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At least 595 records · Page 33

Sensitivity of a Cumulus Parameterization Scheme to Precipitation Production Representation and Its Impact on a Heavy Rain Event over Korea

The sensitivity of a cumulus parameterization scheme (CPS) to a representation of precipitation production is examined. To do this, the parameter that determines the fraction of cloud condensate converted to precipitation in the simplified Arakawa–Schubert (SAS) convection scheme is modified following the results from a cloud-resolving simulation. While the original conversion parameter is assumed to be constant, the revised parameter includes a temperature dependency above the freezing level, whichleadstolessproductionoffrozenprecipitating condensate with height. The revised CPS has been evaluated for a heavy rainfall event over Korea as well as medium-range forecasts using the Global/Regional Integrated Model system (GRIMs). The inefficient conversion of cloud condensate to convective precipitation at colder temperatures generally leads to a decrease in pre-cipitation, especially in the category of heavy rainfall. The resultant increase of detrained moisture induces moistening and cooling at the top of clouds. A statistical evaluation of the medium-range forecasts with the revised precipitation conversion parameter shows an overall improvement of the forecast skill in precipitation and large-scale fields, indicating importance of more realistic representation of microphysical processes in CPSs.

Han, Ji-Young↗

Probing Flavor Asymmetry of Anti-quarks in the Proton by Drell-Yan Experiment SeaQuest

A new measurement on the avor asymmetry between d and u in the proton is reported in this thesis. The proton contains a substantial number of antiquarks which arise from dynamical interactions of gluons such as gluon dissociation to a quark-antiquark pair, g ! q + q, and from non-perturbative processes as described by the pion-cloud model, for example. The antiquarks in the proton undertake an important role in determining the dynamic characteristics of the internal structure of the proton, although its distribution in the proton and its origin are not fully understood. Understanding sea quarks in hadron is an important subject for QCD. The SeaQuest experiment at Fermi National Accelerator Laboratory (Fermilab) is a xed target experiment using the 120 GeV proton beam extracted from the Fermilab Main Injector. One of the goals of the experiment is to measure the avor asymmetry between d quark and u quark in the proton as a function of the target Bjorken x using the Drell-Yan process in the p-p or p-d reactions. This process takes place in hadron-hadron collisions when a quark in one hadron in the beam and an antiquark in other hadron in the target annihilate into a virtual photon that decays into a lepton pair. The avor asymmetry between d and u quarks was found by deep-inelastic scattering experiment NMC at CERN. The E866/NuSea experiment at Fermilab obtained the avor asymmetry in the proton for 0:015 < x < 0:35 using the 800 GeV proton beam extracted from the Fermilab Tevatron. The result indicates the dominance of d; it is 70% larger than u at lower x. The SeaQuest experiment was planned to do a new precise measurement at higher x region. The lower energy beam (120 GeV) increases the Drell-Yan cross section and suppresses the background primarily arising from J/ decays. Therefore, SeaQuest will obtain more statistics in a shorter time than the E866 experiment. After detector construction, detector commissioning and accelerator upgrade, physics data taking started in 2013. The SeaQuest spectrometer is designed to detect dimuon from the Drell-Yan process. It consists of targets, two di-pole magnets, and four tracking detector groups. The third tracking detector group has two drift chambers. One was newly fabricated in Japan by the Japanese group in SeaQuest collaboration and was shipped to Fermilab. The other one was constructed by SeaQuest collaborator in Fermilab under the initiative of the Japanese group. I worked on the construction and installation of the detectors, data taking and data analysis in SeaQuest. I extracted the avor asymmetry as a function of Bjorken x using the SeaQuest data for the rst time. This thesis shows the results using a part of data taken in 2014 and 2015. The asymmetry was extracted for much wider Bjorken x region than the previous experiment. The measured Bjorken x range covers up to 0.58. The result shows that the ratio of d=u is always higher than 1 at 0:1 < x < 0:45, in contrast to the E866 result. For 0:45 < x < 0:58, the result shows that the ratio is close to unity. Predictions made by current PDF parameterizations are in agreement with the present result. Also, a prediction obtained by one of the non-perturbative models, pion-cloud model, is closer to the SeaQuest result than the E866 result. This result of d=u asymmetry at the wide Bjorken x region, 0:1 < x < 0:58, is very important information to understand the inner structure of the proton and the origin of the sea quarks in the proton.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Vertical Structure and Ice Production Processes of Shallow Convective Postfrontal Clouds over the Southern Ocean in MARCUS. Part II: Modeling Study

Abstract Part I of this series presented a detailed overview of postfrontal mixed-phase clouds observed during the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field campaign. In Part II, we focus on a multiday (23–26 February 2018) case with the aim of understanding ice production as well as model sensitivity to ice process parameterizations using the Weather Research and Forecasting (WRF) Model. The control simulation with the Predicted Particle Properties (P3) microphysics scheme underestimates the ice content and overestimates the supercooled liquid water content, contrary to the bias common in global climate models. The simulations targeted at ice production processes show negligible sensitivity to cloud droplet number concentrations. Further, neither increasing ice nuclei particle (INP) concentrations to an unrealistic level nor adjusting it to MARCUS field estimations alone guarantees more ice production in the model. However, the simulated clouds are found to be highly sensitive to the implementation of immersion freezing, the thresholding of condensation/deposition freezing initiation, and the rime splintering process. By increasing immersion freezing of cloud droplets, relaxing thresholds for condensation/deposition freezing, or removing rime splintering thresholds, the model significantly improves its performance in producing ice. The relaxation of the immersion freezing temperature threshold to the observed cloud-top temperature suggests an in-cloud seeder–feeder mechanism. The results of this work call for an increase in observations of INP, especially over the remote Southern Ocean and at relatively high temperatures, and measurements of ice particle size distributions to better constrain ice nucleating processes in models.

Meteorology & Atmospheric Sciences↗

Comparing the interactions between particulate matter and cloud properties over two populated cities in Texas using WRF-Chem fine-resolution modeling

Accurate modeling of aerosol-cloud interactions is essential for reliable weather and air quality simulations, given their significant impact on precipitation patterns, cloud dynamics, and aerosol distributions. This study employed the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to examine the impact of enhanced meteorological simulations, achieved through advanced microphysics parameterization supported by data assimilation techniques, on air quality across Texas on August 19 and 20, 2022. We tested four distinct configurations: (1) the Morrison two-moment bulk microphysics scheme, (2) Morrison's with observation nudging, (3) the Spectral Bin Microphysics (SBM), and (4) SBM with observation nudging. While the SBM scheme is known for its detailed representation of aerosol-cloud interactions, our focus was on how improvements in meteorological accuracy translate to more precise air quality simulations. Our findings demonstrated a progressive improvement in simulation accuracy, starting with the Morrison's scheme and further enhanced by adopting the SBM scheme, complemented by incorporating observation nudging. Specifically, the combination of the SBM scheme and the nudging substantially enhanced the model's ability to capture convective precipitation events, as shown by better alignment with NEXRAD radar reflectivity, with R increasing from –0.21 to 0.82, IOA from 0.10 to 0.87, and NMB decreasing from 99% to 34% in Houston. The enhanced meteorology translated into more accurate PM 2.5 concentration simulations, particularly through the more accurate representation of aerosol washout during precipitation events. In Houston, the SBM scheme with nudging improved the model's PM 2.5 simulations significantly, with NMB decreasing from –20% to 5% and IOA improving from 0.43 to 0.61. In San Antonio, improvements were also notable, with NMB improved from –27% to –22%, R increased from 0.48 to 0.82, and IOA increased from 0.66 to 0.86. Furthermore, our results underscore the crucial role of accurate meteorological simulations in refining our understanding of aerosol behaviors in relation to precipitation patterns, directly enhancing the reliability and effectiveness of air quality modeling.

54 ENVIRONMENTAL SCIENCES↗

Turbulence and Cloudiness in Cumulus-Topped Marine Boundary Layers

Turbulence and cloudiness in cumulus-topped marine boundary layers are studied using data from the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site. The analysis includes eight periods of nonprecipitating shallow cumulus clouds, spanning 141 h and encompassing 603 individual clouds. On average, the cumulus had bases at 558 m, were 99 m thick, had a chord length of 500 m, and exhibited an hourly base-layer cloudiness of 12%. Changes in cloud fraction were primarily driven by variations in cloud number not chord length. High-resolution Doppler lidar and cloud radar observations were used to estimate updraft and downdraft mass fluxes in the cumulus base layer under both clear and cloudy regions. Cloudy updrafts contributed only ∼23% of the total updraft mass flux at cloud base, indicating that most upward mass flux originated from clear-air eddies. Updraft strength, rather than updraft fraction, was found to predominantly control both clear and cloudy updraft mass fluxes. Cloud-base cloudiness strongly correlated with cloudy updraft mass flux but showed negligible correlation with clear-air updraft mass flux. Clear-air downdraft mass flux exhibited a strong relationship with the ratio of surface buoyancy to inversion strength. Mesoscale analysis revealed that moist patches had greater cloudiness, updraft mass flux, and vertical velocity variance compared to dry patches. Additionally, mesoscale base-layer cloud fraction was highly and significantly correlated with cloudy updraft mass flux in both dry and moist environments. Results presented herein have implications for cumulus parameterization development along with climatological and model evaluation studies conducted at the ENA site.

cumulus clouds↗

The Roles of Convection Parameterization in the Formation of Double ITCZ Syndrome in the NCAR CESM: I. Atmospheric Processes

Abstract Several improvements are implemented in the Zhang‐McFarlane (ZM) convection scheme to investigate the roles of convection parameterization in the formation of double intertropical convergence zone (ITCZ) bias in the NCAR CESM1.2.1. It is shown that the prominent double ITCZ biases of precipitation, sea surface temperature (SST), and wind stress in the standard CESM1.2.1 are largely eliminated in all seasons with the use of these improvements in convection scheme. This study for the first time demonstrates that the modifications of convection scheme can eliminate the double ITCZ biases in all seasons, including boreal winter and spring. Further analysis shows that the elimination of the double ITCZ bias is achieved not by improving other possible contributors, such as stratus cloud bias off the west coast of South America and cloud/radiation biases over the Southern Ocean, but by modifying the convection scheme itself. This study demonstrates that convection scheme is the primary contributor to the double ITCZ bias in the CESM1.2.1, and provides a possible solution to the long‐standing double ITCZ problem. The atmospheric model simulations forced by observed SST show that the original ZM convection scheme tends to produce double ITCZ bias in high SST scenario, while the modified convection scheme does not. The impact of changes in each core component of convection scheme on the double ITCZ bias in atmospheric model is identified and further investigated.

54 ENVIRONMENTAL SCIENCES↗

The contribution of black carbon to global ice nucleating particle concentrations relevant to mixed-phase clouds

Significance The Earth’s climate is affected by the radiative properties of clouds. In clouds containing both supercooled water droplets and ice particles (mixed-phase clouds), cloud lifetime and albedo are affected by the presence of ice nucleating particles (INP). After decades of research, the importance of black carbon (BC) as an INP remains unresolved. In this work, we determined the contribution of BC to INP concentrations ([INP]) from real-world wildfires and prescribed burns. We found that BC does not contribute significantly to [INP] in near-field biomass burning plumes. These results were applied as parameterizations to global climate model output. Combined with previous work on diesel-engine exhaust, we find that BC does not contribute significantly to global [INP] relevant to mixed-phase clouds.

54 ENVIRONMENTAL SCIENCES↗

Observational Relationship between Entrainment Rate and Environmental Relative Humidity and Implications for Convection Parameterization

Entrainment rate is a critical but highly uncertain quantity in convective parameterizations; especially, the effects of environmental relative humidity on entrainment rate are controversial, or even opposite, in different studies. Analysis of aircraft observations of cumuli from the RACORO and RICO field campaigns shows that entrainment rate is positively correlated with relative humidity. Physical analysis shows that higher relative humidity promotes entrainment by reducing buoyancy in the cloud cores and by weakening downdrafts near the cloud cores. The reduced buoyancy in the cloud cores and weakened downdrafts surrounding the cores further reduce updrafts in the cloud cores; the cloud cores with smaller updrafts are more significantly affected by their environment, resulting in larger entrainment rate. The relationship between entrainment rate and relative humidity is consistent with the buoyancy sorting concept widely used in convection parameterizations. The results provide reliable in situ observations to improve parameterizations of entrainment rate.

54 ENVIRONMENTAL SCIENCES↗

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↗

How does increasing horizontal resolution in a global climate model improve the simulation of aerosol-cloud interactions?

The Community Atmosphere Model Version 5 is run at horizontal grid spacing of 2, 1, 0.5, and 0.25 degrees, with the meteorology nudged towards the Year Of Tropical Convection analysis, and cloud simulators and the collocated A-Train satellite observations are used to explore the resolution dependence of aerosol-cloud interactions. The higher-resolution model produces results that agree better with observations, showing an increase of susceptibility of cloud droplet size, indicating a stronger first aerosol indirect forcing (AIF), and a decrease of susceptibility of precipitation probability, suggesting a weaker second AIF. The resolution sensitivities of AIF are attributed to those of droplet nucleation and precipitation parameterizations. The annual average AIF in the northern hemisphere mid-latitudes (where most anthropogenic emissions occur) in the 0.25° model is reduced by about 1 W m⁻² (-30%) compared to the 2° model, leading to a 0.26 W m⁻² reduction (-15%) in the global annual average AIF.

Ma, Po -Lun↗

New insights into ice multiplication using remote-sensing observations of slightly supercooled mixed-phase clouds in the Arctic

Significance During secondary ice events, ice particle number concentrations in mixed-phase clouds can increase by orders of magnitude with profound implications for the cloud evolution. However, characterization of secondary ice events in the natural environment has been a challenge for the community for decades. We show the long-term frequency of secondary ice events in Arctic supercooled clouds for temperatures warmer than − 10 ○ C, made possible by applying a remote-sensing technique to 6 y of data. Secondary ice events are found to occur preferentially in the presence of drizzle droplets, compared with the better-known rime-splintering process, causing up to a 1,000-fold enhancement in ice number concentration. These results provide critical insights for model parameterizations and future laboratory experiments.

54 ENVIRONMENTAL SCIENCES↗

Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks

Abstract A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.

54 ENVIRONMENTAL SCIENCES↗

Calibration of cloud and aerosol related parameters for solar irradiance forecasts in WRF-solar

Model parameters are a major source of uncertainty in numerical weather prediction. Recently, the Weather Research and Forecasting model with Solar extensions (WRF-Solar) has been upgraded by enhancing the treatment of sub-grid scale cloud and aerosols with augmentations of a sub-grid scale cloud scheme (CLD3) and an upgraded aerosol-aware Thompson-Eidhammer scheme (TE14). However, the value of model parameters associated with these parameterizations are assigned based on limited measurements or theoretical calculations. Calibrating the most sensitive parameters has the potential to improve solar irradiance predictions. Here, we adopted a multiobjective surrogate-based optimization (SBO) framework to calibrate nine parameters used in CLD3 and TE14 that lead to the largest sensitivity in simulated irradiance. The normalized mean-absolute-error (NMAE) of global horizontal irradiance (GHI) and direct normal irradiance (DNI) are minimized by calibrating WRF-Solar over two regions including the Southern Great Plains (SGP) and Central California, in order to focus on parameter calibration under cloudy conditions with different aerosol loading. The results show that generalized linear model (GLM)-based surrogate models approximate physical models well, particularly when the third order and three-way interaction terms are considered. The SBO framework efficiently searches the parameter space for optimal solutions with less computational costs than directly calibrating the physical model. We first calibrate CLD3 parameters over the less-polluted SGP region. Optimized CLD3 parameters alone result in NMAE reduction by 14% for the site-mean and up to 33% for individual cases over the SGP region. With further calibration of TE14 parameters over the Central California during active fire periods, the optimized parameters lead to over 20% reductions of NMAE. Our investigation reveals, however, that optimizing TE14 has a limited impact on irradiance simulations under less-polluted conditions in the SGP.

14 SOLAR ENERGY↗

Implementing marine organic aerosols into the GEOS-Chem model

Marine-sourced organic aerosols (MOAs) have been shown to play an important role in tropospheric chemistry by impacting surface mass, cloud condensation nuclei, and ice nuclei concentrations over remote marine and coastal regions. In this work, an online marine primary organic aerosol emission parameterization, designed to be used for both global and regional models, was implemented into the GEOS-Chem (Global Earth Observing System Chemistry) model. The implemented emission scheme improved the large underprediction of organic aerosol concentrations in clean marine regions (normalized mean bias decreases from -79% when using the default settings to -12% when marine organic aerosols are added). Model predictions were also in good agreement (correlation coefficient of 0.62 and normalized mean bias of -36%) with hourly surface concentrations of MOAs observed during the summertime at an inland site near Paris, France. Our study shows that MOAs have weaker coastal-to-inland concentration gradients than sea-salt aerosols, leading to several inland European cities having >10% of their surface submicron organic aerosol mass concentration with a marine source. The addition of MOA tracers to GEOS-Chem enabled us to identify the regions with large contributions of freshly emitted or aged aerosol having distinct physicochemical properties, potentially indicating optimal locations for future field studies.

Gantt, B.↗

THE IMPLICATIONS OF EXTREME OUTFLOWS FROM EXTREME STARBURSTS

Interstellar ultraviolet absorption lines provide crucial information about the properties of galactic outflows. In this paper, we augment our previous analysis of the systematic properties of starburst-driven galactic outflows by expanding our sample to include a rare population of starbursts with exceptionally high outflow velocities. In principle, these could be a qualitatively different phenomenon from more typical outflows. However, we find that instead these starbursts lie on, or along the extrapolation of, the trends defined by the more typical systems studied previously by us. We exploit the wide dynamic range provided by this new sample to determine scaling relations of outflow velocity with galaxy stellar mass ( M {sub *}), circular velocity, star formation rate (SFR), SFR/ M {sub *}, and SFR/area. We argue that these results can be accommodated within the general interpretational framework we previously advocated, in which a population of ambient interstellar or circumgalactic clouds is accelerated by the combined forces of gravity and the momentum flux from the starburst. We show that this simple physical picture is consistent with both the strong cosmological evolution of galactic outflows in typical star-forming galaxies and the paucity of such galaxies with spectra showing inflows. We also present simple parameterizations of these results that can be implemented in theoretical models and numerical simulations of galaxy evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

Global quantification of the dispersion effect with POLDER satellite data

Increased aerosols can modify the shape of the cloud Particle Size Distribution (PSD), thereby influencing the radiative properties of clouds, known as the Dispersion Effect (DE). However, a global, observation-based quantification of its impact on Aerosol-Cloud Interactions (ACI) is lacking, leading to DE being typically ignored in satellite-based estimates of ACI forcing. Here we propose a physics-based method that combines polarimetric satellite data on cloud PSD to achieve global observational quantification of DE’s impact on ACI in liquid-phase stratiform clouds. Globally, DE offsets ACI changes induced by droplet number concentration variation and liquid water path adjustment by 7% and −1.4%, respectively. Furthermore, a parameterization based on the global dataset of PSD shape parameters is developed to improve DE estimation in large-scale models. Both the quantification and parameterization enhance our understanding of DE and facilitate the inclusion of this non-negligible impact of DE on ACI in estimating aerosol climate forcing.

54 ENVIRONMENTAL SCIENCES↗

A global model simulation for 3-D radiative transfer impact on surface hydrology over the Sierra Nevada and Rocky Mountains

We investigate 3-D mountain effects on solar flux distributions and their impact on surface hydrology over the western United States, specifically the Rocky Mountains and the Sierra Nevada, using the global CCSM4 (Community Climate System Model version 4; Community Atmosphere Model/Community Land Model – CAM4/CLM4) with a 0.23° × 0.31° resolution for simulations over 6 years. In a 3-D radiative transfer parameterization, we have updated surface topography data from a resolution of 1 km to 90 m to improve parameterization accuracy. In addition, we have also modified the upward-flux deviation (3-D–PP (plane-parallel)) adjustment to ensure that the energy balance at the surface is conserved in global climate simulations based on 3-D radiation parameterization. We show that deviations in the net surface fluxes are not only affected by 3-D mountains but also influenced by feedbacks of cloud and snow in association with the long-term simulations. Deviations in sensible heat and surface temperature generally follow the patterns of net surface solar flux. The monthly snow water equivalent (SWE) deviations show an increase in lower elevations due to reduced snowmelt, leading to a reduction in cumulative runoff. Over higher-elevation areas, negative SWE deviations are found because of increased solar radiation available at the surface. Simulated precipitation increases for lower elevations, while it decreases for higher elevations, with a minimum in April. Liquid runoff significantly decreases at higher elevations after April due to reduced SWE and precipitation.

54 ENVIRONMENTAL SCIENCES↗

A Comprehensive Analysis of Uncertainties in Warm-Rain Parameterizations in Climate Models Based on In Situ Measurements

Abstract Because of the coarse grid size of Earth system models (ESMs), representing warm-rain processes in ESMs is a challenging task involving multiple sources of uncertainty. Previous studies evaluated warm-rain parameterizations mainly according to their performance in emulating collision–coalescence rates for local droplet populations over a short period of a few seconds. The representativeness of these local process rates comes into question when applied in ESMs for grid sizes on the order of 100 km and time steps on the order of 20–30 min. We evaluate several widely used warm-rain parameterizations in ESM application scenarios. In the comparison of local and instantaneous autoconversion rates, the two parameterization schemes based on numerical fitting to stochastic collection equation (SCE) results perform best. However, because of Jessen’s inequality, their performance deteriorates when grid-mean, instead of locally resolved, cloud properties are used in their simulations. In contrast, the effect of Jessen’s inequality partly cancels the overestimation problem of two semianalytical schemes, leading to an improvement in the ESM-like comparison. In the assessment of uncertainty due to the large time step of ESMs, it is found that the rainwater tendency simulated by the SCE is roughly linear for time steps smaller than 10 min, but the nonlinearity effect becomes significant for larger time steps, leading to errors up to a factor of 4 for a time step of 20 min. After considering all uncertainties, the grid-mean and time-averaged rainwater tendency based on the parameterization schemes is mostly within a factor of 4 of the local benchmark results simulated by SCE.

Meteorology & Atmospheric Sciences↗