Showing papers on "Microphysics published in 2017"

Cloud‐resolving model intercomparison of an MC3E squall line case: Part I—Convective updrafts

Abstract: An intercomparison study of a midlatitude mesoscale squall line is performed using the Weather Research and Forecasting (WRF) model at 1 km horizontal grid spacing with eight different cloud microphysics schemes to investigate processes that contribute to the large variability in simulated cloud and precipitation properties. All simulations tend to produce a wider area of high radar reflectivity (Z_e > 45 dBZ) than observed but a much narrower stratiform area. The magnitude of the virtual potential temperature drop associated with the gust front passage is similar in simulations and observations, while the pressure rise and peak wind speed are smaller than observed, possibly suggesting that simulated cold pools are shallower than observed. Most of the microphysics schemes overestimate vertical velocity and Ze in convective updrafts as compared with observational retrievals. Simulated precipitation rates and updraft velocities have significant variability across the eight schemes, even in this strongly dynamically driven system. Differences in simulated updraft velocity correlate well with differences in simulated buoyancy and low-level vertical perturbation pressure gradient, which appears related to cold pool intensity that is controlled by the evaporation rate. Simulations with stronger updrafts have a more optimal convective state, with stronger cold pools, ambient low-level vertical wind shear, and rear-inflow jets. Updraft velocity variability between schemes is mainly controlled by differences in simulated ice-related processes, which impact the overall latent heating rate, whereas surface rainfall variability increases in no-ice simulations mainly because of scheme differences in collision-coalescence parameterizations.

Open-source nuclear equation of state framework based on the liquid-drop model with Skyrme interaction

Abstract: The equation of state (EOS) of dense matter is an essential ingredient for numerical simulations of core-collapse supernovae and neutron star mergers. The properties of matter near and above nuclear saturation density are uncertain, which translates into uncertainties in astrophysical simulations and their multimessenger signatures. Therefore, a wide range of EOSs spanning the allowed range of nuclear interactions are necessary for determining the sensitivity of these astrophysical phenomena and their signatures to variations in input microphysics. We present a new set of finite temperature EOSs based on experimentally allowed Skyrme forces. We employ a liquid-drop model of nuclei to capture the nonuniform phase of nuclear matter at subsaturation density, which is blended into a nuclear statistical equilibrium EOS at lower densities. We also provide a new, open-source code for calculating EOSs for arbitrary Skyrme parametrizations. We then study the effects of different Skyrme parametrizations on thermodynamical properties of dense astrophysical matter, the neutron star mass-radius relationship, and the core collapse of 15 and 40 solar mass stars.

Investigation of the aerosol–cloud–rainfall association over the Indian summer monsoon region

Abstract: . Monsoonal rainfall is the primary source of surface water in India. Using 12 years of in situ and satellite observations, we examined the association of aerosol loading with cloud fraction, cloud top pressure, cloud top temperature, and daily surface rainfall over the Indian summer monsoon region (ISMR). Our results showed positive correlations between aerosol loading and cloud properties as well as rainfall. A decrease in outgoing longwave radiation and an increase in reflected shortwave radiation at the top of the atmosphere with an increase in aerosol loading further indicates a possible seminal role of aerosols in the deepening of cloud systems. Significant perturbation in liquid- and ice-phase microphysics was also evident over the ISMR. For the polluted cases, delay in the onset of collision–coalescence processes and an enhancement in the condensation efficiency allows for more condensate mass to be lifted up to the mixed colder phases. This results in the higher mass concentration of larger-sized ice-phase hydrometeors and, therefore, implies that the delayed rain processes eventually lead to more surface rainfall. A numerical simulation of a typical rainfall event case over the ISMR using a spectral bin microphysical scheme coupled with the Weather Research Forecasting (WRF-SBM) model was also performed. Simulated microphysics also illustrated that the initial suppression of warm rain coupled with an increase in updraft velocity under high aerosol loading leads to enhanced super-cooled liquid droplets above freezing level and ice-phase hydrometeors, resulting in increased accumulated surface rainfall. Thus, both observational and numerical analysis suggest that high aerosol loading may induce cloud invigoration, thereby increasing surface rainfall over the ISMR. While the meteorological variability influences the strength of the observed positive association, our results suggest that the persistent aerosol-associated deepening of cloud systems and an intensification of surface rain amounts was applicable to all the meteorological sub-regimes over the ISMR. Hence, we believe that these results provide a step forward in our ability to address aerosol–cloud–rainfall associations based on satellite observations over the ISMR.

The path to CAM6: coupled simulations with CAM5.4 and CAM5.5

Abstract: . This paper documents coupled simulations of two developmental versions of the Community Atmosphere Model (CAM) towards CAM6. The configuration called CAM5.4 introduces new microphysics, aerosol, and ice nucleation changes, among others to CAM. The CAM5.5 configuration represents a more radical departure, as it uses an assumed probability density function (PDF)-based unified cloud parameterization to replace the turbulence, shallow convection, and warm cloud macrophysics in CAM. This assumed PDF method has been widely used in the last decade in atmosphere-only climate simulations but has never been documented in coupled mode. Here, we compare the simulated coupled climates of CAM5.4 and CAM5.5 and compare them to the control coupled simulation produced by CAM5.3. We find that CAM5.5 has lower cloud forcing biases when compared to the control simulations. Improvements are also seen in the simulated amplitude of the Nino-3.4 index, an improved representation of the diurnal cycle of precipitation, subtropical surface wind stresses, and double Intertropical Convergence Zone biases. Degradations are seen in Amazon precipitation as well as slightly colder sea surface temperatures and thinner Arctic sea ice. Simulation of the 20th century results in a credible simulation that ends slightly colder than the control coupled simulation. The authors find this is due to aerosol indirect effects that are slightly stronger in the new version of the model and propose a solution to ameliorate this. Overall, in these early coupled simulations, CAM5.5 produces a credible climate that is appropriate for science applications and is ready for integration into the National Center for Atmospheric Research's (NCAR's) next-generation climate model.

Predicting Ice Shape Evolution in a Bulk Microphysics Model

Abstract: A novel bulk microphysics scheme that predicts the evolution of ice properties, including aspect ratio (shape), mass, number, size, and density is described, tested, and demonstrated. The scheme is named the Ice-Spheroids Habit Model with Aspect-Ratio Evolution (ISHMAEL). Ice is modeled as spheroids and is nucleated as one of two species depending on nucleation temperature. Microphysical process rates determine how shape and other ice properties evolve. A third aggregate species is also employed, diversifying ice properties in the model. Tests of ice shape evolution during vapor growth and riming are verified against wind tunnel data, revealing that the model captures habit-dependent riming and its effect on fall speed. Lagrangian parcel studies demonstrate that the bulk model captures ice property evolution during riming and melting compared with a bin model. Finally, the capabilities of ISHMAEL are shown in a 2D kinematic framework with a simple updraft. A direct result of predicting ice shape e...

A self-consistent cloud model for brown dwarfs and young giant exoplanets: comparison with photometric and spectroscopic observations

Abstract: We developed a simple, physical and self-consistent cloud model for brown dwarfs and young giant exoplanets. We compared different parametrisations for the cloud particle size, by either fixing particle radii, or fixing the mixing efficiency (parameter fsed) or estimating particle radii from simple microphysics. The cloud scheme with simple microphysics appears as the best parametrisation by successfully reproducing the observed photometry and spectra of brown dwarfs and young giant exoplanets. In particular, it reproduces the L-T transition, due to the condensation of silicate and iron clouds below the visible/near-IR photosphere. It also reproduces the reddening observed for low-gravity objects, due to an increase of cloud optical depth for low gravity. In addition, we found that the cloud greenhouse effect shifts chemical equilibriums, increasing the abundances of species stable at high temperature. This effect should significantly contribute to the strong variation of methane abundance at the L-T transition and to the methane depletion observed on young exoplanets. Finally, we predict the existence of a continuum of brown dwarfs and exoplanets for absolute J magnitude=15-18 and J-K color=0-3, due to the evolution of the L-T transition with gravity. This self-consistent model therefore provides a general framework to understand the effects of clouds and appears well-suited for atmospheric retrievals.

Idealized Simulations of a Squall Line from the MC3E Field Campaign Applying Three Bin Microphysics Schemes: Dynamic and Thermodynamic Structure

Abstract: The squall-line event on 20 May 2011, during the Midlatitude Continental Convective Clouds (MC3E) field campaign has been simulated by three bin (spectral) microphysics schemes coupled into the Weather Research and Forecasting (WRF) Model. Semi-idealized three-dimensional simulations driven by temperature and moisture profiles acquired by a radiosonde released in the preconvection environment at 1200 UTC in Morris, Oklahoma, show that each scheme produced a squall line with features broadly consistent with the observed storm characteristics. However, substantial differences in the details of the simulated dynamic and thermodynamic structure are evident. These differences are attributed to different algorithms and numerical representations of microphysical processes, assumptions of the hydrometeor processes and properties, especially ice particle mass, density, and terminal velocity relationships with size, and the resulting interactions between the microphysics, cold pool, and dynamics. This study...

Aerosol–cloud interactions in mixed-phase convective clouds – Part 1: Aerosol perturbations

Abstract: . Changes induced by perturbed aerosol conditions in moderately deep mixed-phase convective clouds (cloud top height ∼ 5 km) developing along sea-breeze convergence lines are investigated with high-resolution numerical model simulations. The simulations utilise the newly developed Cloud–AeroSol Interacting Microphysics (CASIM) module for the Unified Model (UM), which allows for the representation of the two-way interaction between cloud and aerosol fields. Simulations are evaluated against observations collected during the COnvective Precipitation Experiment (COPE) field campaign over the southwestern peninsula of the UK in 2013. The simulations compare favourably with observed thermodynamic profiles, cloud base cloud droplet number concentrations (CDNC), cloud depth, and radar reflectivity statistics. Including the modification of aerosol fields by cloud microphysical processes improves the correspondence with observed CDNC values and spatial variability, but reduces the agreement with observations for average cloud size and cloud top height. Accumulated precipitation is suppressed for higher-aerosol conditions before clouds become organised along the sea-breeze convergence lines. Changes in precipitation are smaller in simulations with aerosol processing. The precipitation suppression is due to less efficient precipitation production by warm-phase microphysics, consistent with parcel model predictions. In contrast, after convective cells organise along the sea-breeze convergence zone, accumulated precipitation increases with aerosol concentrations. Condensate production increases with the aerosol concentrations due to higher vertical velocities in the convective cores and higher cloud top heights. However, for the highest-aerosol scenarios, no further increase in the condensate production occurs, as clouds grow into an upper-level stable layer. In these cases, the reduced precipitation efficiency ( PE ) dominates the precipitation response and no further precipitation enhancement occurs. Previous studies of deep convective clouds have related larger vertical velocities under high-aerosol conditions to enhanced latent heating from freezing. In the presented simulations changes in latent heating above the 0∘C are negligible, but latent heating from condensation increases with aerosol concentrations. It is hypothesised that this increase is related to changes in the cloud field structure reducing the mixing of environmental air into the convective core. The precipitation response of the deeper mixed-phase clouds along well-established convergence lines can be the opposite of predictions from parcel models. This occurs when clouds interact with a pre-existing thermodynamic environment and cloud field structural changes occur that are not captured by simple parcel model approaches.

Uncertainty from the choice of microphysics scheme in convection-permitting models significantly exceeds aerosol effects

Abstract: . This study investigates the hydrometeor development and response to cloud droplet number concentration (CDNC) perturbations in convection-permitting model configurations. We present results from a real-data simulation of deep convection in the Congo basin, an idealised supercell case, and a warm-rain large-eddy simulation (LES). In each case we compare two frequently used double-moment bulk microphysics schemes and investigate the response to CDNC perturbations. We find that the variability among the two schemes, including the response to aerosol, differs widely between these cases. In all cases, differences in the simulated cloud morphology and precipitation are found to be significantly greater between the microphysics schemes than due to CDNC perturbations within each scheme. Further, we show that the response of the hydrometeors to CDNC perturbations differs strongly not only between microphysics schemes, but the inter-scheme variability also differs between cases of convection. Sensitivity tests show that the representation of autoconversion is the dominant factor that drives differences in rain production between the microphysics schemes in the idealised precipitating shallow cumulus case and in a subregion of the Congo basin simulations dominated by liquid-phase processes. In this region, rain mass is also shown to be relatively insensitive to the radiative effects of an overlying layer of ice-phase cloud. The conversion of cloud ice to snow is the process responsible for differences in cold cloud bias between the schemes in the Congo. In the idealised supercell case, thermodynamic impacts on the storm system using different microphysics parameterisations can equal those due to aerosol effects. These results highlight the large uncertainty in cloud and precipitation responses to aerosol in convection-permitting simulations and have important implications not only for process studies of aerosol–convection interaction, but also for global modelling studies of aerosol indirect effects. These results indicate the continuing need for tighter observational constraints of cloud processes and response to aerosol in a range of meteorological regimes.

Multiple-Scattering Microphysics Tomography

Abstract: Scattering effects in images, including those related to haze, fog and appearance of clouds, are fundamentally dictated by microphysical characteristics of the scatterers. This work defines and derives recovery of these characteristics, in a three-dimensional (3D) heterogeneous medium. Recovery is based on a novel tomography approach. Multi-view (multi-angular) and multi-spectral data are linked to the underlying microphysics using 3D radiative transfer, accounting for multiple-scattering. Despite the nonlinearity of the tomography model, inversion is enabled using a few approximations that we describe. As a case study, we focus on passive remote sensing of the atmosphere, where scatterer retrieval can benefit modeling and forecasting of weather, climate and pollution.

The Importance of the Shape of Cloud Droplet Size Distributions in Shallow Cumulus Clouds. Part II: Bulk Microphysics Simulations

Abstract: In this two-part study, the relationships between the width of the cloud droplet size distribution and the microphysical processes and cloud characteristics of nonprecipitating shallow cumulus clouds are investigated using large-eddy simulations. In Part I, simulations are run with a bin microphysics scheme and the relative widths (standard deviation divided by mean diameter) of the simulated cloud droplet size distributions are calculated. They reveal that the value of the relative width is higher and less variable in the subsaturated regions of the cloud than in the supersaturated regions owing to both the evaporation process itself and enhanced mixing and entrainment of environmental air. Unlike in some previous studies, the relative width is not found to depend strongly on the initial aerosol concentration or mean droplet concentration. Nonetheless, local values of the relative width are found to positively correlate with local values of the droplet concentrations, particularly in the supersat...

Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence

Abstract: Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250m × 20m) to explicitly capture the BL turbulence, associated clouds and entrainment in a global climate model capable of multi-year simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (∼14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers. Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90-day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.

Ice Multiplication by Breakup in Ice–Ice Collisions. Part II: Numerical Simulations

Abstract: In Part I of this two-part paper, a formulation was developed to treat fragmentation in ice–ice collisions. In the present Part II, the formulation is implemented in two microphysically advanced cloud models simulating a convective line observed over the U.S. high plains. One model is 2D with a spectral bin microphysics scheme. The other has a hybrid bin–two-moment bulk microphysics scheme in 3D. The case consists of cumulonimbus cells with cold cloud bases (near 0°C) in a dry troposphere.Only with breakup included in the simulation are aircraft observations of particles with maximum dimensions >0.2 mm in the storm adequately predicted by both models. In fact, breakup in ice–ice collisions is by far the most prolific process of ice initiation in the simulated clouds (95%–98% of all nonhomogeneous ice), apart from homogeneous freezing of droplets. Inclusion of breakup in the cloud-resolving model (CRM) simulations increased, by between about one and two orders of magnitude, the average concentratio...

An Improved Convective Ice Parameterization for the NASA GISS Global Climate Model and Impacts on Cloud Ice Simulation

Abstract: Partitioning of convective ice into precipitating and detrained condensate presents a challenge for GCMs since partitioning depends on the strength and microphysics of the convective updraft. It is an important issue because detrainment of ice from updrafts influences the development of stratiform anvils, impacts radiation, and can affect GCM climate sensitivity. Recent studies have shown that the CMIP5 configurations of the Goddard Institute for Space Studies (GISS) GCM simulated upper-tropospheric ice water content (IWC) that exceeded an estimated upper bound by a factor of 2. Partly in response to this bias, a new GCM parameterization of convective cloud ice has been developed that incorporates new ice particle fall speeds and convective outflow particle size distributions (PSDs) from the NASA African Monsoon Multidisciplinary Analyses (NAMMA), NASA Tropical Composition, Cloud and Climate Coupling (TC4), DOE ARM–NASA Midlatitude Continental Convective Clouds Experiment (MC3E), and DOE ARM Small...

On the Ambiguity in Relativistic Tidal Deformability

Abstract: The LIGO collaboration recently reported the first gravitational-wave constraints on the tidal deformability of neutron stars. I discuss an inherent ambiguity in the notion of relativistic tidal deformability that, while too small to affect the present measurement, may become important in the future. I propose a new way to understand the ambiguity and discuss future prospects for reliably linking observed gravitational waveforms to compact object microphysics.

Modeling Condensation in Deep Convection

Abstract: Cloud-scale models apply two drastically different methods to represent condensation of water vapor to form and grow cloud droplets. Maintenance of water saturation inside liquid clouds is assumed in the computationally efficient saturation adjustment approach used in most bulk microphysics schemes. When super- or subsaturations are allowed, condensation/evaporation can be calculated using the predicted saturation ratio and (either predicted or prescribed) mean droplet radius and concentration. The study investigates differences between simulations of deep unorganized convection applying a saturation adjustment condensation scheme (SADJ) and a scheme with supersaturation prediction (SPRE). A double-moment microphysics scheme with CCN activation parameterized as a function of the local vertical velocity is applied to compare cloud fields simulated applying SPRE and SADJ. Clean CCN conditions are assumed to demonstrate upper limits of the SPRE and SADJ difference. Microphysical piggybacking is used ...

Simulation of Polarimetric Radar Variables from 2013 CAPS Spring Experiment Storm-Scale Ensemble Forecasts and Evaluation of Microphysics Schemes

Abstract: Polarimetric radar variables are simulated from members of the 2013 Center for Analysis and Prediction of Storms (CAPS) Storm-Scale Ensemble Forecasts (SSEF) with varying microphysics (MP) schemes and compared with observations. The polarimetric variables provide information on hydrometeor types and particle size distributions (PSDs), neither of which can be obtained through reflectivity (Z) alone. The polarimetric radar simulator pays close attention to how each MP scheme [including single- (SM) and double-moment (DM) schemes] treats hydrometeor types and PSDs. The recent dual-polarization upgrade to the entire WSR-88D network provides nationwide polarimetric observations, allowing for direct evaluation of the simulated polarimetric variables.Simulations for a mesoscale convective system (MCS) and supercell cases are examined. Five different MP schemes—Thompson, DM Milbrandt and Yau (MY), DM Morrison, WRF DM 6-category (WDM6), and WRF SM 6-category (WSM6)—are used in the ensemble forecasts. Forec...

The microphysics of clouds over the Antarctic Peninsula - Part 2: modelling aspects within Polar WRF

Abstract: The first intercomparisons of cloud microphysics schemes implemented in the Weather Research and Forecasting (WRF) mesoscale atmospheric model (version 3.5.1) are performed in the Antarctic Peninsula using the polar version of WRF (Polar WRF) at 5 km resolution, along with comparisons to the British Antarctic Survey's aircraft measurements (presented in Part 1 of this work, Lachlan-Cope et al., 2016). This study follows previous works suggesting the misrepresentation of the cloud thermodynamic phase in order to explain large radiative biases derived at the surface in Polar WRF continent-wide, and in the Polar WRF-based operational forecast model Antarctic Mesoscale Prediction System (AMPS) over the Larsen C Ice shelf. Several cloud microphysics schemes are investigated: the WRF Single-Moment 5-class scheme (WSM5), the WRF Double-Moment 6-class scheme (WDM6), the Morrison double-moment scheme, the Thompson scheme, and the Milbrandt- Yau Double-Moment 7-class scheme. WSM5 used in AMPS struggles the most to capture the observed supercooled liquid phase mainly because of their ice nuclei parameterisation overestimating the number of activated crystals, while other micro- physics schemes (but not WSM5's upgraded version, WDM6) manage much better to do so. The best performing scheme is the Morrison scheme for its better average prediction of occurrences of clouds, and cloud phase, as well as its lowest surface radiative bias over the Larsen C ice shelf in the infrared. This is important for surface energy budget consideration with Polar WRF since the cloud radiative effect is more pronounced in the infrared over icy surfaces. However, our investigation shows that all the schemes fail at simulating the supercooled liquid mass at some temperatures (altitudes) where observations show evidence of its persistence. An ice nuclei parameterisation relying on both temperature and aerosol content like DeMott et al. (2010) (not currently used in WRF cloud schemes) is in best agreement with the observations, at temperatures and aerosol concentration characteristic of the Antarctic Peninsula where the primary ice production occurs (Part 1), compared to parame- terisation only relying on the atmospheric temperature (used by the WRF cloud schemes). Overall, a realistic ice microphysics implementation is paramount to the correct representation of the supercooled liquid phase in Antarctic clouds.

Marine Fog: A Review on Microphysics and Visibility Prediction

Abstract: Marine fog occurs commonly over the world due to the various physical, chemical, dynamical, and radiative processes active at various time and space scales. These processes are affected by local topographical conditions such as surface height and irregularities, slope, and ocean-land boundaries and sea surface conditions as well as atmospheric physical conditions such as pollution as a source of cloud condensation nuclei, cooling rates, and moisture and heat fluxes. Marine fog is usually the result of the advection of warm air masses over cold surfaces or vice versa. Marine fog impacts transportation and shipping, aviation, and the Earth ecosystem because of reduced visibilities and increased moisture availability. Recent studies suggest that the occurrence of fog is decreasing in many part of the world over the lands but not over the ocean. Its prediction using numerical weather prediction (NWP) models includes large uncertainties on small space scales over the short time periods. In this review, first, fog observations are summarized, and second microphysics of fog and visibility were described. Fog prediction issues related to NWP model uncertainties and observational issues are then provided. In the end, future challenges related to marine fog observations and NWP model based prediction, as well as fog and climate change issues are summarized.

Lagrangian condensation microphysics with Twomey CCN activation

Abstract: . We report the development of a novel Lagrangian microphysics methodology for simulations of warm ice-free clouds. The approach applies the traditional Eulerian method for the momentum and continuous thermodynamic fields such as the temperature and water vapor mixing ratio, and uses Lagrangian super-droplets to represent condensed phase such as cloud droplets and drizzle or rain drops. In other applications of the Lagrangian warm-rain microphysics, the super-droplets outside clouds represent unactivated cloud condensation nuclei (CCN) that become activated upon entering a cloud and can further grow through diffusional and collisional processes. The original methodology allows for the detailed study of not only effects of CCN on cloud microphysics and dynamics, but also CCN processing by a cloud. However, when cloud processing is not of interest, a simpler and computationally more efficient approach can be used with super-droplets forming only when CCN is activated and no super-droplet existing outside a cloud. This is possible by applying the Twomey activation scheme where the local supersaturation dictates the concentration of cloud droplets that need to be present inside a cloudy volume, as typically used in Eulerian bin microphysics schemes. Since a cloud volume is a small fraction of the computational domain volume, the Twomey super-droplets provide significant computational advantage when compared to the original super-droplet methodology. Additional advantage comes from significantly longer time steps that can be used when modeling of CCN deliquescence is avoided. Moreover, other formulation of the droplet activation can be applied in case of low vertical resolution of the host model, for instance, linking the concentration of activated cloud droplets to the local updraft speed. This paper discusses the development and testing of the Twomey super-droplet methodology, focusing on the activation and diffusional growth. Details of the activation implementation, transport of super-droplets in the physical space, and the coupling between super-droplets and the Eulerian temperature and water vapor field are discussed in detail. Some of these are relevant to the original super-droplet methodology as well and to the ice phase modeling using the Lagrangian approach. As a computational example, the scheme is applied to an idealized moist thermal rising in a stratified environment, with the original super-droplet methodology providing a benchmark to which the new scheme is compared.

Improvement of a Cloud Microphysics Scheme for a Global Nonhydrostatic Model Using TRMM and a Satellite Simulator

Abstract: The cloud and precipitation simulated by a global nonhydrostatic model with a 3.5-km horizontal resolution, the Nonhydrostatic Icosahedral Atmospheric Model (NICAM), are evaluated using the Tropical Rainfall Measuring Mission (TRMM) and a satellite simulator. A previous study by Roh and Satoh evaluated the single-moment bulk microphysics and established the modified microphysics scheme for the specific tropical open ocean using a regional version of NICAM. In this study, the authors expanded the evaluation over the entire tropics and parts of the midlatitude areas (20°–36°S, 20°–36°N) using a joint histogram of the cloud-top temperature and precipitation echo-top heights and contoured frequency by altitude diagrams of the deep convective systems. The modified microphysics simulation improves the joint probability density functions of the cloud-top temperatures and precipitation cloud-top heights over not only the tropical ocean but also the land and midlatitude areas. Compared with the default mic...

Derivation of Aerosol Profiles for MC3E Convection Studies and Use in Simulations of the 20 May Squall Line Case

Abstract: . Advancing understanding of deep convection microphysics via mesoscale modeling studies of well-observed case studies requires observation-based aerosol inputs. Here, we derive hygroscopic aerosol size distribution input profiles from ground-based and airborne measurements for six convection case studies observed during the Midlatitude Continental Convective Cloud Experiment (MC3E) over Oklahoma. We demonstrate use of an input profile in simulations of the only well-observed case study that produced extensive stratiform outflow on 20 May 2011. At well-sampled elevations between −11 and −23 °C over widespread stratiform rain, ice crystal number concentrations are consistently dominated by a single mode near ∼ 400 µm in randomly oriented maximum dimension (Dmax). The ice mass at −23 °C is primarily in a closely collocated mode, whereas a mass mode near Dmax ∼ 1000 µm becomes dominant with decreasing elevation to the −11 °C level, consistent with possible aggregation during sedimentation. However, simulations with and without observation-based aerosol inputs systematically overpredict mass peak Dmax by a factor of 3–5 and underpredict ice number concentration by a factor of 4–10. Previously reported simulations with both two-moment and size-resolved microphysics have shown biases of a similar nature. The observed ice properties are notably similar to those reported from recent tropical measurements. Based on several lines of evidence, we speculate that updraft microphysical pathways determining outflow properties in the 20 May case are similar to a tropical regime, likely associated with warm-temperature ice multiplication that is not well understood or well represented in models.

Using VIIRS fire radiative power data to simulate biomass burning emissions, plume rise and smoke transport in a real-time air quality modeling system

Abstract: In this presentation, we present a new smoke modeling system High Resolution Rapid Refresh (HRRR-Smoke) to simulate biomass burning (BB) emissions, plume rise and smoke transport in real time. The HRRR model (without smoke) is run as an operational numerical weather prediction system at the National Weather Service. HRRR is NOAA Earth System Research Laboratory's version of the Weather Research and Forecasting (WRF) model. Here we make use of WRF-Chem (the WRF model coupled with chemistry) and simulate fine particulate matter (smoke) emissions emitted by BB as well as anthropogenic sources. The model includes an aerosol aware double moment Thompson microphysics scheme [1], which allows to simulate smoke feedback on microphysics in a computationally efficient manner.

A ubiquitous ice size bias in simulations of tropical deep convection

Abstract: . The High Altitude Ice Crystals – High Ice Water Content (HAIC-HIWC) joint field campaign produced aircraft retrievals of total condensed water content (TWC), hydrometeor particle size distributions (PSDs), and vertical velocity (w) in high ice water content regions of mature and decaying tropical mesoscale convective systems (MCSs). The resulting dataset is used here to explore causes of the commonly documented high bias in radar reflectivity within cloud-resolving simulations of deep convection. This bias has been linked to overly strong simulated convective updrafts lofting excessive condensate mass but is also modulated by parameterizations of hydrometeor size distributions, single particle properties, species separation, and microphysical processes. Observations are compared with three Weather Research and Forecasting model simulations of an observed MCS using different microphysics parameterizations while controlling for w, TWC, and temperature. Two popular bulk microphysics schemes (Thompson and Morrison) and one bin microphysics scheme (fast spectral bin microphysics) are compared. For temperatures between −10 and −40 °C and TWC > 1 g m−3, all microphysics schemes produce median mass diameters (MMDs) that are generally larger than observed, and the precipitating ice species that controls this size bias varies by scheme, temperature, and w. Despite a much greater number of samples, all simulations fail to reproduce observed high-TWC conditions ( > 2 g m−3) between −20 and −40 °C in which only a small fraction of condensate mass is found in relatively large particle sizes greater than 1 mm in diameter. Although more mass is distributed to large particle sizes relative to those observed across all schemes when controlling for temperature, w, and TWC, differences with observations are significantly variable between the schemes tested. As a result, this bias is hypothesized to partly result from errors in parameterized hydrometeor PSD and single particle properties, but because it is present in all schemes, it may also partly result from errors in parameterized microphysical processes present in all schemes. Because of these ubiquitous ice size biases, the frequently used microphysical parameterizations evaluated in this study inherently produce a high bias in convective reflectivity for a wide range of temperatures, vertical velocities, and TWCs.

UCLALES–SALSA v1.0: a large-eddy model with interactive sectional microphysics for aerosol, clouds and precipitation

Abstract: . Challenges in understanding the aerosol–cloud interactions and their impacts on global climate highlight the need for improved knowledge of the underlying physical processes and feedbacks as well as their interactions with cloud and boundary layer dynamics. To pursue this goal, increasingly sophisticated cloud-scale models are needed to complement the limited supply of observations of the interactions between aerosols and clouds. For this purpose, a new large-eddy simulation (LES) model, coupled with an interactive sectional description for aerosols and clouds, is introduced. The new model builds and extends upon the well-characterized UCLA Large-Eddy Simulation Code (UCLALES) and the Sectional Aerosol module for Large-Scale Applications (SALSA), hereafter denoted as UCLALES-SALSA. Novel strategies for the aerosol, cloud and precipitation bin discretisation are presented. These enable tracking the effects of cloud processing and wet scavenging on the aerosol size distribution as accurately as possible, while keeping the computational cost of the model as low as possible. The model is tested with two different simulation set-ups: a marine stratocumulus case in the DYCOMS-II campaign and another case focusing on the formation and evolution of a nocturnal radiation fog. It is shown that, in both cases, the size-resolved interactions between aerosols and clouds have a critical influence on the dynamics of the boundary layer. The results demonstrate the importance of accurately representing the wet scavenging of aerosol in the model. Specifically, in a case with marine stratocumulus, precipitation and the subsequent removal of cloud activating particles lead to thinning of the cloud deck and the formation of a decoupled boundary layer structure. In radiation fog, the growth and sedimentation of droplets strongly affect their radiative properties, which in turn drive new droplet formation. The size-resolved diagnostics provided by the model enable investigations of these issues with high detail. It is also shown that the results remain consistent with UCLALES (without SALSA) in cases where the dominating physical processes remain well represented by both models.

Effect of cloud microphysics on Indian summer monsoon precipitating clouds: A coupled climate modeling study

Abstract: The quest for one of the most dominant processes controlling the large-scale circulations in the tropics is unraveled. The impact of cloud microphysical processes is known to have effects on rainfall and local atmospheric thermodynamics, however, its effect on the prevailing mean circulations is not yet studied. Two sets of coupled global climate model experiments (ICE and NO ICE microphysics) reveal that ice microphysics improves the strength of the Hadley circulation with respect to observation. Results pinpoint that ICE simulation enhances high cloud fraction (global tropics: ~59 %, India: ~51 %) and stratiform rain (global tropics: ~5 %, India: ~15 %) contribution. ICE and NO ICE cloud microphysics impacts differently on the outgoing longwave radiation (OLR), tropospheric temperature, surface shortwave and longwave radiation. The effect of ice microphysics reduces OLR, which signifies deeper convection in the ICE run. The global annual average of the net radiation flux (shortwave and longwave) at the surface in ICE run (108.1 W/m2) is close to the observation (106 W/m2), which is overestimated in NO ICE run (112 W/m2). The result of apparent heat source term over the land and ocean surface eventually modifies regional Hadley circulation. Thus, the effect of ice microphysics in the global coupled model is important not only because of microphysics but also due to the radiation feedbacks. Therefore, better ice-phase microphysics is required in the new generation of climate forecast model, which may lead to improvements in the simulation of monsoon.

Ice-Phase Precipitation

Abstract: 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 application...