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

Abstract

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.

On the Relationship Between the Marine Cold Air Outbreak M Parameter and Low‐Level Cloud Heights in the Midlatitudes

“…However, when we redid the calculations of Table 2 separately for daytime and nighttime observations at the ENA, the results did not change. The site is situated along the northern coast of the Graciosa Island, which displays some variations in topography with elevations up to 400 m south of the site (e.g., Giangrande et al, 2019). When we removed southerly wind conditions from the ENA data set, the sensitivities of Table 2 did change slightly, enough to suggest that the island has some impact on the observations but not enough to bring sensitivities to surface temperature on par with what is found with the SO data sets.…”

The development of rainfall retrievals from radar at Darwin

“…In order to ensure quality DSDs, artifacts that are due to splashing or other causes need to be removed. Following Giangrande et al (2019) and Wang et al (2018)'s analysis of VDIS DSDs, thresholds that check drop fall speed and particle diameter were applied to filter out splashing. After that, the DSDs were averaged to 1 minute to reduce noise and then fitted to a normalized gamma distribution of the form…”

“…determined by two parameters N w and D 0 (Testud et al, 2001). These fits were produced using the method of moments technique in PyDSD (Ulbrich and Atlas, 1998;Hardin and Guy, 2017) utilized in past ARM efforts analyzing VDIS and J-W DSDs (Giangrande et al, 2014a(Giangrande et al, , 2019Wang et al, 2018). In order to ensure a statistically significant sample required to calculate the gamma distribution parameters, only DSDs with greater than 100 drops and rainfall rates greater than 0.5 mm hr −1 were included.…”

“…The relative absence of extended, ground-based rainfall retrieval validation datasets outside of midlatitude regions poses several challenges for potential global rainfall applications and possible model evaluation. DOE ARM operates multiple fixed sites in distinct global regimes, including the Darwin TWP, the Oklahoma Southern Great Plains (SGP) (Sisterson et al, 2016), and Eastern North Atlantic (ENA) site in the Azores (Giangrande et al, 2019). Prior studies that focused on Darwin (Keenan et al, 1998;Bringi et al, 2003Bringi et al, , 2009Thurai et al, 2010) indicate that midlatitude R esimators and DSD variability are less applicable outside of the midlatitudes.…”

Validation of GPM Precipitation Products by Comparison with Ground-Based Parsivel Disdrometers over Jianghuai Region

“…Raindrop size distribution (DSD) is the most fundamental microphysical property of precipitation. Extensive literature has revealed that the DSD characteristics vary with rain categories, geographical locations, storm to storm, and season to season [16][17][18][19][20][21][22][23]. Modeled DSD parameters are crucial for satellite-based rainfall estimation algorithms.…”