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Full-Text Articles in Physical Sciences and Mathematics
Subset Data From The Nauru 1999 And African Monsoon Multidisciplinary Analysis (Amma) 2006 Cruise And Matlab Code For Generating Plots For The Paper: Wong And Minnett (2017): The Response Of The Ocean Thermal Skin Layer To Variations In Incident Infrared Radiation., Elizabeth Wong
Supplementary Data and Tools
Data in this collection is largely comprised of subsetted data from two research cruises, the Nauru cruise held from June to July 1999 and the African Monsoon Multidisciplinary Analysis (AMMA) cruise held from May to July 2006. The data subset is limited to night conditions under low wind speeds of < 10 m/s and consists of the surface fluxes, radiance measurements from the Marine Atmospheric Emitted Radiance Interferometer (M-AERI), the retrievals of the skin sea surface temperatures and skin sea surface temperature profiles from the M-AERI's radiance spectral measurements. Also included are line-by-line-radiative transfer simulations provided by Dr. Goshka Szczodrak, transmission coefficient spectra obtained from the HITRAN database, and wind speed data from the Special Sensing Microwave Imager (SSM/I) version 6. provided by Dr. Chelle Gentemann. Matlab code is provided which reads the datafile (DATA.mat) and outputs the figures illustrated in the paper Wong and Minnett (2017) (https://doi.org/10.1002/2017JC013351).
Fit To Predict? Ecoinformatics For Predicting The Catchability Of A Pelagic Fish In Near Real-Time, Kylie L. Scales, Elliot L. Hazen, Sara M. Maxwell, Heidi Dewar, Suzanne Kohin, Michael G. Jacox, Christopher A. Edwards, Dana K. Briscoe, Larry B. Crowder, Rebecca L. Lewison, Steven J. Bograd
Fit To Predict? Ecoinformatics For Predicting The Catchability Of A Pelagic Fish In Near Real-Time, Kylie L. Scales, Elliot L. Hazen, Sara M. Maxwell, Heidi Dewar, Suzanne Kohin, Michael G. Jacox, Christopher A. Edwards, Dana K. Briscoe, Larry B. Crowder, Rebecca L. Lewison, Steven J. Bograd
Biological Sciences Faculty Publications
The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing ecoinformatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting. Using 25 years (1990-2014) of NOAA fisheries' observer data from the California drift gillnet fishery, we model relative probability of …