GWTC-2 Air Masses & Water Characteristics in Chesapeake Bay

These datasets are those necessary to carry out the work undertaken in the following research (currently in peer-review): On the Influence of Synoptic Air Masses on Water Conditions in the Chesapeake Bay Cameron C. Lee* (Kent State University; Department of Geography; ClimRISE Lab)Douglas Pirhalla (National Oceanic and Atmospheric Administration) * Corresponding Author Information:433 McGilvrey Hall325 S. Lincoln St.Kent, OH 44240 USAPh: [phone]Em: [e-mail] This data archive consists of the following datasets in MATLAB readable datafiles (.mat): 1) GWTCstuff_ALL.mat: Gridded Weather Typing Classification System (GWTC), version 2 air mass (AM) data. These data, and a description of the GWTC-2 platform are also available here: https://www.personal.kent.edu/~cclee/gwtc2global.html). Specifically herein, this dataset contains: the geographic coordinates (lat/long) of the 81 GWTC gridpoints sampled within the study domain (‘coords’); an 81-cell (corresponding to the 81 coordinates) cell-array quantifying the probability of each day at each gridpoint of being assigned to each of the 11 different GWTC-2 AMs (‘probs’); the final region-wide AM (‘AMall’); timestamps (‘timedata’) for each row in the probs and AMall variables, and a logical time-mask that indicates valid timesteps within our period of study (1985-2023). 2) Deseasonalized standardized anomalies (i.e., deseasonalized z-scores) of six different water characteristics of the Chesapeake Bay (USA) originating from the Regional Ocean Modeling System (ROMS; read more here: https://ches.communitymodeling.org/chesapeake-bay-roms-community-model-chesroms/). The variables are: water temperature (_Temp), salinity (_Salt), dissolved oxygen (_Oxygen), ocean volume x transport ('u-volume flux'; _Ucurrent), ocean volume y transport ('v-volume flux'); _Vcurrent), and sea-surface height (SSH; _Zeta). The first five of these six datasets have the data stored in a 3-cell cell-array called 'dszdata', with dszdata{1} being the uppermost surface layer of the water column, dszdata{2} being the bottom-most layer, and dszdata{3} being the difference between the surface and bottom layers. The sixth dataset (SSH/Zeta) also has the dszdata variable, but there is only a single layer. These datasets also contain a 2-column matrix with the latitude and longitudes of each column of dszdata{x}, and a timestamp variable (‘timedataO’) for these data, which corresponds to each row in dszdata{x}. All variables are unitless (sigma units), since they are standardized relative to the hyperlocal seasonal cycle (of means and standard-deviations). For more information, please email Dr. Cameron C. Lee at [e-mail].