Engineering topics

Griffin, B. M.

Publications and source records attributed to Griffin, B. M..

4 records

DOE OSTI2015

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysics scheme. This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Model computational expense is estimated, and sensitivity to the number of subcolumns is investigated. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in shortwave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysics scheme.This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.

58 GEOSCIENCES↗

DOE OSTI2015

Parameterizing deep convection using the assumed probability density function method

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.

Storer, R. L.↗

NASA NTRS1999

Phototrophs in high-iron-concentration microbial mats: physiological ecology of phototrophs in an iron-depositing hot spring

At Chocolate Pots Hot Springs in Yellowstone National Park the source waters have a pH near neutral, contain high concentrations of reduced iron, and lack sulfide. An iron formation that is associated with cyanobacterial mats is actively deposited. The uptake of [(14)C]bicarbonate was used to assess the impact of ferrous iron on photosynthesis in this environment. Photoautotrophy in some of the mats was stimulated by ferrous iron (1.0 mM). Microelectrodes were used to determine the impact of photosynthetic activity on the oxygen content and the pH in the mat and sediment microenvironments. Photosynthesis increased the oxygen concentration to 200% of air saturation levels in the top millimeter of the mats. The oxygen concentration decreased with depth and in the dark. Light-dependent increases in pH were observed. The penetration of light in the mats and in the sediments was determined. Visible radiation was rapidly attenuated in the top 2 mm of the iron-rich mats. Near-infrared radiation penetrated deeper. Iron was totally oxidized in the top few millimeters, but reduced iron was detected at greater depths. By increasing the pH and the oxygen concentration in the surface sediments, the cyanobacteria could potentially increase the rate of iron oxidation in situ. This high-iron-content hot spring provides a suitable model for studying the interactions of microbial photosynthesis and iron deposition and the role of photosynthesis in microbial iron cycling. This model may help clarify the potential role of photosynthesis in the deposition of Precambrian banded iron formations.

NASA Discipline Exobiology↗