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Patricola, Christina M.

Publications and source records attributed to Patricola, Christina M..

33 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tropical Cyclone Frequency

Abstract The frequency with which tropical cyclones (TCs) occur controls all other aspects of tropical cyclone risk since a storm that does not occur can do no harm. Yet this frequency is poorly understood. There is no accepted theory that explains the average number of TCs that occur each year on the Earth, nor how that number will change with global warming. Arguments based on global budgets of heat or moisture do not yet appear helpful, nor does a detailed understanding of the physical processes of TC genesis. Empirical indices that predict TC frequency as a function of large‐scale environmental variables can explain some of its relative variations in space and time, but not its absolute value. Global numerical models with horizontal grid spacings on the order of 25–50 km have allowed much improved simulations of TC activity, however. Many such models project a decrease in frequency with warming, but some project an increase. Idealized simulations, including those at higher resolutions, offer promise by allowing a systematic, deductive investigation of the roles of individual environmental factors. In addition to the larger‐scale environmental modulation of genesis likelihood, precursor disturbances, or “seeds”, may exert an independent influence on TC frequency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Anthropogenic Influences on Tornadic Storms

The impact of climate change on severe storms and tornadoes remains uncertain, largely owing to inconsistencies in observational data and limitations of climate models. Here, we performed ensembles of convection-permitting climate model simulations to examine how three tornadic storms would change if similar events were to occur in pre-industrial and future climates. The choice of events includes winter, nocturnal, and spring tornadic storms to provide insight into how the timing and seasonality of storms may affect their response to climate change. Updraft helicity (UH), convective available potential energy (CAPE), storm relative helicity (SRH), and convective inhibition (CIN) were used to determine the favorability for the three tornadic storm events in the different climate states. We found that from the pre-industrial to present, the potential for tornadic storms decreased in the winter event and increased in the nocturnal and spring events. With future climate change, the potential for tornadic storms increased in the winter and nocturnal events in association with increased CAPE, and decreased in the spring event despite greater CAPE.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Influence of Ocean Coupling on Simulated and Projected Tropical Cyclone Precipitation in the HighResMIP–PRIMAVERA Simulations

This study aims to quantify the impacts of atmosphere–ocean coupling on simulated and projected tropical cyclone (TC) precipitation globally. We used global climate model (GCM) simulations over 1950–2050 from the High Resolution Model Intercomparison Project (HighResMIP) and compared its fully coupled atmosphere–ocean GCMs (AOGCMs) with atmosphere-only GCMs (AGCMs). We find that ocean coupling generally leads to decreased TC precipitation over ocean and land. Large-scale sea surface temperature (SST) biases are critical drivers of the precipitation difference, with secondary contributions from local TC–ocean feedbacks via SST cold wakes. The two driving factors, attributed to ocean coupling in the AOGCMs, influence TC precipitation in association with decreased TC intensity and specific humidity. The AOGCMs and AGCMs consistently project TC precipitation increases in 2015–2050 relative to 1950–2014 over ocean for all basins, and for landfalling TCs in the North Atlantic and western North Pacific.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Tale of Two Rapidly Intensifying Supertyphoons: Hagibis (2019) and Haiyan (2013)

Devastating Japan in October 2019, Supertyphoon (STY) Hagibis was an important typhoon in the history of the Pacific. A striking feature of Hagibis was its explosive rapid intensification (RI). In 24 h, Hagibis intensified by 100 knots (kt; 1 kt ≈ 0.51 m s –1 ), making it one of the fastest-intensifying typhoons ever observed. After RI, Hagibis’s intensification stalled. Using the current typhoon intensity record holder, i.e., STY Haiyan (2013), as a benchmark, this work explores the intensity evolution differences of these two high-impact STYs. We found that the extremely high prestorm sea surface temperature reaching 30.5°C, deep/warm prestorm ocean heat content reaching 160 kJ cm –2 , fast forward storm motion of ~8 m s –1 , small during-storm ocean cooling effect of ~0.5°C, significant thunderstorm activity at its center, and rapid eyewall contraction were all important contributors to Hagibis’s impressive intensification. There was 36% more air–sea flux for Hagibis’s RI than for Haiyan’s. After its spectacular RI, Hagibis’s intensification stopped, despite favorable environments. Haiyan, by contrast, continued to intensify, reaching its record-breaking intensity of 170 kt. A key finding here is the multiple pathways that storm size affected the intensity evolution for both typhoons. After RI, Hagibis experienced a major size expansion, becoming the largest typhoon on record in the Pacific. This size enlargement, combined with a reduction in storm translational speed, induced stronger ocean cooling that reduced ocean flux and hindered intensification. Furthermore, the large storm size also contributed to slower eyewall replacement cycles (ERCs), which prolonged the negative impact of the ERC on intensification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Influence of Background Divergent Moisture Flux on the Frequency of North Pacific Atmospheric Rivers

The frequency of North Pacific atmospheric rivers (ARs) affects water supply and flood risk over western North America. Thus, understanding factors that affect the variability of landfalling AR frequency is of scientific and societal importance. This study aims at identifying the sources of the moisture for North Pacific ARs and assessing how different modes of variability modulate these sources. To this end, the sources and variability of the background divergent component of the integrated moisture flux (DIVT) in ARs are identified using MERRA reanalysis. It is shown that in the boreal winter, this background DIVT in ARs is related to the outflow from the subsidence over the subtropics which transports moisture northward, while in summer it is related to the Asian monsoon and it transports moisture northwestward. This leads to a seasonal northwest/southeast movement of the AR frequency climatology. At the intra-seasonal scale, propagation of the Madden-Julian Oscillation introduces an anti-clockwise rotation of the background DIVT, with northward transport in phases 1 and 2, westward in 3 and 4, southward in 5 and 6 and eastward in 7 and 8, making landfall over the west coast of North America most likely during the last two phases. Similarly, El Niño Southern Oscillation variability also affects the frequency of ARs through modulation of the westerly background DIVT, favoring landfall over the US west coast during strong El Niño phases. It is shown that in general the likelihood of AR landfall over the western US is correlated with the zonal background DIVT over northeastern Pacific.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Anthropogenic influences on the African easterly jet–African easterly wave system

The African easterly jet (AEJ) and African easterly waves (AEWs) can have both local and far-reaching impacts on weather. It is therefore crucial to understand how the AEJ and AEWs will respond to future climate change. In this study, we examine anthropogenic influences on the AEJ–AEW system using the Weather Research and Forecasting (WRF) model configured as a tropical channel model (TCM). Hindcast simulations for the years 2001–2010 were performed using the WRF TCM, and ten additional years of simulations were performed using the pseudo-global warming method with the initial and boundary conditions of the model modified as if it were the late twenty-first century. A comparison of the simulations from the two climate scenarios indicates robust changes to both the AEJ and AEWs. For the AEJ, the jet is weaker and shifted northwards and upwards in the future climate, in association with an increase in precipitation over the Sahel and a strengthening of the meridional temperature gradient. For the AEWs, there is an increase in the number and strength of the waves in the future climate, in association with an increase in the baroclinic and barotropic energy conversions. Here, the barotropic energy conversion in particular has a larger contribution in the future climate, which manifests in the southern AEW track experiencing greater future strengthening than the northern track.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Uncertainties in Atmospheric River Lifecycles by Detection Algorithms: Climatology and Variability

Atmospheric rivers (ARs) are long and narrow filaments of vapor transport that are responsible for most poleward moisture transport outside of the tropics. Many AR detection algorithms have been developed to automatically identify ARs in climate data. The diversity of these algorithms has introduced appreciable uncertainties in quantitative measures of AR properties and thereby impedes the construction of a unified and internally consistent climatology of ARs. This paper compares nine global AR detection algorithms from the perspective of AR lifecycles following the propagation of ARs from origin to termination in the MERRA2 reanalysis over the period 1980–2017. Uncertainties in AR lifecycle characteristics, including event number, lifetime, intensity, and frequency distribution are discussed. Notably, the number of AR events per year in the Northern Hemisphere can vary by a factor of 5 with different algorithms. Although all algorithms show that the maximum AR origin (termination) frequency is located over the western (eastern) portion of ocean basins, significant disagreements appear in regional distribution. Spreads are large in AR lifetime and intensity. Here, the number of landfalling AR events produced by the algorithms can vary from 16 to 80 events per year, although the agreement improves for stronger ARs. By examining the ARs' connections with the Madden-Julian Oscillation and El Niño Southern Oscillation, we find that the overall responses of ARs (such as changes in AR frequency, origin, and landfall activity) to climate variability are consistent among algorithms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Sources of Subseasonal-To-Seasonal Predictability of Atmospheric Rivers and Precipitation in the Western United States

Atmospheric rivers (ARs) account for a large portion of winter precipitation in the western US. To evaluate the sources of AR and precipitation predictability at subseasonal-to-seasonal timescales, we examine the relationships between two climate modes, the El Niño/Southern Oscillation (ENSO) and Madden-Julian oscillation (MJO), and winter hydroclimate in the western US. Our analysis uses a large ensemble of the Weather Research and Forecast (WRF) model simulations from 1981 to 2017, facilitating the assessment of uncertainty in climate mode-AR relationship due to climate variability and short length of observations. Over the North Pacific basin, we find ENSO-related latitudinal shifts of ARs, but ENSO has little effect on basin-wide averaged AR frequency. Over the western US, there is some uncertainty in the ENSO-AR connection due to the impacts of ENSO indices and datasets. However, extreme El Niño events defined by the ENSO longitude index are consistently linked to increased landfalling AR activity. The MJO can lead to significantly enhanced or suppressed landfalling AR activity in the large-ensembles, depending on the phase of MJO and time lag, while observations are too short in length to robustly show this signal. ENSO substantially modulates the MJO-AR relationship, triggering variegated responses of landfalling ARs and AR precipitation in La Niña and El Niño years. Our findings highlight the need to evaluate concurrent effects of different climate modes on ARs and precipitation, and may shed light on a path toward more accurate subseasonal-to-seasonal prediction of ARs and precipitation over the western US.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Ocean fronts and eddies force atmospheric rivers and heavy precipitation in western North America

Atmospheric rivers (ARs) are responsible for over 90% of poleward water vapor transport in the mid-latitudes and can produce extreme precipitation when making landfall. However, weather and climate models still have difficulty simulating and predicting landfalling ARs and associated extreme precipitation, highlighting the need to better understand AR dynamics. Here, using high-resolution climate models and observations, we demonstrate that mesoscale sea-surface temperature (SST) anomalies along the Kuroshio Extension can exert a remote influence on landfalling ARs and related heavy precipitation along the west coast of North America. Inclusion of mesoscale SST forcing in the simulations results in approximately a 40% increase in landfalling ARs and up to a 30% increase in heavy precipitation in mountainous regions and this remote impact occurs on two-week time scales. The asymmetrical response of the atmosphere to warm vs. cold mesoscale SSTs over the eddy-rich Kuroshio Extension region is proposed as a forcing mechanism that results in a net increase of moisture flux above the planetary boundary layer, prompting AR genesis via enhancing moisture transport into extratropical cyclones in the presence of mesoscale SST forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Past and Future Trends of Severe Storms

The objective of this research is to use machine learning methods to establish past trends in the severe storm record and build on this information to provide severe storms projections in a future climate. This objective aligns with Focal Area 3, which emphasizes big data analytics in combination with knowledge-guided AI.

58 GEOSCIENCES↗
DOE OSTI2021

Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

Abstract While various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Detection of atmospheric rivers with inline uncertainty quantification: TECA-BARD v1.0.1

It has become increasingly common for researchers to utilize methods that identify weather features in climate models. There is an increasing recognition that the uncertainty associated with choice of detection method may affect our scientific understanding. For example, results from the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) indicate that there are a broad range of plausible atmospheric river (AR) detectors and that scientific results can depend on the algorithm used. There are similar examples from the literature on extratropical cyclones and tropical cyclones. It is therefore imperative to develop detection techniques that explicitly quantify the uncertainty associated with the detection of events. We seek to answer the following question: given a “plausible” AR detector, how does uncertainty in the detector quantitatively impact scientific results? We develop a large dataset of global AR counts, manually identified by a set of eight researchers with expertise in atmospheric science, which we use to constrain parameters in a novel AR detection method. We use a Bayesian framework to sample from the set of AR detector parameters that yield AR counts similar to the expert database of AR counts; this yields a set of “plausible” AR detectors from which we can assess quantitative uncertainty. This probabilistic AR detector has been implemented in the Toolkit for Extreme Climate Analysis (TECA), which allows for efficient processing of petabyte-scale datasets. We apply the TECA Bayesian AR Detector, TECA-BARD v1.0.1, to the MERRA-2 reanalysis and show that the sign of the correlation between global AR count and El Niño–Southern Oscillation depends on the set of parameters used.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Enhanced predictability of Eastern North Pacific Tropical cyclone activity using the ENSO Longitude Index

Past studies have indicated that El Nino-Southern Oscillation (ENSO) plays a major role in the interannual variability of Eastern Pacific hurricane activity. The primary mechanism being the eastward displacement of the warm pool during an El Nino, which carries warm water into that basin thereby creating favorable oceanic conditions. Despite this, the question of whether an accurate knowledge of ENSO enhances seasonal predictabiity of Eastern Pacific hurricanes has not been addressed specifically. In this study, we show that unlike traditional indices of ENSO, the ENSO Longitude Index (ELI) is able to predict Eastern Pacific hurricane activity at significant lead times. By capturing changes in the location of deep convection and associated thermocline processes more accurately, ELI explains the most variability in the upper-ocean heat content in the main development region of the Eastern Pacific basin compared to other ENSO indices. These results have substantial implications for operational seasonal forecasts of Eastern Pacific hurricanes.

Balaguru, Karthik↗
DOE OSTI2020

The Shifting Scales of Western U.S. Landfalling Atmospheric Rivers Under Climate Change

Atmospheric rivers (ARs) can be a boon and bane to water resource managers as they have the ability to replenish water reserves, but they can also generate million-to-billion-dollar flood damages. To investigate how anthropogenic climate change may influence AR characteristics in the coastal western United States by end century, we employ a suite of novel tools such as variable resolution in the Community Earth System Model (VR-CESM), the TempestExtremes AR detection algorithm, and the Ralph, Rutz, et al. (2019, https://doi.org/10.1175/BAMS-D-18-0023.1) AR category scale.We show that end-century ARs primarily shift from being “mostly or primarily beneficial” to “mostly or primarily hazardous” with a concomitant sharpening and intensification of winter season precipitation totals. Changes in precipitation totals are due to a significant increase in AR (+260%) rather than non-AR (+7%) precipitation, largely through increases in the most intense category of AR events and a decrease in the interval between landfalling ARs.

54 ENVIRONMENTAL SCIENCES↗