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NASA NTRS2008

Evaluation of Cloud Physical Properties of ECMWF Analysis and Re-Analysis (ERA-40 and ERA Interim) against CERES Tropical Deep Convective Cloud Object Observations

This study presents an approach that converts the vertical profiles of grid-averaged cloud properties from large-scale models to probability density functions (pdfs) of subgrid-cell cloud physical properties measured at satellite footprints. Cloud physical and radiative properties, rather than just cloud and precipitation occurrences, of assimilated cloud systems by the European Center for Medium-range Weather Forecasts (ECMWF) operational analysis (EOA) and ECMWF Re-Analyses (ERA-40 and ERA Interim) are validated against those obtained from Earth Observing System satellite cloud object data for January-August 1998 and March 2000 periods. These properties include ice water path (IWP), cloud-top height and temperature, cloud optical depth and solar and infrared radiative fluxes. Each cloud object, a contiguous region with similar cloud physical properties, is temporally and spatially matched with EOA and ERA-40 data. Results indicate that most pdfs of EOA and ERA-40 cloud physical and radiative properties agree with those of satellite observations of the tropical deep convective cloud-object type for the January-August 1998 period. There are, however, significant discrepancies in selected ranges of the cloud property pdfs such as the upper range of EOA cloud top height. A major discrepancy is that the dependence of the pdfs on the cloud object size for both EOA and ERA-40 is not as strong as in the observations. Modifications to the cloud parameterization in ECMWF that occurred in October 1999 eliminate the clouds near the tropopause but shift power of the pdf to lower cloud-top heights and greatly reduce the ranges of IWP and cloud optical depth pdfs. These features persist in ERA-40 due to the use of the same cloud parameterizations. The downgrade of data assimilation technique and the lack of snow water content information in ERA-40, not the coarser horizontal grid resolution, are also responsible for the disagreements with observed pdfs of cloud physical properties although the detection rates of cloud object occurrence are improved for small size categories. A possible improvement to the convective parameterization is to introduce a stronger dependence of updraft penetration heights with grid-cell dynamics. These conclusions will be rechecked using the ERA Interim data, due to recent changes in the ECMWF convective parameterization (Bechtold et al. 2004, 2008). Results from the ERA Interim will be presented at the meeting.

Xu, Kuan-Man↗

NASA NTRS2002

Parameterization of Cloud Optical Properties for a Mixture of Ice Particles for use in Atmospheric Models

Based on the single-scattering optical properties that are pre-computed using an improve geometric optics method, the bulk mass absorption coefficient, single-scattering albedo, and asymmetry factor of ice particles have been parameterized as a function of the mean effective particle size of a mixture of ice habits. The parameterization has been applied to compute fluxes for sample clouds with various particle size distributions and assumed mixtures of particle habits. Compared to the parameterization for a single habit of hexagonal column, the solar heating of clouds computed with the parameterization for a mixture of habits is smaller due to a smaller cosingle-scattering albedo. Whereas the net downward fluxes at the TOA and surface are larger due to a larger asymmetry factor. The maximum difference in the cloud heating rate is approx. 0.2 C per day, which occurs in clouds with an optical thickness greater than 3 and the solar zenith angle less than 45 degrees. Flux difference is less than 10 W per square meters for the optical thickness ranging from 0.6 to 10 and the entire range of the solar zenith angle. The maximum flux difference is approximately 3%, which occurs around an optical thickness of 1 and at high solar zenith angles.

Chou, Ming-Dah↗

NASA NTRS1989

A scheme for parameterizing ice cloud water content in general circulation models

A method for specifying ice water content in GCMs is developed, based on theory and in-cloud measurements. A theoretical development of the conceptual precipitation model is given and the aircraft flights used to characterize the ice mass distribution in deep ice clouds is discussed. Ice water content values derived from the theoretical parameterization are compared with the measured values. The results demonstrate that a simple parameterization for atmospheric ice content can account for ice contents observed in several synoptic contexts.

Heymsfield, Andrew J.↗

NASA NTRS2016

Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical Schemes

The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.

snow↗

NASA NTRS2006

Performance of Two Cloud-Radiation Parameterization Schemes in the Finite Volume General Circulation Model for Anomalously Wet May and June 2003 Over the Continental United States and Amazonia

An objective assessment of the impact of a new cloud scheme, called Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme (McRAS) (together with its radiation modules), on the finite volume general circulation model (fvGCM) was made with a set of ensemble forecasts that invoke performance evaluation over both weather and climate timescales. The performance of McRAS (and its radiation modules) was compared with that of the National Center for Atmospheric Research Community Climate Model (NCAR CCM3) cloud scheme (with its NCAR physics radiation). We specifically chose the boreal summer months of May and June 2003, which were characterized by an anomalously wet eastern half of the continental United States as well as northern regions of Amazonia. The evaluation employed an ensemble of 70 daily 10-day forecasts covering the 61 days of the study period. Each forecast was started from the analyzed initial state of the atmosphere and spun-up soil moisture from the first-day forecasts with the model. Monthly statistics of these forecasts with up to 10-day lead time provided a robust estimate of the behavior of the simulated monthly rainfall anomalies. Patterns of simulated versus observed rainfall, 500-hPa heights, and top-of-the-atmosphere net radiation were recast into regional anomaly correlations. The correlations were compared among the simulations with each of the schemes. The results show that fvGCM with McRAS and its radiation package performed discernibly better than the original fvGCM with CCM3 cloud physics plus its radiation package. The McRAS cloud scheme also showed a reasonably positive response to the observed sea surface temperature on mean monthly rainfall fields at different time leads. This analysis represents a method for helpful systematic evaluation prior to selection of a new scheme in a global model.

Sud, Y. C.↗

NASA NTRS1990

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 1: A cloud ensemble/radiative parameterization for sensor response (report version)

The physical retrieval of geophysical parameters based upon remotely sensed data requires a sensor response model which relates the upwelling radiances that the sensor observes to the parameters to be retrieved. In the retrieval of precipitation water contents from satellite passive microwave observations, the sensor response model has two basic components. First, a description of the radiative transfer of microwaves through a precipitating atmosphere must be considered, because it is necessary to establish the physical relationship between precipitation water content and upwelling microwave brightness temperature. Also the spatial response of the satellite microwave sensor (or antenna pattern) must be included in the description of sensor response, since precipitation and the associated brightness temperature field can vary over a typical microwave sensor resolution footprint. A 'population' of convective cells, as well as stratiform clouds, are simulated using a computationally-efficient multi-cylinder cloud model. Ensembles of clouds selected at random from the population, distributed over a 25 km x 25 km model domain, serve as the basis for radiative transfer calculations of upwelling brightness temperatures at the SSM/I frequencies. Sensor spatial response is treated explicitly by convolving the upwelling brightness temperature by the domain-integrated SSM/I antenna patterns. The sensor response model is utilized in precipitation water content retrievals.

Olson, William S.↗

NASA NTRS1990

A scheme for parameterizing cirrus cloud ice water content in general circulation models

Clouds strongly influence th earth's energy budget. They control th amount of solar radiative energy absorbed by the climate system, partitioning the energy between the atmosphere and the earth's surface. They also control the loss of energy to space by their effect on thermal emission. Cirrus and altostratus are the most frequent cloud types, having an annual average global coverage of 35 and 40 percent, respectively. Cirrus is composed almost entirely of ice crystals and the same is frequently true of the upper portions of altostratus since they are often formed by the thickening of cirrostratus and by the spreading of the middle or upper portions of thunderstorms. Thus, since ice clouds cover such a large portion of the earth's surface, they almost certainly have an important effect on climate. With this recognition, researchers developing climate models are seeking largely unavailable methods for specifying the conditions for ice cloud formation, and quantifying the spatial distribution of ice water content, IWC, a necessary step in deriving their radiative characteristics since radiative properties are apparently related to IWC. A method is developed for specifying IWC in climate models, based on theory and measurements in cirrus during FIRE and other experiments.

Heymsfield, Andrew J.↗

NASA NTRS2001

Cloud Microphysics Budget in the Tropical Deep Convective Regime

Cloud microphysics budgets in the tropical deep convective regime are analyzed based on a 2-D cloud resolving simulation. The model is forced by the large-scale vertical velocity and zonal wind and large-scale horizontal advections derived from TOGA COARE for a 20-day period. The role of cloud microphysics is first examined by analyzing mass-weighted mean heat budget and column-integrated moisture budget. Hourly budgets show that local changes of mass-weighted mean temperature and column-integrated moisture are mainly determined by the residuals between vertical thermal advection and latent heat of condensation and between vertical moisture advection and condensation respectively. Thus, atmospheric thermodynamics depends on how cloud microphysical processes are parameterized. Cloud microphysics budgets are then analyzed for raining conditions. For cloud-vapor exchange between cloud system and its embedded environment, rainfall and evaporation of raindrop are compensated by the condensation and deposition of supersaturated vapor. Inside the cloud system, the condensation of supersaturated vapor balances conversion from cloud water to raindrop, snow, and graupel through collection and accretion processes. The deposition of supersaturated vapor balances conversion from cloud ice to snow through conversion and riming processes. The conversion and riming of cloud ice and the accretion of cloud water balance conversion from snow to graupel through accretion process. Finally, the collection of cloud water and the melting of graupel increase raindrop to compensate the loss of raindrop due to rainfall and the evaporation of raindrop.

Li, Xiao-Fan↗

NASA NTRS2003

Limits to the Indirect Aerosol Forcing in Stratocumulus

The indirect radiative forcing of aerosols is poorly constrained by the observational data underlying the simple cloud parameterizations in GCMs. signal of cloud response to increased aerosol concentrations from meteorological noise. Recent satellite observations indicate a significant decrease of cloud water in ship tracks, in contrast to an ensemble of in situ measurements showing no average change in cloud water relative to the surrounding clouds. Both results contradict the expectation of cloud water increasing in polluted clouds. We find through large-eddy simulations of stratocumulus that the trend in the satellite data is likely an artifact of sampling only overcast clouds. The simulations instead show cloud cover increasing with droplet concentrations. The simulations also show that increases in cloud water from suppressing drizzle by increased droplet concentrations are favored at night or at extremely low droplet concentrations. At typical droplet concentrations we find that the Twomey effect on cloud albedo is amplified very little by the secondary indirect effect of drizzle suppression, largely because the absorption of solar radiation by cloud water reduces boundary-layer mixing in the daytime and thereby restricts any possible increase in cloud water from drizzle suppression. The cloud and boundary layer respond to radiative heating variations on a time scale of hours, and on longer time scales respond to imbalances between large-scale horizontal advection and the entrainment of inversion air. We analyze the co-varying response of cloud water, cloud thickness, width of droplet size distributions, and dispersion of the optical depth, as well as the overall response of cloud albedo, to changes in droplet concentrations. We also dissect the underlying physical mechanisms through sensitivity studies. Ship tracks represent an ideal natural laboratory to extricate the

Ackerman, Andrew↗

NASA NTRS2017

On the Dependence of Cloud Feedbacks on Physical Parameterizations in WRF Aquaplanet Simulations

We investigate the effects of physical parameterizations on cloud feedback uncertainty in response to climate change. For this purpose, we construct an ensemble of eight aquaplanet simulations using the Weather Research and Forecasting (WRF) model. In each WRF‐derived simulation, we replace only one parameterization at a time while all other parameters remain identical. By doing so, we aim to (i) reproduce cloud feedback uncertainty from state‐of‐the‐art climate models and (ii) understand how parametrizations impact cloud feedbacks. Our results demonstrate that this ensemble of WRF simulations, which differ only in physical parameterizations, replicates the range of cloud feedback uncertainty found in state‐of‐the‐art climate models. We show that microphysics and convective parameterizations govern the magnitude and sign of cloud feedbacks, mostly due to tropical low‐level clouds in subsidence regimes. Finally, this study highlights the advantages of using WRF to analyze cloud feedback mechanisms owing to its plug‐and‐play parameterization capability.

Cesana, Gregory↗

NASA NTRS1999

Parameterizations of Depositional Growth of Cloud Ice in a Bulk Microphysical Scheme

Two aspects of the cloud ice parameterization in the Goddard Cumulus Ensemble Model cloud physics parameterization are examined: the conversion of cloud ice to snow by depositional growth, designated PSFI, and the saturation adjustment scheme. The original formulation of PSFI is shown to produce excessive conversion of cloud ice to snow because of an implicit assumption that the relative humidity is 100% with respect to water even though the air may actually be quite less humid. Two possible corrections to this problem are proposed, the first involving application of a relative humidity dependent correction factor to the original formulation of PSFI, and the second involving a new formulation of PSFI based on the equation for depositional growth of cloud ice. The sensitivity of these formulations of PSFI to the assumed masses of the ice particles is examined. Possible problems associated with using a saturation adjustment scheme for cloud ice are discussed and simulations of a squall line with and without application of the adjustment scheme for ice are compared.

Braun, Scott A.↗

NASA NTRS2008

Application of the CloudSat and NEXRAD Radars Toward Improvements in High Resolution Operational Forecasts

As computational power increases, operational forecast models are performing simulations with higher spatial resolution allowing for the transition from sub-grid scale cloud parameterizations to an explicit forecast of cloud characteristics and precipitation through the use of single- or multi-moment bulk water microphysics schemes. investments in space-borne and terrestrial remote sensing have developed the NASA CloudSat Cloud Profiling Radar and the NOAA National Weather Service NEXRAD system, each providing observations related to the bulk properties of clouds and precipitation through measurements of reflectivity. CloudSat and NEXRAD system radars observed light to moderate snowfall in association with a cold-season, midlatitude cyclone traversing the Central United States in February 2007. These systems are responsible for widespread cloud cover and various types of precipitation, are of economic consequence, and pose a challenge to operational forecasters. This event is simulated with the Weather Research and Forecast (WRF) Model, utilizing the NASA Goddard Cumulus Ensemble microphysics scheme. Comparisons are made between WRF-simulated and observed reflectivity available from the CloudSat and NEXRAD systems. The application of CloudSat reflectivity is made possible through the QuickBeam radiative transfer model, with cautious application applied in light of single scattering characteristics and spherical target assumptions. Significant differences are noted within modeled and observed cloud profiles, based upon simulated reflectivity, and modifications to the single-moment scheme are tested through a supplemental WRF forecast that incorporates a temperature dependent snow crystal size distribution.

Molthan, A. L.↗

NASA NTRS2022

Constraining Clouds and Convective Parameterizations in A Climate Model Using Paleoclimate Data

Cloud and convective parameterizations strongly influence uncertainties in equilibrium climate sensitivity. We provide a proof-of-concept study to constrain these parameterizations in a perturbed parameter ensemble of the atmosphere-only version of the Goddard Institute for Space Studies Model E2.1 simulations by evaluating model biases in the present-day runs using multiple satellite climatologies and by comparing simulated δ 18 O of precipitation (δ 18 O p ), known to be sensitive to parameterization schemes, with a global database of speleothem δ 18 O records covering the Last Glacial Maximum (LGM), mid-Holocene (MH) and pre-industrial (PI) periods. Relative to modern interannual variability, paleoclimate simulations show greater sensitivity to parameter changes, allowing for an evaluation of model uncertainties over a broader range of climate forcing and the identification of parts of the world that are parameter sensitive. Certain simulations reproduced absolute δ 18 O p values across all time periods, along with LGM and MH δ 18 O p anomalies relative to the PI, better than the default parameterization. No single set of parameterizations worked well in all climate states, likely due to the non-stationarity of cloud feedbacks under varying boundary conditions. Future work that involves varying multiple parameter sets simultaneously with coupled ocean feedbacks will likely provide improved constraints on cloud and convective parameterizations.

cloud and convective parameterization↗

NASA NTRS2015

Improving High-Resolution Weather Forecasts using the Weather Research and Forecasting (WRF) Model with an Updated Kain-Fritsch Scheme

Efforts to improve the prediction accuracy of high resolution (1-10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at these spatial scales due to uncertainties in initial meteorological conditions and/or grid-scale cloud microphysics schemes. In particular, it is still unclear to what extent a subgrid-scale convection scheme could be modified to bring in scale-awareness for improving high-resolution short-term precipitation forecasts in the WRF model. To address these issues, we introduced scale-aware parameterized cloud dynamics for high-resolution forecasts by making several changes to the Kain-Fritsch (KF) convective parameterization scheme in the WRF model. These changes include subgrid-scale cloud-radiation interactions, a dynamic adjustment timescale, impacts of cloud updraft mass fluxes on grid-scale vertical velocity, and lifting condensation level-based entrainment methodology that includes scale dependency. A series of 48-hour retrospective forecasts using a combination of three treatments of convection (KF, updated KF, and the use of no cumulus parameterization), two cloud microphysics schemes and two types of initial condition datasets were performed over the U.S. southern Great Plains on 9- and 3-km grid spacings during the summers of 2002 and 2010. Results indicate that (1) the source of initial conditions play a key role in high-resolution precipitation forecasting, and (2) our updated KF scheme greatly alleviates the excessive precipitation at 9-km grid spacing and improves results at 3-km grid spacing as well. Overall, we found that the updated KF scheme incorporated into a high-resolution model does provide better forecasts for precipitation location and intensity.

convective parameterization↗

NASA NTRS1998

Cloud Distribution Statistics from LITE

The Lidar In-Space Technology Experiment (LITE) mission has demonstrated the utility of spaceborne lidar in observing multilayer clouds and has provided a dataset showing the distribution of tropospheric clouds and aerosols. These unambiguous observations of the vertical distribution of clouds will allow improved verification of current cloud climatologies and GCM cloud parameterizations. Although there is now great interest in cloud profiling radar, operating in the mm-wave region, for the spacebased observation of cloud heights the results of the LITE mission have shown that satellite lidars can also make significant contributions in this area.

Winker, David M.↗

NASA NTRS2014

A Two-Habit Ice Cloud Optical Property Parameterization for GCM Application

We present a novel ice cloud optical property parameterization based on a two-habit ice cloud model that has been proved to be optimal for remote sensing applications. The two-habit ice model is developed with state-of-the-art numerical methods for light scattering property calculations involving individual columns and column aggregates with the habit fractions constrained by in-situ measurements from various field campaigns. Band-averaged bulk ice cloud optical properties including the single-scattering albedo, the mass extinction/absorption coefficients, and the asymmetry factor are parameterized as functions of the effective particle diameter for the spectral bands involved in the broadband radiative transfer models. Compared with other parameterization schemes, the two-habit scheme generally has lower asymmetry factor values (around 0.75 at the visible wavelengths). The two-habit parameterization scheme was widely tested with the broadband radiative transfer models (i.e. Rapid Radiative Transfer Model, GCM version) and global circulation models (GCMs, i.e. Community Atmosphere Model, version 5). Global ice cloud radiative effects at the top of the atmosphere are also analyzed from the GCM simulation using the two-habit parameterization scheme in comparison with CERES satellite observations.

Yi, Bingqi↗

NASA NTRS2022

Novel Parameterization of Ice Cloud Effective Diameter from Collocated CALIOP-IIR and CloudSat Retrievals

Satellite-based measurements of global ice cloud microphysical properties are sampled to develop a novel set of physical parameterizations, relating to cloud layer temperature and effective diameter D(e), that can be implemented for two separate applications: in numerical weather prediction models and lidar-based cloud radiative forcing studies. Ice cloud optical properties (i.e., spectral scattering and absorption) are estimated based on the effective size and habit mixture of the cloud particles. Historically, the ice cloud D(e) has been parameterized from aircraft in situ measurements. However, aircraft-based parameterizations are opportunistic in that they only represent specific types of clouds (e.g., convective anvil, tropopause-topped cirrus) in the regions in which they were sampled and, in some cases, are limited in fully resolving the entire vertical cloud layer. Breaking away from the aircraft-based parameterization paradigm, this study is the first of its kind to attempt a parameterization of D(e) as a function of temperature, ice water content (IWC), and lidar-derived extinction from satellite-based global oceanic measurements of ice clouds. Data from both active and passive remote sensing sensors from two of NASA’s A-Train satellites, CloudSat and CALIPSO, are collected to guide development of globally robust parameterizations of all ice cloud types and one exclusively for cirrus clouds.

Ice Cloud↗

NASA NTRS2004

Cloud Detection Using Measured and Modeled State Parameters

In this study, hourly RUC analyses were used to examine the differences between RH and temperature values from RUC reanalysis data and from radiosonde atmospheric profiles obtained at the ARM SCF. The results show that the temperature observations from the SONDE and RUC are highly correlated. The RHs are also well-correlated, but the SONDE values generally exceed those from RUC. Inside cloud layers, the RH from RUC is 2-14% lower than the RH from SONDE for all RUC layers. Although the layer mean RH within clouds is much greater than the layer mean RH outside cloud or in the clear-sky, RH thresholds chosen as a function of temperature can more accurately diagnose cloud occurrence for either dataset. For overcast clouds, it was found that the 50% probability RH threshold for diagnosing a cloud, within a given upper tropospheric layer is roughly 90% for the Vaisala RS80-15LH radisonde and 80% for RUC data. While for the partial cloud (cloud amount is less than 90%), the RH thresholds of SONDE are close to RUC for a given probability in upper tropospheric layers. The probabilities of detecting clouds at a given RH and temperature should be useful for a variety of application such as the development of new cloud parameterizations or for estimating the vertical profile of cloudiness underneath a given cloud observed from the satellite to construct a 3-D cloud data set for computing atmospheric radiative heating profiles or determining potential aircraft icing conditions.

Yi, Y.↗