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DOE OSTI2026

Examining Aerosol Vertical Transport and Removal during Deep Convective Events

Atmospheric aerosols affect the global energy budget by scattering and absorbing sunlight (direct effects) and by changing the microphysical structure, lifetime, and coverage of clouds (indirect effects). Globally, the free troposphere is a major source of nucleation- and Aitken-mode aerosols due to the enhanced new particle formation rates at high altitudes. Recent studies have shown deep convective systems are capable of transporting these small aerosols from the free troposphere to the boundary layer by strong convective downdrafts and weaker downward motions in the stratiform regions. These vertically transported aerosols can grow into cloud condensation nuclei (CCN) and play a significant role in the global climate. During the deep convective processes, existing accumulation-mode aerosols that act as coagulation sinks of smaller particles are also removed by wet scavenging. Compared to the vertical transport of these particles by entrainment mixing, which is slower but more prevalent, the deep convective downdraft processes may be more rapid and efficient in the vertical transport of aerosols. However, most of the current climate models do not include this mechanism as a source of CCN, mainly because the frequency of deep convective events varies significantly with geographic location and thus their contributions to CCN are unpredictable. We target this critical gap in understanding the vertical transport and removal of aerosols by deep convections. We proposed to analyze a multi-year, multi-site measurement record available from the U.S. Department of Energy (DOE) ARM program, including the observations from the 2014/15 Observations and Modeling of the Green Ocean Amazon (GoAmazon) field campaign, the 2017/18 Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign, the 2018/19 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign, the 2021/22 Tracking Aerosol Convection Interactions Experiment (TRACER) field campaign, and the long-term measurements collected at the Southern Great Plains (SGP) atmospheric observatory, where deep convective clouds were frequently observed. This project is aimed at the following three objectives: (1) Gaining a detailed and quantitative understanding of the aerosols transported by a convective downdraft and their evolution in the atmosphere; (2) Examining the wet scavenging mechanisms and efficiencies of aerosols at altitudes of deep convective systems based on ground and aircraft measurements; (3) Evaluating the contribution of deep convective systems to CCN as both a source and a sink of atmospheric aerosols and its seasonal variabilities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A high-resolution database of mesoscale convective systems and isolated deep convection in the United States for 2004 – 2017

The database provides high-resolution (4-km, hourly) information of mesoscale convective systems (MCSs) and isolated deep convection events (IDC) east of the Rocky Mountains over the contiguous United States from 2004 – 2017. The database contains various characteristics of MCSs and IDC, such as their lifecycle evolutions, lifetimes, spatial coverages, echo-top heights, precipitation features, convective and stratiform separation, convective core features, propagation speed, etc.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A high-resolution database of mesoscale convective systems and isolated deep convection in the United States for 2004 – 2017

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

An Observational Study on Cloud Spectral Width in North China

Cloud droplet size distribution (CDSD) is a critical characteristic for a number of processes related to clouds, considering that cloud droplets are formed in different sizes above the cloud-base. This paper analyzes the in-situ aircraft measurements of CDSDs and aerosol concentration ( N a ) performed in stratiform clouds in Hebei, China, in 2015 to reveal the characteristics of cloud spectral width, commonly known as relative dispersion ( ε , ratio of standard deviation (σ) to mean radius (r) of the CDSD). A new algorithm is developed to calculate the contributions of droplets of different sizes to ε . It is found that small droplets with the size range of 1 to 5.5 μm and medium droplets with the size range of 5.5 to 10 μm are the major contributors to ε, and the medium droplets generally dominate the change of ε. The variation of ε with N a can be well explained by comparing the normalized changes of σ and r ( k σ /σ and k r /r ), rather than k σ and k r only ( k σ is Δσ/Δ N a and k r is Δr/Δ N a ). From the perspective of external factors affecting ε change, the effects of N a and condensation are examined. As a result, it is found that ε increases initially and decreases afterward as N a increases, and “condensational broadening” occurs up to 1 km above cloud-base, potentially providing observational evidence for recent numerical simulations in the literature.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2012

Some Issues in Uncertainty Quantification and Parameter Tuning: A Case Study of Convective Parameterization Scheme in the WRF Regional Climate Model

The current tuning process of parameters in global climate models is often performed subjectively, or treated as an optimization procedure to minimize the difference between model fields and observations. The later approach may be generating a set of tunable parameters that approximate the observed climate but via an unrealistic balance of physical processes and/or compensating errors over different regions in the globe. In this study, we run the Weather Research and Forecasting (WRF) regional model constrained by the reanalysis data over the Southern Great Plains (SGP) where abundant observational data from various resources are available for calibration of the input parameters and validation of the model results. Our goal is to quantify the uncertainty ranges and identify the optimal values of five key input parameters in a new Kain-Frisch (KF) convective parameterization scheme incorporated in the WRF model. A stochastic sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA), is employed to efficiently sample the input parameters in KF scheme based on the skill score so that the algorithm progressively moves toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP show that the model bias for precipitation can be significantly reduced by using five optimal parameters identified by the MVFSA algorithm. The model performance is very sensitive to downdraft and entrainment related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreases as the ratio of downdraft to updraft flux increases. Larger CAPE consumption time results in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by only constraining precipitation generates positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25 km simulation, both the magnitude and spatial pattern of simulated precipitation are improved at 12-km spatial resolution. The optimal parameters identified from the SGP region have also improved the simulation of precipitation when moving model domain to another region with a different climate regime (i.e. North America monsoon region). These results suggest the improvement of precipitation simulation by using the optimal parameters remains when the model domain or spatial resolution is changed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Marine boundary layer structure as observed by A-train satellites

Abstract. The marine boundary layer (MBL) structure is important to the marine low cloud processes, and the exchange of heat, momentum, and moisture between oceans and the low atmosphere. This study examines the MBL structure over the eastern Pacific region and further explores the controlling factors of MBL structure over the global oceans with a new 4-year satellite-based data set. The MBL top (boundary layer height, BLH) and the mixing layer height (MLH) were identified using the MBL aerosol lidar backscattering from the CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations). Results showed that the MBL is generally decoupled with MLH ∕ BLH ratio ranging from ∼ 0.5 to ∼ 0.8 over the eastern Pacific Ocean region. The MBL decoupling magnitude is mainly controlled by estimated inversion strength (EIS), which in turn controls the cloud top entrainment process. The systematic differences between drizzling and non-drizzling stratocumulus tops also show dependence on EIS. This may be related to the meso-scale circulations or gravity wave in the MBL. Further analysis indicates that the MBL shows a similar decoupled structure for clear-sky and cumulus-cloud-topped conditions, but is better mixed under stratiform cloud breakup and overcast conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

A novel approach for characterizing the variability in mass–dimension relationships: results from MC3E

Abstract. Mass–dimension (m–D) relationships determining bulkmicrophysical properties such as total water content (TWC) and radarreflectivity factor (Z) from particle size distributions are used in bothnumerical models and remote sensing retrievals. The a and b coefficientsrepresenting m=aD b relationships, however, can vary significantlydepending on meteorological conditions, particle habits, the definition ofparticle maximum dimension, the probes used to obtain the data, techniquesused to process the cloud probe data, and other unknown reasons. Thus,considering a range of a,b coefficients may be more applicable for use innumerical models and remote sensing retrievals. Microphysical data collectedby two-dimensional optical array probes (OAPs) installed on the University ofNorth Dakota (UND) Citation aircraft during the Mid-latitude Continental ConvectiveClouds Experiment (MC3E) were used in conjunction with TWC data from aNevzorov probe and ground-based S-band radar data to determine a and busing a technique that minimizes the chi-square difference between the TWC andZ derived from the OAPs and those directly measured by a TWC probe andradar. All a and b values within a specified tolerance were regarded as equallyplausible solutions. Of the 16 near-constant-temperature flight legs analyzedduring the 25 April, 20 May, and 23 May 2011 events, the derived surfaces ofsolutions on the first 2 days where the aircraft-sampled stratiform cloudhad a larger range in a and b for lower temperature environments thatcorrespond to less variability in N(D), TWC, and Z for a flight leg.Because different regions of the storm were sampled on 23 May, differences inthe variability in N(D), TWC, and Z influenced the distribution ofchi-square values in the (a,b) phase space and the specified tolerance in away that yielded 2.8 times fewer plausible solutions compared to the flightlegs on the other dates. These findings show the importance of representingthe variability in a,b coefficients for numerical modeling and remotesensing studies, rather than assuming fixed values, as well as the need tofurther explore how these surfaces depend on environmental conditions inclouds containing ice hydrometeors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Open cells exhibit weaker entrainment of free-tropospheric biomass burning aerosol into the south-east Atlantic boundary layer

This work presents synergistic satellite, airborne and surface-based observations of a pocket of open cells (POC) in the remote south-east Atlantic. The observations were obtained over and upwind of Ascension Island during the CLouds and Aerosol Radiative Impacts and Forcing (CLARIFY) and the Layered Smoke Interacting with Clouds (LASIC) field experiments. A novel aspect of this case study is that an extensive free-tropospheric biomass burning aerosol plume that had been transported from the African continent was observed to be in contact with the boundary layer inversion over the POC and the surrounding closed cellular cloud regime. The in situ measurements show marked contrasts in the boundary layer thermodynamic structure, cloud properties, precipitation and aerosol conditions between the open cells and surrounding overcast cloud field. The data demonstrate that the overlying biomass burning aerosol was mixing down into the boundary layer in the stratocumulus cloud downwind of the POC, with elevated carbon monoxide, black carbon mass loadings and accumulation-mode aerosol concentrations measured beneath the trade-wind inversion. The stratocumulus cloud in this region was moderately polluted and exhibited very little precipitation falling below cloud base. A rapid transition to actively precipitating cumulus clouds and detrained stratiform remnants in the form of thin quiescent veil clouds was observed across the boundary into and deep within the POC. The subcloud layer in the POC was much cleaner than that in the stratocumulus region. The clouds in the POC formed within an ultra-clean layer (accumulation-mode aerosol concentrations of approximately a few cm -3 ) in the upper region of the boundary layer, which was likely to have been formed via efficient collision–coalescence and sedimentation processes. Enhanced Aitken-mode aerosol concentrations were also observed intermittently in this ultra-clean layer, suggesting that new particle formation was taking place. Across the boundary layer inversion and immediately above the ultra-clean layer, accumulation-mode aerosol concentrations were ~1000 cm -3 . Importantly, the air mass in the POC showed no evidence of elevated carbon monoxide over and above typical background conditions at this location and time of year. As carbon monoxide is a good tracer for biomass burning aerosol that is not readily removed by cloud processing and precipitation, it demonstrates that the open cellular convection in the POC is not able to entrain large quantities of the free-tropospheric aerosol that was sitting directly on top of the boundary layer inversion. This suggests that the structure of the mesoscale cellular convection may play an important role in regulating the transport of aerosol from the free troposphere down into the marine boundary layer. We then develop a climatology of open cellular cloud conditions in the south-east Atlantic from 19 years of September Moderate Resolution Imaging Spectroradiometer (MODIS) Terra imagery. This shows that the maxima in open cell frequency (> 0.25) occurs far offshore and in a region where subsiding biomass burning aerosol plumes may often come into contact with the underlying boundary layer cloud. If the results from the observational case study applied more broadly, then the apparent low susceptibility of open cells to free-tropospheric intrusions of additional cloud condensation nuclei could have some important consequences for aerosol–cloud interactions in the region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

The Green Ocean: Precipitation Insights from the GoAmazon2014/5 Experiment

This study summarizes the precipitation properties collected during the GoAmazon2014/5 campaign near Manaus in central Amazonia, Brazil. Precipitation breakdowns, summary radar rainfall relationships and self-consistency concepts from a coupled disdrometer and radar wind profiler measurements are presented. The properties of Amazon cumulus and associated stratiform precipitation are discussed, including segregations according to seasonal (Wet/Dry regime) variability, cloud echo-top height and possible aerosol influences on the apparent oceanic characteristics of the precipitation drop size distributions. Overall, we observe that the Amazon precipitation straddles behaviors found during previous U.S. Department of Energy Atmospheric Radiation Measurements program (ARM) tropical deployments, with distributions favoring higher concentrations of smaller drops than ARM continental examples. Oceanic type precipitation characteristics are predominantly observed during the Amazon Wet seasons. Finally, an exploration of the controls on Wet season precipitation properties reveals that wind direction, as compared with other standard radiosonde thermodynamic parameters or aerosol count/regime classifications performed at the ARM site, provides a good indicator for those Wet season Amazon events having an oceanic character for their precipitation drop size distributions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Sunlight-absorbing aerosol amplifies the seasonal cycle in low-cloud fraction over the southeast Atlantic

Abstract. The mean altitude of the smoke loading over the southeast Atlantic moves from the boundary layer in July to the free troposphere by October. This study details the month-by-month changes in cloud properties and the large-scale environment as a function of the biomass burning aerosol loading at Ascension Island (8∘ S, 14.5∘ W) from July to October, based on island measurements, satellite retrievals, and reanalysis. In July and August, the smoke loading predominantly varies within the boundary layer. During both months, the low-cloud fraction is less and is increasingly cumuliform when more smoke is present, with the exception of a late morning boundary layer deepening that encourages a short-lived cloud development. The meteorology varies little, suggesting aerosol–cloud interactions explain the cloudiness changes. September marks a transition month during which midlatitude disturbances can intrude into the Atlantic subtropics, constraining the free tropospheric aerosol closer to the African coast. Stronger boundary layer winds on cleaner days help deepen, dry, and cool much of the marine boundary layer compared to that on days with high smoke loadings, with stratocumulus reducing everywhere but at the northern deck edge. The September free troposphere is better mixed on smoky days compared to October. Longwave cooling rates, generated by a sharp water vapor gradient at the aerosol layer top, encourage a small-scale vertical mixing that could help maintain the well-mixed smoky September free troposphere. The October meteorology primarily varies as a function of the strength of the free tropospheric winds advecting aerosol offshore. The free tropospheric aerosol loading is less than in September, and the moisture variability is greater. Low-level clouds increase and are more stratiform in October when the smoke loadings are higher. The increased free tropospheric moisture can help sustain the clouds through a reduction in evaporative drying during cloud-top entrainment. Enhanced subsidence above the coastal upwelling region, increasing cloud droplet number concentrations, may further prolong cloud lifetime through microphysical interactions. Reduced subsidence underneath stronger free tropospheric winds at Ascension Island supports slightly higher cloud tops during smokier conditions. Overall, the monthly changes in the large-scale aerosol and moisture vertical structure act to amplify the seasonal cycle in low-cloud amount and morphology. This is climatically important, as cloudiness changes dominate changes in the top-of-atmosphere radiation budget.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

The importance of Aitken mode aerosol particles for cloud sustenance in the summertime high Arctic – a simulation study supported by observational data

The potential importance of Aitken mode particles (diameters ~ 25–80 nm) for stratiform mixed-phase clouds in the summertime high Arctic (>80° N) has been investigated using two large-eddy simulation models. We find that, in both models, Aitken mode particles significantly affect the simulated microphysical and radiative properties of the cloud and can help sustain the cloud when accumulation mode concentrations are low (< 10–20 cm –3 ), even when the particles have low hygroscopicity (hygroscopicity parameter – κ=0.1). However, the influence of the Aitken mode decreases if the overall liquid water content of the cloud is low, either due to a higher ice fraction or due to low radiative cooling rates. An analysis of the simulated supersaturation (ss) statistics shows that the ss frequently reaches 0.5 % and sometimes even exceeds 1 %, which confirms that Aitken mode particles can be activated. The modelling results are in qualitative agreement with observations of the Hoppel minimum obtained from four different expeditions in the high Arctic. Our findings highlight the importance of better understanding Aitken mode particle formation, chemical properties and emissions, particularly in clean environments such as the high Arctic.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

The influence of multiple groups of biological ice nucleating particles on microphysical properties of mixed-phase clouds observed during MC3E

Abstract. A new empirical parameterization (EP) for multiple groups of primary biological aerosol particles (PBAPs) is implemented in the aerosol–cloud model (AC) to investigate their roles as ice nucleating particles (INPs). The EP describes the heterogeneous ice nucleation by (1) fungal spores, (2) bacteria, (3) pollen, (4) detritus of plants, animals, and viruses, and (5) algae. Each group includes fragments from the originally emitted particles. A high-resolution simulation of a midlatitude mesoscale squall line by AC is validated against airborne and ground observations. Sensitivity tests are carried out by varying the initial vertical profiles of the loadings of individual PBAP groups. The resulting changes in warm and ice cloud microphysical parameters are investigated. The changes in warm microphysical parameters, including liquid water content and cloud droplet number concentration, are minimal (<10 %). Overall, PBAPs have little effect on the ice number concentration (<6 %) in the convective region. In the stratiform region, increasing the initial PBAP loadings by a factor of 1000 resulted in less than 40 % change in ice number concentrations. The total ice concentration is mostly controlled by various mechanisms of secondary ice production (SIP). However, when SIP is intentionally shut down in sensitivity tests, increasing the PBAP loading by a factor of 100 has an effect of less than 3 % on the ice phase. Further sensitivity tests revealed that PBAPs have little effect on surface precipitation and on the shortwave and longwave flux (<4 %) for a 100-fold perturbation in PBAPs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Regime-based aerosol–cloud interactions from CALIPSO-MODIS and the Energy Exascale Earth System Model version 2 (E3SMv2) over the Eastern North Atlantic

This study investigates aerosol-cloud interactions in marine boundary layer (MBL) clouds using an advanced deep-learning-driven synoptic-regime-based framework, combining satellite data (CALIPSO vertically resolved aerosol extinction and MODIS cloud properties) with 1° nudged Energy Exascale Earth System Model version 2 (E3SMv2) simulation over the Eastern North Atlantic (ENA; ∼10°×10°, 2006–2014). The E3SMv2 captures observed seasonal variations in cloud droplet number concentrations (N d ) and liquid water path (LWP), though it systematically underestimates N d . We then partition ENA meteorology into four synoptic regimes (Pre-Trough, Post-Trough, Ridge, Trough) via a deep-learning clustering of ERA5 reanalysis fields, enabling regime-dependent aerosol-cloud interactions analyses. Both satellite and E3SMv2 exhibit an inverted-V LWP-N d relationship. In Post-Trough and Ridge regimes, the satellite shows stronger negative LWP-N d sensitivities than in Pre-Trough regime. The Trough regime displays a muted satellite LWP response. In comparison, the model predicts more exaggerated LWP responses across regimes, with LWP increasing too quickly at low N d and decreasing more sharply at high N d , especially in Pre-Trough and Trough regimes. These exaggerated model LWP sensitivities may stem from uncertainties in representing drizzle processes, entrainment, and turbulent mixing. As for N d susceptibility to aerosols, N d increases with MBL aerosol extinction in both datasets, but the simulated aerosol-cloud interactions appear oversensitive to meteorological conditions. Overall, E3SMv2 better captures aerosol effects under regimes that favor stratiform clouds (Post-Trough, Ridge), but performance deteriorates for regimes with deeper, dynamically complex clouds (Trough), highlighting the need for improved representations of those cloud processes in climate models.

Environmental sciences↗

DOE OSTI2021

Retrieving microphysical properties of concurrent pristine ice and snow using polarimetric radar observations

Abstract. Ice and mixed-phase clouds play a key role in our climate system because of their strong controls on global precipitation and radiation budget. Their microphysical properties have been characterized commonly by polarimetric radar measurements. However, there remains a lack of robust estimates of microphysical properties of concurrent pristine ice and aggregates because larger snow aggregates often dominate the radar signal and mask contributions of smaller pristine ice crystals. This paper presents a new method that separates the scattering signals of pristine ice embedded in snow aggregates in scanning polarimetric radar observations and retrieves their respective abundances and sizes for the first time. This method, dubbed ENCORE-ice, is built on an iterative stochastic ensemble retrieval framework. It provides the number concentration, ice water content, and effective mean diameter of pristine ice and snow aggregates with uncertainty estimates. Evaluations against synthetic observations show that the overall retrieval biases in the combined total microphysical properties are within 5 % and that the errors with respect to the truth are well within the retrieval uncertainty. The partitioning between pristine ice and snow aggregates also agrees well with the truth. Additional evaluations against in situ cloud probe measurements from a recent campaign for a stratiform cloud system are promising. Our median retrievals have a bias of 98 % in the total ice number concentration and 44 % in the total ice water content. This performance is generally better than the retrieval from empirical relationships. The ability to separate signals of different ice species and to provide their quantitative microphysical properties will open up many research opportunities, such as secondary ice production studies and model evaluations for ice microphysical processes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Partition between supercooled liquid droplets and ice crystals in mixed-phase clouds based on airborne in situ observations

Abstract. The onset of ice nucleation in mixed-phase clouds determines the lifetime and microphysical properties of ice clouds. In this work, we develop a novel method that differentiates between various phases of mixed-phase clouds, such as clouds dominated by pure liquid or pure ice segments, compared with those having ice crystals surrounded by supercooled liquid water droplets or vice versa. Using this method, we examine the relationship between the macrophysical and microphysical properties of Southern Ocean mixed-phase clouds at −40 to 0 °C (e.g. stratiform and cumuliform clouds) based on the in situ aircraft-based observations during the US National Science Foundation Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) flight campaign. The results show that the exchange between supercooled liquid water and ice crystals from a macrophysical perspective, represented by the increasing spatial ratio of regions containing ice crystals relative to the total in-cloud region (defined as ice spatial ratio), is positively correlated with the phase exchange from a microphysical perspective, represented by the increasing ice water content (IWC), decreasing liquid water content (LWC), increasing ice mass fraction, and increasing ice particle number fraction (IPNF). The mass exchange between liquid and ice becomes more significant during phase 3 when pure ice cloud regions (ICRs) start to appear. Occurrence frequencies of cloud thermodynamic phases show a significant phase change from liquid to ice at a similar temperature (i.e. −17.5 °C) among three types of definitions of mixed-phase clouds based on ice spatial ratio, ice mass fraction, or IPNF. Aerosol indirect effects are quantified for different phases using number concentrations of aerosols greater than 100 or 500 nm (N>100 and N>500, respectively). N>500 shows stronger positive correlations with ice spatial ratios compared with N>100. This result indicates that larger aerosols potentially contain ice-nucleating particles (INPs), which facilitate the formation of ice crystals in mixed-phase clouds. The impact of N>500 is also more significant in phase 2 when ice crystals just start to appear in the mixed phase compared with phase 3 when pure ICRs have formed, possibly due to the competing aerosol indirect effects on primary and secondary ice production in phase 3. The thermodynamic and dynamic conditions are quantified for each phase. The results show stronger in-cloud turbulence and higher updraughts in phases 2 and 3 when liquid and ice coexist compared with pure liquid or ice (phases 1 and 4, respectively). The highest updraughts and turbulence are seen in phase 3 when supercooled liquid droplets are surrounded by ice crystals. These results indicate both updraughts and turbulence support the maintenance of supercooled liquid water amongst ice crystals. Overall, these results illustrate the varying effects of aerosols, thermodynamics, and dynamics through various stages of mixed-phase cloud evolution based on this new method that categorizes cloud phases.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Rainbows and Climate Change: A tutorial on climate model diagnostics and parameterization

Earth System Models (ESMs) must represent processes below the grid scale of a model using representations (parameterizations) of physical and chemical processes. As a tutorial exercise to understand diagnostics and parameterization, this work presents a representation of rainbows for an ESM: the Community Earth System Model version 2 (CESM2). Using the 'state' of the model, basic physical laws, and some assumptions, we generate a representation of this unique optical phenomena as a diagnostic output. Rainbow occurrence and it's possible changes are related to cloud occurrence and rain formation which are critical uncertainties for climate change prediction. The work highlights issues which are typical of many diagnostics parameterizations such as assumptions, uncertain parameters and the difficulty of evaluation against uncertain observations. Results agree qualitatively with limited available global 'observations' of Rainbows. Rainbows are seen in expected locations in the sub-tropics over the ocean where broken clouds and frequent precipitation occurs. The diurnal peak is in the morning over ocean and in the evening over land. The representation of rainbows is found to be quantitatively sensitive to the assumed amount of cloudiness and the amount of stratiform rain. Rainbows are projected to have decreased, mostly in the Northern Hemisphere, due to aerosol pollution effects increasing cloud coverage since 1850. In the future, continued climate change is projected to decrease cloud cover, associated with a positive cloud feedback. As a result the rainbow diagnostic projects that rainbows will increase in the future, with the largest changes at mid-latitudes. The diagnostic may be useful for assessing cloud parameterizations, and is an exercise in how to build and test parameterizations of atmospheric phenomena.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1

Abstract. This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1∘ horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of changes in 10-year mean zonal averages include the following: up to 0.5 K of warming in the lower troposphere and cooling in the tropical and subtropical upper troposphere, 1 %–10 % decreases in relative humidity throughout the troposphere, and 10 %–20 % decreases in cloud fraction in the upper troposphere and decreases exceeding 20 % in the subtropical lower troposphere. In terms of the 10-year mean geographical distribution, systematic decreases of 20 %–50 % are seen in total cloud cover and cloud radiative effects in the subtropics. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; to regain optimal climate fidelity in the absence of those truncation errors, the model would require retuning. A coarse-grained attribution of the time step sensitivities is carried out by shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection, and stratiform cloud macrophysics and microphysics parameterizations but rather by the step sizes used outside those subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM significantly affects the subtropical marine stratocumulus decks, while deep convection has significant impacts on trade cumulus. The step size of the cloud macrophysics and microphysics subcycle itself appears to have a primary impact on cloud fraction in the upper troposphere and also in the midlatitude near-surface layers. Impacts of step sizes used by the dynamical core and the radiation parameterization appear to be relatively small. These results provide useful clues for future studies aiming at understanding and addressing the root causes of sensitivities to time step sizes and process coupling frequencies in EAM. While this study focuses on EAMv1 and the conclusions are likely model-specific, the presented experimentation strategy has general value for weather and climate model development, as the methodology can help researchers identify and understand sources of time integration error in sophisticated multi-component models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains

Abstract. Based on long-term observations at the Southern Great Plains site by the Atmospheric Radiation Measurement (ARM) program for training and validation, a deep-learning model is developed to simulate the daytime evolution of boundary layer clouds (BLCs) from the perspective of land–atmosphere coupling. The model takes ARM measurements (including early-morning soundings and diurnally varying surface meteorological conditions and heat fluxes) as inputs and predicts hourly estimates (including cloud occurrence, the positions of cloud boundaries, and the vertical profile of the cloud fraction) as outputs. The deep-learning model offers good agreement with the observed cloud fields, especially in the accuracy with which cloud occurrence and base height are reproduced. When the inputs are substituted by reanalysis data from ERA5 and MERRA-2, the outputs of the deep-learning model provide a better agreement with observation than the cloud fields extracted from ERA5 and MERRA-2 themselves. Thus, the deep-learning model shows great potential to serve as a diagnostic tool for the performance of physics-based models in simulating stratiform and cumulus clouds. By quantifying biases in clouds and attributing them to the simulated atmospheric state variables versus the model-parameterized cloud processes, this observation-based deep-learning model may offer insights into the directions needed to improve the simulation of BLCs in physics-based models for weather forecasting and climate prediction.

54 ENVIRONMENTAL SCIENCES↗