Weather Research and Forecasting Innovation Act (

Advanced Search

Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

Advanced Search
Custom Query

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Clear All

Query Builder

Query box

Clear All

For additional assistance using the Custom Query please check out our Help Page

Narrow Results:

2023 1
2022 1

Journal Article 2

1 - 2 of 2 Results

Refine Results

Refine Results:

Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation

CITE Title : Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation Personal Author(s) : Pringle, William J.;Burnett, Zachary;Sargsyan, Khachik;Moghimi, Saeed;Myers, Edward; Published Date : 2023 Source : Artificial Intelligence for the Earth Systems, 2(2) DOI : https://doi.org/10.1175/aies-d-22-0040.1 Journal Title : Artificial Intelligence for the Earth Systems Pringle, William J. et al. (2023). Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation. 2(2). https://doi.org/10.1175/aies-d-22-0040.1 Pringle, William J. et al. "Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation" 2, no. 2 (2023), https://doi.org/10.1175/aies-d-22-0040.1 Pringle, William J. et al. "Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation" vol. 2, no. 2, 2023, https://doi.org/10.1175/aies-d-22-0040.1 Export RIS Citation Information.

:

Pringle, William J.

;

Burnett, Zachary

2023 | Artificial Intelligence for the Earth Systems, 2(2)

:

This study proposes and assesses a methodology to obtain high-quality probabilistic predictions and uncertainty information of near-landfall tropical ...
Dissipation and Bathymetric Sensitivities in an Unstructured Mesh Global Tidal Model

CITE Title : Dissipation and Bathymetric Sensitivities in an Unstructured Mesh Global Tidal Model Personal Author(s) : Blakely, Coleman P.;Ling, Guoming;Pringle, William J.;Contreras, María Teresa;Wirasaet, Damrongsak;Westerink, Joannes J.;Moghimi, Saeed;Seroka, Greg;Shi, Lei;Myers, Edward;Owensby, Margaret;Massey, Chris; Published Date : 2022 Source : Journal of Geophysical Research: Oceans, 127(5) DOI : https://doi.org/10.1029/2021JC018178 Journal Title : Journal of Geophysical Research: Oceans Blakely, Coleman P. et al. (2022). Dissipation and Bathymetric Sensitivities in an Unstructured Mesh Global Tidal Model. 127(5). https://doi.org/10.1029/2021JC018178 Blakely, Coleman P. et al. "Dissipation and Bathymetric Sensitivities in an Unstructured Mesh Global Tidal Model" 127, no. 5 (2022), https://doi.org/10.1029/2021JC018178 Blakely, Coleman P. et al. "Dissipation and Bathymetric Sensitivities in an Unstructured Mesh Global Tidal Model" vol. 127, no. 5, 2022, https://doi.org/10.1029/2021JC018178 Export RIS Citation Information.

:

Blakely, Coleman P.

;

Ling, Guoming

2022 | Journal of Geophysical Research: Oceans, 127(5)

:

The mechanisms and geographic distribution of global tidal dissipation in barotropic tidal models are examined using a high resolution unstructured me...