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NASA NTRS1995

Cloud model-based simulation of spaceborne radar observations

Simulations of observations from potential spaceborne radars are made based on storm structure generated from the three-dimensional (3D) Goddard cumulus ensemble model simulation of an intense overland convective system. Five frequencies of 3, 10, 14, 35, and 95 GHz are discussed, but the Tropical Rainfall Measuring Mission precipitation radar sensor frequency (14 GHz) is the focus of this study. Radar reflectives and their attenuation in various atmospheric conditions are studied in this simulation. With the attenuation from cloud and precipitation in the estimation of reflectivity factor (dBZ), the reflectivities in the lower atmosphere in the convective cores are significantly reduced. With spatial resolution of 4 km X 4 km, attenuation at 14 GHz may cause as large as a 20-dBZ difference between the simulated measurements of the peak, Z(sub mp) and near-surface reflectivity, Z(sub ms) in the most intense convective region. The Z(sub mp) occurs at various altitudes depending on the hydrometeor concentrations and their vertical distribution. Despite the significant attenuation in the intense cores, the presence of the rain maximum is easily detected by using information of Z(sub mp). In the stratiform region, the attenuation is quite limited (usually less than 5 dBZ), and the reduction of reflectivity is mostly related to the actual vertical structure of cloud distribution. Since Z(sub ms) suffers severe attenuation and tends to underestimate surface rainfall intensity in convective regions. Z(sub mp) can be more representative for rainfall retrieval in the lower atmosphere in these regions. In the stratiform region where attenuation is negligible, however, Z(sub mp) tends to overestimate surface rainfall and Z(sub ms) is more appropriate for rainfall retrieval. A hybrid technique using a weight between the two rain intensities is tested and found potentially usefull for future applications. The estimated surface rain-rate map based on this hybrid approach captures many of the details of the cloud model rain field but still slightly underestimates the rain-rate maximum.

Yeh, H.-Y. M.↗

NASA NTRS2001

Comparing the Degree of Land-Atmosphere Interaction in Four Atmospheric General Circulation Models

Land-atmosphere feedback, by which (for example) precipitation-induced moisture anomalies at the land surface affect the overlying atmosphere and thereby the subsequent generation of precipitation, has been examined and quantified with many atmospheric general circulation models (AGCMs). Generally missing from such studies, however, is an indication of the extent to which the simulated feedback strength is model dependent. Four modeling groups have recently performed a highly controlled numerical experiment that allows an objective inter-model comparison of land-atmosphere feedback strength. The experiment essentially consists of an ensemble of simulations in which each member simulation artificially maintains the same time series of surface prognostic variables. Differences in atmospheric behavior between the ensemble members then indicates the degree to which the state of the land surface controls atmospheric processes in that model. A comparison of the four sets of experimental results shows that feedback strength does indeed vary significantly between the AGCMs.

Koster, Randal D.↗

NASA NTRS1988

Numerical simulation of tropical cumulus clouds and their interaction with the subcloud layer

A two-dimensional numerical model, with an emphasis on turbulent processes in the boundary layer and in clouds, was developed for simulating an ensemble of cumulus clouds. The model was used to investigate the response of tropical cumulus clouds to imposed large-scale vertical advection by performing two simulations which were identical except that one was with upward large-scale vertical velocity (the 'disturbed' case) and the other was without any advection (the 'undisturbed' case). The results showed that deep cumulus clouds formed in the disturbed case, while only shallow clouds formed in the undisturbed case. The subcloud layer (SCL) in the disturbed case was strongly affected by cumulus circulations and rain evaporation, with both cumulus updrafts and downdrafts being important contributors to the SCL sensible and latent heat fluxes. Cumulus-scale circulation in the disturbed SCL determined where new clouds formed by creating convergence zones and moisture anomalies.

Krueger, Steven K.↗

NASA NTRS1981

A stochastic-dynamical approach to the study of the natural variability of the climate

A method, suggested by Leith (1975), which employed stochastic-dynamic forecasts obtained from a general circulation model in such a way as to satisfy the definition of climatic noise, was used to validate assumptions accounting for the effects of external influences in estimating the climatic noise. Two assumptions were investigated: (1) that the weather fluctuations can be represented as a Markov process, and (2) that changing external conditions do not influence the atmosphere's statistical properties on short time scales. The general circulation model's simulation of the daily weather fluctuations was generated by performing integrations with prescribed climatological boundary conditions for random initial atmospheric states, with resulting dynamical forecasts providing an ensemble of simulated data for the autoregressive modeling of weather fluctuations. To estimate the climatic noise from the observational data (consisting of hourly values of sea level pressure and surface temperature at 54 U.S. stations for the month of January for the years 1949-1975) use of the short time-scale assumption is made. The simulated and observed data were found not to be consistent with either white noise or a Markov process of weather fluctuations. Good agreement was found between the results of the hypothetical testing of the simulated and the observed surface temperatures; and only partial support was found for the short time-scale assumption, i.e., for sea level pressure.

Straus, D. M.↗

NASA NTRS2024

Dust Model Sensitivity to Dust Source Mask, Sandblasting Efficiency, Air Density, and Land Use: Implications for Model Improvement

This study compares dust storm simulations using two commonly adopted methods for representing four important dust emission parameters. Compared to a dynamic dust source mask based on land use and vegetation cover, a static mask based solely on land use overestimates dust concentration and optical depth by a factor of 2, besides generating spurious emissions. The results reinforce that seasonal variations in vegetation cover can significantly affect dust emissions. For sandblasting efficiency, a clay-dependent semiempirical expression produces 10 times more dust than a physics-based expression. Simulations using model-predicted versus a fixed constant for air density differ by only 8%. However, this difference could range between 12 and 22% for annual simulations over global dust source regions. Simulations with updated versus old land use data, using the same dust source mask, differ twofold, indicating the significant impact of land use change on regional dust emission in central Arizona. The differences in the pairs of these simulations are generally larger than the uncertainty due to meteorology. The simulations align better with observation when using the dynamic dust source mask, the physics-based sandblasting efficiency, and the up-to-date land use data. Given the high sensitivity of dust to surface conditions, the results discussed have implications for improving the dust cycle in weather and climate models and for interpreting model intercomparisons.

Dust-emission source↗

NASA NTRS2023

Breaking Wave Field Statistics With A Multi-Layer Model

The statistics of breaking wave fields are characterised within a novel multi-layer framework, which generalises the single-layer Saint-Venant system into a multi-layer and non-hydrostatic formulation of the Navier–Stokes equations. We simulate an ensemble of phase-resolved surface wave fields in physical space, where strong nonlinearities, including directional wave breaking and the subsequent highly rotational flow motion, are modelled, without surface overturning. We extract the kinematics of wave breaking by identifying breaking fronts and their speed, for freely evolving wave fields initialised with typical wind wave spectra. The Λ(c) distribution, defined as the length of breaking fronts (per unit area) moving with speed c to c + dc following Phillips (J. Fluid Mech., vol. 156, 1985, pp. 505–531), is reported for a broad range of conditions. We recover the Λ(c) ∝ c−6 scaling without wind forcing for sufficiently steep wave fields. A scaling of Λ(c) based solely on the root-mean-square slope and peak wave phase speed is shown to describe the modelled breaking distributions well. The modelled breaking distributions are in good agreement with field measurements and the proposed scaling can be applied successfully to the observational data sets. The present work paves the way for simulations of the turbulent upper ocean directly coupled to a realistic breaking wave dynamics, including Langmuir turbulence, and other sub-mesoscale processes.

Jiarong Wu↗

NASA NTRS2012

NASA Center for Climate Simulation (NCCS) Presentation

The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.

Webster, William P.↗

NASA NTRS1993

Using x ray images to detect substructure in a sample of 40 Abell clusters

Using a method for constraining the dynamical state of a galaxy cluster by examining the moments of its x-ray surface brightness distribution, we determine the statistics of cluster substructure for a sample of 40 Abell clusters. Using x-ray observations from the Einstein Observatory Imaging Proportional Counter (IPC), we measure the first moment M1(r), the ellipsoidal orientation angle theta2(r), and the axial ratio eta(r) at several different radii in the cluster. We determine the effects of systematics such as x-ray point source emission, telescope vignetting, Poisson noise, and characteristics of the IPC by measuring the same parameters on an ensemble of simulated cluster images. Due to the small band-pass of the IPC, the ICM emissivity is nearly independent of temperature so the intensity at each point in the IPC images is simply proportional to the emission measure calculated along the line of sight through the cluster (e.g. Fabricant et al. 1980). Therefore, barring a change superposition of two x-ray emitting clusters, a significant variation in the image centroid M1(r) as a function of radius indicates that the center of mass of the intra-cluster medium (ICM) varies with radius. We argue that such a configuration (essentially an m = 1 component in the ICM density distribution) is a non-equilibrium component; it results from an off-center subclump or a recent merger in the ICM.

Mohr, J. J.↗

NASA NTRS1993

An X-ray method for detecting substructure in galaxy clusters - Application to Perseus, A2256, Centaurus, Coma, and Sersic 40/6

We use the moments of the X-ray surface brightness distribution to constrain the dynamical state of a galaxy cluster. Using X-ray observations from the Einstein Observatory IPC, we measure the first moment FM, the ellipsoidal orientation angle, and the axial ratio at a sequence of radii in the cluster. We argue that a significant variation in the image centroid FM as a function of radius is evidence for a nonequilibrium feature in the intracluster medium (ICM) density distribution. In simple terms, centroid shifts indicate that the center of mass of the ICM varies with radius. This variation is a tracer of continuing dynamical evolution. For each cluster, we evaluate the significance of variations in the centroid of the IPC image by computing the same statistics on an ensemble of simulated cluster images. In producing these simulated images we include X-ray point source emission, telescope vignetting, Poisson noise, and characteristics of the IPC. Application of this new method to five Abell clusters reveals that the core of each one has significant substructure. In addition, we find significant variations in the orientation angle and the axial ratio for several of the clusters.

Mohr, Joseph J.↗

NASA NTRS2011

Towards a Model Climatology of Relative Humidity in the Upper Troposphere for Estimation of Contrail and Contrail-Induced Cirrus

The formation of contrails and contrail cirrus is very sensitive to the relative humidity of the upper troposphere. To reduce uncertainty in an estimate of the radiative impact of aviation-induced cirrus, a model must therefore be able to reproduce the observed background moisture fields with reasonable and quantifiable fidelity. Here we present an upper tropospheric moisture climatology from a 26-year ensemble of simulations using the GEOS CCM. We compare this free-running model's moisture fields to those obtained from the MLS and AIRS satellite instruments, our most comprehensive observational databases for upper tropospheric water vapor. Published comparisons have shown a substantial wet bias in GEOS-5 assimilated fields with respect to MLS water vapor and ice water content. This tendency is clear as well in the GEOS CCM simulations. The GEOS-5 moist physics in the GEOS CCM uses a saturation adjustment that prevents supersaturation, which is unrealistic when compared to in situ moisture observations from MOZAIC aircraft and balloon sondes as we will show. Further, the large-scale satellite datasets also consistently underestimate super-saturation when compared to the in-situ observations. We place these results in the context of estimates of contrail and contrail cirrus frequency.

Selkirk, Henry B.↗

NASA NTRS2011

Quantifying the Aerosol Semi-Direct Effect in the NASA GEOS-5 AGCM

Aerosols such as black carbon, dust, and some organic carbon species both scatter and absorb incoming solar radiation. This direct aerosol radiative forcing (DARF) redistributes solar energy both by cooling the surface and warming the atmosphere. As a result, these aerosols affect atmospheric stability and cloud cover (the semi-direct effect, or SDE). Furthermore, in regions with persistent high loadings of absorbing aerosols (e.g. Asia), regional circulation patterns may be altered, potentially resulting in changes in precipitation patterns. Here we investigate aerosol-climate coupling using the NASA Goddard Earth Observing System model version 5 (GEOS-5) atmospheric general circulation model (AGCM), in which we have implemented an online version of the Goddard Chemistry, Aerosol, Radiation and Transport (GOCART) model. GOCART includes representations of the sources, sinks, and chemical transformation of externally mixed dust, sea salt, sulfate, and carbonaceous aerosols. We examine a series of free-running ensemble climate simulations of the present-day period (2000-2009) forced by observed sea surface temperatures to determine the impact of aerosols on the model climate. The SDE and response of each simulation is determined by differencing with respect to the control simulation (no aerosol forcing). In a free-running model, any estimate of the SDE includes changes in clouds due both to atmospheric heating from aerosols and changes in circulation. To try and quantify the SDE without these circulation changes we then examine the DARF and SDE in GEOS-5 with prescribed meteorological analyses introduced by the MERRA analysis. By doing so, we are able to examine changes in model clouds that occur on shorter scales (six hours). In the GEOS-5 data assimilation system (DAS), the analysis is defined as the best estimate of the atmospheric state at any given time, and it is determined by optimally combining a first-guess short-term GCM forecast with all available observations. The Incremental Analysis Update (IAU) is added to the model forecast tendencies to align them with the analysis every six hours, thus preventing longer timescale feedbacks due to the aerosol forcing. We calculate the SDE by comparing model runs with and without aerosols, and the difference in the IAU between these runs is a useful metric with which to evaluate the impact of the SDE on the model atmosphere and clouds. Decreasing the IAU indicates that the aerosol direct and semi-direct effects act to reduce the bias between the model and observations and vice versa.

Randles, Cynthia A.↗

NASA NTRS2016

What Would Happen to Superstorm Sandy Under the Influence of a Substantially Warmer Atlantic Ocean?

Based on ensemble numerical simulations, we find that possible responses of Sandy-like superstorms under the influence of a substantially warmer Atlantic Ocean bifurcate into two groups. In the first group, storms are similar to present-day Sandy from genesis to extratropical transition, except they are much stronger, with peak Power Destructive Index (PDI) increased by 50-80%, heavy rain by 30-50%, and maximum storm size (MSS) approximately doubled. In the second group, storms amplify substantially over the interior of the Atlantic warm pool, with peak PDI increased by 100-160%, heavy rain by 70-180%, and MSS more than tripled compared to present-day Superstorm Sandy. These storms when exiting the warm pool, recurve northeastward out to sea, subsequently interact with the developing midlatitude storm by mutual counterclockwise rotation around each other and eventually amplify into a severe Northeastern coastal storm, making landfall over the extreme northeastern regions from Maine to Nova Scotia.

radar reflectivities↗

NASA NTRS2018

Climate Change Impact and Adaptation for Wheat Protein

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1 percentage points, representing a relative change of −8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.

grain protein↗

NASA NTRSDate not supplied

Sampling the ENSO response to tropical volcanic eruptions in the GISS-E2-1 model: physical & biogeochemical ocean effects

Despite observational evidence that an El-Niño is likely to follow tropical volcanic eruptions (Predybaylo et al, 2017), modelling studies have so far reached no consensus on either the sign or physical mechanism of El Niño response to volcanism (Khodri et al, 2017) . A previous modelling study found that following the Pinatubo eruption, the tropical Pacific developed El Niño-like conditions that triggered a decrease in the upwelling of DIC and increased carbon uptake (Eddebbar et al., 2019). However, the carbon cycle response to volcanisms as it depends on ENSO phase remains unclear. Here we perform thirty ensemble control simulations using the GISS-E2-1-G model to sample the pre-industrial control ENSO cycle and thirty more to superimpose a Pinatubo-like volcanic eruption. We find that the model tends to favor the development of a weak El-Niño following the volcanic eruption only in the case of a volcano that erupts at the start of a neutral ENSO phase. In response to the weak El-Niño, some anomalies have the same sign as those that develop from a strong El-Niño, such as weaker winds, shallower mixed layer depths, less direct but more diffuse radiation at the surface of the ocean, less nitrate, and lower primary productivity. However, other anomalies show the opposite sign as those from a strong El-Niño, such as more precipitation, less surface DIC, and less surface ocean pCO 2 . In contrast to the neutral phase, the volcanic response during positive ENSO and negative ENSO phases are swamped by the model’s internal variability.

ENSO↗

NASA NTRS1998

Upper Limits of Predictability in Long-Range Climate/Hydrologic Forecasts

The accurate forecasting of el nino or la nina conditions in the tropical Pacific can potentially lead to valuable predictions of hydrological anomalies over land at seasonal to interannual timescales. Even with highly accurate earth system models, though, our ability to generate these continental forecasts will always be limited by the chaotic nature of the atmospheric circulation. The nature of this fundamental limitation is explored through the use of 16-member ensembles of multi-decade GCM simulations. In each simulation of the first ensemble, sea surface temperatures (SSTs) are given the same realistic interannual variations over a 45-year period, and land surface state is allowed to evolve with that of the atmosphere. Analysis of the results shows that the SSTs control the temporal organization of continental precipitation anomalies to a significant extent in the tropics and to a much smaller extent in midlatitudes. In each simulation of the second ensemble, we prescribe SSTs as before, but we also prescribe interannual variations in the low frequency component of evaporation efficiency over land. Thus, in the second ensemble, we effectively make the extreme assumption that surface boundary conditions across the globe are perfectly predictable, and we quantify the consistency with which the atmosphere (particularly precipitation) responds to these boundary conditions. The resulting "absolute upper limit" on the predictability of precipitation is found to be quite high in the tropics yet only moderate in many midlatitude regions.

Koster, R. D.↗

NASA NTRS2020

Clouds and Convective Self-Aggregation in a Multi-Model Ensemble of Radiative-Convective Equilibrium Simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective56equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climatecsensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique amongst intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than un-aggregated simulations. Plain Language Summary This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The dataset of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We don’t find a conclusive result for how cloud clustering changes as the climate warms.

Allison A. Wing↗

NASA NTRS2001

Forced and Free Intra-Seasonal Variability Over the South Asian Monsoon Region Simulated by 10 AGCMs

This study examines intra-seasonal (20-70 day) variability in the South Asian monsoon region during 1997/98 in ensembles of 10 simulations with 10 different atmospheric general circulation models. The 10 ensemble members for each model are forced with the same observed weekly sea surface temperature (SST) but differ from each other in that they are started from different initial atmospheric conditions. The results show considerable differences between the models in the simulated 20-70 day variability, ranging from much weaker to much stronger than the observed. A key result is that the models do produce, to varying degrees, a response to the imposed weekly SST. The forced variability tends to be largest in the Indian and western Pacific Oceans where, for some models, it accounts for more than 1/4 of the 20-70 day intra-seasonal variability in the upper level velocity potential during these two years. A case study of a strong observed MJO (intraseasonal oscillation) event shows that the models produce an ensemble mean eastward propagating signal in the tropical precipitation field over the Indian Ocean and western Pacific, similar to that found in the observations. The associated forced 200 mb velocity potential anomalies are strongly phase locked with the precipitation anomalies, propagating slowly to the east (about 5 m/s) with a local zonal wave number two pattern that is generally consistent with the developing observed MJO. The simulated and observed events are, however, approximately in quadrature, with the simulated response 2 leading by 5-10 days. The phase lag occurs because, in the observations, the positive SST anomalies develop upstream of the main convective center in the subsidence region of the MJO, while in the simulations, the forced component is in phase with the SST. For all the models examined here, the intraseasonal variability is dominated by the free (intra-ensemble) component. The results of our case study show that the free variability has a predominately zonal wave number one pattern, and has propagation speeds (10 - 15 m/s) that are more typical of observed MJO behavior away from the convectively active regions. The free variability appears to be synchronized with the forced response, at least, during the strong event examined here. The results of this study support the idea that coupling with SSTs plays an important, though probably not dominant, role in the MJO. The magnitude of the atmospheric response to the SST appears to be in the range of 15% - 30% of the 20-70 day variability over much of the tropical eastern Indian and western Pacific Oceans. The results also highlight the need to use caution when interpreting atmospheric model simulations in which the prescribed SST resolve MJO time scales.

Wu, Man Li C.↗

NASA NTRS1994

A statistical analysis of the dependency of closure assumptions in cumulus parameterization on the horizontal resolution

Simulated data from the UCLA cumulus ensemble model are used to investigate the quasi-universal validity of closure assumptions used in existing cumulus parameterizations. A closure assumption is quasi-universally valid if it is sensitive neither to convective cloud regimes nor to horizontal resolutions of large-scale/mesoscale models. The dependency of three types of closure assumptions, as classified by Arakawa and Chen, on the horizontal resolution is addressed in this study. Type I is the constraint on the coupling of the time tendencies of large-scale temperature and water vapor mixing ratio. Type II is the constraint on the coupling of cumulus heating and cumulus drying. Type III is a direct constraint on the intensity of a cumulus ensemble. The macroscopic behavior of simulated cumulus convection is first compared with the observed behavior in view of Type I and Type II closure assumptions using 'quick-look' and canonical correlation analyses. It is found that they are statistically similar to each other. The three types of closure assumptions are further examined with simulated data averaged over selected subdomain sizes ranging from 64 to 512 km. It is found that the dependency of Type I and Type II closure assumptions on the horizontal resolution is very weak and that Type III closure assumption is somewhat dependent upon the horizontal resolution. The influences of convective and mesoscale processes on the closure assumptions are also addressed by comparing the structures of canonical components with the corresponding vertical profiles in the convective and stratiform regions of cumulus ensembles analyzed directly from simulated data. The implication of these results for cumulus parameterization is discussed.

Xu, Kuan-Man↗