The relative importance of macrophysical and cloud albedo changes for aerosol-induced radiative effects in closed-cell stratocumulus: insight from the modelling of a case study

Aerosol–cloud interactions are explored using 1 km simulations of a case study of predominantly closed-cell SE Pacific stratocumulus clouds. The simulations include realistic meteorology along with newly implemented cloud microphysics and sub-grid cloud schemes. The model was critically assessed against observations of liquid water path (LWP), broadband fluxes, cloud fraction (fc), droplet number concentrations (Nd), thermodynamic profiles, and radar reflectivities. Aerosol loading sensitivity tests showed that at low aerosol loadings, changes to aerosol affected shortwave fluxes equally through changes to cloud macrophysical characteristics (LWP, fc) and cloud albedo changes due solely to Nd changes. However, at high aerosol loadings, only the Nd albedo change was important. Evidence was also provided to show that a treatment of sub-grid clouds is as important as order of magnitude changes in aerosol loading for the accurate simulation of stratocumulus at this grid resolution. Overall, the control model demonstrated a credible ability to reproduce observations, suggesting that many of the important physical processes for accurately simulating these clouds are represented within the model and giving some confidence in the predictions of the model concerning stratocumulus and the impact of aerosol. For example, the control run was able to reproduce the shape and magnitude of the observed diurnal cycle of domain mean LWP to within  ∼  10 g m−2 for the nighttime, but with an overestimate for the daytime of up to 30 g m−2. The latter was attributed to the uniform aerosol fields imposed on the model, which meant that the model failed to include the low-Nd mode that was observed further offshore, preventing the LWP removal through precipitation that likely occurred in reality. The boundary layer was too low by around 260 m, which was attributed to the driving global model analysis. The shapes and sizes of the observed bands of clouds and open-cell-like regions of low areal cloud cover were qualitatively captured. The daytime fc frequency distribution was reproduced to within Δfc = 0.04 for fc >  ∼ 0.7 as was the domain mean nighttime fc (at a single time) to within Δfc = 0.02. Frequency distributions of shortwave top-of-the-atmosphere (TOA) fluxes from the satellite were well represented by the model, with only a slight underestimate of the mean by 15 %; this was attributed to near–shore aerosol concentrations that were too low for the particular times of the satellite overpasses. TOA long-wave flux distributions were close to those from the satellite with agreement of the mean value to within 0.4 %. From comparisons of Nd distributions to those from the satellite, it was found that the Nd mode from the model agreed with the higher of the two observed modes to within  ∼  15 %

How biased is aircraft cloud sampling?

Aircraft are the dominant method for in-situ sampling of cloud properties. Resource limitations mean that aircraft tend to follow a sampling strategy when there are more that one cloud to choose from. This can result in biased cloud statistics that are used for parametrization development and model testing. In this study, order statistics are used to estimate the potential magnitude of this bias when a strategy based on choosing the larger cloud is employed. It is found, for cloud properties following gamma distributions, that a typical bias of a factor of 1.5 can result when the larger of two clouds are repeatedly chosen for sampling

Scalability tests of R-GMA-based grid job monitoring system for CMS Monte Carlo data production

Copyright @ 2004 IEEEHigh-energy physics experiments, such as the compact muon solenoid (CMS) at the large hadron collider (LHC), have large-scale data processing computing requirements. The grid has been chosen as the solution. One important challenge when using the grid for large-scale data processing is the ability to monitor the large numbers of jobs that are being executed simultaneously at multiple remote sites. The relational grid monitoring architecture (R-GMA) is a monitoring and information management service for distributed resources based on the GMA of the Global Grid Forum. We report on the first measurements of R-GMA as part of a monitoring architecture to be used for batch submission of multiple Monte Carlo simulation jobs running on a CMS-specific LHC computing grid test bed. Monitoring information was transferred in real time from remote execution nodes back to the submitting host and stored in a database. In scalability tests, the job submission rates supported by successive releases of R-GMA improved significantly, approaching that expected in full-scale production

Simulated Lightning in a Convection Permitting Global Model

High‐resolution (grid spacing 10 km in midlatitudes) model simulations using explicitly resolved convection in the Met Office Unified Model, as part of the Horizon 2020 PRIMAVERA project, are used to provide a global lightning climatology. The results show for the first time that global simulations can capture the strong diurnal flash rate variation as well as the seasonal variation. The lightning parametrization uses information about the graupel and ice water path to estimate a total lightning flash rate. Comparisons are made with the World Lightning Location Network (that mainly detects cloud to ground lightning) and combined Lightning Imaging Sensor and Optical Transients Detector data set (that provides an estimate of total flash rate). The model results generally capture the temporal behavior and spatial distribution of the lightning over land. Over the ocean, the lightning in the Intertropical Convergence Zone appears excessive

Opinion: Cloud-phase climate feedback and the importance of ice-nucleating particles

Shallow clouds covering vast areas of the world's middle- and high-latitude oceans play a key role in dampening the global temperature rise associated with CO2. These clouds, which contain both ice and supercooled water, respond to a warming world by transitioning to a state with more liquid water and a greater albedo, resulting in a negative “cloud-phase” climate feedback component. Here we argue that the magnitude of the negative cloud-phase feedback component depends on the amount and nature of the small fraction of aerosol particles that can nucleate ice crystals. We propose that a concerted research effort is required to reduce substantial uncertainties related to the poorly understood sources, concentration, seasonal cycles and nature of these ice-nucleating particles (INPs) and their rudimentary treatment in climate models. The topic is important because many climate models may have overestimated the magnitude of the cloud-phase feedback, and those with better representation of shallow oceanic clouds predict a substantially larger climate warming. We make the case that understanding the present-day INP population in shallow clouds in the cold sector of cyclone systems is particularly critical for defining present-day cloud phase and therefore how the clouds respond to warming. We also need to develop a predictive capability for future INP emissions and sinks in a warmer world with less ice and snow and potentially stronger INP sources

A method to represent subgrid-scale updraft velocity in kilometer-scale models: Implication for aerosol activation

©2014. American Geophysical Union. All Rights Reserved. Updraft velocities strongly control the activation of aerosol particles or that component that act as cloud condensation nuclei (CCN). For kilometer-scale models, vertical motions are partially resolved but the subgrid-scale (SGS) contribution needs to be parametrized or constrained to properly represent the activation of CCNs. This study presents a method to estimate the missing SGS (or unresolved) contribution to vertical velocity variability in models with horizontal grid sizes up to ∼2 km. A framework based on Large Eddy Simulations (LES) and high-resolution aircraft observations of stratocumulus and shallow cumulus clouds has been developed and applied to output from the United Kingdom Met Office Unified Model (UM) operating at kilometer-scale resolutions in numerical weather prediction configuration. For a stratocumulus deck simulation, we show that the UM 1 km model underestimates significantly the variability of updraft velocity with an averaged cloud base standard deviation between 0.04 and 0.05 m s-1 compared to LES and aircraft estimates of 0.38 and 0.54 m s-1, respectively. Once the SGS variability is considered, the UM corrected averages are between 0.34 and 0.44 m s-1. Off-line calculations of CCN-activated fraction using an activation scheme have been performed to illustrate the implication of including the SGS vertical velocity. It suggests increased CCN-activated fraction from 0.52 to 0.89 (respectively, 0.10 to 0.54) for a clean (respectively, polluted) aerosol environment for simulations with a 1 km horizontal grid size. Our results highlight the importance of representing the SGS vertical velocity in kilometer-scale simulations of aerosol-cloud interactions. Key PointsWe seek to improve the aerosol activation behavior in kilometer-scale modelsA method to constrain the subgrid-scale updraft velocity is presentedWe highlight the potential implication for aerosol-cloud interactions modeling.This work was funded by the Natural Environment Research Council (NERC) Aerosol-Cloud Interactions—a Directed Programme to Reduce Uncertainty in Forcing (ACID-PRUF) programme, grant code NE/I020121/1. The authors thank the scientists, ground crew and aircrew of the FAAM BAe-146 and C-130 aircraft, who were instrumental in the collection of the data analyzed from the VOCALS-REx campaign. The C-130 data were provided by NCAR/EOL, under sponsorship of the National Science Foundation. http://data.eol. ucar.edu/. The FAAM BAe-146 is jointly funded by the UK Met Office and the Natural Environment Research Council. VOCALS was supported by the UK Met Office and NERC, the latter through grant NE/F019874/1

Prediction of heavy precipitation in the eastern China flooding events of 2016: Added value of convection‐permitting simulations

During the period from June 30th to July 6th, 2016, a heavy rainfall event affected the middle and lower reaches of the Yangtze River valley in eastern China. The event was characterized by high‐intensity, long‐duration (lasted more than 6 days) precipitation and huge amounts (over 600.0 mm) of rainfall. The rainfall moved eastward from the Sichuan basin to the middle Yangtze River valley during the first 2 days, then Mei‐yu front formed and circulations became more “quasi‐stationary”. During the second‐phase, successive heavy rainfall systems occurred repeatedly over the same areas along the front, leading to widespread and catastrophic flooding. In this study, limited‐area convection‐permitting models (CPMs) covering all of eastern China, and global‐model simulations from the Met Office Unified Model are compared to investigate the added values of CPMs on the veracity of short‐range predictions of the heavy rainfall event. The results show that all the models can successfully simulate the accumulated amount and the evolution of this heavy rainfall event. However, the global model produces too much light rainfall (10.0 mm/day), fails to simulate the small‐scale features of both atmospheric circulations and precipitation, and tends to generate steady heavy rainfall over mountainous region. Afternoon precipitation is also excessively suppressed in global model. By comparison, the CPMs add some value in reproducing the spatial distribution of precipitation, the smaller‐scale disturbances within the rain‐bands, the diurnal cycle of precipitation and also reduce the spurious topographical rainfall, although there is a tendency for heavy rainfall to be too intense in CPMs

Chapter 6: Ice-Phase Precipitation

Ice-phase precipitation occurs at Earth’s surface and may include various types of pristine crystals, rimed crystals, freezing droplets, secondary crystals, aggregates, graupel, hail, or combinations of any of these. Formation of ice-phase precipitation is directly related to environmental and cloud meteorological parameters that include available moisture, temperature, and three-dimensional wind speed and turbulence, as well as processes related to nucleation, cooling rate, and microphysics. Cloud microphysical parameters in the numerical models are resolved based on various processes such as nucleation, mixing, collision and coalescence, accretion, riming, secondary ice particle generation, turbulence, and cooling processes. These processes are usually parameterized based on assumed particle size distributions and ice crystal microphysical parameters such as mass, size, and number and mass density. Microphysical algorithms in the numerical models are developed based on their need for applications. Observations of ice-phase precipitation are performed using in situ and remote sensing platforms, including radars and satellite-based systems. Because of the low density of snow particles with small ice water content, their measurements and predictions at the surface can include large uncertainties. Wind and turbulence affecting collection efficiency of the sensors, calibration issues, and sensitivity of ground-based in situ observations of snow are important challenges to assessing the snow precipitation. This chapter’s goals are to provide an overview for accurately measuring and predicting ice-phase precipitation. The processes within and below cloud that affect falling snow, as well as the known sources of error that affect understanding and prediction of these processes, are discussed

Effects of aerosol in simulations of realistic shallow cumulus cloud fields in a large domain

Previous study of shallow convection has generally suffered from having to balance domain size with resolution, resulting in high-resolution studies which do not capture large-scale behaviour of the cloud fields. In this work we hope to go some way towards addressing this by carrying out cloud-resolving simulations on large domains. Simulations of trade wind cumulus are carried out using the Met Office Unified Model (UM), based on a case study from the Rain In Cumulus over the Ocean (RICO) field campaign. The UM is run with a nested domain of 500 km with 500 m resolution, in order to capture the large-scale behaviour of the cloud field, and with a double-moment interactive microphysics scheme. Simulations are run using baseline aerosol profiles based on observations from RICO, which are then perturbed. We find that the aerosol perturbations result in changes to the convective behaviour of the cloud field, with higher aerosol leading to an increase (decrease) in the number of deeper (shallower) clouds. However, despite this deepening, there is little increase in the frequency of higher rain rates. This is in contrast to the findings of previous work making use of idealised simulation setups. In further contrast, we find that increasing aerosol results in a persistent increase in domain mean liquid water path and decrease in precipitation, with little impact on cloud fraction

Contrasting Responses of Idealised and Realistic Simulations of Shallow Cumuli to Aerosol Perturbations

Shallow clouds remain greatly significant in improving our understanding of the atmosphere. Using the Met Office Unified Model, we compare highly idealised simulations of shallow cumuli with those using more realistic domains, with open lateral boundaries and varying large-scale forcing. We find that the realistic simulations are more capable of representing the cloud field on large spatial scales, and appear to limit the aerosol perturbations leading to impacts on the thermodynamic conditions. Aerosol perturbations lead to changes in the cloud vertical structure, and thermodynamic evolution of the idealised simulations; a central feature of behavior seen previously in idealised simulations. Modelling approaches with open boundaries and time-varying forcing may allow for improved representation of shallow clouds in the atmosphere, and greater understanding of how they may respond to perturbations