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  • Author or Editor: F. Chen x
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Shuyi S. Chen
,
James F. Price
,
Wei Zhao
,
Mark A. Donelan
, and
Edward J. Walsh
Full access
Yang Chen
,
Wei Chen
,
Qin Su
,
Feifei Luo
,
Sarah Sparrow
,
David Wallom
,
Fangxing Tian
,
Buwen Dong
,
Simon F. B. Tett
, and
Fraser C. Lott
Full access
James H. Ruppert Jr.
,
Steven E. Koch
,
Xingchao Chen
,
Yu Du
,
Anton Seimon
,
Y. Qiang Sun
,
Junhong Wei
, and
Lance F. Bosart

Abstract

Over the course of his career, Fuqing Zhang drew vital new insights into the dynamics of meteorologically significant mesoscale gravity waves (MGWs), including their generation by unbalanced jet streaks, their interaction with fronts and organized precipitation, and their importance in midlatitude weather and predictability. Zhang was the first to deeply examine “spontaneous balance adjustment”—the process by which MGWs are continuously emitted as baroclinic growth drives the upper-level flow out of balance. Through his pioneering numerical model investigation of the large-amplitude MGW event of 4 January 1994, he additionally demonstrated the critical role of MGW–moist convection interaction in wave amplification. Zhang’s curiosity-turned-passion in atmospheric science covered a vast range of topics and led to the birth of new branches of research in mesoscale meteorology and numerical weather prediction. Yet, it was his earliest studies into midlatitude MGWs and their significant impacts on hazardous weather that first inspired him. Such MGWs serve as the focus of this review, wherein we seek to pay tribute to his groundbreaking contributions, review our current understanding, and highlight critical open science issues. Chief among such issues is the nature of MGW amplification through feedback with moist convection, which continues to elude a complete understanding. The pressing nature of this subject is underscored by the continued failure of operational numerical forecast models to adequately predict most large-amplitude MGW events. Further research into such issues therefore presents a valuable opportunity to improve the understanding and forecasting of this high-impact weather phenomenon, and in turn, to preserve the spirit of Zhang’s dedication to this subject.

Full access
Chunhui Lu
,
Jie Jiang
,
Ruidan Chen
,
Safi Ullah
,
Rong Yu
,
Fraser C. Lott
,
Simon F. B. Tett
, and
Buwen Dong
Open access
Rouke Li
,
Delei Li
,
Nergui Nanding
,
Xuan Wang
,
Xuewei Fan
,
Yang Chen
,
Fangxing Tian
,
Simon F. B. Tett
,
Buwen Dong
, and
Fraser C. Lott
Open access
Haosu Tang
,
Jun Wang
,
Yang Chen
,
Simon F. B. Tett
,
Ying Sun
,
Lijing Cheng
,
Sarah Sparrow
, and
Buwen Dong

Current human-induced warming has led to approximately a 30-fold increase in the occurrence probability of 2021 northwestern Pacific concurrent marine and terrestrial summer heat.

Open access
Robert A. Houze Jr.
,
Shuyi S. Chen
,
Wen-Chau Lee
,
Robert F. Rogers
,
James A. Moore
,
Gregory J. Stossmeister
,
Michael M. Bell
,
Jasmine Cetrone
,
Wei Zhao
, and
S. Rita Brodzik

The Hurricane Rainband and Intensity Change Experiment (RAINEX) used three P3 aircraft aided by high-resolution numerical modeling and satellite communications to investigate the 2005 Hurricanes Katrina, Ophelia, and Rita. The aim was to increase the understanding of tropical cyclone intensity change by interactions between a tropical cyclone's inner core and rainbands. All three aircraft had dual-Doppler radars, with the Electra Doppler Radar (ELDORA) on board the Naval Research Laboratory's P3 aircraft, providing particularly detailed Doppler radar data. Numerical model forecasts helped plan the aircraft missions, and innovative communications and data transfer in real time allowed the flights to be coordinated from a ground-based operations center. The P3 aircraft released approximately 600 dropsondes in locations targeted for optimal coordination with the Doppler radar data, as guided by the operations center. The storms were observed in all stages of development, from tropical depression to category 5 hurricane. The data from RAINEX are readily available through an online Field Catalog and RAINEX Data Archive. The RAINEX dataset is illustrated in this article by a preliminary analysis of Hurricane Rita, which was documented by multiaircraft flights on five days 1) while a tropical storm, 2) while rapidly intensifying to a category 5 hurricane, 3) during an eye-wall replacement, 4) when the hurricane became asymmetric upon encountering environmental shear, and 5) just prior to landfall.

Full access
R. M. Rasmussen
,
F. Chen
,
C.H. Liu
,
K. Ikeda
,
A. Prein
,
J. Kim
,
T. Schneider
,
A. Dai
,
D. Gochis
,
A. Dugger
,
Y. Zhang
,
A. Jaye
,
J. Dudhia
,
C. He
,
M. Harrold
,
L. Xue
,
S. Chen
,
A. Newman
,
E. Dougherty
,
R. Abolafia-Rosenzweig
,
N. D. Lybarger
,
R. Viger
,
D. Lesmes
,
K. Skalak
,
J. Brakebill
,
D. Cline
,
K. Dunne
,
K. Rasmussen
, and
G. Miguez-Macho

Abstract

A unique, high-resolution, hydroclimate reanalysis, 40-plus-year (October 1979–September 2021), 4 km (named as CONUS404), has been created using the Weather Research and Forecasting Model by dynamically downscaling of the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate dataset (ERA5) over the conterminous United States. The paper describes the approach for generating the dataset, provides an initial evaluation, including biases, and indicates how interested users can access the data. The motivation for creating this National Center for Atmospheric Research (NCAR)–U.S. Geological Survey (USGS) collaborative dataset is to provide research and end-user communities with a high-resolution, self-consistent, long-term, continental-scale hydroclimate dataset appropriate for forcing hydrological models and conducting hydroclimate scientific analyses over the conterminous United States. The data are archived and accessible on the USGS Black Pearl tape system and on the NCAR supercomputer Campaign storage system.

Open access
Baoqiang Xiang
,
Lucas Harris
,
Thomas L. Delworth
,
Bin Wang
,
Guosen Chen
,
Jan-Huey Chen
,
Spencer K. Clark
,
William F. Cooke
,
Kun Gao
,
J. Jacob Huff
,
Liwei Jia
,
Nathaniel C. Johnson
,
Sarah B. Kapnick
,
Feiyu Lu
,
Colleen McHugh
,
Yongqiang Sun
,
Mingjing Tong
,
Xiaosong Yang
,
Fanrong Zeng
,
Ming Zhao
,
Linjiong Zhou
, and
Xiaqiong Zhou

Abstract

A subseasonal-to-seasonal (S2S) prediction system was recently developed using the GFDL Seamless System for Prediction and Earth System Research (SPEAR) global coupled model. Based on 20-yr hindcast results (2000–19), the boreal wintertime (November–April) Madden–Julian oscillation (MJO) prediction skill is revealed to reach 30 days measured before the anomaly correlation coefficient of the real-time multivariate (RMM) index drops to 0.5. However, when the MJO is partitioned into four distinct propagation patterns, the prediction range extends to 38, 31, and 31 days for the fast-propagating, slow-propagating, and jumping MJO patterns, respectively, but falls to 23 days for the standing MJO. A further improvement of MJO prediction requires attention to the standing MJO given its large gap with its potential predictability (38 days). The slow-propagating MJO detours southward when traversing the Maritime Continent (MC), and confronts the MC prediction barrier in the model, while the fast-propagating MJO moves across the central MC without this prediction barrier. The MJO diversity is modulated by stratospheric quasi-biennial oscillation (QBO): the standing (slow-propagating) MJO coincides with significant westerly (easterly) phases of QBO, partially explaining the contrasting MJO prediction skill between these two QBO phases. The SPEAR model shows its capability, beyond the propagation, in predicting their initiation for different types of MJO along with discrete precursory convection anomalies. The SPEAR model skillfully predicts the observed distinct teleconnections over the North Pacific and North America related to the standing, jumping, and fast-propagating MJO, but not the slow-propagating MJO. These findings highlight the complexities and challenges of incorporating MJO prediction into the operational prediction of meteorological variables.

Full access
Chidong Zhang
,
Gregory R. Foltz
,
Andy M. Chiodi
,
Calvin W. Mordy
,
Catherine R. Edwards
,
Christian Meinig
,
Dongxiao Zhang
,
Edoardo Mazza
,
Edward D. Cokelet
,
Eugene F. Burger
,
Francis Bringas
,
Gustavo J. Goni
,
Hristina G. Hristova
,
Hyun-Sook Kim
,
Joaquin A. Trinanes
,
Jun A. Zhang
,
Kathleen E. Bailey
,
Kevin M. O’Brien
,
Maria Morales-Caez
,
Noah Lawrence-Slavas
,
Richard Jenkins
,
Shuyi S. Chen
, and
Xingchao Chen

Abstract

On 30 September 2021, a saildrone uncrewed surface vehicle (USV) was steered into category 4 Hurricane Sam, the most intense storm of the 2021 Atlantic hurricane season. It measured significant wave heights up to 14 m (maximum wave height = 27 m) and near-surface winds exceeding 55 m s−1. This was the first time in more than seven decades of hurricane observations that in real time a USV transmitted scientific data, images, and videos of the dynamic ocean surface near a hurricane’s eyewall. The saildrone was part of a five-saildrone deployment of the NOAA 2021 Atlantic Hurricane Observations Mission. These saildrones observed the atmospheric and oceanic near-surface conditions of five other tropical storms, of which two became hurricanes. Such observations inside tropical cyclones help to advance the understanding and prediction of hurricanes, with the ultimate goal of saving lives and protecting property. The 2021 deployment pioneered a new practice of coordinating measurements by saildrones, underwater gliders, and airborne dropsondes to make simultaneous and near-collocated observations of the air–sea interface, the ocean immediately below, and the atmosphere immediately above. This experimental deployment opened the door to a new era of using remotely piloted uncrewed systems to observe one of the most extreme phenomena on Earth in a way previously impossible. This article provides an overview of this saildrone hurricane observations mission, describes how the saildrones were coordinated with other observing platforms, presents preliminary scientific results from these observations to demonstrate their potential utility and motivate further data analysis, and offers a vision of future hurricane observations using combined uncrewed platforms.

Open access