Presented on April 10, 2024, by

Jia-Yuh Yu, Professor
Department of Atmospheric Sciences
National Central University
Taiwan

ABSTRACT

Using the fifth generation European Center for Medium-range Weather Forecasts (ERA5) reanalysis data, we present a detailed examination of the climatological features of convectively coupled Kelvin waves (CCKWs) over the Indian and Pacific basins. The composited horizontal structure of Indian CCKWs resembles the theoretical Kelvin waves, with a maximum wave response at the equator. In contrast, the Pacific counterpart exhibits a very different pattern, characterized by a significant northward shift of the convective center, along with enhanced meridional winds and a relatively stronger wave response. The moist static energy (MSE) budget analysis is conducted to elucidate the physical factors that control the energetics of CCKWs. Despite the marked contrast in horizontal structure between Pacific and Indian CCKWs, the energy cycle and the physical factors that maintain this cycle are rather similar. During the recharge period (days -2 and -1), the column process (including vertical MSE advection, apparent heat source and moisture sink) functions to destabilize the atmosphere by importing the MSE; while the horizontal MSE advection tends to destabilize the atmosphere on day -2 but starts to stabilize the atmosphere earlier on day -1. During the discharge and transition period (from days 0 to +2), the column process functions to stabilize the atmosphere by exporting the MSE; while the horizontal MSE advection inclines to stabilize the atmosphere on days 0 and +1 but again starts to destabilize the atmosphere earlier on day +2. The leading of horizontal MSE advection to the recharge-discharge cycle clearly points out the importance of the former in driving the eastward propagation of CCKWs. Both the horizontal MSE advection and column process are vital in maintaining the energy cycle of CCKWs, as they often take turns leading the role in recharging and discharging the atmosphere.

BIO
My research interests focus on climate variability and oscillation involving complex interactions between cumulus convection, large-scale circulation and radiation. Specific topics include (1) developing a physically-based, convective quasi-equilibrium (CQE) theory for climate variability and oscillation as well as climate change studies; (2) exploring the dynamics and energetics of cloud-radiation-circulation interactions in tropical convectively-coupled waves and oscillation (e.g., Kelvin wave, Rossby wave, Madden-Julian Oscillation and El Niño/Southern Oscillation) in both the present and future warming climate states; (3) projecting the potential impacts of global warming on TC activity (including genesis frequency, intensity and track) over the Western North Pacific and South China Sea.

Presented on April 3, 2024, by

Dr. Richard Rotunno
NSF NCAR Senior Scientist

ABSTRACT

This study considers a two-layer fluid with constant density in each layer connected by a layer of continuously varying density for flows past topography in which hydraulic jumps with lee vortices are expected based on shallow-water theory. Numerical integrations of the Navier–Stokes equations at a Reynolds number high enough for a direct numerical simulation of turbulent flow allow an examination of the internal mechanics of the turbulent leeside hydraulic jump and how this mechanics is related to lee vortices. Analysis of the statistically steady state shows that the original source of lee-vortex vertical vorticity is through the leeside descent of baroclinically produced spanwise vorticity associated with the hydraulic jump. This spanwise vorticity is tilted to the vertical at the spanwise extremities of the leeside hydraulic jump. Turbulent energy dissipation in flow through the hydraulic jump allows this leeside vertical vorticity to diffuse and extend downstream. The present simulations also suggest a geometrical interpretation of lee-vortex potential-vorticity creation, a concept central to interpretations of lee vortices based on the shallow-water equations.

BIO

Dr. Richard Rotunno is a Senior Scientist in the Mesoscale and Microscale Meteorology Laboratory of the National Center for Atmospheric Research in Boulder, Colorado. He received a Ph. D. in 1976 in Geophysical Fluid Dynamics from Princeton University. Over the past 48 years he has contributed to a wide range of topics in mesoscale dynamical meteorology including, tornadoes, rotating thunderstorms, squall lines, hurricanes, polar lows, midlatitude cyclones, fronts, mountain-valley and sea-breeze circulations and coastally trapped disturbances in addition to a variety of related problems such as the dynamics of density currents, vortex stability, convection and atmospheric predictability. Through a combination of theory and numerical modeling, his work is directed at the understanding needed to make progress in the forecasting of mesoscale weather phenomena. He is a recipient of the American Meteorological Society’s Banner I. Miller Award (1991 with K. Emanuel and 2010 with G. Bryan), Severe Local Storms Research Lifetime Achievement Award (2018), Jule G. Charney Award (2004) and Carl-Gustaf Rossby
Research Medal (2017). In 2023 he was elected to the National Academy of Science of the United States.
Dr. Richard Rotunno has been an active participant on national and international committees and in summer schools and colloquia concerning the science of weather and weather forecasting. Recent scientific activities have focused on tropical cyclones, orographic precipitation and atmospheric predictability.

Presented on March 27, 2024, by

Dr. Everette Joseph, Director
National Center for Atmospheric Research

ABSTRACT

The National Science Foundation National Center for Atmospheric Research (NSF NCAR) was established by the NSF in 1960 to provide the university community with world-class facilities and capabilities that were beyond the reach of any individual institution. More than a half-century later, NSF NCAR is still delivering on that mission. NSF NCAR develops and applies state-of-the-art resources, including supercomputers, research aircraft, sophisticated computer models, and extensive data sets to empower the university community to solve complex scientific problems related to Earth systems science. Our staff of preeminent researchers and engineers work with a wide range of collaborators to take on the current global-scale environmental challenges that are unprecedented in modern history, including weather extremes, wildfires, air pollution, and solar storms. This work is focused on advancing fundamental understanding of the Earth as a coupled system — the atmosphere, oceans, land, cryosphere, geospace, and the Sun — and how they interact and are influenced by human systems. Actionable solutions for societal challenges is a result of this work. NCAR also provides rich education and outreach opportunities, from fellowships for early career scientists to free public lectures to scientific workshops. Specifically, NSF NCAR hosts faculty and student visitors from across the US and the international community to collaborate with our scientists. Dr. Joseph in his seminar will provide an overview of NCAR, review some of the latest research and how NSF NCAR is positioning itself for success in the future, and will provide his vision on where NSF NCAR is headed. He will also talk about ways students and faculty can collaborate with NSF NCAR to advance their research.

BIO

Everette Joseph joined NCAR as director in 2019 from the University at Albany, State University of New York, where he was director of the Atmospheric Sciences Research Center.

While at Albany, Joseph co-led the $30.5 million New York State Mesonet for advanced weather detection and the New York State Center of Excellence for the Weather Enterprise. He has served as principal or co-principal investigator on over $90 million in research grants from NSF, the National Oceanic and Atmospheric Administration, NASA, the Army High Performance Computing Research Center, and other agencies. He joined the UCAR Board of Trustees in 2011, where his colleagues elected him vice chair in 2015 and chair in 2017.

Joseph has been a member of the Board on Atmospheric Sciences and Climate of the National Academy of Sciences, Engineering and Medicine since 2014. Other roles have included membership on the Steering Committee of the NASEM Decadal Survey for Earth Science and Applications from space; the NOAA Science Advisory Board; and the American Meteorological Society Commission on the Weather, Water and Climate Enterprise. He also is principal investigator for the NSF-sponsored US-Taiwan Program for International Research and Education and co-PI on the NOAA Aerosol and Ocean Science Expeditions, a series of trans-Atlantic intensive observation campaigns to gain an understanding of the impacts of long-range transport of aerosols over the tropical ocean.

Prior to his position at the University at Albany, Joseph was director of Howard University’s Program in Atmospheric Sciences, where he dedicated himself to teaching, mentoring, and inspiring the next generation. He also served as director of the Beltsville Center for Climate System Observation, a NASA University Research Center. In that position, he brought together colleagues at Howard, NASA, NOAA, Penn State, University of Maryland Baltimore County, and other institutions to develop an interdisciplinary, multi-institutional, multi-agency center studying key atmospheric processes with particular relevance to predictive capability in weather, climate, and air quality.

Joseph earned his Ph.D. in physics with an emphasis on atmospheric science from the University at Albany.

Presented on March 20, 2024, by

Dr. Francis Fujioka
Research Meteorologist, Retired
USDA Forest Service, Pacific Southwest Research Station

ABSTRACT

The National Weather Service fire weather forecast for West Maui on August 8, 2023 predicted dry and windy conditions well before they materialized and drove the rapidly advancing fire that devastated Lahaina. In retrospect, one might argue that the weather information by itself conveys only partially the wildfire threat assessment that is needed for fire protection planning. This seminar describes a fire spread model developed for federal wildland fire management more than 50 years ago, and currently used nationwide for fire behavior and fire danger prediction. It will cover pc-based simulations of the model for the Lahaina fire, using weather data from 1) the NWS predictions for that day, and 2) gridded weather routinely produced by Dr. Yi-Leng Chen of the Atmospheric Sciences Department. The fire model has been used in research and development projects in Hawai’i before the work was terminated for lack of funding in 2012. Prospects for an operational version of a fire threat assessment system for Hawai’i will be discussed.

Presented on March 13, 2024, by

Dr. Chieh-Ying Ke
Department of Atmospheric Sciences
National Central University
Taoyuan City, Taiwan

ABSTRACT

A Mei-Yu front with an accumulated rainfall of over 550 mm in 8 hours stagnated in northern Taiwan in the early morning of June 1-2, 2017. This study investigates the primary characteristics of this extreme rainfall event using both observational data and numerical model simulations. A modified k-means clustering method is applied to classify 128-member ensemble simulations into five groups by rainfall map. The dynamic features on both the meso-α and meso-β scales are discussed to diagnose the key factors responsible for the front stagnation and heavy rainfall in northern Taiwan while also understanding the forecast uncertainty. The low-level jet plays a significant role in the extreme rainfall process and highlights the importance of the connection between short-wave troughs and the rainband spatial distributions. Through analysis, two types can be further distinguished within five clusters, providing a comprehensive explanation of the interaction between the mid-to-low-level trough and the front in northern Taiwan. In summary, this clustering analysis not only aids in analyzing the dynamic structure of the Mei-Yu front but also assists in evaluating model simulations’ performance, offering an overview of Mei-Yu processes at different scales.

BIO

Dr. Ke is a Postdoctoral Research Fellow at the National Central University, Taiwan. Her current project is in weather radar meteorology, including observation, dynamic and thermodynamic analysis, retrieval of wind field, data assimilation, ensemble simulation, and machine learning.

Presented on March 6, 2024, by

Prof. Junshi Ito
Department of Geophysics
Graduate School of Science
Tohoku University
Sendai, Miyagi, Japan

ABSTRACT

A quasi-stationary back-building convective system is reproduced using a regional weather prediction model initialized with a single representative sounding in which the land–sea distribution around the observed convective system is crudely simplified. The simulated convective system and heavy precipitation are reasonably similar to observations. Horizontal resolution finer than 1 km is found to be necessary for reproducing the convective system. The area of heavy precipitation tends to shift downstream with finer horizontal resolution. The surface temperature contrasts at the northern and southern coastlines cause sea breezes and a stationary convergence line between them continuously triggers cumulus clouds. The horizontal convergence near the surface is further enhanced by preceding cumulus clouds that cause the latent heating aloft and generate a mesoscale surface pressure depression. Vertical shear of the environmental wind is also found to be important for organizing the convective system but veering of its wind direction and a cold pool are not essential. A succeeding study for sub-grid modeling using this framework will also be presented.

Presented on February 21, 2024, by

Shu-Chih Yang, Distinguished Professor
Department Chair of Atmospheric Sciences
Director of GPS Science and Application Research Center
National Central University, Jhongli, Taiwan

ABSTRACT

A multi-scale radar ensemble data assimilation system has been developed by applying the successive covariance localization (SCL) to the WRF-Radar LETKF assimilation system (WLRAS). The multi-scale WLRAS is applied to study a heavy rainfall event that occurred on 6-7 June 2022 during the IOP3 in the Taiwan-Area Heavy rain Observation and Prediction Experiment (TAHOPE)/Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP) field campaign. Two experiments are conducted and they differ only in using the convective-scale (RDA) or multi-scale corrections (MRDA) in the assimilation of radar radial velocity. The objective of this study is twofold. One is to evaluate the benefit of using multi-scale WLRAS by comparing RDA and MRDA. The other is to understand the mechanisms of the convection development at the western coast of Taiwan as the mei-yu front hovers in northern Taiwan.

Compared to RDA, theMRDA experiment exhibits large-area wind corrections, which help reshape and relocate a low-level meso-vortex offshore of western central Taiwan and enhance the frontal intensity offshore of northwestern Taiwan. Consequently, the MRDA improves the heavy very short-term (6h) rainfall prediction over the coast of western Taiwan and better represents the elongated rainband in northern Taiwan during the 3 to 6-h forecast hours. Sensitivity experiments demonstrate the importance of assimilating the radial wind of Chigu and S-Pol radars in establishing the low-level meso-vortex and convergence zones. Although a significant impact on rainfall prediction can be obtained from updating the moisture variable with the SCL method, the moisture correction at far distances may be less reliable.

Presented on February 14, 2024, by

Yannik Glasser
PhD Candidate, Information & Computer Science
Justin Stopa, Ph.D.
Associate Professor Department of Ocean & Resources Engineering

Abstract:

Synthetic aperture radars (SAR) aboard space-borne satellites measure sub-mesoscale oceanic and atmospheric phenomena at a global scale. This work uses the European Space Agency (ESA) Sentinel-1 (S-1) SAR mission’s sea surface roughness to study sub-mesoscale phenomena such as turbulence in the atmosphere, rain, and slicks. To utilize the large S-1 archive (>1Pb), we develop automatic image detection methods using deep learning. We developed a foundational contrastive model trained solely on millions of S-1 images. This model, called WVNET, exceeds the performance of other models such as ImageNet in a variety of tasks including regression and classification. With the improved model performance, we have more confidence in estimating the climatology of the sea surface roughness morphology. We find the atmosphere dominates the SAR imagery. The time-space mapping of WVNet’s predictions is relevant for the study of air-sea interactions.

Presented on January 24, 2024, by

Dr. Tom Robinson, PhD
National Oceanic and Atmospheric Administration
Oak Ridge National Laboratory
Geophysical Fluid Dynamics Laboratory

ABSTRACT

The Atmosphere Model 4, Coupled Model 4, and Earth System Model 4 developed by the Geophysical Fluid Dynamics Laboratory (GFDL) as a part of the Climate Model Intercomparison Project 6 (CMIP6) were developed, tuned, and run on the supercomputer Gaea located at Oak Ridge National Laboratory. The models run efficiently on this computer, but are untested and unsupported on any other systems. With increasing desire for open source and open science in the climate community, the GFDL has begun developing portable containers to share and distribute the next-generation models. The model environments that are developed can run on any x86 system. Leveraging the knowledge of the Extreme Scale Scientific Software Stack (E4S), these containers are built using spack caches for pulling model dependencies. The containers can run at the same speed as a model built on the host system. Model containers are going to make the next generation GFDL models more accessible to everyone.

BIO

Tom Robinson is a physical scientist in the modeling systems division at The Geophysical Fluid Dynamics Lab located in Princeton, NJ. Tom has a Bachelor’s Degree in chemistry from the College of New Jersey, a Master’s Degree in Environmental Studies from the University of Massachusetts Lowell, and a PhD in meteorology from the University of Hawaii.

Presented on November 29, 2023, by

Dale Durran, Professor
Atmospheric Sciences
University of Washington

ABSTRACT

We compare the performance of a global deep-learning weather-prediction (DLWP) model with reanalysis data and forecasts from the European Center for Medium Range Weather Forecasts (ECMWF).

The model is trained using ECMWF ReAnalysis 5 (ERA5) data with convolutional neural networks (CNNs) on a HEALPix mesh using a loss function that minimizes forecast error over a single 24-hour period. The model predicts seven 2D shells of atmospheric data on an equal-area pixelization at resolutions of roughly 200 km.

Notably, our model can be iterated forward indefinitely to produce forecasts at 3-hour temporal resolution for any lead time. We present case studies showing the extent to which the model is able to reproduce the dynamical evolution of atmospheric systems and its ability to learn “model physics” to forecast two-meter temperature and precipitation.

Extensions to a full earth-system model are presented using similar deep learning architecture to forecast sea surface temperatures. The SST model can be stably stepped forward for a year and shows skill in forecasting El
Niños.

Short Bio

Dale Durran is a professor and past Chair of Department of Atmospheric Sciences at the University of Washington. His research foci include atmospheric predictability, mountain meteorology, and numerical weather prediction. Most recently he has been exploring how deep learning can change our current paradigm for numerical weather prediction, sub-seasonal, and seasonal forecasting. He is a fellow of the American Meteorological Society (AMS) and a recipient of the AMS’s Jule Charney Award. He has written over 125 scientific publications, the graduate-level textbook “Numerical methods for Fluid Dynamics with Applications to Geophysics” and “perspective” articles about climate change for the Washington Post. His sculpture was included in the first ArtScience Virtual Exhibit exhibit of American Geophysical Union’s 2022 Fall Meeting.