edu.ucar.opensky::articles:25982 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T20:00:09.578847 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7t157jw https://doi.org/10.5067/GHAAO-4BC02 https Related Dataset #1 GHRSST Level 4 AVHRR_OI Global Blended Sea Surface Temperature Analysis (GDS version 2) from NCEI https://doi.org/10.5067/GHCMC-4FM03 https Related Dataset #2 GHRSST Level 4 CMC0.1deg Global Foundation Sea Surface Temperature Analysis (GDS version 2) https://doi.org/10.5067/GHG1S-4FP01 https Related Dataset #3 GHRSST Level 4 G1SST Global Foundation Sea Surface Temperature Analysis https://doi.org/10.5067/GHGPB-4FO02 https Related Dataset #4 GHRSST Level 4 OSPO Global Foundation Sea Surface Temperature Analysis (GDS version 2) https://doi.org/10.5067/GHK10-L4N01 https Related Dataset #5 GHRSST Level 4 K10_SST Global 10 km Analyzed Sea Surface Temperature from Naval Oceanographic Office (NAVO) in GDS2.0 https://doi.org/10.5067/GHOST-4FK01 https Related Dataset #6 GHRSST Level 4 OSTIA Global Foundation Sea Surface Temperature Analysis Simulating the Chesapeake Bay breeze: Sensitivities to water surface temperature 2022-11-01T00:00:00Z publication https://n2t.org/ark:/85065/d7t157jw https://doi.org/10.1175/JAMC-D-22-0002.1 Hawbecker, Patrick author Knievel, Jason C. author UCAR/NCAR - Library publisher Simulations of Chesapeake Bay breezes are performed with varying water surface temperature (WST) datasets and formulations for the diurnal cycle of WST to determine whether more accurate depictions of water surface temperature improve prediction of bay breezes. The accuracy of simulations is measured against observed WST, inland wind speed and temperature, and in simulations' ability to detect bay breezes via a detection algorithm developed for numerical model output. Missing WST data are found to be problematic within the Weather Research and Forecasting (WRF) Model framework, especially when activating the prognostic equation for skin temperature, sst_skin. This is alleviated when filling all missing WST values with skin temperature values within the initial and boundary conditions. Performance of bay-breeze prediction is shown to be somewhat associated with the resolution of the WST dataset. Further, model performance in simulating WST as well as in simulating the Chesapeake Bay breeze is improved when diurnal fluctuations of WST are considered via the sst skin option. Prior to running simulations, model performance in simulating the bay breeze can be accurately predicted through the use of a simple formulation. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. None eng geoscientificInformation