The Green Ocean: Precipitation Insights from the GoAmazon2014/5 Experiment

Wang, Dié; Giangrande, Scott; Bartholomew, Mary Jane; Hardin, Joseph; Feng, Zhe; Thalman, Ryan; Machado, Luiz A. T.

doi:10.5194/acp-2018-101

Cited by 16 publications

(25 citation statements)

References 35 publications

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“…For completeness, Table includes a cumulative ENA data set relationship and a matched relationship for Deep conditions. In these examples, cumulative and Deep cloud conditions report empirical fit coefficients more in line with widespread stratiform rainfall studies from previous ARM midlatitude convective and/or Amazon tropical X band efforts (e.g., Giangrande, Collis, et al, ; Wang et al, ).…”

Section: Low Cloud Precipitation: Relationships With Cloud Propertiessupporting

confidence: 78%

“…These wavelengths are those most relevant for the ARM ENA facility radars. Additional details on disdrometer processing from previous ARM deployments and similar units are described in Giangrande, Bartholomew, et al (), Giangrande, Collis, et al (), Thompson et al (), and Wang et al (). For this data set, 5‐min DSD aggregation windows are used to reduce possible noisiness found in 1‐min light rain observations.…”

Section: The Arm Ena Site: Instruments and Data Set Processing Overviewmentioning

confidence: 99%

“…Numerous disdrometer data sets have expanded the archive of detailed, quantitative precipitation characteristics into remote global environments, strengthening opportunities for cloud process studies in support of global climate model improvement (e.g., Dolan et al, ; Giangrande, Bartholomew, et al, ; Leinonen et al, ; Thompson et al, ; Wang et al, ). Several efforts focus on surface‐based DSD regime classifications to isolate convective clouds and processes (typically, higher drop concentrations) from stratiform (typically, smaller drop concentrations), as introduced by Bringi et al (, ) predominantly in Darwin, Australia, for maritime continental deeper convective system contexts.…”

Section: Seasonal and Cloud Regime Precipitation Breakdowns: An Intermentioning

confidence: 99%

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Midlatitude Oceanic Cloud and Precipitation Properties as Sampled by the ARM Eastern North Atlantic Observatory

et al. 2019

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Marine low clouds are critical to the climate system because of their extensive coverage and associated controls on boundary layer dynamics and radiative energy balance. The primary foci for this study are marine low cloud observations over a heavily instrumented site on the Azores archipelago in the Eastern North Atlantic and their associated raindrop size distribution (DSD) properties, relative low cloud contributions to the precipitation, and additional sampling (instrument, environmental) considerations. The contribution from low clouds (e.g., cloud top < 4 km) to the overall precipitation over midlatitude oceans is poorly understood, in part because of the lack of coupled, high‐quality measurements of precipitation and low cloud properties. Cloud regime and precipitation breakdowns performed for a multiyear (2014–2017) record emphasize diurnal precipitation and raindrop size distribution characteristics for both low and deeper clouds, as well as differences between the two disdrometer types used. Results demonstrate that marine low clouds over this Eastern North Atlantic location account for a significant (45%) contribution to the total rainfall and exhibit a diurnal cycle in cloud (thickness, top, and base) and precipitation characteristics similar to satellite records. Additional controls on observed surface rainfall characteristics of low clouds allowed by the extended ground‐based facility data sets are also explored. From those analyses, it is suggested that the synoptic state exerts a significant control on low cloud and surface precipitation properties.

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Section: Low Cloud Precipitation: Relationships With Cloud Propertiessupporting

confidence: 78%

Section: The Arm Ena Site: Instruments and Data Set Processing Overviewmentioning

confidence: 99%

Section: Seasonal and Cloud Regime Precipitation Breakdowns: An Intermentioning

confidence: 99%

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Midlatitude Oceanic Cloud and Precipitation Properties as Sampled by the ARM Eastern North Atlantic Observatory

et al. 2019

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“…Nevertheless, there are several areas that still necessitate further research to complete the picture of cloud processes in Amazonas. For instance, a detailed microphysical description of clouds as a function of the two patterns of convection, cumuliform, and deep convection is still wanting (see Wang et al, 2018). Changes in the microphysical properties and mixed phase are some of the unknown behaviours of cloud processes.…”

Section: Discussionmentioning

confidence: 99%

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

et al. 2018

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Abstract. 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 massweighted 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 durPublished by Copernicus Publications on behalf of the European Geosciences Union. L. A. T. Machado et al.: Overview: Precipitation characteristics and sensitivities to environmental conditionsing 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.

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“…During the transition season, however, the average precipitating cloud profile contains more upper‐level cloud water, although the cloud top height of deep clouds is similar to that during dry and wet seasons (Figure S4). The cloud top height for daytime deep clouds in all seasons detected by CloudSat is about 2–3 km higher than the cloud top detected by ground‐based RWP near Manacapuru, Brazil, possibly because the 1,290‐MHz RWP is not sensitive to cloud‐sized particles (Wang et al, ). During the transition season, CAPE, boundary layer air temperature, and surface heat fluxes on rainy days (Figures S3 and S5) all reach their yearly maxima, broadly consistent with in situ observations (Zhuang et al, ).…”

Section: Climatology Of Precipitating Clouds and Meteorological Parammentioning

confidence: 99%

Thresholds for Atmospheric Convection in Amazonian Rainforests

Lee

2019

Geophysical Research Letters

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The Amazon rainforest is known as the “Green Ocean” for its maritime‐like convection and cloud microphysics during the wet season. Although previous studies suggest the dominant thermodynamic processes involved in deep convection may differ between land and ocean, a comprehensive understanding of the thermodynamics of Amazonian convection is lacking. Using 404,971 daytime precipitating cloud profiles from the CloudSat satellite, we observe a regime transition from congestus dominance to cumulonimbus dominance when convective available potential energy exceeds a threshold in Amazonia and also in shrublands, but not in oceanic regions. In addition, the cloud regime transition is linked to boundary layer moisture in the two continental regions, while it is linked to lower‐free‐tropospheric moisture in the oceanic region. As the dry season progresses in Amazonia and modifies the free‐tropospheric stability, a moderate plant water stress and increased incoming solar energy facilitate the initiation of deep convection and the onset of the wet season.

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The Green Ocean: Precipitation Insights from the GoAmazon2014/5 Experiment

Abstract: Abstract. This study summarizes the precipitation properties collected during the GoAmazon2014/5 campaign near Manaus in central Amazonia, Brazil. Precipitation breakdowns, summary radar rainfall relationships and self-consistency concepts

Cited by 16 publications

References 35 publications

Midlatitude Oceanic Cloud and Precipitation Properties as Sampled by the ARM Eastern North Atlantic Observatory

Midlatitude Oceanic Cloud and Precipitation Properties as Sampled by the ARM Eastern North Atlantic Observatory

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

Thresholds for Atmospheric Convection in Amazonian Rainforests

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