Tami Toto

RACORO EXTENDED-TERM AIRCRAFT OBSERVATIONS OF BOUNDARY LAYER CLOUDS

A first-of-a-kind, extended-term cloud aircraft campaign was conducted to obtain an in situ statistical characterization of continental boundary layer clouds needed to investigate cloud processes and refine retrieval algorithms. Coordinated by the Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign operated over the ARM Southern Great Plains (SGP) site from 22 January to 30 June 2009, collecting 260 h of data during 59 research flights. A comprehensive payload aboard the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft measured cloud microphysics, solar and thermal radiation, physical aerosol properties, and atmospheric state parameters. Proximity to the SGPs extensive complement of surface measurements provides ancillary data that support modeling studies and facilitates evaluation of a variety of surface retrieval algorithms. The five-...

Amazon boundary layer aerosol concentration sustained by vertical transport during rainfall

The nucleation of atmospheric vapours is an important source of new aerosol particles that can subsequently grow to form cloud condensation nuclei in the atmosphere. Most field studies of atmospheric aerosols over continents are influenced by atmospheric vapours of anthropogenic origin (for example, ref. 2) and, in consequence, aerosol processes in pristine, terrestrial environments remain poorly understood. The Amazon rainforest is one of the few continental regions where aerosol particles and their precursors can be studied under near-natural conditions, but the origin of small aerosol particles that grow into cloud condensation nuclei in the Amazon boundary layer remains unclear. Here we present aircraft- and ground-based measurements under clean conditions during the wet season in the central Amazon basin. We find that high concentrations of small aerosol particles (with diameters of less than 50 nanometres) in the lower free troposphere are transported from the free troposphere into the boundary layer during precipitation events by strong convective downdrafts and weaker downward motions in the trailing stratiform region. This rapid vertical transport can help to maintain the population of particles in the pristine Amazon boundary layer, and may therefore influence cloud properties and climate under natural conditions.

RACORO continental boundary layer cloud investigations. 2. Large-eddy simulations of cumulus clouds and evaluation with in-situ and ground-based observations

A 60-hour case study of continental boundary layer cumulus clouds is examined using two large-eddy simulation (LES) models. The case is based on observations obtained during the RACORO Campaign (Routine Atmospheric Radiation Measurement [ARM] Aerial Facility [AAF] Clouds with Low Optical Water Depths [CLOWD] Optical Radiative Observations) at the ARM Climate Research Facilitys Southern Great Plains site. The LES models are driven by continuous large-scale and surface forcings, and are constrained by multi-modal and temporally varying aerosol number size distribution profiles derived from aircraft observations. We compare simulated cloud macrophysical and microphysical properties with ground-based remote sensing and aircraft observations. The LES simulations capture the observed transitions of the evolving cumulus-topped boundary layers during the three daytime periods, and generally reproduce variations of droplet number concentration with liquid water content (LWC), corresponding to the gradient between the cloud centers and cloud edges at given heights. The observed LWC values fall within the range of simulated values; the observed droplet number concentrations are commonly higher than simulated, but differences remain on par with potential estimation errors in the aircraft measurements. Sensitivity studies examine the influences of bin microphysics versus bulk microphysics, aerosol advection, supersaturation treatment, and aerosol hygroscopicity. Simulated macrophysical cloud properties are found to be insensitive in this non-precipitating case, but microphysical properties are especially sensitive to bulk microphysics supersaturation treatment and aerosol hygroscopicity.

RACORO continental boundary layer cloud investigations: 1. Case study development and ensemble large‐scale forcings

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60 h case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in situ measurements from the Routine AAF (Atmospheric Radiation Measurement (ARM) Aerial Facility) CLOWD (Clouds with Low Optical Water Depth) Optical Radiative Observations (RACORO) field campaign and remote sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be ~0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing data sets are derived from the ARM variational analysis, European Centre for Medium-Range Weather Forecasts, and a multiscale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in “trial” large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.

Polarimetric radar and aircraft observations of saggy bright bands during MC3E

Polarimetric radar observations increasingly are used to understand cloud microphysical processes, which is critical for improving their representation in cloud and climate models. In particular, there has been recent focus on improving representations of ice collection processes (e.g., aggregation and riming), as these influence precipitation rate, heating profiles, and ultimately cloud life cycles. However, distinguishing these processes using conventional polarimetric radar observations is difficult, as they produce similar fingerprints. This necessitates improved analysis techniques and integration of complementary data sources. The Midlatitude Continental Convective Clouds Experiment (MC3E) provided such an opportunity. Quasi-vertical profiles of polarimetric radar variables in two MC3E stratiform precipitation events reveal episodic melting layer sagging. Integrated analyses using scanning and vertically pointing radar and aircraft measurements reveal that saggy bright band signatures are produced when denser, faster-falling, more isometric hydrometeors (relative to adjacent times) descend into the melting layer. In one case, strong circumstantial evidence for riming is found during bright band sagging times. A bin microphysical melting layer model successfully reproduces many aspects of the signature, supporting the observational analysis. If found to be a reliable indicator of riming, saggy bright bands could be a proxy for the presence of supercooled liquid water in stratiform precipitation, which may provide important information for mitigating aircraft icing risks and for constraining microphysical models.

Convective cloud vertical velocity and mass‐flux characteristics from radar wind profiler observations during GoAmazon2014/5

A radar wind profiler (RWP) dataset collected during the two-year DOE ARM Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign is used to estimate convective cloud vertical velocity, area fraction and mass flux profiles. Vertical velocity observations are presented using cumulative frequency histograms and weighted-mean profiles to provide insights in a manner suitable for GCM-model scale comparisons (spatial domains from 20 km to 60 km). Convective profile sensitivity to changes in environmental conditions and seasonal regime controls is also considered. Aggregate and ensemble average vertical velocity, convective area fraction and mass flux profiles, as well as magnitudes and relative profile behaviors, are found consistent with previous studies. Updrafts and downdrafts increase in magnitude with height to mid-levels (6 to 10 km), with updraft area also increasing with height. Updraft mass flux profiles similarly increase with height, showing a peak in magnitude near 8 km. Downdrafts are observed to be most frequent below the freezing level, with downdraft area monotonically decreasing with height. Updraft and downdraft profile behaviors are further stratified according to environmental controls. These results indicate stronger vertical velocity profile behaviors under higher CAPE and lower low-level moisture conditions. Sharp contrasts in convective area fraction and mass flux profiles are most pronounced when retrievals are segregated according to Amazonian wet and dry season conditions. During this deployment, wet season regimes favored higher domain mass flux profiles, attributed to more frequent convection that offsets weaker average convective cell vertical velocities.

Development of fine‐resolution analyses and expanded large‐scale forcing properties: 1. Methodology and evaluation

We produce fine-resolution, three-dimensional fields of meteorological and other variables for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS-DA) framework that is used within the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. The MS-DA algorithm uses existing reanalysis products and constrains fine-scale atmospheric properties by assimilating high-resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system. Evaluations also show that the large-scale forcing derived from the fine-resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine-resolution fields are used to characterize the contribution of subgrid variability to the large-scale forcing and to derive hydrometeor forcing, which are presented in companion papers.

RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facilitys Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the models shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

Development of fine‐resolution analyses and expanded large‐scale forcing properties: 2. Scale awareness and application to single‐column model experiments

Fine-resolution three-dimensional fields have been produced using the Community Gridpoint Statistical Interpolation (GSI) data assimilation system for the U.S. Department of Energys Atmospheric Radiation Measurement Program (ARM) Southern Great Plains region. The GSI system is implemented in a multiscale data assimilation framework using the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. From the fine-resolution three-dimensional fields, large-scale forcing is derived explicitly at grid-scale resolution; a subgrid-scale dynamic component is derived separately, representing subgrid-scale horizontal dynamic processes. Analyses show that the subgrid-scale dynamic component is often a major component over the large-scale forcing for grid scales larger than 200 km. The single-column model (SCM) of the Community Atmospheric Model version 5 is used to examine the impact of the grid-scale and subgrid-scale dynamic components on simulated precipitation and cloud fields associated with a mesoscale convective system. It is found that grid-scale size impacts simulated precipitation, resulting in an overestimation for grid scales of about 200 km but an underestimation for smaller grids. The subgrid-scale dynamic component has an appreciable impact on the simulations, suggesting that grid-scale and subgrid-scale dynamic components should be considered in the interpretation of SCM simulations.

Insights from modeling and observational evaluation of a precipitating continental cumulus event observed during the MC3E field campaign

A case of shallow cumulus and precipitating cumulus congestus sampled at the Atmospheric Radiation Measurement Program Southern Great Plains supersite during the Midlatitude Continental Convective Clouds Experiment is analyzed using a multisensor observational approach and numerical simulation. Observations from a new radar suite surrounding the facility are used to characterize the evolving statistical behavior of the precipitating cloud system. This is accomplished using distributions of different measures of cloud geometry and precipitation properties. Large-eddy simulation (LES) with size-resolved (bin) microphysics is employed to determine the forcings most important in producing the salient aspects of the cloud system captured in the radar observations. Our emphasis is on assessing the importance of time-varying versus steady state large-scale forcing on the models ability to reproduce the evolutionary behavior of the cloud system. Additional consideration is given to how the characteristic spatial scale and homogeneity of the forcing imposed on the simulation influences the evolution of cloud system properties. Results indicate that several new scanning radar estimates such as distributions of cloud top are useful to differentiate the value of time-varying (or at least temporally well-matched) forcing on LES solution fidelity.