SHORT DESCRIPTION OF INTERESTS:
Our group studies extreme weather and climate events, their impacts, and changes in response to climate variations. Specific topics include tropical cyclones, winter storms, severe convection, and midlatitude cyclones.
- Storm-Scale Dynamical Changes of Extratropical Transition Events in Present-Day and Future High-Resolution Global Simulations , JOURNAL OF CLIMATE (2021)
- The Response of Extratropical Transition of Tropical Cyclones to Climate Change: Quasi-Idealized Numerical Experiments , JOURNAL OF CLIMATE (2021)
- The Sensitivity of Persistent Geopotential Anomalies to the Climate of a Moist Channel Model , JOURNAL OF CLIMATE (2021)
- A New Variable-Threshold Persistent Anomaly Index: Northern Hemisphere Anomalies in the ERA-Interim Reanalysis , MONTHLY WEATHER REVIEW (2020)
- An Evaluation of Snowband Predictability in the High-Resolution Rapid Refresh , WEATHER AND FORECASTING (2019)
- Climatological Changes in the Extratropical Transition of Tropical Cyclones in High-Resolution Global Simulations , JOURNAL OF CLIMATE (2019)
- Evaluation of a Unique Approach to High-Resolution Climate Modelling using the Model for Prediction Across Scales (MPAS) version 5.1 , Geoscientific Model Development Discussions (2019)
- Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales - Atmosphere (MPAS-A) version 5.1 , GEOSCIENTIFIC MODEL DEVELOPMENT (2019)
- Extratropical Transition of Hurricane Irene (2011) in a Changing Climate , JOURNAL OF CLIMATE (2019)
- Hydrometeor Lofting and Mesoscale Snowbands , MONTHLY WEATHER REVIEW (2019)
Persistent anomalies in the atmospheric circulation are unusual states of the atmospheric flow and conditions that remain approximately fixed over periods longer than a few days. Such states disrupt the daily march of weather in the extratropics. Many impacts of weather on human and natural systems are cumulative: the desiccation of soils and vegetation in a drought, the saturation of the ground during an extended period of rain, and the toll taken on people and societal infrastructure by prolonged heat or cold. Thus, persistent anomalies produce significant human impacts. Understanding and ultimately projecting how the frequency, distribution, and intensity of persistent anomalies will change with changes in global climate is necessary for projecting the impacts of climate change on nature and society. Interactions with extratropical cyclones are critical for initiating and sustaining persistent anomalies. The work proposed here focuses on these interactions and builds on the PIsâ€™ prior research exploring the changes in cyclones with climate. It was found that the increases with global warming in specific humidity leads to increased release of latent heat in storms, with consequent effects on storm structure and intensity. The representation of these effects was shown to exhibit strong sensitivity to model resolution. The studies proposed here are motivated by hypotheses that address the importance of cyclones, especially strong cyclones, for persistent anomalies, through their initiation and maintenance and through their conditioning of the large scale circulation on which persistent anomalies occur. Simulations will include ensemble studies of individual persistent anomaly events and the climatology of persistent anomalies in multi-year experiments, under present-day and future climate conditions. It is anticipated that model configurations (resolutions and choices of parameterizations) that produce better hindcasts of individual events will yield better climatologies of persistent anomalies under present-day conditions. These configurations can then be applied to future events and climatologies, by imposing global warming conditions. Results will be analyzed using potential vorticity and Rossby wave-breaking diagnostics and cyclone tracking. Key precursors to persistent anomalies in the case studies will be determined using model â€œsurgeryâ€, in which dynamical features can be deleted from the initial conditions. A single-layer model will be used to obtain dynamical understanding of the importance of changes in cyclones and the background flow in producing changes in persistent anomalies.
The frequency and intensity of both floods and droughts are expected to increase in response to climate change; however, significant uncertainties remain regarding regional changes, especially for extreme rainfall. In particular, North Carolinaâ€™s geographic position makes it vulnerable to several natural hazards that pose significant flooding risks, including hurricanes, severe thunderstorms, and large winter storms. The most obvious problems within NC in recent years are the pluvial and fluvial flooding from notable hurricanes which paralyzed the eastern NC highway system for days to weeks. The heavy rainfall associated with Hurricanes Floyd (1999), Matthew (2016), Florence (2018), and Dorian (2019) generated record-breaking fluvial flooding along key economic corridors including I-95, I-40, US-70, NC-12, and US-64, and created a chain of transportation infrastructure problems that affected emergency response operations and the transportation of goods. In particular, I-95 facilitates 40 percent of the Nationâ€™s GDP while US-70 and I-40 are key routes for supporting the military, agriculture and the economy in eastern NC. Though hurricanes receive a lot of attention in resilient design, as they should, transportation engineers face additional challenges, including possible changes to rainfall intensity from localized thunderstorms and even drought. NC officials, recognizing the risks posed by a changing climate, developed Executive Order 80 (EO80) to help protect the people, natural environment, and economy of North Carolina. NC DOT is likewise working to implement solutions to become more resilient to weather extremes in a changing climate. This objective of this study is to improve confidence in climate change projections by quantifying future precipitation extremes within NC for resilient design (e.g., precipitation intensity, duration, frequency curves). This project will incorporate guidance developed for the National Cooperative Highway Transportation Research Board, NCHRP 15-61, with additional methods and numerical model experiments to improve confidence in future precipitation extremes, and to inform design concepts for potential future events.
Severe storms in the Southeastern U.S. are associated with higher fatality rates and lower warning skill scores than those in the Plains. Many such events occur in environments characterized by large environmental vertical wind shear (â€œhigh shearâ€) but weak instability (â€œlow CAPEâ€). These high-shear low-CAPE (â€œHSLCâ€) conditions are associated with both low predictability and high tornado warning false alarm rates. Our regional NWS collaborators have identified these issues as among the most pressing concerns for their WFOs. The goal of this proposal is to address several remaining gaps in our understanding of HSLC severe weather predictability and facilitate an effective transition of the results into operations. The NCSU research team is particularly well prepared to undertake work on this problem, having conducted a number of CSTAR studies specifically targeting HSLC severe weather, and having a long-established relationship with many regional NWS WFOs.
Mesoscale snow bands have been the subject of extensive research over the past few decades, owing in large part to their ability to impart significant societal impacts. Previously, we developed an automated snowband detection algorithm, and applied it to produce an objective snow band climatology and to evaluate band predictability in the HRRR model. We also tested object-oriented band verification strategies. An additional component of the project explored two novel model diagnostics that show promise in the prediction of heavy snowfall: the vertical snow flux, and the depositional snow growth. Here, we extend these previous efforts into the realm of high-resolution ensemble prediction, with emphasis on ensemble verification and predictability, and on further exploration of model output diagnostics. Now that weâ€™ve developed and tested automated detection methods for mesoscale snow bands, we are able to run the detection algorithm on model forecasts, and for the case of convection-allowing ensembles, we can use the algorithm to generate probabilistic snow band predictions. We propose novel visualization strategies for band forecasts, including paintball plots, glyphs, probabilistic heat maps, and ensemble surface slicing; we will draw on visualization and science communication expertise at NC State in other departments to optimize these displays. User ability to interpret such graphics is equally important to the development of visuals. In this regard, we propose to take advantage of the recent addition of science-communication expertise at NC State. Modern numerical weather prediction models often include sophisticated cloud and precipitation microphysical parameterizations (MP). Under prior support, we recognized that some crucial microphysical information that is computed with high accuracy in the Thompson MP is not written as output. We modified a recent release of the Weather Research and Forecasting model, configured similarly to the HRRR operational model, to output the vertical snow flux and also the depositional and total snow growth. This exercise proved to be revealing: These metrics show distinct signatures within and upwind of heavy snowfall, with lofting of snow being ubiquitous upwind of mesoscale snow bands. Furthermore, forecasters often utilize visualization software such as BUFKIT to subjectively evaluate the presence of depositional snow growth. We propose that it would be more reliable to output this quantity directly from the HRRR model, and visualize it as a 2- or 3-dimensional field. In an ensemble sense, this could be combined with the aforementioned methods to provide operational forecasters with a much more complete picture of the microphysical structure of winter storms. During previous collaborative research, we have established collaborations at the Weather Prediction Center (WPC), the Environmental Modeling Center (EMC), and several NWS Forecast Offices. We have participated in the WPC Winter Experiment in the past, and have been invited to participate again this winter (Feb 2019). Such participation would provide an ideal opportunity to implement and test our methods in an operational setting. Graduate student Jacob Radford, who completed his MS thesis under prior support on this topic, will continue as a PhD student; Jacob is highly capable with various computational platforms, and his expertise will allow us to directly implement any of the proposed methods found to be of operational utility.
The purpose of this work is to quantify and elucidate the role of frontal and diabatic processes and mesoscale dynamics in atmospheric rivers (ARs). In addition to conceptual understanding, the proposed work would provide valuable outcomes related to real-time prediction, observational measurements, and model resolution requirements for ARs. The latter holds important implications for climate change studies of ARs.
The problem of tropical cyclones (TCs) and climate change has been the focus of intensive research in recent years, yet important knowledge gaps remain. Aspects of the problem that have received less attention include changes in the intensity and frequency of recurving tropical cyclones, and the question of how climate change will affect the intensity and frequency of systems undergoing extratropical transition (ET). Previous research identified the mitigating effect that a tropical upper-tropospheric warming maximum would have on future TC intensity. However, this warming maximum is strongest in the tropics and sub-tropics; TCs moving to higher latitudes would move into an environment that features less warming aloft. Thus, one hypothesis is that robust recurving TCs will show a greater intensity increase with warming than would TCs that remain in the tropics. Warming effects on TCs that undergo extratropical transition are challenging to ascertain owing to competing physical processes. If the hypothesis that recurving TCs will exhibit additional relative strengthening with warming is correct, a second hypothesis is that an increased fraction of TCs will undergo ET. Further, more intense precursor TCs could lead to stronger ET events. On the other hand, reduced TC frequency with warming would work to lower ET frequency. Changes in TC occurrence during early- or late-season months, and in geographical regions poleward of the traditional TC development regions are related to the above hypotheses, and would be examined using the same suite of numerical model simulations needed to test the hypotheses on recurving and ET. High-resolution model simulations of the North Atlantic and North Pacific basins must include the tropics, sub-tropics, and adjacent midlatitude regions in order to address the proposed questions. The Weather Research and Forecasting (WRF) model, in regional and global configurations, will be used in conjunction with the Pseudo-Global Warming approach to test the above hypotheses. The intellectual merit of this work is that it would address gaps in current understanding of (i) how climate change would influence the intensity and frequency of recurving and extratropically transitioning tropical cyclones, and (ii) geographical and seasonal changes in tropical cyclone activity with climate change. Broader impacts of the proposed project are that these weather systems feature heightened potential for societal impacts, and also in mentoring graduate and undergraduate researchers, improved understanding of climate change and its consequences, and testing the WRF model in climate applications. The proposed project is potentially transformative in addressing questions related to aspects of climate change that have not received sufficient research attention, yet which old important implications for climate change impact on society.
Banded precipitation in winter storms is challenging to predict, yet results in major societal impacts. The environmental factors associated with mesoscale precipitation bands have been identified in several previous studies, such as intense mid-level frontogenesis in the presence of small moist symmetric stability. A recent study of the predictability of banded snowfall using an ensemble forecast system by Novak and Colle (2012) demonstrates the challenges of numerical prediction for both the timing and location of the bands, even at lead times of less than 24 h. Further, large case-to-case variability in the predictability was observed between the 3 cases they examined. Here, we propose that an additional physical process is at work in mesoscale bands: hydrometeor lofting. Numerous observational and numerical studies of winter storms document upward vertical velocities exceeding 1 m s-1, which is approximately the fall velocity of snow. For frontogenetically forced bands of slantwise ascent exceeding this value, snow is lofted, and strong hydrometeor convergence is hypothesized to occur at the downstream edge of the zone of ascent. This mechanism is compatible with the aforementioned environmental factors of strong frontogenesis and weak symmetric stability, which give rise to strong ascent. However, it also suggests a sharp cut-off threshold, below which banding would not occur or would be greatly reduced. The sharpness of this threshold would depend on the hydrometeor fall velocity distribution among other factors. Representation of this lofting process in numerical models demands a high-resolution convection-allowing model (CAM) configuration. If this mechanism serves to create strongly inhomogeneous snowfall distributions, proper representation in CAMs must be explored in operational forecasting. Note that the Novak and Colle (2012) predictability study utilized an ensemble with 12-km grid spacing, and parameterized convection. Additionally, if the lofting mechanism is important, we further hypothesize considerable sensitivity to the model microphysics scheme, and in particular, the snow crystal size distribution and fall velocity parameterization. The lofting mechanism also suggests a readily accessible set of operational diagnostic plots, such as upward snow mass flux, or threshold plots of vertical motion in regions of active crystal growth. Diagnostics of this type would allow forecasters to quickly assess the potential for banding through interrogation of high-resolution CAM output, such as from the High-Resolution Rapid Refresh (HRRR) model. Our specific objectives are as follows: (i) Test the hypothesis that hydrometeor lofting is important in the formation of mesoscale snow bands, (ii) extend the predictability study of Novak and Colle (2012) to CAM resolutions, evaluating the HRRR along with experimental WRF forecasts for a set of banded snowfall cases, (iii) examine the sensitivity of banding to details of microphysics representations, including fall velocity and crystal habit/size distribution, (iv) undertake a resolution sensitivity study to identify the requisite grid length for operational prediction of snow bands, and (v) develop diagnostic plotting capabilities to allow forecasters to easily assess the potential for snow band formation in operational model output. Our study region will focus on cases in the Central and Eastern US, and on synoptically-forced winter storms, though the results also hold relevance for lake-effect convection.
Newly available out from a suite of medium- and high-resolution global atmospheric modeling experiments, conducted by the United Kingdom Meteorological Office, will be used to test the joint sensitivities of the mid-latitude storm tracks to global warming and to model resolution.
The Tropospheric Airborne Meteorological Data Reporting (TAMDAR) system is transitioning from a North American-based system to a global observing system. Because of this expansion, AirDat will be implementing an operational high-resolution global model with a hybrid 4D-Variational Ensemble Kalman Filter assimilation system to generate forecast products, and perform quality assurance and optimization refinements on raw TAMDAR data. This global model will provide lateral boundary conditions and initial conditions to a suite of limited area models. Impact studies and analysis of error statistics will be performed on all phases of flight, so that unique bias characteristics can be defined on a more granular basis for this asynoptic data set. In addition to the implementation of the new global forecast system, code optimization and additional parallelization will also be required for computational efficiency.
Severe convective storms in environments with large vertical wind shear and marginal instability (so-called â€œhigh-shear low-CAPEâ€, or â€œHSLCâ€ events) represent a significant short-term, high-impact forecasting and warning challenge, particularly in the Southeastern and Mid-Atlantic states of the U.S. Such environments account for a substantial fraction of severe wind and tornado reports in the region, and they are present for many hours each year. Based upon our previous research, it appears that there are several useful environment cues (lower and middle tropospheric lapse rates as well as bulk vertical wind shear) for HSLC severe weather outbreaks, and that there is some possible (although limited in range) skill in using WSR-88D azimuthal shear for issuing tornado warnings. Unfortunately, there is only a cursory understanding of the basic dynamics, evolution, and large-scale interactions of HSLC storms, and to date there has also been no thorough assessment of how well HSLC events are represented and predicted by numerical weather prediction (NWP) models. Also, to the point there is little understanding of the commonalities and differences between the synoptic settings that produce HSLC environments, including cold season outbreaks, post-frontal outbreaks, and post-landfall TCs. These gaps in the knowledge base are important because they currently pose the most significant hindrance to quality forecasts and warnings for hazardous weather in the Eastern Region. This application represents the next logical steps toward addressing this problem. The specific aims of the proposed research are: a) Improve HSLC nowcasting and warning operations by advancing the understanding and interpretation of HSLC radar imagery. To do this we propose to perform idealized simulations of HSLC convective storms, within which we will study the dynamical processes at work and compare them to pseudo-radar measurements of the simulated storms. b) Improve short-to-medium range prediction and situational awareness of HSLC scenarios by more thoroughly understanding the quality of NWP forecasts, investigating the resolution requirements for useful guidance, and assessing whether model skill is a function of synoptic setting/regime. To do this we propose to perform operational NWP-like hindcasts of notable HSLC events and nulls and test the sensitivity of these hindcasts to grid spacing and model configuration. c) Improve short-to-extended range prediction and situational awareness of HSLC scenarios by investigating and improving the probabilistic information that is available from operational models. To do this we propose to apply dynamically-based statistical downscaling techniques in order to exploit the information available from the SREF and ExREF model ensembles. Development of this proposal has been guided by input from 11 regional field offices of the National Weather Service as well as the Storm Prediction Center, and the proposed research is directly relevant to the NWS Eastern Region priorities listed in the CSTAR program announcement.