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Tidal datum conversion grids for the Eastern Shore of Virginia and surrounding waters (2013)

2018· dataset· en· W6939682699 on OpenAlex

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Bibliographic record

VenueEnvironmental Data Initiative · 2018
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsGeodetic datumShoreElevation (ballistics)Sea levelTidal ModelNorth American Datum of 1927Baseline (sea)Interpolation (computer graphics)

Abstract

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Data consists of conversion factors that can be used to convert between numerous vertical tidal datums and the North American Vertical Datum of 1988 (NAVD88). The data cover the Eastern Shore of Virginia and parts of southeastern Maryland along with the surrounding coastal waters and are represented as approximately 100m (100.584m) resolution grids. The six included tidal datums are local mean sea level (LMSL), mean tidal level (MTL), mean low water (MLW), mean lower low water (MLLW), mean high water (MHW), and mean higher high water (MHHW). All vertical units are in meters. By combining multiple conversions to and from NAVD88, conversion between the various tidal datums is possible. Two versions of the conversion factor grids are provided for each NAVD88-to-tidal-datum pairing: one that only contains data for areas not masked as nodata by the NOAA VDatum program (original source data) and one that contains both the original and interpolated data (see below for details). Naming conventions used were "cfactor_DDD" for the original VDatum-detrived dataset where "DDD" is the local tidal datum and "cf_nd_DDD" for the dataset that includes interpolated values within the nodata masks (IDW interpolation across masked areas, typically upland regions but also shallow seaside bays and creeks for which no adequate tidal benchmarks were available). By definition, the baseline elevation (sea level or 0.0m elevation) for NAVD88 is referenced to the fixed International Great Lakes Datum of 1985 local mean sea level height value, at Rimouski, Quebec, Canada. Additional tidal bench mark elevations were not used to calculate NAVD88 due to the demonstrated variations in sea surface topography, i.e., the fact that mean sea level is not the same equipotential surface at all tidal benchmarks. The magnitude of the difference between local mean sea level (LMSL) at the tidal benchmarks of the Eastern Shore of Virginia and the NAVD88 defined sea-level varies from 0.039 to 0.149 meters BELOW zero NAVD88. Tidal prisms also vary at each tidal benchmark (in part due to differences in basin configuration and tidal interactions) causing the conversion factors for the other tidal datums to also vary spatially in similar but not identical patterns. The VDatum 3.2 software program from NOAA (http://vdatum.noaa.gov/) was used to convert the x,y,z center points of the 100m gridded data wherein all Z elevations were set equal to zero (0) from NAVD88 to each of the six local tidal datums (the X,Y horizontal WGS84 UTM 18N coordinates remained unchanged). The resulting conversion factors represent the new elevation at which the NAVD88 zero level would lie in reference to the new datum; thus, to convert from NAVD88 and the new tidal datum, one would add this conversion factor to the NAVD88 elevations to get elevations relative to the chosen tidal datum. To convert to NAVD88 from a given tidal datum, one would subtract the conversion factor from the tidal elevation. Data were turned back into gridded data with the same resolution and horizontal extent as the original data grid. The internal data grids used by the VDatum program mask as nodata most land areas (including marshes) plus many of the seaside shallow bays, either in part or in full, for which reliable tidal benchmark data is/was not available. As a result, the program cannot be used in these nodata areas, even if immediately adjacent to data areas. So as to make conversion factors available for these coastal bays and marshes and seaside watersheds of interest to the VCRLTER, conversion factors for gridded regions within the NOAA nodata masks were interpolated from neighboring data values using the inverse distance weighting (IDW) techniques employed by ESRI's ArcGIS 10.1 software. IDW interpolation resulted in conversion factors that varied gradually spatially when adjacent to the NOAA VDatum data grids but that often showed relatively sharp transitions when equidistant between different far-apart basins (such as mid-peninsula between the Chesapeake Bay and Atlantic Ocean, or within South Bay bounded by data constructed from tidal datums for the Atlantic Ocean (east), Ship Shoal Inlet (south), Sand Shoal Inlet (north), and Magothy Channel (west)). It is suggested that the appropriate use of this data is to convert elevation datasets referenced to a tidal datum to NAVD88 if integrating multiple datasets together over large areas, such as across the full Eastern Shore or across multiple watersheds or coastal bays, so as to not introduce artificial IDW-related transitions into otherwise vertically-consistent upland elevations or basin-scale bathymetric surveys. When converting elevations of fringing upland marshes, the conversion factors (including interpolated values) can likely be used directly on a cell-by-cell level to adjust the tidal elevations to NAVD88 or to another tidal datum without the involvement of any IDW-related transitions. Likewise for many of the back-barrier seaside marshes and bays of Accomack County in the northern portion of the data coverage where no channel tidal datums intervene between the Atlantic coastline and the Chesapeake Bay. However, when converting bathymetric survey data for individual bays or basins with significant nodata-masked areas that exhibit sharp IDW-related transitions, it is suggested that it would be more appropriate to use a single area-averaged conversion factor calculated across the whole basin (or across the whole basin minus any portion where the conversion factor is closer [more-related] to a channel on the other side of an upland barrier without connecting flow paths). Likewise when converting to tidal datums full upland mainland watersheds. This again should prevent introducing sharp transitions and steps into the bathymetry survey data, which it is assumed is otherwise internally consistent.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0020.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.284
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

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Citations2
Published2018
Admission routes1
Has abstractyes

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