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DOE OSTI2024

Cloud-Resolving ICON Simulations of Secondary Ice Production in Arctic Mixed-Phase Stratocumuli Observed during M-PACE

Field measurements and modeling studies suggest that secondary ice production (SIP) may close the gap between observed Arctic ice nucleating particle (INP) concentrations and ice crystal number concentrations ni. Here, we explore sensitivities with respect to the complexity of different INP parameterizations under the premise that ni is governed by SIP. Idealized, cloud-resolving simulations are performed for the marine cold air outbreak cloud deck sampled during the Mixed-Phase Arctic Cloud Experiment (M-PACE) with the Icosahedral Nonhydrostatic (ICON) model. The impact of the droplet shattering (DS) of raindrops and collisional breakup (BR) in addition to the existing Hallet–Mossop rime splintering mechanism were investigated. Overall, 12 different model experiments (12-h runs) were performed and analyzed. Despite the considerable amount of uncertainty remaining with regard to SIP mechanisms and their process representation in numerical models, we conclude from these experiments that (i) only simulations where DS dominates the SIP signal (potentially amplified by BR) capture observed ice-phase and liquid-phase cloud properties, and (ii) SIP events cluster around the convective outflow region and are structurally linked to mesoscale cloud organization. In addition, interactions with primary nucleation parameterizations of varied complexity were investigated. Here, our simulations show that (i) a stable long-lived mixed-phase cloud (MPC) can be maintained in the absence of primary nucleation once SIP is established, (ii) experiments using a computationally more efficient relaxation-based parameterization of primary nucleation are statistically invariant from simulations considering prognostic INP, and (iii) primary nucleation at cloud-top controls the areal extent of the mixed-phase cloud region, and reduces SIP efficacy via DS due to increased depletion of cloud liquid throughout the entire cloud column.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

Session on modeling of radiative transfer processes

The session on modeling of radiative transfer processes is reviewed. Six critical issues surfaced in the discussion concerning scale-interactive radiative processes relevent to the mesoscale convective systems (MCS's). These issues are the need to expand basic knowledge of how MCS's influence climate through extensive cloud shields and increased humidity in the upper troposphere; to improve radiation parameterizations used in mesoscale and General Circulation Model (GCM) models; to improve our basic understanding of the influence of radiation on MCS dynamics due to diabatic heating, production of condensate, and vertical and horizontal heat fluxes; to quantify our understanding of radiative impacts of MCS's on the surface and free atmosphere energy budgets; to quantify and identify radiative and microphysical processes important in the evolution of MCS's; and to improve the capability to remotely sense MCS radiative properties from space and ground-based systems.

Flatau, Piotr↗

NASA NTRS2008

Understanding Differences Between Co-Incident CloudSat, Aqua/MODIS and NOAA18 MHS Ice water Path Retrievals Over the Tropical Oceans

Accurate measurement of the physical and radiative properties of clouds and their representation in climate models continues to be a challe nge. Model parameterizations are still subject to a large number of t unable parameters; furthermore, accurate and representative in situ o bservations are very sparse, and satellite observations historically have significant quantitative uncertainties, particularly with respect to particle size distribution (PSD) and cloud phase. Ice Water Path (IWP), or amount of ice present in a cloud column, is an important cl oud property to accurately quantify, because it is an integral measur e of the microphysical properties of clouds and the cloud feedback pr ocesses in the climate system. This paper investigates near co-incident retrievals of IWP over tropical oceans using three diverse measurem ent systems: radar from CloudSat, Vis/IR from Aqua/MODIS, and microwa ve from NOAA-18IMHS. CloudSat 94 GHz radar measurements provide high resolution vertical and along-orbit structure of cloud reflectivity a nd enable IWP (and IWC) retrievals. Overlapping MODIS measurements of cloud optical thickness and phase allow estimates of IWP when cloud tops are identified as being ice. Periodically, NOAA18 becomes co-inci dent in space I time to enable comparison of A-Train measurements to IWP inferred from the 157 and 89 GHz channel radiances. This latter m easurement is effective only for thick convective anvil systems. We s tratify these co-incident data (less than 4 minutes separation) into cirrus only, cirrus overlying liquid water clouds, and precipitating d eep convective clouds. Substantial biases in IWP and ice effective ra dius are found. Systematic differences in these retrievals are consid ered in light of the uncertainties in a priori assumptions ofPSDs, sp ectral sensitivity and algorithm strategies, which have a direct impact on the IWP product.

Pittman, Jasna↗

NASA NTRS2015

Incorporation of New Convective Ice Microphysics into the NASA GISS GCM and Impacts on Cloud Ice Water Path (IWP) Simulation

The CMIP5 configurations of the GISS Model-E2 GCM simulated a mid- and high latitude ice IWP that decreased by 50 relative to that simulated for CMIP3 (Jiang et al. 2012; JGR). Tropical IWP increased by 15 in CMIP5. While the tropical IWP was still within the published upper-bounds of IWP uncertainty derived using NASA A-Train satellite observations, it was found that the upper troposphere (200 mb) ice water content (IWC) exceeded the published upper-bound by a factor of 2. This was largely driven by IWC in deep-convecting regions of the tropics.Recent advances in the model-E2 convective parameterization have been found to have a substantial impact on tropical IWC. These advances include the development of both a cold pool parameterization (Del Genio et al. 2015) and new convective ice parameterization. In this presentation, we focus on the new parameterization of convective cloud ice that was developed using data from the NASA TC4 Mission. Ice particle terminal velocity formulations now include information from a number of NASA field campaigns. The new parameterization predicts both an ice water mass weighted-average particle diameter and a particle cross sectional area weighted-average size diameter as a function of temperature and ice water content. By assuming a gamma-distribution functional form for the particle size distribution, these two diameter estimates are all that are needed to explicitly predict the distribution of ice particles as a function of particle diameter.GCM simulations with the improved convective parameterization yield a 50 decrease in upper tropospheric IWC, bringing the tropical and global mean IWP climatologies into even closer agreement with the A-Train satellite observation best estimates.

tropical regions↗

NASA NTRS2015

Kinematic and Microphysical Control of Lightning Flash Rate over Northern Alabama

The Deep Convective Clouds and Chemistry (DC3) experiment seeks to examine the relationship between deep convection and the production of nitrogen oxides (NO (sub x)) via lightning (LNO (sub x)). A critical step in estimating LNO (sub x) production in a cloud-resolving model (CRM) without explicit lightning is to estimate the flash rate from available model parameters that are statistically and physically correlated. As such, the objective of this study is to develop, improve and evaluate lightning flash rate parameterizations in a variety of meteorological environments and storm types using radar and lightning mapping array (LMA) observations taken over Northern Alabama from 2005-2012, including during DC3. UAH's Advanced Radar for Meteorological and Operational Research (ARMOR) and the Weather Surveillance Radar - 1988 Doppler (WSR 88D) located at Hytop (KHTX) comprises the dual-Doppler and polarimetric radar network, which has been in operation since 2004. The northern Alabama LMA (NA LMA) in conjunction with Vaisala's National Lightning Detection Network (NLDN) allow for a detailed depiction of total lightning during this period. This study will integrate ARMOR-KHTX dual Doppler/polarimetric radar and NA LMA lightning observations from past and ongoing studies, including the more recent DC3 results, over northern Alabama to form a large data set of 15-20 case days and over 20 individual storms, including both ordinary multicell and supercell convection. Several flash rate parameterizations will be developed and tested, including those based on 1) graupel/small hail volume; 2) graupel/small hail mass, and 3) convective updraft volume. Sensitivity of the flash rate parameterizations to storm intensity, storm morphology and environmental conditions will be explored.

Carey, Lawrence D.↗

NASA NTRS2001

Satellite Imagery Analysis for Nighttime Temperature Inversion Clouds

Clouds play important roles in the climate system. Their optical and microphysical properties, which largely determine their radiative property, need to be investigated. Among several measurement means, satellite remote sensing seems to be the most promising. Since most of the cloud algorithms proposed so far are daytime use which utilizes solar radiation, Minnis et al. (1998) developed a nighttime use one using 3.7-, 11 - and 12-microns channels. Their algorithm, however, has a drawback that is not able to treat temperature inversion cases. We update their algorithm, incorporating new parameterization by Arduini et al. (1999) which is valid for temperature inversion cases. This updated algorithm has been applied to GOES satellite data and reasonable retrieval results were obtained.

Kawamoto, K.↗

NASA NTRS2002

Cloud-Scale Numerical Modeling of the Arctic Boundary Layer

The research objective of this NASA grant-funded project was to determine in detail how large-scale processes. in combination with cloud-scale radiative, microphysical, and dynamical processes, govern the formation and multi-layered structure of Arctic stratus clouds. This information will be useful for developing and improving 1D (one dimensional) boundary layer models for the Arctic. Also, to quantitatively determine the effects of leads on the large-scale budgets of sensible heat, water vapor, and condensate in a variety of Arctic winter conditions. This information will be used to identify the most important lead-flux processes that require parameterization in climate models. Our approach was to use a high-resolution numerical model, the 2D (two dimensional) University of Utah Cloud Resolving Model (UU CRM), and its 1D version, the University of Utah Turbulence Closure Model (UU TCM), a boundary layer model based on third-moment turbulence closure, as well as a large-eddy simulation (LES) model originally developed by C.H. Moeng.

Kruegen, Steven K.↗

NASA NTRS2006

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CFWs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1 998 and 1999). In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Tao, Wei-Kuo↗

DOE OSTI2026

An Optimized Parameterization of Sub‐Grid Scale Advection for Convection Permitting Models

Convection‐permitting models (CPMs) explicitly resolve deep convection yet under‐resolve the organized lateral exchanges among drafts and their environment that control entrainment/detrainment, precipitation efficiency, and mesoscale structure. In this work, we introduce the Optimized Advection Scheme (OAS), which introduces a small rotation of the Cartesian frame of reference for the horizontal winds relative to other variables used in advection that induces cross‐gradient transport to mimic under‐resolved convective mixing. The rotation angle is selected to minimize the Kullback–Leibler divergence between the simulated and satellite observed precipitation intensity distributions, yielding a physically consistent perturbation that is computationally inexpensive and portable. Optimized Advection Scheme is implemented in WRF and evaluated over Amazon (April 2014). It shifts precipitation–precipitable‐water joint distributions toward lighter rain, reduces overly intense rates, and improves mesoscale convective system (MCS) lifetime and propagation. Mechanistically, the added cross‐gradient transport promotes convective detrainment and environmental mixing, which cools and moistens the mid‐troposphere, weakens downward momentum transport, alleviates excessive downwelling shortwave biases, and warms the surface temperature. The optimized rotation angle yields comparable improvements at 4‐km and 1‐km grid spacing, demonstrating resolution‐independent benefits across the CPM gray zone. By targeting the dynamical root of under‐mixed convective circulations, rather than tuning model microphysics or closures, OAS delivers robust, scale‐aware improvements in precipitation statistics, cloud vertical structure, and characteristics of MCS (MCSs), offering a practical pathway to more reliable CPM simulations for weather and climate applications.

CPM↗

DOE OSTI2020

Simulating Observations of Southern Ocean Clouds and Implications for Climate

Southern Ocean (S. Ocean) clouds are important for climate prediction. Yet previous global climate models failed to accurately represent cloud phase distributions in this observation-sparse region. In this study, data from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES) experiment is compared to constrained simulations from a global climate model (the Community Atmosphere Model, CAM). Nudged versions of CAM are found to reproduce many of the features of detailed in situ observations, such as cloud location, cloud phase, and boundary layer structure. The simulation in CAM6 has improved its representation of S. Ocean clouds with adjustments to the ice nucleation and cloud microphysics schemes that permit more supercooled liquid. Comparisons between modeled and observed hydrometeor size distributions suggest that the modeled hydrometeor size distributions represent the dual peaked shape and form of observed distributions, which is remarkable given the scale difference between model and observations. Comparison to satellite observations of cloud physics is difficult due to model assumptions that do not match retrieval assumptions. Some biases in the model's representation of S. Ocean clouds and aerosols remain, but the detailed cloud physical parameterization provides a basis for process level improvement and direct comparisons to observations. This is crucial because cloud feedbacks and climate sensitivity are sensitive to the representation of S. Ocean clouds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Pluminate: Quantifying aerosol injection behavior from simulation, experimentation and observations

Marine aerosol injections are a key component in further understanding of both the potentials of deliberate injection for marine cloud brightening (MCB), a potential climate intervention (CI) strategy, and key aerosol-cloud interaction behaviors that currently form the largest uncertainty in global climate model (GCM) predictions of our climate. Since the rate of spread of aerosols in a marine environment directly translates to the effectiveness and ability of aerosol injections in impacting cloud radiative forcing, it is crucial to understand the spatial and temporal extent of injected-aerosol effects following direct injection into marine environments. The ubiquity of ship-injected aerosol tracks from satellite imagery renders observational validation of new parameterizations possible in 2D, however, 3D compatible data is more scarce, and necessary for the development of subgrid scale parameterizations of aerosol-cloud interactions in GCMs. This report introduces two novel parameterizations of atmospheric aerosol injection behavior suitable for both 3D (GCM-compatible) and 2D (observation-related) modeling. Their applicability is highlighted using a wealth of different observational data: small and larger scale salt-aerosol injection experiments conducted at SNL, 3D large eddy simulations of ship-injected aerosol tracks and 2D satellite images of ship tracks. The power of experimental data in enhancing knowledge of aerosol-cloud interactions is in particular emphasized by studying key aerosol microphysical and optical properties as observed through their mixing in cloud-like environments.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2008

Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model

The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.

Molthan, Andrew L.↗

DOE OSTI2023

Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations

Abstract. Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first time, how model-simulated INP concentrations compare with year-round INP measurements during the Macquarie Island Cloud Radiation Experiment (MICRE) campaign from 2017–2018. We simulate immersion-mode INP concentrations using the Energy Exascale Earth System Model version 1 (E3SMv1) by combining simulated aerosols with recently developed deterministic INP parameterizations and the native classical nucleation theory (CNT) for mineral dust in E3SMv1. Because MICRE did not collect aerosol measurements of super-micron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and overestimates sea spray aerosol concentrations by 1 to 2 orders of magnitude for most of the high-latitude sites in the Southern Hemisphere. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 d) and processed offline using the Colorado State University ice spectrometer (IS) in immersion freezing mode. We find that when deterministic parameterizations for both dust and sea spray INPs are used, simulated INPs are within a factor of 10 of observed INPs more than 60 % of the time during summer. Our results also indicate that the E3SM's current treatment of mineral dust immersion freezing in the SO is impacted by compensating biases – an underprediction of dust amount was compensated by an overprediction of its effectiveness as INPs. We also perform idealized droplet freezing experiments to quantify the implications of the time-dependent behavior assumed by the E3SM's CNT-parameterization and compare with the ice spectrometer observations. We find that the E3SM CNT 10 s diagnostic used in this study is a reasonable approximation of the exact formulation of CNT, when applied to ice spectrometer measurements in low-INP conditions similar to Macquarie Island. However, the linearized 10 s diagnostic underestimates the exact formula by an order of magnitude or more in places with high-INP conditions like the Sahara. Overall, our findings suggest that it is important to correct the biases in E3SM's simulated dust life cycle and update E3SM's INP parameterizations. INP prediction errors of 2 to 3 orders of magnitude can have considerable impacts on the simulated cloud and radiative properties in global climate models. On comparing INP concentrations during MICRE against ship-based campaigns, Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) and Antarctic Circumnavigation Expedition (ACE), we find that INPs from the latter are significantly higher only in regions closer to Macquarie Island. This alludes to the fact that physical, chemical and biological processes affecting INP concentrations as stimulated by the island could be partly responsible for the high INP concentrations observed at Macquarie Island during the MICRE campaign. Therefore, improvements to both aerosol simulation and INP parameterizations are required to adequately simulate INPs and their cloud impacts in E3SM. It will be helpful to include a parallel measurement of the size-resolved aerosol composition and explore opportunities for long-term measurement platforms in future field campaigns studying INP sources in remote marine regions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global CCMs where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AtmOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) chemistry-climate model through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗

NASA NTRSDate not supplied

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global chemistry-climate models (CCMs) where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) CCM through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗

NASA NTRS2005

A Hierarchical Modeling Study of the Interactions Among Turbulence, Cloud Microphysics, and Radiative Transfer in the Evolution of Cirrus Clouds

This project used a hierarchy of cloud resolving models to address the following science issues of relevance to CRYSTAL-FACE: What ice crystal nucleation mechanisms are active in the different types of cirrus clouds in the Florida area and how do these different nucleation processes influence the evolution of the cloud system and the upper tropospheric humidity? How does the feedback between supersaturation and nucleation impact the evolution of the cloud? What is the relative importance of the large-scale vertical motion and the turbulent motions in the evolution of the crystal size spectra? How does the size spectra impact the life-cycle of the cloud, stratospheric dehydration, and cloud radiative forcing? What is the nature of the turbulence and waves in the upper troposphere generated by precipitating deep convective cloud systems? How do cirrus microphysical and optical properties vary with the small-scale dynamics? How do turbulence and waves in the upper troposphere influence the cross-tropopause mixing and stratospheric and upper tropospheric humidity? The models used in this study were: 2-D hydrostatic model with explicit microphysics that can account for 30 size bins for both the droplet and crystal size spectra. Notably, a new ice crystal nucleation scheme has been incorporated into the model. Parcel model with explicit microphysics, for developing and evaluating microphysical parameterizations. Single column model for testing bulk microphysics parameterizations

Curry, Judith↗

DOE OSTI2022

Coupling Warm Rain With an Eddy Diffusivity/Mass Flux Parameterization: 2. Sensitivities and Comparison to Observations

Abstract This is the second part of the description and validation of the coupling of a warm‐rain microphysics scheme to a stochastic multi‐plume eddy‐diffusivity/mass‐flux parameterization. Part 1 provides the model description and initial validation of the parameterization in a single column model (SCM) against large eddy simulations. This manuscript provides additional comparisons against satellite observations of 500 unique simulation cases, an analysis of model parameter‐based sensitivities in those 500 cases, and an evaluation of the idealized LES case study paradigm for parameterization development. The SCM is forced by a weather reanalysis in the subtropical northeast Pacific region characterized by the stratocumulus‐to‐cumulus cloud transition. 18 scalar outputs are examined to identify the sensitivities to 22 of the model's parameters. The model is highly sensitive to parameters that determine the behavior of convective plumes, which collectively lead to the most sensitivity in 13 of the 18 outputs. Only a few parameters contribute sensitivities that are not highly correlated with those of other parameters. While forcing the model with two canonical field campaign cases results in similar picture of which parameters lead to high sensitivity in model outputs, the sensitivity magnitudes can be overestimated compared to when the model is forced by weather reanalyzes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) Final Campaign Report

The extensive coverage of low clouds over the subtropical eastern oceans greatly impacts the current climate. In addition, the response of low clouds to changes in atmospheric greenhouse gases and aerosols is a major source of uncertainty, which thwarts accurate prediction of future climate change. Low clouds are poorly simulated in climate models, partly due to inadequate long-term simultaneous observations of their macrophysical and microphysical structure, radiative effects, and associated aerosol distribution in regions where their impact is greatest. The thickness and extent of subtropical low clouds is dependent on tight couplings between surface fluxes of heat and moisture, radiative cooling, boundary layer turbulence, and precipitation (much of which evaporates before reaching the ocean surface and is closely connected to the abundance of cloud condensation nuclei). These couplings have been documented as a result of past field programs and model studies. However, extensive research is still required to achieve a quantitative understanding sufficient for developing parameterizations, which adequately predict aerosol indirect effects and low cloud response to climate perturbations. This is especially true of the interactions between clouds, aerosol, and precipitation. These processes take place in an ever-changing synoptic environment that can confound interpretation of short time period observations.

54 ENVIRONMENTAL SCIENCES↗