An algorithm has been developed to identify precipitation features ($75 km2 in size) in two land and two

This paper presents a critical review of a number of popular methods that have been developed to retrieve cloud and precipitation properties from satellite radiance measurements. The emphasis of the paper is on the retrieval uncertainties associated with these methods, as these shape future data assimilation applications, either in the form of direct radiance assimilation or assimilation of retrieved geophysical data, or even in the use of retrieved information as a source of model error characterization. It is demonstrated throughout the paper how cloud and precipitation observing systems developed around seemingly simple concepts are in fact very complex and largely underconstrained, which explains, in part, why assigning realistic errors to these properties has been so elusive in the past. Two primary sources of error that define the observing system are highlighted throughout: (i) the first source is errors associated with the identifi-cation of cloudy scenes from clear scenes and the identification of precipitation in cloudy scenes from nonprecipitating cloudy scenes. The problems of discriminating of cloud clear and cloud precipitation are illustrated using examples drawn from microwave cloud liquid water path and precipitation retrievals. (ii) The second source is errors introduced by the forward model and its related parameters. The forward model generally contains two main components: a model of the atmosphere and the cloud and precipitation

The 3D Goddard Cumulus Ensemble model is used to simulate two convective events observed during the Tropical Rainfall Measuring Mission Large-Scale Biosphere–Atmosphere (TRMM LBA) experiment in Brazil. These two events epitomized the type of convective systems that formed in two distinctly different environments observed during TRMM LBA. The 26 January 1999 squall line formed within a sheared low-level easterly wind flow. On 23 February 1999, convection developed in weak low-level westerly flow, resulting in weakly organized, less intense convection. Initial simulations captured the basic organization and intensity of each event. However, improvements to the model resolution and microphysics produced better simulations as compared to observations. More realistic diurnal convective growth was achieved by lowering the horizontal grid spacing from 1000 to 250 m. This produced a gradual transition from shallow to deep convection that occurred over a span of hours as opposed to an abrupt appearance of deep convection. Eliminating the dry growth of graupel in the bulk microphysics scheme effectively removed the unrealistic presence of high-density ice in the simulated anvil. However, comparisons with radar reflectivity data using contoured-frequency-with-altitude diagrams (CFADs) revealed that the resulting snow contents were too large. The excessive snow was reduced primarily by lowering the collection efficiency of cloud

This paper presents a new scheme that classifies convective and stratiform (C/S) precipitation areas over oceans using microwave brightness temperature. In this scheme, data are first screened to eliminate nonraining pixels. For raining pixels, C/S indices are computed from brightness temperatures and their variability for emission (19 and 37 GHz) and scattering (85 GHz). Since lower-resolution satellite data generally contain mixtures of convective and stratiform precipitation, a probability matching method is employed to relate the C/S index to a convective fraction of precipitation area. The scheme has been applied on synthetic data generated from a dynamical cloud model and radiative transfer computations to simulate the frequencies and resolutions of the Tropical Rainfall Measuring Mission (TRMM) Microwave (TMI) Imager as well as the Special Sensor Microwave/Imager (SSM/I). The results from simulated TMI data during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment agree very well with the ground-based radar classification maps. The classification accuracy degrades when SSM/I data is used, due largely to the lower spatial resolution of the SSM/I. The successful launch of TRMM satellite in November 1997 has made it possible to test this scheme on actual TMI data. Preliminary results of TMI derived C/S classification compared with that from the first spaceborne precipitation radar has shown a very good agreement. Further verification and improvement of this scheme are under way. 1.

[1] This study investigated the consistency between microwave and optical water path

While a large number of methods exist in the literature for retrieving rainfall from passive microwave brightness temperatures, little has been written about the quantitative assessment of the expected uncer-tainties in these rainfall products at various time and space scales. The latter is the result of two factors: sparse validation sites over most of the world’s oceans, and algorithm sensitivities to rainfall regimes that cause inconsistencies against validation data collected at different locations. To make progress in this area, a simple probabilistic algorithm is developed. The algorithm uses an a priori database constructed from the Tropical Rainfall Measuring Mission (TRMM) radar data coupled with radiative transfer computations. Unlike efforts designed to improve rainfall products, this algorithm takes a step backward in order to focus on uncertainties. In addition to inversion uncertainties, the construction of the algorithm allows errors resulting from incorrect databases, incomplete databases, and time- and space-varying databases to be examined. These are quantified. Results show that the simple algorithm reduces errors introduced by imperfect knowledge of precipitation radar (PR) rain by a factor of 4 relative to an algorithm that is tuned to the PR rainfall. Database completeness does not introduce any additional uncertainty at the global scale, while climatologically distinct space/time domains add approximately 25 % uncertainty that cannot be detected by a radiometer alone. Of this value, 20 % is attributed to changes in cloud morphology and microphysics, while 5 % is a result of changes in the rain/no-rain thresholds. All but 2%–3 % of this variability can be accounted for by considering the implicit assumptions in the algorithm. Additional uncertainties introduced by the details of the algorithm formulation are not quantified in this study because of the need for independent measurements that are beyond the scope of this paper. A validation strategy for these errors is outlined. 1.

To provide guidance for the development of satellite microwave rainfall-retrieval algorithms, the basic rela-tionships between emission and scattering signals in natural clouds must be understood. In this study, the relationship between two parameters observed from microwave satellite data—the polarization difference at 19 GHz D and the polarization-corrected temperature PCT—is investigated over the global ocean on a monthly and 58 (lat) 3 58 (long) mean basis. Using data from January and July 1993, the occurrence frequencies and latitudinal variation and horizontal distribution of the D–PCT relationships are investigated. The D–PCT slope is studied by dividing the entire weather range into three regimes: nonprecipitation, light precipitation, and heavy precipitation. The analysis shows that small variation of PCT in the nonprecipitation regime could be achieved by employing a variable coefficient in the PCT definition equation. The slopes in the light precipitation regime are latitude dependent. Although the interpretation is inconclusive, it is felt that the differences in the fractional coverage and the rain layer depth in different latitudes is responsible for the latitudinal dependence. No clear latitudinal dependence of slopes in the heavy precipitation regime is found. The connection of the D–PCT relationship to the performances of an emission-based and a scattering-based rainfall algorithm are investigated using the Second WetNet Precipitation Intercomparison Project rainfall cases. The results of this study emphasize the necessity of incorporating the scattering signal in rainfall rate retrieval algorithms. Additionally, the D–PCT slope information can be used to help categorize precipitation types, which may be useful in determining the specific algorithm best used for a certain precipitation type and/or regime. 1.

Abstract not found

Abstract—For future remote sensing applications the potential of the millimeter wavelength range for precipitation observations from geostationary orbits is investigated. Therefore, a database consisting of hydrometeor profiles from various mid-latitude pre-cipitation cases over Europe and corresponding simulated bright-ness temperatures at 18 microwave frequencies was built using the cloud resolving model Méso-NH and the radiative transfer model MicroWave MODel. The information content of the database was investigated by applying simple statistical methods, as well as developing first-order retrieval approaches. The results show that, particularly for snow and graupel, the total column content can be retrieved accurately with relative errors smaller than 25 % in dominantly stratiform precipitation cases over land and ocean surfaces. The performance for rain-water path is similar to the one for graupel and snow in light precipitation cases. For the cases with higher precipitation amounts, the relative errors for rain-water path are larger particularly over land. The same behavior can be seen in the surface rain rate retrieval with the difference that the relative errors are doubled in comparison to the rain-water path. Algorithms with reduced number of frequencies show that window channels at higher frequencies are important for the surface rain rate retrieval because these are sensitive to the scattering in the ice phase related to the rain below. For the frozen hydrometeor retrieval, good results can be achieved by retrieval algorithms based only on frequencies at 150 GHz and above which are suit-able for geostationary applications due to their reduced demands concerning the antenna size. Index Terms—Hydrometeor, millimeter wave radiometry, re-mote sensing, retrieval, satellite applications. I.

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