of parameter estimation (axis ratio, canting angle) of raindrops, and for classifying raindrops in a raindrop/graupel mixture. Simulations have been used to evaluate these techniques. Our results show that axis ratios of raindrops can be accurately estimated using both Fourier and moment methods. We also show that the canting angle of the raindrop image can be accurately estimated using the moment method. Two image classification techniques were applied to data from below the melting level in a convective storm for classifying raindrops and graupel. The potential usefulness of such techniques is demonstrated in this paper.

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Francisco J. Tapiador, Ziad S. Haddad, and Joe Turk

Abstract

The raindrop size distribution (RDSD) is defined as the relative frequency of raindrops per given diameter in a volume. This paper describes a mathematically consistent modeling of the RDSD drawing on probability theory. It is shown that this approach is simpler than the use of empirical fits and that it provides a more consistent procedure to estimate the rainfall rate (R) from reflectivity (Z) measurements without resorting to statistical regressions between both parameters. If the gamma distribution form is selected, the modeling expresses the integral parameters Z and R in terms of only the total number of drops per volume (N T), the sample mean [m = E(D)], and the sample variance [σ 2 = E(mD)2] of the drop diameters (D) or, alternatively, in terms of N T, E(D), and E[log(D)]. Statistical analyses indicate that (N T, m) are independent, as are (N T, σ 2). The ZR relationship that arises from this model is a linear R = T × Z expression (or Z = T −1 R), with T a factor depending on m and σ 2 only and thus independent of N T. The ZR so described is instantaneous, in contrast with the operational calculation of the RDSD in radar meteorology, where the ZR arises from a regression line over a usually large number of measurements. The probabilistic approach eliminates the need of intercept parameters N 0 or , which are often used in statistical approaches but lack physical meaning. The modeling presented here preserves a well-defined and consistent set of units across all the equations, also taking into account the effects of RDSD truncation. It is also shown that the rain microphysical processes such as coalescence, breakup, or evaporation can then be easily described in terms of two parameters—the sample mean and the sample variance—and that each of those processes have a straightforward translation in changes of the instantaneous ZR relationship.

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C. Kidd, P. Bauer, J. Turk, G. J. Huffman, R. Joyce, K.-L. Hsu, and D. Braithwaite

Abstract

Satellite-derived high-resolution precipitation products (HRPP) have been developed to address the needs of the user community and are now available with 0.25° × 0.25° (or less) subdaily resolutions. This paper evaluates a number of commonly available satellite-derived HRPPs covering northwest Europe over a 6-yr period. Precipitation products include the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), the Climate Prediction Center (CPC) morphing (CMORPH) technique, the CPC merged microwave technique, the Naval Research Laboratory (NRL) blended technique, and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) technique. In addition, the Geosynchronous Operational Environmental Satellite (GOES) precipitation index (GPI) and the European Centre for Medium-Range Weather Forecasting (ECMWF) operational forecast model products are included for comparison. Surface reference data from the European radar network is used as ground truth, supported by the Global Precipitation Climatology Centre (GPCC) precipitation gauge analysis and gauge data over the United Kingdom. Measures of correlation, bias ratio, probability of detection, and false alarm ratio are used to evaluate the products. Results show that satellite products generally exhibit a seasonal cycle in correlation, bias ratio, probability of detection, and false alarm ratio, with poorer statistics during the winter. The ECMWF model also shows a seasonal cycle in the correlation, although the results are poorer during the summer, while the bias ratio, probability of detection, and false alarm ratio are consistent through all seasons. Importantly, all the satellite HRPPs underestimate precipitation over northwest Europe in all seasons.

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Elizabeth E. Ebert, Michael Turk, Sheldon J. Kusselson, Jianbin Yang, Matthew Seybold, Peter R. Keehn, and Robert J. Kuligowski

Abstract

Ensemble tropical rainfall potential (eTRaP) has been developed to improve short-range forecasts of heavy rainfall in tropical cyclones. Evolving from the tropical rainfall potential (TRaP), a 24-h rain forecast based on estimated rain rates from microwave sensors aboard polar-orbiting satellites, eTRaP combines all single-pass TRaPs generated within ±3 h of 0000, 0600, 1200, and 1800 UTC to form a simple ensemble. This approach addresses uncertainties in satellite-derived rain rates and spatial rain structures by using estimates from different sensors observing the cyclone at different times. Quantitative precipitation forecasts (QPFs) are produced from the ensemble mean field using a probability matching approach to recalibrate the rain-rate distribution against the ensemble members (e.g., input TRaP forecasts) themselves. ETRaPs also provide probabilistic forecasts of heavy rain, which are potentially of enormous benefit to decision makers. Verification of eTRaP forecasts for 16 Atlantic hurricanes making landfall in the United States between 2004 and 2008 shows that the eTRaP rain amounts are more accurate than single-sensor TRaPs. The probabilistic forecasts have useful skill, but the probabilities should be interpreted within a spatial context. A novel concept of a “radius of uncertainty” compensates for the influence of location error in the probability forecasts. The eTRaPs are produced in near–real time for all named tropical storms and cyclones around the globe. They can be viewed online (http://www.ssd.noaa.gov/PS/TROP/etrap.html) and are available in digital form to users.

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Stanley Q. Kidder, John A. Knaff, Sheldon J. Kusselson, Michael Turk, Ralph R. Ferraro, and Robert J. Kuligowski

Abstract

Inland flooding caused by heavy rainfall from landfalling tropical cyclones is a significant threat to life and property. The tropical rainfall potential (TRaP) technique, which couples satellite estimates of rain rate in tropical cyclones with track forecasts to produce a forecast of 24-h rainfall from a storm, was developed to better estimate the magnitude of this threat. This paper outlines the history of the TRaP technique, details its current algorithms, and offers examples of its use in forecasting. Part II of this paper covers verification of the technique.

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