393 research outputs found
Rotating radiative-convective equilibrium simulated by a cloud-resolving model
The results of a series of cloud-resolving radiative-convective equilibrium (RCE) simulations are presented. The RCE simulations, used as an idealization for the mean tropical climate, are run for a wide range of prescribed sea-surface temperatures (SSTs), from 21[superscript o]C to 36[superscript o]C, representing the range of past, present, and, possibly, future mean tropical SSTs. The RCE with constant Coriolis parameter f is contrasted with nonrotating RCE. The Coriolis parameter is artificially increased from typical values in the Tropics by about one order of magnitude to allow multiple tropical cyclones (TCs) to coexist in a relatively small 2300 Ă 2300 km[superscript 2] domain with a 3 km horizontal grid spacing. Nonrotating RCE is also simulated, but using a substantially smaller, 384 Ă 384 km[superscript 2] domain. Rotating RCE, which we nickname âTC World,â contains from 8 to 26 TCs with the average number of TCs monotonically decreasing with increasing SST. At the same time, the TCs' size, intensity, and per-TC precipitation rate tend to increase in response to increasing SST. For example, the average per-TC kinetic energy and precipitation rate tend to double for every 6[superscript o]C SST increase. These results are consistent with scaling laws in which TC velocities and inner core diameters scale with the potential intensity and its ratio to the Coriolis parameter, respectively, while the separation between cyclone centers appears to scale with the deformation radius. It is also found that the outflow temperature of TC's, as defined as the height of the local maximum of the upper-troposphere cloud fraction, remains relatively invariant with SST. The cold-point tropopause height in TC World is found to be about 2 km higher than the corresponding height in nonrotating RCE.National Science Foundation (U.S.) (Grant AGS1032244
Large-eddy simulation of stratocumulus-topped boundary layer with an explicit and a new bulk microphysics scheme.
The realism of the model is evaluated by a direct comparison of the model predictions with the aircraft observations of the STBL. The first case study is based on the UKMRF flight 526 measurements collected over the North Sea on 22 July 1982; the second case study corresponds to the ASTEX flight A209 flown on 12-13 June 1992. The model is able to reproduce reasonably well most of the observed boundary layer parameters, including turbulent fluxes and variances of various fields, intensity and vertical distribution of the turbulent kinetic energy, upward and downward radiation fluxes, and the cloud drop spectra.I designed a new bulk microphysical parameterization using the explicit model as a benchmark for comparison. The liquid water is divided into two categories--non-precipitable cloud water and drizzle, similar to traditional Kessler-type parameterizations. The water content and drop concentration are predicted for each category. The source/sink terms such as autoconversion of cloud water into drizzle are deduced directly from the drop size spectra predicted by the explicit microphysical model. The predictions of the LES model using the new bulk microphysics are compared with the predictions using explicit microphysics for two cases: non-drizzling and heavy-drizzling STBL. The results show that the new bulk microphysical model satisfactorily reproduces many characteristics of the STBL as simulated by explicit microphysical model.A case of stratocumulus-to-cumulus transition triggered by the depletion of CCN is simulated. It is shown that the response of the STBL to the increase in drizzle due to CCN depletion is the reduction of its cloud fractional cover and change of the character of circulation toward the cumulus convection. The boundary layer after the Sc-to-Cu transition consists of two layers: the well-mixed cloud free surface layer driven by surface heat fluxes and shear, and the conditionally unstable upper layer capped by the inversion with embedded cumulus clouds connected to the moisture and CCN supply in the surface layer.A new LES dynamical framework coupled with an explicit microphysical module has been developed. It is verified against analytical solution (linear mountain wave test) and against predictions from the other LES models. The results of the tests of the microphysical module convincingly show that the drop spectrum resolution in our model is adequate to accurately predict the cloud microphysics parameters
Super-Droplet Method for the Numerical Simulation of Clouds and Precipitation: a Particle-Based Microphysics Model Coupled with Non-hydrostatic Model
A novel simulation model of cloud microphysics is developed, which is named
Super-Droplet Method (SDM). SDM enables accurate calculation of cloud
microphysics with reasonable cost in computation. A simple SDM for warm rain,
which incorporates sedimentation, condensation/evaporation, stochastic
coalescence, is developed. The methodology to couple SDM and a non-hydrostatic
model is also developed. It is confirmed that the result of our Monte Carlo
scheme for the coalescence of super-droplets agrees fairly well with the
solution of stochastic coalescence equation. A preliminary simulation of a
shallow maritime cumulus formation initiated by a warm bubble is presented to
demonstrate the practicality of SDM. Further discussions are devoted for the
extension and the computational efficiency of SDM to incorporate various
properties of clouds, such as, several types of ice crystals, several sorts of
soluble/insoluble CCNs, their chemical reactions, electrification, and the
breakup of droplets. It is suggested that the computational cost of SDM becomes
lower than spectral (bin) method when the number of attributes becomes
larger than some critical value, which may be
Global Cloud-Resolving Models
Global cloud-resolving models (GCRMs) are a new category of atmospheric global models designed to solve different flavors of the nonhydrostatic equations through the use of kilometer-scale global meshes. GCRMs make it possible to explicitly simulate deep convection, thereby avoiding the need for cumulus parameterization and allowing for clouds to be resolved by microphysical models responding to grid-scale forcing. GCRMs require high-resolution discretization over the globe, for which a variety of mesh structures have been proposed and employed. The first GCRM was constructed 15 years ago, and in recent years, other groups have also begun adopting this approach, enabling the first intercomparison studies of such models. Because conventional general circulation models (GCMs) suffer from large biases associated with cumulus parameterization, GCRMs are attractive tools for researchers studying global weather and climate. In this review, GCRMs are described, with some emphasis on their historical development and the associated literature documenting their use. The advantages of GCRMs are presented, and currently existing GCRMs are listed and described. Future prospects for GCRMs are also presented in the final section
Recommended from our members
Understanding and representing atmospheric convection across scales: recommendations from the meeting held at Dartington Hall, Devon, UK, 28â30 January 2013
As weather and climate models move toward higher resolution, there is growing excitement about potential future improvements in the understanding and prediction of atmospheric convection and its interaction with larger-scale phenomena. A meeting in January 2013 in Dartington, Devon was convened to address the best way to maximise these improvements, specifically in a UK context but with international relevance. Specific recommendations included increased convective-scale observations, high-resolution virtual laboratories, and a system of parameterization test beds with a range of complexities. The main recommendation was to facilitate the development of physically based convective parameterizations that are scale-aware, non-local, non-equilibrium, and stochastic
On the computation of moist-air specific thermal enthalpy
The specific thermal enthalpy of a moist-air parcel is defined analytically
following a method in which specific moist entropy is derived from the Third
Law of thermodynamics. Specific thermal enthalpy is computed by integrating
specific heat content with respect to absolute temperature and including the
impacts of various latent heats (i.e., solid condensation, sublimation,
melting, and evaporation). It is assumed that thermal enthalpies can be set to
zero at K for the solid form of the main chemically inactive components of
the atmosphere (solid- oxygen and nitrogen, hexagonal ice). The moist
thermal enthalpy is compared to already existing formulations of moist static
energy (MSE). It is shown that the differences between thermal enthalpy and the
thermal part of MSE may be quite large. This prevents the use of MSE to
evaluate the enthalpy budget of a moist atmosphere accurately, a situation that
is particularly true when dry-air and cloud parcels mix because of
entrainment/detrainment processes along the edges of cloud. Other differences
are observed when MSE or moist-air thermal enthalpy is plotted on a
psychrometric diagram or when vertical profiles of surface deficit are plotted.Comment: Paper accepted for publication (January 2014) in the Quarterly
Journal of the Royal Meteorological Society (39 pages, 12 Figures, 7 Tables
Monsoon Intraseasonal Oscillations as simulated by the Superparameterized Community Atmosphere Model
The relative success of the Community Atmosphere Model with superparameterized convection (SP-CAM) in simulating the space-time characteristics of the Madden Julian Oscillation encourages us to examine its simulation of the Indian summer monsoon and monsoon intraseasonal oscillations (MISOs). While the model simulates the onset and withdrawal of the Indian monsoon realistically, it has a significant wet bias in boreal summer precipitation over the Asian monsoon region. The space-time characteristics of the MISOs simulated by the SP-CAM are examined in detail and compared with those of the observed MISO to gain insight into the model's bias in simulating the seasonal mean. During northern summer, the model simulates a 20 day mode and a 60 day mode in place of the observed 15 and 45 day modes, respectively. The simulated 20 day mode appears to have no observed analog with a baroclinic vertical structure and strong northward propagation over Indian longitudes. The simulated 60 day mode seems to be a lower-frequency version of the observed 45 day mode with relatively slower northward propagation. The model's underestimation of light rain events and overestimation of heavy rain events are shown to be responsible for the wet bias of the model. More frequent occurrence of heavy rain events in the model is, in turn, related to the vertical structure of the higher-frequency modes. Northward propagation of the simulated 20 day mode is associated with a strong cyclonic vorticity at low levels north of the heating maximum associated with a smaller meridional scale of the simulated mode. The simulated vertical structure of heating indicates a strong maximum in the upper troposphere between 200 and 300 hPa. Such a heating profile seems to generate a higher-order baroclinic mode response with smaller meridional structure, stronger low-level cyclonic vorticity, enhanced low-level moisture convergence, and higher precipitation. Therefore, the vertical structure of heating simulated by the cloud-resolving model within SP-CAM may hold the key for improving the precipitation bias in the model
Evaluation of an entraining droplet activation parameterization using in situ cloud data
This study investigates the ability of a droplet activation parameterization (which considers the effects of entrainment and mixing) to reproduce observed cloud droplet
number concentration (CDNC) in ambient clouds. Predictions of the parameterization are compared against cloud averages of CDNC from ambient cumulus and stratocumulus clouds sampled during CRYSTALâFACE (Key West, Florida, July 2002) and CSTRIPE (Monterey, California, July 2003), respectively. The entrainment parameters required by the
parameterization are derived from the observed liquid water content profiles. For the cumulus clouds considered in the study, CDNC is overpredicted by 45% with the adiabatic
parameterization. When entrainment is accounted for, the predicted CDNC agrees within 3.5%. Cloudâaveraged CDNC for stratocumulus clouds is well captured when entrainment is
not considered. In all cases considered, the entraining parameterization compared favorably against a statistical correlation developed from observations to treat entrainment effects on droplet number. These results suggest that including entrainment effects in the calculation of CDNC, as presented here, could address important overprediction biases associated with using adiabatic CDNC to represent cloudâscale average values
Marine stratocumulus aerosol-cloud relationships in the MASE-II experiment: Precipitation susceptibility in eastern Pacific marine stratocumulus
Observational data on aerosol-cloud-drizzle relationships in marine stratocumulus are presented from the second Marine Stratus/Stratocumulus Experiment (MASE-II) carried out in July 2007 over the eastern Pacific near Monterey, California. Observations, carried out in regions of essentially uniform meteorology with localized aerosol enhancements due to ship exhaust (âship tracksâ), demonstrate, in accord with those from numerous other field campaigns, that increased cloud drop number concentration Nc and decreased cloud top effective radius r_e are associated with increased subcloud aerosol concentration. Modulation of drizzle by variations in aerosol levels is
levels is clearly evident.
Variations of cloud base drizzle rate R_(cb) are found to be consistent with the proportionality,
R_(cb) / H^3/N_c, where H is cloud depth. Simultaneous aircraft and A-Train satellite
observations are used to quantify the precipitation susceptibility of clouds to aerosol
perturbations in the eastern Pacific region
The multi-scale aerosol-climate model PNNL-MMF: model description and evaluation
Anthropogenic aerosol effects on climate produce one of the largest uncertainties in estimates of radiative forcing of past and future climate change. Much of this uncertainty arises from the multi-scale nature of the interactions between aerosols, clouds and large-scale dynamics, which are difficult to represent in conventional general circulation models (GCMs). In this study, we develop a multi-scale aerosol-climate model that treats aerosols and clouds across different scales, and evaluate the model performance, with a focus on aerosol treatment. This new model is an extension of a multi-scale modeling framework (MMF) model that embeds a cloud-resolving model (CRM) within each grid column of a GCM. In this extension, the effects of clouds on aerosols are treated by using an explicit-cloud parameterized-pollutant (ECPP) approach that links aerosol and chemical processes on the large-scale grid with statistics of cloud properties and processes resolved by the CRM. A two-moment cloud microphysics scheme replaces the simple bulk microphysics scheme in the CRM, and a modal aerosol treatment is included in the GCM. With these extensions, this multi-scale aerosol-climate model allows the explicit simulation of aerosol and chemical processes in both stratiform and convective clouds on a global scale. <br><br> Simulated aerosol budgets in this new model are in the ranges of other model studies. Simulated gas and aerosol concentrations are in reasonable agreement with observations (within a factor of 2 in most cases), although the model underestimates black carbon concentrations at the surface by a factor of 2â4. Simulated aerosol size distributions are in reasonable agreement with observations in the marine boundary layer and in the free troposphere, while the model underestimates the accumulation mode number concentrations near the surface, and overestimates the accumulation mode number concentrations in the middle and upper free troposphere by a factor of about 2. The overestimation of accumulation model number concentrations in the middle and upper free troposphere is consistent with large aerosol mass fraction above 5 km in the MMF model compared with other models. Simulated cloud condensation nuclei (CCN) concentrations are within the observational variations. Simulated aerosol optical depths (AOD) are in reasonable agreement with observations (within a factor of 2), and the spatial distribution of AOD is consistent with observations, while the model underestimates AOD over regions with strong fossil fuel and biomass burning emissions. Overall, this multi-scale aerosol-climate model simulates aerosol fields as well as conventional aerosol models
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