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  • Author or Editor: Jennifer S. Haase x
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Minghua Zheng
,
Luca Delle Monache
,
Xingren Wu
,
F. Martin Ralph
,
Bruce Cornuelle
,
Vijay Tallapragada
,
Jennifer S. Haase
,
Anna M. Wilson
,
Matthew Mazloff
,
Aneesh Subramanian
, and
Forest Cannon

Abstract

Conventional observations of atmospheric rivers (ARs) over the northeastern Pacific Ocean are sparse. Satellite radiances are affected by the presence of clouds and heavy precipitation, which impact their distribution in the lower atmosphere and in precipitating areas. The goal of this study is to document a data gap in existing observations of ARs in the northeastern Pacific, and to investigate how a targeted field campaign called AR Reconnaissance (AR Recon) can effectively fill this gap. When reconnaissance data are excluded, there is a gap in AR regions from near the surface to the middle troposphere (below 450 hPa), where most water vapor and its transport are concentrated. All-sky microwave radiances provide data within the AR object, but their quality is degraded near the AR core and its leading edge, due to the existence of thick clouds and precipitation. AR Recon samples ARs and surrounding areas to improve downstream precipitation forecasts over the western United States. This study demonstrates that despite the apparently extensive swaths of modern satellite radiances, which are critical to estimate large-scale flow, the data collected during 15 AR Recon cases in 2016, 2018, and 2019 supply about 99% of humidity, 78% of temperature, and 45% of wind observations in the critical maximum water vapor transport layer from the ocean surface to 700 hPa in ARs. The high-vertical-resolution dropsonde observations in the lower atmosphere over the northeastern Pacific Ocean can significantly improve the sampling of low-level jets transporting water vapor to high-impact precipitation events in the western United States.

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Angelyn W. Moore
,
Ivory J. Small
,
Seth I. Gutman
,
Yehuda Bock
,
John L. Dumas
,
Peng Fang
,
Jennifer S. Haase
,
Mark E. Jackson
, and
Jayme L. Laber

Abstract

During the North American Monsoon, low-to-midlevel moisture is transported in surges from the Gulf of California and Eastern Pacific Ocean into Mexico and the American Southwest. As rising levels of precipitable water interact with the mountainous terrain, severe thunderstorms can develop, resulting in flash floods that threaten life and property. The rapid evolution of these storms, coupled with the relative lack of upper-air and surface weather observations in the region, make them difficult to predict and monitor, and guidance from numerical weather prediction models can vary greatly under these conditions. Precipitable water vapor (PW) estimates derived from continuously operating ground-based GPS receivers have been available for some time from NOAA’s GPS-Met program, but these observations have been of limited utility to operational forecasters in part due to poor spatial resolution. Under a NASA Advanced Information Systems Technology project, 37 real-time stations were added to NOAA’s GPS-Met analysis providing 30-min PW estimates, reducing station spacing from approximately 150 km to 30 km in Southern California. An 18–22 July 2013 North American Monsoon event provided an opportunity to evaluate the utility of the additional upper-air moisture observations to enhance National Weather Service (NWS) forecaster situational awareness during the rapidly developing event. NWS forecasters used these additional data to detect rapid moisture increases at intervals between the available 1–6-h model updates and approximately twice-daily radiosonde observations, and these contributed tangibly to the issuance of timely flood watches and warnings in advance of flash floods, debris flows, and related road closures.

Full access
Minghua Zheng
,
Luca Delle Monache
,
Xingren Wu
,
F. Martin Ralph
,
Bruce Cornuelle
,
Vijay Tallapragada
,
Jennifer S. Haase
,
Anna M. Wilson
,
Matthew Mazloff
,
Aneesh Subramanian
, and
Forest Cannon
Full access
Michael T. Montgomery
,
Christopher Davis
,
Timothy Dunkerton
,
Zhuo Wang
,
Christopher Velden
,
Ryan Torn
,
Sharanya J. Majumdar
,
Fuqing Zhang
,
Roger K. Smith
,
Lance Bosart
,
Michael M. Bell
,
Jennifer S. Haase
,
Andrew Heymsfield
,
Jorgen Jensen
,
Teresa Campos
, and
Mark A. Boothe

The principal hypotheses of a new model of tropical cyclogenesis, known as the marsupial paradigm, were tested in the context of Atlantic tropical disturbances during the National Science Foundation (NSF)-sponsored Pre-Depression Investigation of Cloud Systems in the Tropics (PREDICT) experiment in 2010. PREDICT was part of a tri-agency collaboration, along with the National Aeronautics and Space Administration's Genesis and Rapid Intensification Processes (NASA GRIP) experiment and the National Oceanic and Atmospheric Administration's Intensity Forecasting Experiment (NOAA IFEX), intended to examine both developing and nondeveloping tropical disturbances.

During PREDICT, a total of 26 missions were flown with the NSF/NCAR Gulfstream V (GV) aircraft sampling eight tropical disturbances. Among these were four cases (Fiona, ex-Gaston, Karl, and Matthew) for which three or more missions were conducted, many on consecutive days. Because of the scientific focus on the Lagrangian nature of the tropical cyclogenesis process, a wave-relative frame of reference was adopted throughout the experiment in which various model- and satellite-based products were examined to guide aircraft planning and real-time operations. Here, the scientific products and examples of data collected are highlighted for several of the disturbances. The suite of cases observed represents arguably the most comprehensive, self-consistent dataset ever collected on the environment and mesoscale structure of developing and nondeveloping predepression disturbances.

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David A. Lavers
,
Anna M. Wilson
,
F. Martin Ralph
,
Vijay Tallapragada
,
Florian Pappenberger
,
Carolyn Reynolds
,
James D. Doyle
,
Luca Delle Monache
,
Chris Davis
,
Aneesh Subramanian
,
Ryan D. Torn
,
Jason M. Cordeira
,
Luca Centurioni
, and
Jennifer S. Haase
Open access
F. Martin Ralph
,
Forest Cannon
,
Vijay Tallapragada
,
Christopher A. Davis
,
James D. Doyle
,
Florian Pappenberger
,
Aneesh Subramanian
,
Anna M. Wilson
,
David A. Lavers
,
Carolyn A. Reynolds
,
Jennifer S. Haase
,
Luca Centurioni
,
Bruce Ingleby
,
Jonathan J. Rutz
,
Jason M. Cordeira
,
Minghua Zheng
,
Chad Hecht
,
Brian Kawzenuk
, and
Luca Delle Monache

Abstract

Water management and flood control are major challenges in the western United States. They are heavily influenced by atmospheric river (AR) storms that produce both beneficial water supply and hazards; for example, 84% of all flood damages in the West (up to 99% in key areas) are associated with ARs. However, AR landfall forecast position errors can exceed 200 km at even 1-day lead time and yet many watersheds are <100 km across, which contributes to issues such as the 2017 Oroville Dam spillway incident and regularly to large flood forecast errors. Combined with the rise of wildfires and deadly post-wildfire debris flows, such as Montecito (2018), the need for better AR forecasts is urgent. Atmospheric River Reconnaissance (AR Recon) was developed as a research and operations partnership to address these needs. It combines new observations, modeling, data assimilation, and forecast verification methods to improve the science and predictions of landfalling ARs. ARs over the northeast Pacific are measured using dropsondes from up to three aircraft simultaneously. Additionally, airborne radio occultation is being tested, and drifting buoys with pressure sensors are deployed. AR targeting and data collection methods have been developed, assimilation and forecast impact experiments are ongoing, and better understanding of AR dynamics is emerging. AR Recon is led by the Center for Western Weather and Water Extremes and NWS/NCEP. The effort’s core partners include the U.S. Navy, U.S. Air Force, NCAR, ECMWF, and multiple academic institutions. AR Recon is included in the “National Winter Season Operations Plan” to support improved outcomes for emergency preparedness and water management in the West.

Free access
F. Martin Ralph
,
Forest Cannon
,
Vijay Tallapragada
,
Christopher A. Davis
,
James D. Doyle
,
Florian Pappenberger
,
Aneesh Subramanian
,
Anna M. Wilson
,
David A. Lavers
,
Carolyn A. Reynolds
,
Jennifer S. Haase
,
Luca Centurioni
,
Bruce Ingleby
,
Jonathan J. Rutz
,
Jason M. Cordeira
,
Minghua Zheng
,
Chad Hecht
,
Brian Kawzenuk
, and
Luca Delle Monache
Full access
Yolande L. Serra
,
Jennifer S. Haase
,
David K. Adams
,
Qiang Fu
,
Thomas P. Ackerman
,
M. Joan Alexander
,
Avelino Arellano
,
Larissa Back
,
Shu-Hua Chen
,
Kerry Emanuel
,
Zeljka Fuchs
,
Zhiming Kuang
,
Benjamin R Lintner
,
Brian Mapes
,
David Neelin
,
David Raymond
,
Adam H. Sobel
,
Paul W. Staten
,
Aneesh Subramanian
,
David W. J. Thompson
,
Gabriel Vecchi
,
Robert Wood
, and
Paquita Zuidema
Full access
Florence Rabier
,
Aurélie Bouchard
,
Eric Brun
,
Alexis Doerenbecher
,
Stéphanie Guedj
,
Vincent Guidard
,
Fatima Karbou
,
Vincent-Henri Peuch
,
Laaziz El Amraoui
,
Dominique Puech
,
Christophe Genthon
,
Ghislain Picard
,
Michael Town
,
Albert Hertzog
,
François Vial
,
Philippe Cocquerez
,
Stephen A. Cohn
,
Terry Hock
,
Jack Fox
,
Hal Cole
,
David Parsons
,
Jordan Powers
,
Keith Romberg
,
Joseph VanAndel
,
Terry Deshler
,
Jennifer Mercer
,
Jennifer S. Haase
,
Linnea Avallone
,
Lars Kalnajs
,
C. Roberto Mechoso
,
Andrew Tangborn
,
Andrea Pellegrini
,
Yves Frenot
,
Jean-Noël Thépaut
,
Anthony McNally
,
Gianpaolo Balsamo
, and
Peter Steinle

The Concordiasi project is making innovative observations of the atmosphere above Antarctica. The most important goals of the Concordiasi are as follows:

  • To enhance the accuracy of weather prediction and climate records in Antarctica through the assimilation of in situ and satellite data, with an emphasis on data provided by hyperspectral infrared sounders. The focus is on clouds, precipitation, and the mass budget of the ice sheets. The improvements in dynamical model analyses and forecasts will be used in chemical-transport models that describe the links between the polar vortex dynamics and ozone depletion, and to advance the under understanding of the Earth system by examining the interactions between Antarctica and lower latitudes.

  • To improve our understanding of microphysical and dynamical processes controlling the polar ozone, by providing the first quasi-Lagrangian observations of stratospheric ozone and particles, in addition to an improved characterization of the 3D polar vortex dynamics. Techniques for assimilating these Lagrangian observations are being developed.

A major Concordiasi component is a field experiment during the austral springs of 2008–10. The field activities in 2010 are based on a constellation of up to 18 long-duration stratospheric super-pressure balloons (SPBs) deployed from the McMurdo station. Six of these balloons will carry GPS receivers and in situ instruments measuring temperature, pressure, ozone, and particles. Twelve of the balloons will release dropsondes on demand for measuring atmospheric parameters. Lastly, radiosounding measurements are collected at various sites, including the Concordia station.

Full access