GG 646/446 Semester Project Suggestions

Data Processing and Models

1. Surface albedo models in Streamer. Add a greater variety of surface types in the Streamer radiative transfer model and test their effect on the retrieval of cloud properties or aerosol amounts.
2. BASE validation. Validation of cloud optical depth and radiative fluxes measured by aircraft and estimated with satellite data during the Beaufort and Arctic Storms Experiment. Also a comparison to parameters provided through the International Satellite Cloud Climatology Project (ISCCP).
3. Horizontally inhomogeneous clouds. Investigate how horizontal variations in cloud and surface characteristics (e.g., cloud optical depth and surface reflectance) affect large-area surface radiative fluxes. Analyses will be done with a 3-D radiative transfer model (SHDOM).
4. Vertical distribution of Re. Cloud particle effective radius (Re) is generally inhomogeneous in the vertical dimension. So when Re is estimated from satellite data, what does it correspond to? The mean? Re at the cloud top? Analyses will be done with aircraft measurements of Re, a radiative transfer model, and satellite data.
5. Surface temperature under cloud cover. Infrared sensors are used for surface temperature (Ts) retrieval but are restricted to clear sky conditions. What is the relationship between the clear sky and cloudy sky Ts? Is there any way to estimate the cloudy sky Ts knowing the nearby clear sky Ts, cloud properties, etc.? The investigation will involve the use of an energy balance model as well as the examination of in situ data. Any derived relationships must be tested with satellite data.
6. Albedo and cloud Re/tau retrieval with a bidirectionally reflecting surface. Currently implemented procedures for estimating cloud properties and surface albedo assume an isotropically reflecting (Lambertian) surface. For snow this is obviously incorrect. What is the magnitude of the error, and under what conditions? Use a radiative transfer model to generate the data necessary to modify existing retrieval algorithms. Implement and test the new procedure.
7. Estimating cloud properties from surface radiative fluxes. It has been shown that cloud optical depth can be estimated from downwelling shortwave radiation at the surface. What more can be learned about cloud characteristics by including the downwelling longwave flux?
8. Determining cloud particle phase with AVHRR data. Develop a method to determine the whether a cloud is composed of liquid or solid (ice) particles using AVHRR visible and thermal channels. Use a radiative transfer model to aid in the algorithm development, and test is with AVHRR data.
9. Aerosol estimation. Using direct beam solar radiation measurements at three different wavelengths to estimate solar extinction primarily due to atmospheric aerosols at Mauna Loa. The effects of the El Chicon eruption will be illustrated. (Stevens) Minor Fortran programming required; definitely needs to be extended.
10. Moisture retrieval. Passive microwave satellite data from the SSM/I sensor on-board the Defense Meteorological Satellite Program platforms are used to estimate column water vapor and cloud liquid water. (Stevens) Fortran programming and calculus required; may need to be extended.
11. Temperature sounding. Thermal infrared data from the HIRS sensor on NOAA satellites are employed in the estimation of vertical profiles of temperature and humidity. (Stevens) Fortran programming required.

Literature Reviews

1. Survey of surface-based remote sensing instruments.
2. Survey of data assimilation methods and applications.
3. Survey of aerosol estimation methods, including an aerosol climatology.