SPRING 2020
Wednesdays at 3:00 pm, Seminar Room SLAB 103 (unless stated otherwise)
Jan 15: Dr. Pierre Sochala
BRGM (French Meteorological Survey), Orleans, France
Propagation of Uncertainty for the Prediction of Hurricane-Induced Storm Surges
Recording Available at COMPASS ON DEMAND
In this talk, we present a polynomial chaos-based framework to quantify the uncertainties in predicting hurricane-induced storm surges. Perturbation strategies are proposed to characterize poorly known time-dependent input parameters, such as tropical cyclone track and wind as well as space-dependent bottom stresses, using a handful of stochastic variables. The input uncertainties are then propagated through an ensemble calculation and a model surrogate is constructed to represent the changes in model output caused by changes in the model input. The statistical analysis is then performed using the model surrogate once its reliability has been established. The procedure is illustrated by simulating the flooding caused by Hurricane Gustav 2008 using the ADvanced CIRCulation model. The hurricane’s track and intensity are perturbed along with the bottom friction coefficients. A sensitivity analysis suggests that the track of the tropical cyclone is the dominant contributor to the peak water level forecast, while uncertainties in wind speed and in the bottom friction coefficient show minor contributions. Exceedance probability maps with different levels are also estimated to identify the most vulnerable areas.
Jan 22: NO SEMINAR
Jan 29 (Auditorium): Dr. Pavel Berloff
Imperial College London, UK
Some Novel Approaches for Parameterizing Mesoscale Eddies
Recording Available at COMPASS ON DEMAND
This talk focuses on some new approaches for parameterizing oceanic mesoscale eddy effects for use in non-eddy-resolving and eddy-permitting general circulation models. The context is provided in terms of discussing the existing ideas and problems with their realizations. A specific example of eddy-rich eastward jet extensions of western boundary currents and their adjacent recirculation zones is considered in the classical multi-layer quasigeostrophic model of the wind-driven midlatitude circulation. First, the key dynamical mechanism operating in the eddy-resolving model and maintaining the eastward jet is identified as the "eddy backscatter", which is based on persistent and positive time-lag correlations between the transient part of the nonlinear eddy forcing and the large-scale flow response. Second, this mechanism has to be ultimately parameterized, and discussing how this can be done is the main part of the talk. We will systematically (but not too technically) discuss four different, novel parameterization approaches, which are complimentary to the existing ones: (1) direct stochastic forcing (DSF); (2) implicit stochastic footprints (ISF); (3) data-driven eddy emulations (DEE); and (4) local eddy amplification (LEA). The DSF approach explicitly adds statistically constrained stochastic forcing to the coarse model. The ISF approach imposes statistically constrained stochastic forcing on an intermediate-complexity eddy-resolving model, obtains its nonlinear response in terms of the coarse-grained footprint, and then imposes local footprints on the coarse model. The DEE approach emulates eddies via multi-layer nonlinear regression, then feeds them to the deterministic eddy forcing operator coupled to the large-scale flow fields, and adds the resulting forcing to the coarse model. The LEA approach interactively identifies eddies and amplifies them locally and in a simple way – this is the simplest and also most practical approach for the present state of modelling. Relative strengths and weaknesses of these approaches, as well as some future developments will be also discussed.
Feb 05 (Auditorium): Shun-Nan Wu
Department of Atmospheric Sciences, RSMAS
(one-hour MPO student seminar)
The Role of Clouds in Tropical Cyclone Intensification
Recording Available at COMPASS ON DEMAND
This study examines the signature of tropical cyclone (TC) intensification in cloud ice, and investigates the effect of radiative heating from clouds on TC genesis and intensification using both satellite measurements and model simulations. Traditionally, latent heating is considered as the major energy source for TC intensification. Due to a lack of observational latent heat release, we used the amount of cloud ice as a proxy for latent heat release to examine its relationship with TC intensification, as cloud ice and latent heat release are produced simultaneously in the upward branch of transverse circulations. To do this, two satellite-based measurements, CloudSat and SPARE-ICE, were used here. It is found that intensifying TCs tend to have greater ice water content than weakening TCs throughout the entire TC, with the largest differences within 100 km of the TC center. The signature of this overall enhancement of ice water content in intensifying TCs occurs as early as 24 hours prior to intensity change. Interestingly, the horizontally extensive increase of ice water content in intensifying TCs largely exceeds the area where latent heating can effectively regulate TC intensity. Therefore, we speculated that such extensive increase in cloud ice may provide extra cloud radiative heating to strengthen TC intensity. There is a growing recognition that clouds may also play an important role in regulating the intensity of tropical convective systems through interactions with radiation. That is, clouds can alter the spatial distribution of radiative heating, and then subsequently change the distribution of clouds and the intensity of tropical convective systems. To examine the effect of cloud-radiative interactions on the development of TCs, we adopted NASA Cloud and the Earth's Radiant Energy System (CERES) measurements and idealized WRF simulations, performing a series of experiments. It is found that intensifying TCs often have a greater amount of cloud radiative heating than weakening TCs. Moreover, we demonstrated that tropical depressions that grow to the intensity of TCs in the future also have an overall larger cloud radiative heating than those don't. Since the correlation doesn't necessarily mean causality, we adopted idealized WRF simulations and performed a series of experiments in order to examine the effect of cloud-radiative interactions on TC genesis. The results show that cloud-radiative interactions play a crucial role in governing TC genesis under harsh environmental conditions. Even under a favorable environmental condition, tropical depressions tend to spend longer time to grow to TC intensity.
Feb 12: Dr. Levi Cowan
Invited Speaker of the Department of Atmospheric Sciences
Florida State University, Tallahassee
Atlantic Tropical Cyclone Interactions With Upper Tropospheric Flow:
Identification, Climatology, and Modulation of Tropical Cyclone Intensity
Recording Available at COMPASS ON DEMAND
Interactions of Atlantic tropical cyclones (TCs) with upper tropospheric flow are identified in 37 years of ERA-Interim reanalysis data and analyzed from multiple perspectives. Upper tropospheric troughs are identified in a more comprehensive way than past methodologies, targeting features on the dynamic tropopause to reduce exclusivity of feature selection and sensitivity to the background environment. To overcome some limitations of the trough perspective, a new approach to analyzing TC-environment interactions is developed through the identification of upper tropospheric jets near TCs. Jet axes are identified in 200-hPa wind fields within 3000 km of TCs using a robust, objective algorithm, forming a novel dataset that provides a unique way of characterizing and subsetting environmental flow. The climatology of these jets is explored through various means, including an objective clustering technique, which yielded seven statistically distinct groups of jets associated with recognizable flow patterns near TCs. The dynamical coupling between TCs and nearby jets is also quantified, with acceleration of jets downstream of the TC found to be a nearly ubiquitous feature, and entrance regions of jet streaks are observed to significantly enhance the strength of the TC secondary circulation. The influence of nearby upper tropospheric troughs and jets on TC intensity is also assessed through a variety of approaches. In order to minimize systematic sampling biases when quantifying this impact, a spatially varying climatology of TC intensification rate is developed using a secondorder, generalized least squares regression model, allowing TC intensity responses to external forcing to be evaluated as departures from their expected value. Both troughs and jets are found to be net negative influences on TC intensity, on average, primarily due to increasing vertical shear with proximity to the vortex. Differences between rapidly intensifying (RI) and rapidly weakening (RW) cases during TC-trough-jet interactions depend not only on shear, but on dynamic forcing imposed by baroclinic processes and eddy momentum fluxes that can counter the influence of shear. Intensifying cases are primarily associated with jets that approach the poleward side of the TC and possess jet streaks that amplify over time, increasing dynamic forcing for ascent near the TC core while maintaining enough distance to prevent shear from overwhelming those effects. This study expands the set of tools for analyzing TC interactions with upper tropospheric flow by improving trough identification and introducing a new perspective through the use of jets. Jets afford greater specificity in describing environmental flow, and allow unique methods of quantifying its impact on TCs. Close links are found between jet proximity and vertical shear, as well as jet acceleration and dynamically-forced ascent, both relationships that have been physically understood, but until now unidentified in bulk observational datasets. Some measures of jet entrance region orientation are found to correlate with the relative magnitude of shear and baroclinic forcing, exposing the subtlety in how flow geometries differ between intensifying and weakening TC cases. Prior research has tended to evaluate upper tropospheric influences on TCs individually or relied on case studies to elucidate their collective impact on a single storm. This body of work seeks to illuminate relationships between TCs and upper tropospheric flow that are robust across large samples of TCs and storm environments, utilizing novel approaches such as the jet perspective to extract previously unquantified information.
Feb 19: Dr. Leif Denby
School of Earth and Environment, University of Leeds, UK
Discovering the Importance of Mesoscale Cloud Organization
Through Unsupervised Classification
Recording Available at COMPASS ON DEMAND
The representation of shallow trade wind convective clouds in climate models dominates the uncertainty in climate sensitivity estimates. In particular the radiative impact of cloud spatial organization is poorly understood. This work presents the first unsupervised neural network model which autonomously discovers cloud organization regimes in satellite images. Trained on 10,000 GOES-16 satellite images (tropical Atlantic and boreal winter) the regimes found are shown to exist in a hierarchy of organizational scales, with sub-clusters having distinct radiative properties. The model requires no time-consuming and subjective hand-labeled data based on predefined structures allowing for objective study of very large data sets. The model enables the study of environmental conditions in different organizational regimes and in transitions between regimes and objective comparisons of model behavior with observations through cloud structures emerging in both. These abilities enable the discovery of previously unknown physical relationships in cloud processes, enabling better representation of clouds in weather and climate simulations.
Feb 26: Dr. David B. Parsons
School of Meteorology, University of Oklahoma, Norman
Does the Rain in the Night Stay Mainly on the Plains?
and
Are These Storms Gregarious?
Recording Available at COMPASS ON DEMAND
The interaction between convective systems and their environment has long been a topic of interest in the atmospheric sciences. For example, numerous studies have suggested that convective systems can generate gravity waves that cause upward displacements at lower levels in a mesoscale region surrounding the heating. This ascent creates an environment more favorable for new convection. This study investigates interactions between nocturnal convective systems and the continental environment over the Great Plains. This work suggests that wave responses often occur with these nocturnal storms. The complex characteristics of the Great Plains environment with a nocturnal low-level jet and sloped terrain also means that wave ascent can be relatively more efficient in the initiation and maintenance of deep convection. This study also suggests that some continental convection systems can become coupled to Rossby wave dynamics and the inability of global models to represent this coupling can lead to downstream forecast failures. Deep learning techniques have also provided us with some insight into the characteristics of the flow regimes associated with these forecast failures. Placing these results within the framework of predictability studies dating back to Lorenz’s work, we propose that a butterfly hoping to impact the large-scale needs to consider where and for how long they should the flap their wings.
Mar 04 (Auditorium): Dr. Everette Joseph
SEEDS and RSMAS / DEIC 2020 Distinguished Lecturer
National Center for Atmospheric Research, Boulder, Colorado
Update on the NY State Mesonet: Retrieval of Particulate Matter Profile
and Boundary Layer From Network Profilers
The New York State Mesonet (NYSM) is a comprehensive network of environmental monitoring stations deployed statewide that was completed in 2018. It includes 126 surface stations at an average spacing of 27 km consisting of standard meteorological measurements in addition to automated measurement of snow depth, soil moisture and temperature; 17 sites with observations of the vertical profiles of wind, moisture and temperature from active and passive sensors; and additional sites with surface energy budget and snow water equivalent measurements. The primary goal of the NYSM is to provide high quality weather data at high spatial and temporal scales to improve atmospheric monitoring and prediction, especially for extreme weather events. An overview of the system will be given focusing on data quality and the development of various products for atmospheric monitoring for early warning. Specific attention will be given to the profiler network and preliminary research to develop algorithms to derive PM profile and boundary layer structure across this network.
Dr. 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.
Mar 11 (Auditorium): Wei Zhang
Department of Atmospheric Sciences, RSMAS
(one-hour MPO student seminar)
Understanding Decadal Climate Predictability in the Global Ocean
Recording Available at COMPASS ON DEMAND
There is a continuously growing demand for the development of decadal climate predictions. Making robust and skillful decadal predictions has clear societal benefits in terms of supporting decision-making processes in agriculture, energy and water management. However, forecasting the climate over decades remains a challenge. This study is focused on addressing three main challenges in decadal climate predictability and prediction, namely: (i) lack of understanding of sources and mechanisms of decadal predictability, (ii) existence of the signal-to-noise paradox (low signal-to-noise ratio in model predictions), and (iii) finite resolution of ocean models. The results suggest that currently available coupled models (e.g., CMIP5) generally underestimate decadal climate predictability, which is closely related to the existence of the signal-to-noise paradox. A suite of CCSM4 model experiments has been performed and we argue that decadal SST predictability can be significantly influenced by the internal atmospheric noise, ocean-atmosphere interactions, and ocean model resolutions. Specifically, the impact of the internal atmospheric noise on decadal predictability is not simply a linear problem but more complex and largely dependent on locations. With increased ocean model resolution (e.g, eddy-resolving ocean model), the signal-to-noise issue can be at least partly eliminated, which will provide improved estimates of decadal climate predictability, especially in eddy-rich regions. Essentially, this research attempts to improve our understanding of decadal climate predictability and may potentially inform the development of the near-term climate prediction systems.
Mar 18: NO SEMINAR
Mar 25: NO SEMINAR
Apr 01: NO SEMINAR
Apr 08: NO SEMINAR
Apr 15: NO SEMINAR
Apr 22: NO SEMINAR
Apr 29: NO SEMINAR
