Assessment of Ground-Reference Data and Validation of the H-SAF Precipitation Products in Brazil

Abstract

The uncertainties associated with rainfall estimates comprise various measurement scales: from rain gauges and ground-based radars to the satellite rainfall retrievals. The quality of satellite rainfall products has improved significantly in recent decades; however, such algorithms require validation studies using observational rainfall data. For this reason, this study aims to apply the H-SAF consolidated radar data processing to the X-band radar used in the CHUVA campaigns and apply the well established H-SAF validation procedure to these data and verify the quality of EUMETSAT H-SAF operational passive microwave precipitation products in two regions of Brazil (Vale do Paraíba and Manaus). These products are based on two rainfall retrieval algorithms: the physically based Bayesian Cloud Dynamics and Radiation Database (CDRD algorithm) for SSMI/S sensors and the Passive microwave Neural network Precipitation Retrieval algorithm (PNPR) for cross-track scanning radiometers (AMSU-A/AMSU-B/MHS sensors) and for the ATMS sensor. These algorithms, optimized for Europe, Africa and the Southern Atlantic region, provide estimates for the MSG full disk area. Firstly, the radar data was treated with an overall quality index which includes corrections for different error sources like ground clutter, range distance, rain-induced attenuation, among others. Different polarimetric and non-polarimetric QPE algorithms have been tested and the Vulpiani algorithm (hereafter, R q 2 V u 15 ) presents the best precipitation retrievals when compared with independent rain gauges. Regarding the results from satellite-based algorithms, generally, all rainfall retrievals tend to detect a larger precipitation area than the ground-based radar and overestimate intense rain rates for the Manaus region. Such behavior is related to the fact that the environmental and meteorological conditions of the Amazon region are not well represented in the algorithms. Differently, for the Vale do Paraíba region, the precipitation patterns were well detected and the estimates are in accordance with the reference as indicated by the low mean bias values.

A New Orbiting Deployable System for Small Satellite Observations for Ecology and Earth Observation

“…A typical output of this application consists of reflectivity measurements collected at different altitudes within the tropospheric columns, called the Vertical Profile of Reflectivity (VPR) (e.g., [249]). A quality control chain is needed to remove random and systematic errors, including the correction of the vertical reflectivity profiles (i.e., removal of bright band effects), and the mitigation of attenuation along the path (e.g., [250][251][252]). This quality control procedure is propaedeutic for a proper validation of the measures, performed through reflectivity data collected by traditional ground-based weather radar, and for a real time application inherent to the monitoring of precipitation events.…”

RAINBOW: An Operational Oriented Combined IR-Algorithm

“…At the end of this operational process chain, the Surface Rainfall Intensity (SRI) product is provided over a 1 × 1 km 2 grid with a temporal resolution of 10 min. The SRI is obtained taking into account the orography (and the clutter associated), the technical characteristics of the radar (e.g., the various elevation angles and the scanning time frequency, the correction of the partial beam blocking [74,75]. In particular, the single-site SRI is estimated considered the whole radar volume in polar coordinates, then the national The processing system aims at identifying most of the uncertainty sources in order to compensate them, whenever it is possible, before estimating precipitation.…”

“…In particular, the single-site SRI is estimated considered the whole radar volume in polar coordinates, then the national composite is computed in Cartesian coordinates. For a given geographical location, the single site SRI is retrieved combining the radar observations at all elevation scans θ k , through a quality-weighted average [71,75,76]. Finally, the national SRI composite is built by combining the single-radar rainfall maps through a quality-weighted approach.…”

Editorial for Special Issue “Remote Sensing of Precipitation”

“…The study by Lu et al [13] assesses the performance of the latest GPM Integrated Multi-satellite Retrievals (IMERG V5) and Global Satellite Mapping of Precipitation version 7 (GSMaP V7) products and their hydrological application over the Tibetan Plateau. Two IMERG Final Run products Martins Costa do Amaral et al [14] apply the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) consolidated radar data processing to the X-band radar used in the CHUVA (Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement) campaigns in Brazil. They apply the well-established H-SAF validation procedure to these data and verify the quality of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) H-SAF operational passive microwave precipitation products in two regions of Brazil, namely, Vale do Paraíba and Manaus.…”