Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets
by
Reed, Kevin A
, Zarzycki, Colin M
, Ullrich, Paul A
, Pinheiro, Marielle C
, Stansfield, Alyssa M
, McClenny, Elizabeth E
in
Algorithms
/ Atmospheric blocking
/ Atmospheric depressions
/ Automation
/ Climate
/ Climatology
/ Cyclones
/ Data analysis
/ Datasets
/ Detection
/ Extratropical cyclones
/ Fields
/ Frameworks
/ Heat waves
/ Heatwaves
/ Hurricanes
/ Kernels
/ Mathematical analysis
/ Precipitation
/ Software
/ Tracking
/ Tropical climate
/ Tropical cyclones
/ Wind profiles
2021
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets
by
Reed, Kevin A
, Zarzycki, Colin M
, Ullrich, Paul A
, Pinheiro, Marielle C
, Stansfield, Alyssa M
, McClenny, Elizabeth E
in
Algorithms
/ Atmospheric blocking
/ Atmospheric depressions
/ Automation
/ Climate
/ Climatology
/ Cyclones
/ Data analysis
/ Datasets
/ Detection
/ Extratropical cyclones
/ Fields
/ Frameworks
/ Heat waves
/ Heatwaves
/ Hurricanes
/ Kernels
/ Mathematical analysis
/ Precipitation
/ Software
/ Tracking
/ Tropical climate
/ Tropical cyclones
/ Wind profiles
2021
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets
by
Reed, Kevin A
, Zarzycki, Colin M
, Ullrich, Paul A
, Pinheiro, Marielle C
, Stansfield, Alyssa M
, McClenny, Elizabeth E
in
Algorithms
/ Atmospheric blocking
/ Atmospheric depressions
/ Automation
/ Climate
/ Climatology
/ Cyclones
/ Data analysis
/ Datasets
/ Detection
/ Extratropical cyclones
/ Fields
/ Frameworks
/ Heat waves
/ Heatwaves
/ Hurricanes
/ Kernels
/ Mathematical analysis
/ Precipitation
/ Software
/ Tracking
/ Tropical climate
/ Tropical cyclones
/ Wind profiles
2021
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets
Journal Article
TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets
2021
Request Book From Autostore
and Choose the Collection Method
Overview
TempestExtremes (TE) is a multifaceted framework for feature detection, tracking, and scientific analysis of regional or global Earth system datasets on either rectilinear or unstructured/native grids. Version 2.1 of the TE framework now provides extensive support for examining both nodal (i.e., pointwise) and areal features, including tropical and extratropical cyclones, monsoonal lows and depressions, atmospheric rivers, atmospheric blocking, precipitation clusters, and heat waves. Available operations include nodal and areal thresholding, calculations of quantities related to nodal features such as accumulated cyclone energy and azimuthal wind profiles, filtering data based on the characteristics of nodal features, and stereographic compositing. This paper describes the core algorithms (kernels) that have been added to the TE framework since version 1.0, including algorithms for editing pointwise trajectory files, composition of fields around nodal features, generation of areal masks via thresholding and nodal features, and tracking of areal features in time. Several examples are provided of how these kernels can be combined to produce composite algorithms for evaluating and understanding common atmospheric features and their underlying processes. These examples include analyzing the fraction of precipitation from tropical cyclones, compositing meteorological fields around extratropical cyclones, calculating fractional contribution to poleward vapor transport from atmospheric rivers, and building a climatology of atmospheric blocks.
This website uses cookies to ensure you get the best experience on our website.