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Lee, Dongmin

Publications and source records attributed to Lee, Dongmin.

13 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

An Evaluation of Clouds and Radiation in a Large-Scale Atmospheric Model Using a Cloud Vertical Structure Classification

We revisit the concept of the cloud vertical structure (CVS) classes we have previously employed to classify the planet's cloudiness (Oreopoulos et al., 2017). The CVS classification reflects simple combinations of simultaneous cloud occurrence in the three standard layers traditionally used to separate low, middle, and high clouds and was applied to a dataset derived from active lidar and cloud radar observations. This classification is now introduced in an atmospheric global climate model, specifically a version of NASA's GEOS-5, in order to evaluate the realism of its cloudiness and of the radiative effects associated with the various CVS classes. Such classes can be defined in GEOS-5 thanks to a sub column cloud generator paired with the model's radiative transfer algorithm, and their associated radiative effects can be evaluated against observations. We find that the model produces 50% more clear skies than observations in relative terms and produces isolated high clouds that are slightly less frequent than in observations, but optically thicker, yielding excessive planetary and surface cooling. Low clouds are also brighter than in observations, but underestimates of the frequency of occurrence (by ~20% in relative terms) help restore radiative agreement with observations. Overall the model better reproduces the longwave radiative effects of the various CVS classes because cloud vertical location is substantially constrained in the CVS framework.

Lee, Dongmin↗
NASA NTRS2017

Contributions of Mixed-Phase Clouds to Reduced Arctic Amplification

Earth’s Arctic is particularly sensitive to global warming. The climate record shows that Arctic changes in surface temperatures far exceed that of the global mean, a phenomenon referred to as Arctic amplification. Here, we show that warming of the Arctic atmosphere causes mixed-phase clouds in the region to contain less ice and more supercooled liquid, which in turn tends to increase their amount and thick- ness, thereby inducing a positive feedback mainly by increasing downward longwave (LW) radiation at the surface. The increased downward LW radiation decreases the positive lapse rate feedback in the Arctic, thus resulting in reduced Arctic amplification. The strength of this feedback depends on the initial mean-state supercooled liquid fraction (SLF) and the ice crystal effective radii. We also show that reduced precipitation rates can result from large mean-state ice effective radii being replaced by relatively more smaller liquid droplets in the cloud phase feedback, despite having high mean-state SLFs, demonstrating the importance of the representation of cloud microphysics in the Arctic.

Tan, Ivy↗
NASA NTRS2017

Strong Constraints on Aerosol-Cloud Interactions from Volcanic Eruptions

Aerosols have a potentially large effect on climate, particularly through their interactions with clouds, but the magnitude of this effect is highly uncertain. Large volcanic eruptions produce sulfur dioxide, which in turn produces aerosols; these eruptions thus represent a natural experiment through which to quantify aerosol-cloud interactions. Here we show that the massive 2014-2015 fissure eruption in Holuhraun, Iceland, reduced the size of liquid cloud droplets - consistent with expectations - but had no discernible effect on other cloud properties. The reduction in droplet size led to cloud brightening and global-mean radiative forcing of around minus 0.2 watts per square metre for September to October 2014. Changes in cloud amount or cloud liquid water path, however, were undetectable, indicating that these indirect effects, and cloud systems in general, are well buffered against aerosol changes. This result will reduce uncertainties in future climate projections, because we are now able to reject results from climate models with an excessive liquid-water-path response.

atmospheric science↗
NASA NTRS2016

Simplified ISCCP Cloud Regimes for Evaluating Cloudiness in CMIP5 Models

We take advantage of the ISCCP simulator implemented in many CMIP5 models, in order to introduce a credible method to compare model cloud output with corresponding ISCCP observations based on the cloud regime (CR) concept. A novel simplified CR derivation method is introduced that exploits the co-variations of three variables, cloud optical thickness, cloud top pressure and cloud fraction (, pc, CF). Following evaluation criteria established in a previous paper of ours, we assess model cloud simulation performance based on how well the simplified CRs are simulated in terms of similarity of centroids, global values and map correlations of relative frequency-of-occurrence (RFO), and long term total clouds amounts (as opposed to average instantaneous cloud fractions). Mirroring prior results, modeled clouds tend to be too thick optically and not as extensive as in observations. Averaging across models does not help in this or other evaluation aspects, except for cloud geographical locations. A good model for one criterion is usually found to be also a good performer for other criteria despite plenty of exceptions for the criterion of centroid similarity. On the other hand, CRs that include convectively generated high-altitude clouds are not as well simulated here compared to the previous study, but other regimes containing low clouds with high CF improve. Models that have previously performed well distinguish themselves again here, but improvements from other models are also found. The simplified cloud evaluation method thus proves to be more forgiving while still good enough to reveal model weaknesses.

global climate models↗
NASA NTRS2016

Cloud Regimes as a Tool for Systematic Study of Various Aerosol-Cloud-Precipitation Interactions

Systematic changes of clouds and precipitation are notoriously difficult to ascribe to aerosols. This presentation will showcase yet one more attempt to at least credibly detect the signal of aerosol-cloud-precipitation interactions. We surmise that the concept of cloud regimes (CRs) is appropriate to conduct such an investigation. Previous studies focused on what we call here dynamical CRs, and while we continue to adopt those too for our analysis, we have found that a different way of organizing cloud systems, namely via microphysical regimes is also promising. Our analysis relies on MODIS Collection 6 Level-3 data for clouds and aerosols, and TRMM-TMPA data for precipitation. The regimes are derived by applying clustering analysis on MODIS joint histograms, and once each grid cell is assigned a regime, aerosol and precipitation data can be spatiotemporally matched and composited by regime. The composites of various cloud and precipitation variables for high (upper quartile of distribution) and low (lower quartile) aerosol loadings can then be contrasted. We seek evidence of aerosol effects both in regimes with large fractions of deep ice-rich clouds, as well as regimes where low liquid phase clouds dominate. Signals can be seen, especially when the analysis is broken by land-ocean and when additional filters are applied, but there are of course caveats which will be discussed.

cloud regimes↗
NASA NTRS2014

An Examination of the Nature of Global MODIS Cloud Regimes

We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.

radiation↗
NASA NTRS2014

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.

CALIOP and MODIS↗
NASA NTRS2013

Estimating the Direct Radiative Effect of Absorbing Aerosols Overlying Marine Boundary Layer Clouds in the Southeast Atlantic Using MODIS and CALIOP

Absorbing aerosols such as smoke strongly absorb solar radiation, particularly at ultraviolet and visible/near-infrared (VIS/NIR) wavelengths, and their presence above clouds can have considerable implications. It has been previously shown that they have a positive (i.e., warming) direct aerosol radiative effect (DARE) when overlying bright clouds. Additionally, they can cause biased passive instrument satellite retrievals in techniques that rely on VIS/NIR wavelengths for inferring the cloud optical thickness (COT) and effective radius (re) of underlying clouds, which can in turn yield biased above-cloud DARE estimates. Here we investigate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical property retrieval biases due to overlying absorbing aerosols observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and examine the impact of these biases on above-cloud DARE estimates. The investigation focuses on a region in the southeast Atlantic Ocean during August and September (2006-2011), where smoke from biomass burning in southern Africa overlies persistent marine boundary layer stratocumulus clouds. Adjusting for above-cloud aerosol attenuation yields increases in the regional mean liquid COT (averaged over all ocean-only liquid clouds) by roughly 6%; mean re increases by roughly 2.6%, almost exclusively due to the COT adjustment in the non-orthogonal retrieval space. It is found that these two biases lead to an underestimate of DARE. For liquid cloud Aqua MODIS pixels with CALIOP-observed above-cloud smoke, the regional mean above-cloud radiative forcing efficiency (DARE per unit aerosol optical depth (AOD)) at time of observation (near local noon for Aqua overpass) increases from 50.9Wm(sup-2)AOD(sup-1) to 65.1Wm(sup-2)AOD(sup -1) when using bias-adjusted instead of nonadjusted MODIS cloud retrievals.

aerosols↗
NASA NTRS2012

Longwave Band-by-band Cloud Radiative Effect and its Application in GCM Evaluation

The cloud radiative effect (CRE) of each longwave (LW) absorption band of a GCM fs radiation code is uniquely valuable for GCM evaluation because (1) comparing band-by-band CRE avoids the compensating biases in the broadband CRE comparison and (2) the fractional contribution of each band to the LW broadband CRE (f(sub CRE)) is sensitive to cloud top height but largely insensitive to cloud fraction, presenting thus a diagnostic metric to separate the two macroscopic properties of clouds. Recent studies led by the first author have established methods to derive such band ]by ]band quantities from collocated AIRS and CERES observations. We present here a study that compares the observed band-by-band CRE over the tropical oceans with those simulated by three different atmospheric GCMs (GFDL AM2, NASA GEOS-5, and CCCma CanAM4) forced by observed SST. The models agree with observation on the annual ]mean LW broadband CRE over the tropical oceans within +/-1W/sq m. However, the differences among these three GCMs in some bands can be as large as or even larger than +/-1W/sq m. Observed seasonal cycles of f(sub CRE) in major bands are shown to be consistent with the seasonal cycle of cloud top pressure for both the amplitude and the phase. However, while the three simulated seasonal cycles of f(sub CRE) agree with observations on the phase, the amplitudes are underestimated. Simulated interannual anomalies from GFDL AM2 and CCCma CanAM4 are in phase with observed anomalies. The spatial distribution of f(sub CRE) highlights the discrepancies between models and observation over the low-cloud regions and the compensating biases from different bands.

Huang, Xianglei↗
NASA NTRS2011

The Impacts of an Observationally-Based Cloud Fraction and Condensate Overlap Parameterization on a GCM's Cloud Radiative Effect

It has been shown that the details of how cloud fraction overlap is treated in GCMs has substantial impact on shortwave and longwave fluxes. Because cloud condensate is also horizontally heterogeneous at GCM grid scales, another aspect of cloud overlap should in principle also be assessed, namely the vertical overlap of hydrometeor distributions. This type of overlap is usually examined in terms of rank correlations, i.e., linear correlations between hydrometeor amount ranks of the overlapping parts of cloud layers at specific separation distances. The cloud fraction overlap parameter and the rank correlation of hydrometeor amounts can be both expressed as inverse exponential functions of separation distance characterized by their respective decorrelation lengths (e-folding distances). Larger decorrelation lengths mean that hydrometeor fractions and probability distribution functions have high levels of vertical alignment. An analysis of CloudSat and CALIPSO data reveals that the two aspects of cloud overlap are related and their respective decorrelation lengths have a distinct dependence on latitude that can be parameterized and included in a GCM. In our presentation we will contrast the Cloud Radiative Effect (CRE) of the GEOS-5 atmospheric GCM (AGCM) when the observationally-based parameterization of decorrelation lengths is used to represent overlap versus the simpler cases of maximum-random overlap and globally constant decorrelation lengths. The effects of specific overlap representations will be examined for both diagnostic and interactive radiation runs in GEOS-5 and comparisons will be made with observed CREs from CERES and CloudSat (2B-FLXHR product). Since the radiative effects of overlap depend on the cloud property distributions of the AGCM, the availability of two different cloud schemes in GEOS-5 will give us the opportunity to assess a wide range of potential cloud overlap consequences on the model's climate.

Oreopoulos, Lazaros↗
NASA NTRS2011

The Precipitation Characteristics of ISCCP Tropical Weather States

We examine the daytime precipitation characteristics of the International Satellite Cloud Climatology Project (ISCCP) weather states in the extended tropics (35 deg S to 35 deg N) for a 10-year period. Our main precipitation data set is the TRMM Multisatellite Precipitation Analysis 3B42 data set, but Global Precipitation Climatology Project daily data are also used for comparison. We find that the most convective weather state (WS1), despite an occurrence frequency below 10%, is the most dominant state with regard to surface precipitation, producing both the largest mean precipitation rates when present and the largest percent contribution to the total precipitation of the tropical zone of our study; yet, even this weather state appears to not precipitate about half the time. WS1 exhibits a modest annual cycle of domain-average precipitation rate, but notable seasonal shifts in its geographic distribution. The precipitation rates of the other weather states tend to be stronger when occurring before or after WS1. The relative contribution of the various weather states to total precipitation is different between ocean and land, with WS1 producing more intense precipitation on average over ocean than land. The results of this study, in addition to advancing our understanding of the current state of tropical precipitation, can serve as a higher order diagnostic test on whether it is distributed realistically among different weather states in atmospheric models.

Lee, Dongmin↗