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Loftus, Adrian

Publications and source records attributed to Loftus, Adrian.

4 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

The OpenSSP Snow Particle and Scattering Property Database: Current Status and Future Plans

Understanding the connection between microphysical properties of falling snow and remote sensing observations requires detailed models of snow particles and the related electromagnetic scattering properties. To this end, we have created a database of synthetically-grown snow particles along with electromagnetic scattering properties calculated using advanced computational methods. We showcase the breadth of the catalog, current work, applications of the catalog, and future plans.

Adams, Ian S.↗
NASA NTRS2019

Active and Passive Radiative Transfer Simulations for GPM-Related Field Campaigns

Using a three-dimensional radiative transfer model combined with cloud-resolving model output, we simulate active and passive sensor observations of clouds and precipitaiton. This combination of tools allows us to diagnose the contributions of various hydrometeor types. Radar multiple scattering is most closely associated with the presence of graupel. At Wband, massive amounts multiple scattering in deep convection can decorrelate the reflectivity profile from the vertical structure, but for less intense events, multiple scattering could be a useful indicator of riming. For passive sensors, polarization differences at 166 GHz indicate the presence of horizontally aligned frozen particles with pronounced aspect ratios, while high concentrations of more isotropic aggregates and graupel dampen the polarization difference while also contributing to the lowest brightness temperature depressions. The insights into remote sensing measurements will facilitate the development of improved algorithms and advanced sensors.

Adams, Ian S.↗
NASA NTRS2019

Active and Passive Radiative Transfer Simulations for GPM-Related Field Campaigns

Radiative transfer modeling is an important tool for interpreting remote sensing observations. It allows us to determine how sensor characteristics will impact observations, and it gives us a framework for us to test assumptions about the phenomena we are attempting to observe. In this work, we use cloud simulations for precipitation events observed during various GPM-related field campaigns. The simulations show how various properties of clouds and precipitation affect the measurements.

Adams, Ian S.↗