ROSES Proposals

Above-cloud smoke aerosols are a persistent phenomenon in the SE Atlantic (SEA) with significant impacts on the regional to global radiative energy budget through their direct radiative effect (DRE), as well as semi-direct and indirect effects. In this project, we will develop sophisticated algorithms to retrieve above-cloud aerosols and determine their DRE by integrating the hyperspectral OCI spectrometer with the multiangular HARP2 polarimeter. This will enable the PACE mission to accurately characterize the properties of above-cloud smoke aerosols and underlying clouds in the SEA. Specifically, we will carry out the following research activities:

• Algorithm development and integration: Two distinct above-cloud smoke detection algorithms will be developed—one utilizing spectral color ratio data from OCI and the other employing polarimetric reflectance data from HARP2. We will adapt our multispectral algorithm from MODIS/VIIRS for simultaneous aerosol and cloud property retrieval to OCI specifications. Additionally, we will calculate two independent sets of smoke DRE, one via radiative transfer simulations, the other through direct hyperspectral radiance-to-flux conversion. These algorithms will be integrated into the same cloud product code framework leveraged for the operational OCI cloud products.
• Uncertainty quantification and product performance verification: We will adapt an existing approach to estimate pixel-level uncertainties, addressing all identifiable error sources in the retrieved and derived products. The performance of our retrieval products will be verified by benchmarking against our past study results.
• Publication of the algorithm and implementation of operational product: All the developed algorithms will be documented in Algorithm Theoretical Basis Documents (ATBD) and disseminated through peer-reviewed journals. At the end of project, we will submit these algorithms and sample datasets to the PACE Project Science Office for potential incorporation into the PACE Science Data Segment.

The novelty and importance of our research are threefold: Firstly, it extends the data record of above-cloud AOD retrievals initiated in the A-Train era, crucial for understanding long-term variations of above-cloud smoke in the SEA. Secondly, it enhances the PACE cloud product by detecting above-cloud smoke and correcting COT and CER retrievals, thereby helping users circumvent systematic cloud property biases and providing insights into aerosol-cloud interactions. Lastly, the hyperspectral method we develop for deriving aerosol DRE based on OCI observations could set a precedent for other NASA missions featuring hyperspectral shortwave observations, such as the Earth Surface Mineral Dust Source Investigation (EMIT), the Airborne Visible-Infrared Imaging Spectrometer- Next Generation (AVIRIS-NG), and the Surface Biology and Geology (SBG) Designated Observable mission.

Do-I: Daniel Miller (NASA), Student: Adeleke Segun (UMBC)