C. Karstens

发表

Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather

S. E. Haupt, Travis M. Smith, A. McGovern, 2017 .

A Comparison of Multiscale GSI-Based EnKF and 3DVar Data Assimilation Using Radar and Conventional Observations for Midlatitude Convective-Scale Precipitation Forecasts

Louis J. Wicker, Christopher D. Karstens, Jacob R. Carley, 2015 .

Breaking New Ground in Severe Weather Prediction: The 2015 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment

S. J. Weiss, James Correia, Burkely T. Gallo, 2017 .

Observations and laboratory simulations of tornadoes in complex topographical regions

C. Karstens, 2012 .

Improved understanding of near-ground winds in hurricanes and tornadoes

C. Karstens, 2009 .

Improved Doppler Velocity Dealiasing for Radar Data Assimilation and Storm-Scale Vortex Detection

Travis M. Smith, C. Karstens, Qingyun Zhao, 2013 .

The Bowdle, South Dakota, Cyclic Tornadic Supercell of 22 May 2010: Surface Analysis of Rear-Flank Downdraft Evolution and Multiple Internal Surges

C. Karstens, C. Finley, Bruce D. Lee, 2012 .

Development of a Human–Machine Mix for Forecasting Severe Convective Events

Kristin M. Calhoun, Lans P. Rothfusz, John L. Cintineo, 2018 .

An Investigation of Local and National NWS Warning Outbreaks for Severe Convective Events

C. Karstens, Zachary S. Bruick, 2017 .

Evaluation of Near Real-Time Preliminary Tornado Damage Paths

Travis M. Smith, Douglas A. Speheger, C. Karstens, 2016 .

Boundary-layer Decoupling Affects on Tornadoes

C. Karstens, 2008 .

Quasi-Operational Testing of Real-Time Storm-Longevity Prediction via Machine Learning

Amy McGovern, Christopher D. Karstens, Travis M. Smith, 2019, Weather and Forecasting.

Analysis of Tornado-Induced Tree Fall Using Aerial Photography from the Joplin, Missouri, and Tuscaloosa–Birmingham, Alabama, Tornadoes of 2011*

Christopher D. Karstens, William A. Gallus, W. Gallus, 2013 .

A Climatology of Operational Storm-Based Warnings: A Geospatial Analysis

Christopher D. Karstens, C. Karstens, David Harrison, 2017 .

WSR-88D Tornado Intensity Estimates. Part II: Real-Time Applications to Tornado Warning Time Scales

Richard L. Thompson, Douglas A. Speheger, Bryan T. Smith, 2020 .

FACETs: A Proposed Next-Generation Paradigm for High-Impact Weather Forecasting

Lans P. Rothfusz, Russell S. Schneider, Alan Gerard, 2018, Bulletin of the American Meteorological Society.

Evaluation of a Probabilistic Forecasting Methodology for Severe Convective Weather in the 2014 Hazardous Weather Testbed

Kristin M. Calhoun, Lans P. Rothfusz, Darrel M. Kingfield, 2015 .

A Comparison of Mid-Level Frontogenesis to Radar-Indicated Heavy Snowbands

C. Karstens, 2006 .

WSR-88D Tornado Intensity Estimates. Part I: Real-Time Probabilities of Peak Tornado Wind Speeds

Richard L. Thompson, Douglas A. Speheger, Bryan T. Smith, 2020 .

Near-Ground Pressure and Wind Measurements in Tornadoes*

Christopher D. Karstens, William A. Gallus, Timothy M. Samaras, 2010 .

Quality Control of Weather Radar Data Using Polarimetric Variables

Valliappa Lakshmanan, Lin Tang, Christopher Karstens, 2014 .

Which Polarimetric Variables Are Important for Weather/No-Weather Discrimination?

Alexander V. Ryzhkov, Valliappa Lakshmanan, Christopher Karstens, 2015 .

Collaborative Efforts between the United States and United Kingdom to Advance Prediction of High-Impact Weather

Israel L. Jirak, Adam J. Clark, Christopher D. Karstens, 2017 .

Generating Probabilistic Next-Day Severe Weather Forecasts from Convection-Allowing Ensembles Using Random Forests

Adam J. Clark, Christopher D. Karstens, C. Karstens, 2020 .

Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather

S. E. Haupt, Travis M. Smith, A. McGovern, 2017 .

DETERMINING WHEN AND HOW A RANDOM FOREST ADDS VALUE TO DAY 1 SPC HAIL FORECASTS

Bryan T. Smith, D. Jahn, C. Karstens, 2021 .

TWISTEX 2008: IN SITU AND MOBILE MESONET OBSERVATIONS OF TORNADOES

C. Karstens, C. Finley, Bruce D. Lee, 2008 .