ABSTRACT
This paper presents the physical basis of the EPIC cloud product algorithms and an initial evaluation of their performance. Since June 2015, EPIC has been providing observations of the sunlit side of the Earth with its 10 spectral channels ranging from the UV to the near-IR. A suite of algorithms has been developed to generate the standard EPIC Level 2 Cloud Products that include cloud mask, cloud effective pressure/height, and cloud optical thickness. The EPIC cloud mask adopts the threshold method and utilizes multichannel observations and ratios as tests. Cloud effective pressure/height is derived with observations from the O2 A-band (780 nm and 764 nm), and B-band (680 nm and 688 nm) pairs. The EPIC cloud optical thickness retrieval adopts a single channel approach where the 780 nm and 680 nm channels are used for retrievals over ocean and over land, respectively. Comparison with co-located cloud retrievals from geosynchronous earth orbit (GEO) and low earth orbit (LEO) satellites shows that the EPIC cloud product algorithms are performing well and are consistent with theoretical expectations. These products are publicly available at the Atmospheric Science Data Center at the NASA Langley Research Center for climate studies and for generating other geophysical products that require cloud properties as input.
ABSTRACT
Ozone within deep convective clouds is controlled by several factors involving photochemical reactions and transport. Gas-phase photochemical reactions and heterogeneous surface chemical reactions involving ice, water particles, and aerosols inside the clouds all contribute to the distribution and net production and loss of ozone. Ozone in clouds is also dependent on convective transport that carries low troposphere/boundary layer ozone and ozone precursors upward into the clouds. Characterizing ozone in thick clouds is an important step for quantifying relationships of ozone with tropospheric H2O, OH production, and cloud microphysics/transport properties. Although measuring ozone in deep convective clouds from either aircraft or balloon ozonesondes is largely impossible due to extreme meteorological conditions associated with these clouds, it is possible to estimate ozone in thick clouds using backscattered solar UV radiation measured by satellite instruments. Our study combines Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) satellite measurements to generate a new research product of monthly-mean ozone concentrations in deep convective clouds between 30°S to 30°N for October 2004 - April 2016. These measurements represent mean ozone concentration primarily in the upper levels of thick clouds and reveal key features of cloud ozone including: persistent low ozone concentrations in the tropical Pacific of ~10 ppbv or less; concentrations of up to 60 pphv or greater over landmass regions of South America, southern Africa, Australia, and India/east Asia; connections with tropical ENSO events; and intra-seasonal/Madden-Julian Oscillation variability. Analysis of OMI aerosol measurements suggests a cause and effect relation between boundary layer pollution and elevated ozone inside thick clouds over land-mass regions including southern Africa and India/east Asia.
ABSTRACT
Quantitative assessment of the UV effects on aquatic ecosystems requires an estimate of the in-water radiation field. Actual ocean UV reflectances are needed for improving the total ozone retrievals from the total ozone mapping spectrometer (TOMS) and the ozone monitoring instrument (OMI) flown on NASA's Aura satellite. The estimate of underwater UV radiation can be done on the basis of measurements from the TOMS/OMI and full models of radiative transfer (RT) in the atmosphere-ocean system. The Hydrolight code, modified for extension to the UV, is used for the generation of look-up tables for in-water irradiances. A look-up table for surface radiances generated with a full RT code is input for the Hydrolight simulations. A model of seawater inherent optical properties (IOPs) is an extension of the Case 1 water model to the UV. A new element of the IOP model is parameterization of particulate matter absorption based on recent in situ data. A chlorophyll product from ocean color sensors is input for the IOP model. Verification of the in-water computational scheme shows that the calculated diffuse attenuation coefficient Kd is in good agreement with the measured Kd.
