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Nicholas M. Leonardo
and
Brian A. Colle

Abstract

Nested idealized baroclinic wave simulations at 4-km and 800-m grid spacing are used to analyze the precipitation structures and their evolution in the comma head of a developing extratropical cyclone. After the cyclone spins up by hour 120, snow multibands develop within a wedge-shaped region east of the near-surface low center within a region of 700–500-hPa potential and conditional instability. The cells deepen and elongate northeastward as they propagate north. There is also an increase in 600–500-hPa southwesterly vertical wind shear prior to band development. The system stops producing bands 12 h later as the differential moisture advection weakens, and the instability is depleted by the convection. Sensitivity experiments are run in which the initial stability and horizontal temperature gradient of the baroclinic wave are adjusted by 5%–10%. A 10% decrease in initial instability results in less than half the control run potential instability by 120 h and the cyclone fails to produce multibands. Meanwhile, a 5% decrease in instability delays the development of multibands by 18 h. Meanwhile, decreasing the initial horizontal temperature gradient by 10% delays the growth of vertical shear and instability, corresponding to multibands developing 12–18 h later. Conversely, increasing the horizontal temperature gradient by 10% corresponds to greater vertical shear, resulting in more prolific multiband activity developing ∼12 h earlier. Overall, the relatively large changes in band characteristics over a ∼12-h period (120–133 h) and band evolutions for the sensitivity experiments highlight the potential predictability challenges.

Significance Statement

Multiple-banded precipitation structures are difficult to predict and can greatly impact snowfall forecasts. This study investigates the precipitation bands in the comma head of a low pressure system in a numerical model to systematically isolate the roles of different ambient conditions. The results emphasize that environments with instability (e.g., air free to rise after small upward displacement) and increasing winds with height favor the development of banded structures. The forecast challenge for these bands is illustrated by starting the model with relatively small changes in the temperature field. Decreasing the instability by 10% suppresses band development, while increasing (decreasing) the horizontal temperature change across the system by 10% corresponds to the bands developing 12 h earlier (later).

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Clairisse A. Reiher
and
Andrew C. Winters

Abstract

A vertical superposition of the polar and subtropical jet streams constitutes a unique synoptic-scale environment with the potential to induce high-impact weather, including anomalously strong surface cyclones that are accompanied by heavy precipitation and strong winds. Jet superpositions are not always a sufficient condition for the occurrence of high-impact weather, however, so understanding the dynamical and thermodynamic environments that favor the development of high-impact weather in association with jet superpositions is essential for improving sensible weather forecasts during these events. In this study, we pair a climatology of jet superpositions with climatologies of atmospheric rivers and surface cyclones to determine the frequency with which these features accompany jet superpositions. We subsequently construct two subsets of jet superpositions for further analysis. “High-impact” jet superposition cases are defined as those that feature an atmospheric river and a highly anomalous surface cyclone relative to climatology, which can potentially support extreme near-surface winds and precipitation. In contrast, “null” cases are defined as jet superposition cases that are not associated with a surface cyclone and are therefore less likely to support widespread high-impact weather. Composite analyses are then performed to identify discriminating environmental factors between high-impact and null cases, and how these factors influence jet superposition dynamics. We find that stronger environmental baroclinicity and a sufficient moisture supply within the near-jet environment are common characteristics of high-impact cases. These characteristics subsequently support the development of a more vigorous ageostrophic transverse circulation beneath the superposed jet’s exit region during high-impact cases and more intense surface cyclogenesis.

Significance Statement

A jet superposition event occurs when the normally separate polar and subtropical jets combine to form a single jet. This study aims to understand what factors differentiate jet superposition events that coincide with strong winds and heavy precipitation, or “high-impact weather,” from those that are less likely to coincide with such weather conditions. We identified several important environmental characteristics that tend to precede jet superposition events with a large potential to induce high-impact weather, including increased moisture and a strengthened pole-to-equator temperature gradient. These results provide indicators forecasters may consider when predicting the impacts of a jet superposition event.

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Tobias I. D. Ross
and
Sonia Lasher-Trapp

Abstract

Cold pools produced by deep convection can initiate new convection, and their representation in larger-scale weather and climate models could improve prediction of the extent and timing of upscale growth. Cold pools originate from latent cooling from precipitation changing phase, but little attention has been paid to microphysical influences on cold pool characteristics, particularly CCN effects. Datasets obtained from the CACTI and RELAMPAGO field campaigns, along with idealized numerical modeling, are utilized to investigate the hypothesis that convective storms forming in higher-CCN environments generate their first surface rainfall later, delaying cold pool initiation. Aircraft observations of CCN and shallow convection on 9 days do suggest a CCN effect. Those ingesting more CCN contained fewer drizzle drops, although a decreased cloud depth with increasing CCN was also likely a limiting factor. In three of those cases that later developed into deep convection, the timing of cold pool onset was not ubiquitously delayed in environments with more CCN. Idealized numerical simulations suggest that an ordinary thunderstorm can experience small delays in cold pool onset with increasing CCN due to changes in graupel production, but CCN effects on the cold pool from a supercell thunderstorm can be easily overpowered by its unique dynamics. A strong inverse relationship between cold pool strength, expansion rate, and depth with increasing CCN is suggested by the results of the ordinary thunderstorm simulation. Further consideration of CCN appears warranted for future cold pool parameterization development, but other environmental factors affecting storm morphology and precipitation cannot be ignored.

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Mariko Oue
,
Brian A. Colle
,
Sandra E. Yuter
,
Pavlos Kollias
,
Phillip Yeh
, and
Laura M. Tomkins

Abstract

Limited knowledge exists about ∼100-m-scale precipitation processes within U.S. northeast coastal snowstorms because of a lack of high-resolution observations. We investigate characteristics of microscale updraft regions within the cyclone comma head and their relationships with snowbands, wind shear, frontogenesis, and vertical mass flux using high-spatiotemporal-resolution vertically pointing Ka-band radar measurements, soundings, and reanalysis data for four snowstorms observed at Stony Brook, New York. Updraft regions are defined as contiguous time–height plotted areas with upward Doppler velocity without hydrometeor sedimentation that is equal to or greater than 0.4 m s−1. Most updraft regions in the time–height data occur on a time scale of seconds (<20 s), which is equivalent to spatial scales < 500 m. These small updraft regions within cloud echo occur more than 30% of the time for three of the four cases and 18% for the other case. They are found at all altitudes and can occur with or without frontogenesis and with or without snowbands. The updraft regions with relatively large Doppler spectrum width (>0.4 m s−1) occur more frequently within midlevels of the storms, where there are strong wind shear layers and moist shear instability layers. This suggests that the dominant forcing for the updrafts appears to be turbulence associated with the vertical shear instability. The updraft regions can be responsible for upward mass flux when they are closer together in space and time. The higher values of column mean upward mass flux often occur during snowband periods.

Significance Statement

Small-scale (<500 m) upward motions within four snowstorms along the U.S. northeast coast are analyzed for the first time using high-spatiotemporal-resolution millimeter-wavelength cloud radar pointed vertically. The analysis reveals that updrafts appear in the storms regardless of whether snowbands are present or whether there is larger-scale forcing for ascent. The more turbulent and stronger updrafts frequently occur in midlevels of storms associated with instability from vertical shear and contribute to upward mass flux during snowband periods when they are closer together in space and time.

Open access
Ron McTaggart-Cowan
,
David S. Nolan
,
Rabah Aider
,
Martin Charron
,
Jan-Huey Chen
,
Jean-François Cossette
,
Stéphane Gaudreault
,
Syed Husain
,
Linus Magnusson
,
Abdessamad Qaddouri
,
Leo Separovic
,
Christopher Subich
, and
Jing Yang

Abstract

The operational Canadian Global Deterministic Prediction System suffers from a weak-intensity bias for simulated tropical cyclones. The presence of this bias is confirmed in progressively simplified experiments using a hierarchical system development technique. Within a semi-idealized, simplified-physics framework, an unexpected insensitivity to the representation of relevant physical processes leads to investigation of the model’s semi-Lagrangian dynamical core. The root cause of the weak-intensity bias is identified as excessive numerical dissipation caused by substantial off-centering in the two time-level time integration scheme used to solve the governing equations. Any (semi)implicit semi-Lagrangian model that employs such off-centering to enhance numerical stability will be afflicted by a misalignment of the pressure gradient force in strong vortices. Although the associated drag is maximized in the tropical cyclone eyewall, the impact on storm intensity can be mitigated through an intercomparison-constrained adjustment of the model’s temporal discretization. The revised configuration is more sensitive to changes in physical parameterizations and simulated tropical cyclone intensities are improved at each step of increasing experimental complexity. Although some rebalancing of the operational system may be required to adapt to the increased effective resolution, significant reduction of the weak-intensity bias will improve the quality of Canadian guidance for global tropical cyclone forecasting.

Significance Statement

Global numerical weather prediction systems provide important guidance to forecasters about tropical cyclone development, motion, and intensity. Despite recent improvements in the Canadian operational model’s ability to predict tropical cyclone formation, the system systematically underpredicts the intensity of these storms. In this study, we use a set of increasingly simplified experiments to identify the source of this error, which lies in the numerical time-stepping scheme used to solve the model equations. By decreasing numerical drag on the tropical cyclone circulation, intensity predictions that resemble those of other global modeling systems are achieved. This will improve the quality of Canadian tropical cyclone guidance for forecasters around the world.

Open access
Minghua Zheng
,
Ryan Torn
,
Luca Delle Monache
,
James Doyle
,
Fred Martin Ralph
,
Vijay Tallapragada
,
Christopher Davis
,
Daniel Steinhoff
,
Xingren Wu
,
Anna Wilson
,
Caroline Papadopoulos
, and
Patrick Mulrooney

Abstract

During a 6-day intensive observing period in January 2021, Atmospheric River Reconnaissance (AR Recon) aircraft sampled a series of atmospheric rivers (ARs) over the northeastern Pacific that caused heavy precipitation over coastal California and the Sierra Nevada. Using these observations, data denial experiments were conducted with a regional modeling and data assimilation system to explore the impacts of research flight frequency and spatial resolution of dropsondes on model analyses and forecasts. Results indicate that dropsondes significantly improve the representation of ARs in the model analyses and positively impact the forecast skill of ARs and quantitative precipitation forecasts (QPF), particularly for lead times > 1 day. Both reduced mission frequency and reduced dropsonde horizontal resolution degrade forecast skill. On the other hand, experiments that assimilated only G-IV data and experiments that assimilated both G-IV and C-130 data show better forecast skill than experiments that only assimilated C-130 data, suggesting that the additional information provided by G-IV data is necessary for improving forecast skill. Although this is a case study, the 6-day period studied encompassed multiple AR events that are representative of typical AR behavior. Therefore, the results indicate that future operational AR Recon missions incorporate daily mission or back-to-back flights, maintain current dropsonde spacing, support high-resolution data transfer capacity on the C-130s, and utilize G-IV aircraft in addition to C-130s.

Restricted access
Linfan Zhou
,
Lili Lei
,
Jeffrey S. Whitaker
, and
Zhe-Min Tan

Abstract

Hyperspectral infrared (IR) satellites can provide high-resolution vertical profiles of the atmospheric state, which significantly contributes to the forecast skill of numerical weather prediction, especially for regions with sparse observations. One challenge in assimilating the hyperspectral radiances is how to effectively extract the observation information, due to the interchannel correlations and correlated observation errors. An adaptive channel selection method is proposed, which is implemented within the data assimilation scheme and selects the radiance observation with the maximum reduction of variance in observation space. Compared to the commonly used channel selection method based on the maximum entropy reduction (ER), the adaptive method can provide flow-dependent and time-varying channel selections. The performance of the adaptive selection method is evaluated by assimilating only the synthetic Fengyun-4A (FY-4A) GIIRS IR radiances in an observing system simulation experiment (OSSE), with model resolutions from 7.5 to 1.5 km and then 300 m. For both clear-sky and all-sky conditions, the adaptive method generally produces smaller RMS errors of state variables than the ER-based method given similar amounts of assimilated radiances, especially with fine model resolutions. Moreover, the adaptive method has minimum RMS errors smaller than or approaching those with all channels assimilated. For the intensity of the tropical cyclone, the adaptive method also produces smaller errors of the minimum dry air mass and maximal wind speed at different levels, compared to the ER-based selection method.

Significance Statement

Assimilating satellite radiances has been essential for numerical weather prediction. Hyperspectral infrared satellites provide high-resolution vertical profiles for the atmospheric state and can further improve the numerical weather prediction. Due to limited computational resources, and correlated observations and associated errors, efficient and effective ways to assimilate the hyperspectral radiances are needed. An adaptive channel selection method that is incorporated with data assimilation is proposed. The adaptive channel selection can effectively extract the information from hyperspectral radiances under both clear- and all-sky conditions, with increased model resolutions from kilometers to subkilometers.

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Wei-Ting Fang
,
Pao-Liang Chang
, and
Ming-Jen Yang

Abstract

Intensification of Typhoon Chanthu (2021) along the eastern coast of Taiwan was accompanied by pronounced asymmetry in eyewall convection dominated by wavenumber-1 features, as observed by a dense radar network in Taiwan. The maximum wind speed at 3-km altitude, retrieved from radar observations, exhibited a rapid increase of approximately 18 m s−1 within an 11-h period during the intensification stage, followed by a significant decrease of approximately 19 m s−1 within 8 h during the weakening stage. Namely, Chanthu underwent both rapid intensification (RI) and rapid weakening (RW) within the 24-h analyzed period, posing challenges for intensity forecasts. During the intensifying stages, the region of maximum eyewall convection asymmetry underwent a sudden cyclonic rotation from the eastern to the northern semicircle immediately after the initiation of terrain-induced boundary inflow from the south of the typhoon, as observed by surface station data. This abrupt rotation of eyewall asymmetry exhibited better agreement with radar-derived vertical wind shear (VWS) than that derived from global reanalysis data. This finding suggests that the meso-β-scale VWS is more representative for tropical cyclones than meso-α-scale VWS when the terrain-induced forcing predominates in the environmental conditions. Further examination of the radar-derived VWS indicated that the VWS profile pattern provided a more favorable environment for typhoon intensification. In summary, Chanthu’s RI was influenced by the three factors: 1) terrain-induced boundary inflow from the south of the typhoon, observed by surface station data; 2) low-level flow pointing toward the upshear-left direction; and 3) weak upper-level VWS.

Significance Statement

Tropical cyclone intensity change has been an important issue for both real-time operation and research, but the influence of terrain on intensity change has not been fully understood. Typhoon Chanthu (2021) underwent a significant intensity change near the complex terrain of Taiwan that was observed by a dense radar network. This study analyzes 24 h of radar and weather station data to investigate Chanthu’s evolution. The analyses indicate that the complex terrain affected the low-level flow near the TC. Such a change in flow pattern provided additional boundary inflow and a relatively favorable vertical wind shear pattern for TC intensification.

Open access
Fang-Ching Chien
and
Yen-Chao Chiu

Abstract

This paper investigates the impact of the environmental conditions during the first half of the 2020 mei-yu season (Y20) and the southwest vortex (SWV), as well as their interaction, on heavy precipitation in southern Taiwan during late May 2020, based on a quantitative approach through ensemble simulations. The control experiment successfully replicates observed heavy precipitation in southern and central Taiwan and reveals a positive spatial correlation between precipitation occurrence probabilities and mean accumulated precipitation, emphasizing continuous rainfall accumulation over intermittent extreme events. Comparative analyses with sensitivity experiments elucidate that the Y20, featuring an extended western North Pacific subtropical high, intensify pressure gradients and southwesterly flow near Taiwan, favoring precipitation in windward regions but hindering it in the east. The SWV creates a moist and vortical environment near Taiwan, amplifying moisture supply and westerly winds, promoting precipitation in southern Taiwan, and enhancing frontal activity. The interaction between the SWV and the Y20, though limited in its impact on providing favorable wind and moisture conditions for precipitation southwest of Taiwan, significantly contributes to precipitation in southern Taiwan. The reason is that although the SWV primarily enhances moisture and the Y20 predominantly boost southwesterly flow, creating favorable conditions for rainfall, substantial precipitation occurs only when both factors converge in a nonlinear interaction. The interaction increases frontal activity over the Taiwan Strait and influences the movement and strength of the SWV, enhancing southwesterly flow and moisture flux in southwestern Taiwan.

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Amanda Richter
and
Timothy J. Lang

Abstract

NASA’s Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign gathered data using “satellite-simulating” (albeit with higher-resolution data than satellites currently provide) and in situ aircraft to study snowstorms, with an emphasis on banding. This study used three IMPACTS microwave instruments—two passive and one active—chosen for their sensitivity to precipitation microphysics. The 10–37-GHz passive frequencies were well suited for detecting light precipitation and differentiating rain intensities over water. The 85–183-GHz frequencies were more sensitive to cloud ice, with higher cloud tops manifesting as lower brightness temperatures, but this did not necessarily correspond well to near-surface precipitation. Over land, retrieving precipitation information from radiometer data is more difficult, requiring increased reliance on radar to assess storm structure. A dual-frequency ratio (DFR) derived from the radar’s Ku- and Ka-band frequencies provided greater insight into storm microphysics than reflectivity alone. Areas likely to contain mixed-phase precipitation (often the melting layer/bright band) generally had the highest DFR, and high-altitude regions likely to contain ice usually had the lowest DFR. The DFR of rain columns increased toward the ground, and snowbands appeared as high-DFR anomalies.

Significance Statement

Winter precipitation was studied using three airborne microwave sensors. Two were passive radiometers covering a broad range of frequencies, while the other was a two-frequency radar. The radiometers did a good job of characterizing the horizontal structure of winter storms when they were over water, but struggled to provide detailed information about winter storms when they were over land. The radar was able to provide vertically resolved details of storm structure over land or water, but only provided information at nadir, so horizontal structure was less well described. The combined use of all three instruments compensated for individual deficiencies, and was very effective at characterizing overall winter storm structure.

Open access