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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Development of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) Value-Added Product Based on the lagtraj Framework

The Atmospheric Radiation Measurement (ARM) large-scale forcing data developed based on the constrained variational analysis (VARANAL) value-added product (VAP) (Zhang and Lin 1997, Zhang et al. 2001, Xie et al. 2004, Tang et al. 2019) has been widely used for single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulation models (LESs) to understand and improve physical processes in models. Recently, the U.S. Department of Energy (DOE) ARM user facility conducted several major field campaigns using ship-based moving observational platforms. For example, the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign focused on the role of subtropical marine-boundary layer (MBL) clouds, and the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign aimed to improve understanding of the coupled climate systems in the Arctic. Observations from moving platforms are critical to provide a comprehensive characterization of coupled-system processes associated with all stages of the cloud and/or sea-ice life cycle. Traditional ARM large-scale forcing data have been developed at fixed locations. They need to be extended to include these moving platforms to address data needs for ship-based field campaigns or to support LES modeling in a Lagrangian framework. With these considerations in mind, we develop ARM-type Lagrangian large-scale forcing data sets based on the lagtraj framework (Boeing et al. 2020) with notable enhancements in generating forcings that are more suitable for ARM field campaigns. The lagtraj is a novel tool that generates forcings for LES and SCM simulation in both Lagrangian and Eulerian perspective. This technical report focuses on the major changes we performed on the lagtraj algorithm and provides an overview of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) value-added products.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Spectroscopic studies of model polar stratospheric cloud films

Fourier transform infrared (FTIR) spectroscopy has been used to study nitric-acid/ice films representative of type I polar stratospheric clouds (PSCs). These studies reveal that in addition to amorphous nitric acid/ice mixtures, there are three stable stoichiometric hydrates of nitric acid: nitric-acid monohydrate (NAM), dihydrate (NAD), and trihydrate (NAT). We also observe two distinct crystalline forms of the trihydrate, which we denote alpha- and beta-NAT. These two forms appear to differ in their concentration of crystalline defects, but not in their chemical composition. In addition to probing the composition of type I PSCs, we have also used FTIR spectroscopy to study the interaction of HCl with model PSC films. In this work we find that for HCl pressures in the range 10 exp -5 to 10 exp -7 Torr, HCl is taken up by ice at 155 K to form a thin layer of HCl.6H2O. At 193 K, the uptake of HCl by ice was consistent with less than or equal to monolayer coverage. Uptake of HCl by alpha and beta-NAT at 175 K was also consistent with less than or equal to monolayer coverage.

Tolbert, Margaret A.↗
NASA NTRS2003

The Chemistry and Excitation of Water in Molecular Clouds

We model the chemistry and thermal balance of opaque molecular clouds exposed to an external flux of ultraviolet photons. We include the processes of gas phase and grain surface chemical reactions; in particular we examine closely the freezing of atoms and molecules onto grain surfaces and the desorption of molecules from grain surfaces as a function of depth into a molecular cloud. We find that on the surface of a molecular cloud the gas phase water abundances are low because of photodissociation, and the grain phase water (ice) abundance is low because of photodesorption of water from the grain surfaces. Deeper into the cloud, at A(sub v) less than or approximately 2-8 depending on the strength of the external ultraviolet flux, the gas phase water abundance increases with depth as the photodissociation rates decline due to dust attenuation of the ultraviolet field. However, beyond A(sub v) less than or approximately 2-8 the gas phase water abundance declines because the water freezes as water ice on the grains, and photodesorption is no longer effective in clearing the ice. A peak water abundance of about 10(exp -6) to 10(exp -7) occurs at about A(sub v) approximately 2-8, relatively independent of the gas density and the ultraviolet field. We show that such a model matches very closely the observations of the Submillimeter Wave Astronomical Satellite (SWAS), a NASA Small Explorer Mission. The model elucidates several mechanisms that have been recently invoked to understand gas phase chemistry in clouds, including-the freeze-out of molecules onto grain surface, the desorption of these molecules from the surfaces, and the abundance gradients of molecules as functions of depth into molecular clouds.

Hollenbach, David↗
NASA NTRS2010

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.

Tao, Wei--Kuo↗
NASA NTRS2003

Properties of Backscattered Ultraviolet Reflectances in Cloudy Atmosphere

We use a Plane-Parallel Cloud (PPC) model to illustrate how Mie scattering from cloud particles interacts with Rayleigh scattering in the atmosphere and produces a complex wavelength dependence in the top-of-the-atmosphere (TOA) reflectances measured by satellite instruments that operate in the ultraviolet (UV) part of the spectrum. Comparisons of the PPC model-derived spectral dependence of reflectances with the Total Ozone Mapping Spectrometer (TOMS) measurements show surprisingly good agreement over a wide range of observational conditions. The PPC model results also are compared with the results of two other cloud models: Lambert Equivalent Reflectivity (LER) and Modified Lambert Equivalent Reflectivity (MLER) that have been used to analyze satellite data in the UV. These models assume that clouds are opaque Lambertian reflectors rather than Mie scattering particles. Although one of these models (MLER) agrees reasonably well with the data, the results from this model appear somewhat unphysical and may not be suitable for interpreting satellite data if one desires high accuracy. We also use the PPC model to illustrate how clouds can perturb tropospheric O3 absorption in complex ways that cannot be explained by models that treat them as reflecting surfaces rather than as volume scatterers.

Ahmad, Z.↗
NASA NTRS1989

Cloud parameterization for climate modeling - Status and prospects

The current status of cloud parameterization research is reviewed. It is emphasized that the upper tropospheric stratiform clouds associated with deep convection are both physically important and poorly parameterized in current models. Emerging parameterizations are described in general terms, with emphasis on prognostic cloud water and fractional cloudiness, and how these relate to the problem just mentioned.

Randall, David A.↗
NASA NTRS1993

Fourier transform infrared studies of the interaction of HCl with model polar stratospheric cloud films

Heterogeneous reactions involving hydrochloric acid adsorbed on the surfaces of polar stratospheric clouds (PSCs) are postulated to contribute to polar ozone loss. Using FTIR spectroscopy to probe the condensed phase, we have examined the interaction of HCl with ice and nitric acid trihydrate (NAT) films representative of types II and I PSCs, respectively. For HCl pressures in the range of 10 exp -7 to 10 exp -5 Torr, our FTIR studies show that a small amount of crystalline HCl-6H2O formed on or in ice at 155 K. However, for higher HCl pressures, we observed that the entire film of ice rapidly converted into an amorphous 4:1 H2O:HCl mixture. From HCl-uptake experiments with P(HCl) = 8 x 10 exp -7 Torr, we estimate roughly that the diffusion coefficient of HCl in ice is around 2 x 10 exp -12 sq cm/s at 158 K. For higher temperatures more closely approximating those found in the stratosphere, we were unable to detect bulk HCl uptake by ice. Indirect evidence suggests that HCl adsorption onto the surface of model PSC films inhibited the evaporation of both ice and NAT by 3-5 K.

Koehler, Birgit G.↗
NASA NTRS1995

Vertical transport by convective clouds: Comparisons of three modeling approaches

A preliminary comparison of the GEOS-1 (Goddard Earth Observing System) data assimilation system convective cloud mass fluxes with fluxes from a cloud-resolving model (the Goddard Cumulus Ensemble Model, GCE) is reported. A squall line case study (10-11 June 1985 Oklahoma PRESTORM episode) is the basis of the comparison. Regional (central U. S.) monthly total convective mass flux for June 1985 from GEOS-1 compares favorably with estimates from a statistical/dynamical approach using GCE simulations and satellite-derived cloud observations. The GEOS-1 convective mass fluxes produce reasonable estimates of monthly-averaged regional convective venting of CO from the boundary layer at least in an urban-influenced continental region, suggesting that they can be used in tracer transport simulations.

Pickering, Kenneth E.↗
NASA NTRS2003

Radar Reflectivity Simulated by a 2-D Spectra Bin Model: Sensitivity of Cloud-aerosol Interaction

The Goddard Cumulus Ensemble (GCE) model with bin spectra microphysics is used to simulate mesoscale convective systems.The model uses explicit bins to represent size spectra of cloud nuclei, water drops, ice crystals, snow and graupel. Each hydrometeorite category is described by 33 mass bins. The simulations provide a unique data set of simulated raindrop size distribution in a realistic dynamic frame. Calculations of radar parameters using simulated drop size distribution serve as an evaluation of numerical model performance. In addition, the GCE bin spectra modes is a very useful tool to study uncertainties related to radar observations; all the environmental parameters are precisely known. In this presentation, we concentrate on the discussion of Z-R (ZDR-R) relation in the simulated systems. Due to computational limitations, the spectra bin model has been run in two dimensions with 31 stretched vertical layers and 1026 horizontal grid points (1 km resolution). Two different cases, one in midlatitude continent, the other in tropical ocean, have been simulated. The continental case is a strong convection which lasted for two hours. The oceanic case is a persistent system with more than 10 hours' life span. It is shown that the simulated Z-R (ZDR-R) relations generally agree with observations using radar and rain gauge data. The spatial and temporal variations of Z-R relation in different locations are also analyzed. Impact of aerosols on cloud formation and raindrop size distribution was studied. Both clean (low CCN) and dirty (high CCN) cases are simulated. The Z-R relation is shown to vary considerable in the initial CCN concentrations.

Li, Kiaowen↗
NASA NTRS2011

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy~ precipitation processes will be discussed.

Tao, Wei-Kuo↗
NASA NTRS1989

Photoionization-regulated star formation and the structure of molecular clouds

A model for the rate of low-mass star formation in Galactic molecular clouds and for the influence of this star formation on the structure and evolution of the clouds is presented. The rate of energy injection by newly formed stars is estimated, and the effect of this energy injection on the size of the cloud is determined. It is shown that the observed rate of star formation appears adequate to support the observed clouds against gravitational collapse. The rate of photoionization-regulated star formation is estimated and it is shown to be in agreement with estimates of the observed rate of star formation if the observed molecular cloud parameters are used. The mean cloud extinction and the Galactic star formation rate per unit mass of molecular gas are predicted theoretically from the condition that photionization-regulated star formation be in equilibrium. A simple model for the evolution of isolated molecular clouds is developed.

Mckee, Christopher F.↗
DOE OSTI2020

Description of the Three-Dimensional Large-Scale Forcing Data from the 3D Constrained Variational Analysis (VARANAL3D)

This technical report introduces a Three-Dimensional Constrained Variational Analysis (3DCVA) (Tang and Zhang 2015) and its product of three-dimensional large-scale forcing data to drive single-column models (SCM), cloud-resolving models (CRM), and large-eddy simulation (LES) models, and to evaluate model results. The 3DCVA algorithm is an extension of the original 1D constrained variational analysis (1DCVA) (Zhang and Lin 1997, Zhang et al. 2001). The three-dimensional structure of the forcing data allows studies of spatial variation of the large-scale forcing fields and tests of physical parameterizations across scales. In the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility, the 3D forcing data are assigned the datastream name varanal3d. In this technical report, 3DCVA will be used to refer to the algorithm, while VARANAL3D will be used to refer to the data product.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Developing and Testing a Novel Stochastic Ice Microphysics Parameterization for Cloud and Climate Models Using ARM Field Campaign Data (Final Progress Report)

The major goals of this project were: 1) to use field campaign measurements from DOE’s Atmospheric Radiation Measurement (ARM) program to characterize variability of important parameters describing properties of ice particles in the atmosphere; 2) based on this observational analysis, to develop a parameterization scheme for weather and climate models that stochastically varies these parameters, and implement the new scheme into a weather model called the Weather Research and Forecasting model (WRF); 3) to use WRF coupled with the new stochastic scheme to simulate ARM field campaign thunderstorm cases and analyze how accounting for this parameter variability affects the model simulations. This work was performed jointly between the National Center for Atmospheric Research, University of Oklahoma, and University of Utah. To accomplish these goals, we extended an approach previously developed to characterize the variability in the size distribution of ice particles to parameters that are explicitly represented in models (i.e., relationships between ice particle mass and size, and between particle fall velocity and size). Our project was, to our knowledge, the first to apply observationally-constrained estimates of this parameter variability describing mass-size and fall velocity-size in a modeling framework. Our results showed efficacy of the approach, evaluated using ARM observations. Similarly, to our knowledge, work in this project was the first to propose and evaluate in detail a stochastic approach for unresolved turbulent mixing in high-resolution model simulations against detailed, benchmark large eddy simulations and ARM observations. Results showed some promising behavior, particularly with increased mixing and dilution of air in thunderstorm cores with surrounding environmental air, bringing the stochastic simulations closer to the benchmark large eddy simulations; however, results were somewhat degraded using stochastic mixing compared to observations from the AMIE/DYNAMO field campaign. This project also further refined and applied a modeling methodology called “piggybacking” that can robustly separate dynamical and thermodynamic impacts of model changes, and comparison studies of different models based on cases developed from ARM observations. Finally, this project directly supported three graduate students who completed their PhDs as well as a postdoctoral research fellow.

54 ENVIRONMENTAL SCIENCES↗