ALBERT

Description: This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. This study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weighted mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.

Description: 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.

Description: This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM–PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h−1 (PR) and −0.157 mm h−1 (S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 (PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM–Large-Scale Biosphere–Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h−1. NESDIS1 overestimated for both wind regimes but presented the best westerly representation. NESDIS2, GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

Description: The GOES-16 mesoscale domain sector (MDS) scans with 1-min intervals are used in this study to analyze a severe thunderstorm case that occurred in southeastern Brazil. The main objective is to evaluate the GOES-16 MDS rapid scans against the operational full-disk scans with lower temporal resolution for nowcasting. Data from a C-band radar, observed sounding, and a ground-based lightning network are also used in the analysis. A group of thunderstorms formed in the afternoon of 29 November 2017 in an environment of moderate convective available potential energy (CAPE) and deep-layer shear. The storms presented supercell characteristics and intense lightning activity with peak rates in excess of 150 flashes per 5 min. The satellite-derived trends with 1-min interval were skillful in detecting thunderstorm intensification, mainly in the developing stage. The decrease in cloud-top 10.35-μm brightness temperature was accompanied by increases in ice mass flux, concentration of small ice particles at cloud top, and storm depth. In the mature stage, there is no evident trend in the satellite-derived parameters that could indicate storm intensification, but the cluster area expands suggesting cloud-top divergence. The 1-min rapid scans indicate greater lead time to severe weather relative to 10- and 15-min-resolution imagery, but also presented numerous false alarms (indication of severe weather but no occurrence) due to oscillations in the satellite-derived parameters. The parameters calculated every 5 min presented better skill than 10 and 15 min and fewer false alarms than 1 min.

Description: CHUVA, meaning “rain” in Portuguese, is the acronym for the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (GPM). The CHUVA project has conducted five field campaigns; the sixth and last campaign will be held in Manaus in 2014. The primary scientific objective of CHUVA is to contribute to the understanding of cloud processes, which represent one of the least understood components of the weather and climate system. The five CHUVA campaigns were designed to investigate specific tropical weather regimes. The first two experiments, in Alcantara and Fortaleza in northeastern Brazil, focused on warm clouds. The third campaign, which was conducted in Belém, was dedicated to tropical squall lines that often form along the sea-breeze front. The fourth campaign was in the Vale do Paraiba of southeastern Brazil, which is a region with intense lightning activity. In addition to contributing to the understanding of cloud process evolution from storms to thunderstorms, this fourth campaign also provided a high-fidelity total lightning proxy dataset for the NOAA Geostationary Operational Environmental Satellite (GOES)-R program. The fifth campaign was carried out in Santa Maria, in southern Brazil, a region of intense hailstorms associated with frequent mesoscale convective complexes. This campaign employed a multimodel high-resolution ensemble experiment. The data collected from contrasting precipitation regimes in tropical continental regions allow the various cloud processes in diverse environments to be compared. Some examples of these previous experiments are presented to illustrate the variability of convection across the tropics.

Description: The dominant hydrometeor types associated with Brazilian tropical precipitation systems are identified via research X-band dual-polarization radar deployed in the vicinity of the Manaus region (Amazonas) during both the GoAmazon2014/5 and ACRIDICON-CHUVA field experiments. The present study is based on an agglomerative hierarchical clustering (AHC) approach that makes use of dual polarimetric radar observables (reflectivity at horizontal polarization ZH, differential reflectivity ZDR, specific differential-phase KDP, and correlation coefficient ρHV) and temperature data inferred from sounding balloons. The sensitivity of the agglomerative clustering scheme for measuring the intercluster dissimilarities (linkage criterion) is evaluated through the wet-season dataset. Both the weighted and Ward linkages exhibit better abilities to retrieve cloud microphysical species, whereas clustering outputs associated with the centroid linkage are poorly defined. The AHC method is then applied to investigate the microphysical structure of both the wet and dry seasons. The stratiform regions are composed of five hydrometeor classes: drizzle, rain, wet snow, aggregates, and ice crystals, whereas convective echoes are generally associated with light rain, moderate rain, heavy rain, graupel, aggregates, and ice crystals. The main discrepancy between the wet and dry seasons is the presence of both low- and high-density graupel within convective regions, whereas the rainy period exhibits only one type of graupel. Finally, aggregate and ice crystal hydrometeors in the tropics are found to exhibit higher polarimetric values compared to those at midlatitudes.

Description: This is study provides an overview of precipitation processes and their sensitivities to environmental conditions, in the Central Amazon Basin, during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. Taking advantage of the numerous measuring platforms and instruments systems operating during both campaigns sampling cloud structure and environmental conditions during 2014 and 2015, the rainfall variability among seasons, aerosol loading, land surface type, and topography have carefully been characterized. Differences between the wet and dry seasons were examined from a variety of different perspectives. The rain rate distribution, the total amount of rainfall, and the raindrop size distribution (the mean mass-weighted diameter) were quantified for the two seasons. The dry season has a higher average rain rate than the wet season and reflects more intense rain. While the cumulative wet season rainfall amount was four times larger than the total dry season rainfall, reflecting in large total rainfall accumulation. The typical size and life cycle of the Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as well their differences among the seasons. Moreover, we analyse the monthly mean thermodynamical and dynamical variables, measured by radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to the atmospheric aerosol loading is discussed with regard to the mean mass-weighted diameter and rain rate. This topic was evaluated during the wet season only due to the insignificant statistics of rainfall events for different ranges of aerosol loadings and the low frequency of precipitation events during the dry season. The aerosol impacts on the cloud droplet diameter is different for small and large drops. For the wet season, we observe no dependence on land surface type on the rain rate. However, during the dry season, urban areas exhibit the largest rain rate tail distribution, and deforested regions have the lowest mean rain rate. Airplane measurements were performed to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. The vertical motion turned out to be uncorrelated with cloud droplet sizes, but the cloud droplets number concentration revealed a linear relationship to the vertical motion. Clouds over forest exhibit larger droplets than clouds over pastures at all cloud levels. Finally, the connections between topography and rain rate were evaluated, showing a higher rain rate over higher elevations for the dry season.

Description: The dominant hydrometeor types associated with Brazilian tropical precipitation systems are identified via research X-band dual-polarization radar deployed in the vicinity of the Manaus region (Amazonas) during both the GoAmazon2014/5 and ACRIDICON-CHUVA field experiments. The present study is based on an Agglomerative Hierarchical Clustering (AHC) approach that makes use of dual polarimetric radar observables (reflectivity at horizontal polarization ZH, differential reflectivity ZDR, specific differential phase KDP, and correlation coefficient ρHV) and temperature data inferred from sounding balloons. The sensitivity of the agglomerative clustering scheme for measuring the inter-cluster dissimilarities (linkage criterion) is evaluated through the wet season dataset. Both the weighted and Ward linkages exhibit better abilities to retrieve cloud microphysical species, whereas clustering outputs associated with the centroid linkage are poorly defined. The AHC method is then applied to investigate the microphysical structure of both the wet and dry seasons. The stratiform regions are composed of five hydrometeor classes: drizzle, rain, wet snow, aggregates, and ice crystals, whereas convective echoes are generally associated with light rain, moderate rain, heavy rain, graupels, aggregates and ice crystals. The main discrepancy between the wet and dry seasons is the presence of both low- and high-density graupels within convective regions, whereas the rainy period exhibits only one type of graupel. Finally, aggregate and ice crystal hydrometeors in the tropics are found to exhibit higher polarimetric values compared to those at mid-latitudes.