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Feimin Zhang
,
Kaixuan Bi
,
Sentao Wei
, and
Chenghai Wang

Abstract

This study investigates the influences of initial soil moisture over the Tibetan Plateau (TP) on precipitation simulation, and the respective effects of boundary layer vertical diffusion for heat (Kh ) and vapor (Kq ). Results indicate that the responses of boundary layer vertical diffusion to soil moisture are obvious mainly in the daytime. Wetter land surface corresponds to weaker vertical diffusion, which could strengthen thermal forcing and dynamic lifting in the lower atmosphere, and encourage water vapor saturation near the top of boundary layer to prevent the environmental dry air entrainment/invasion, which would be beneficial to more convection and precipitation. Wetter land surface over the TP could enhance the contrast between the cold in the northwestern TP and the warm in the southeastern TP, which would be conducive to the southeastward propagation of precipitation. The simulation of heat and moisture in the boundary layer could be improved by perturbing the relative intensity of Kh and Kq . From the perspective of heat and moisture, Kh affects atmospheric stability, while Kq affects moisture and its vertical transport in the boundary layer. The Kh and Kq have competitive effects on precipitation intensity by influencing the relative importance of moisture and atmospheric stability conditions in the boundary layer. Adjusting the relative intensity of Kh and Kq would deactivate the competitive effects. Stronger Kh but weaker Kq would alleviate the overestimated precipitation by inhibiting vertical transport of moisture to the top of boundary layer and attenuating convective instability in the boundary layer.

Significance Statement

The purpose of this study is to better understand the effects of boundary layer vertical heat and moisture diffusion in the response of precipitation to soil moisture. This is important because boundary layer vertical diffusion is a crucial factor influencing the relation between soil moisture and precipitation. Our results reveal the competitive effects of boundary layer vertical diffusion for heat and vapor on the simulation of precipitation. These results point a potential way toward better understanding the response of precipitation to soil moisture.

Open access
Michael L. Wasserstein
and
W. James Steenburgh

Abstract

Heavy orographic snowfall can disrupt transportation and threaten life and property in mountainous regions but benefits water resources, winter sports, and tourism. Little Cottonwood Canyon (LCC) in northern Utah’s Wasatch Range is one of the snowiest locations in the interior western United States and frequently observes orographic snowfall extremes with threats to transportation, structures, and public safety due to storm-related avalanche hazards. Using manual new-snow and liquid precipitation equivalent (LPE) observations, ERA5 reanalyses, and operational radar data, this paper examines the characteristics of cool-season (October–April) 12-h snowfall extremes in upper LCC. The 12-h extremes, defined based on either 95th percentile new snow or LPE, occur for a wide range of crest-level flow directions. The distribution of LPE extremes is bimodal with maxima for south-southwest or north-northwest flow whereas new snow extremes occur most frequently during west-northwest flow, which features colder storms with higher snow-to-liquid ratios. Both snowfall and LPE extremes are produced by diverse synoptic patterns, including inland-penetrating or decaying atmospheric rivers from the south through northwest that avoid the southern high Sierra Nevada, frontal systems, post-cold-frontal northwesterly flow, south-southwesterly cold-core flow, and closed low pressure systems. Although often associated with heavy precipitation in other mountainous regions, the linkages between local integrated water vapor transport (IVT) and orographic precipitation extremes in LCC are relatively weak, and during post-cold-frontal northwesterly flow, highly localized and intense snowfall can occur despite low IVT. These results illustrate the remarkable diversity of storm characteristics producing orographic snowfall extremes at this interior continental mountain location.

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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 nine 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 easily be 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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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 to assimilate the hyperspectral radiances is how to effectively extract the observation information, due to the inter-channel 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 FY-4A GIIRS IR radiances in an observing system simulation experiment (OSSE), with model resolutions from 7.5 km 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.

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Grant LaChat
,
Kevin A. Bowley
, and
Melissa Gervais

Abstract

Rossby wave breaking (RWB) can be manifested by the irreversible overturning of isentropes on constant potential vorticity (PV) surfaces. Traditionally, the type of breaking is categorized as anticyclonic (AWB) or cyclonic (CWB) and can be identified using the orientation of streamers of high potential temperature (θ) and low θ air on a PV surface. However, an examination of the differences in RWB structure and their associated tropospheric impacts within these types remains unexplored. In this study, AWB and CWB are identified from overturning isentropes on the dynamic tropopause (DT), defined as the 2 potential vorticity unit (PVU; 1 PVU = 10−6 K kg−1 m2 s−1) surface, in the ERA5 dataset during December, January, and February 1979–2019. Self-organizing maps (SOM), a machine learning method, is used to cluster the identified RWB events into archetypal patterns, or “flavors,” for each type. AWB and CWB flavors capture variations in the θ minima/maxima of each streamer and the localized meridional θ gradient (∇θ) flanking the streamers. Variations in the magnitude and position of ∇θ between flavors correspond to a diversity of jet structures leading to differences in vertical motion patterns and troposphere-deep circulations. A subset of flavors of AWB (CWB) events are associated with the development of strong surface high (low) pressure systems and the generation of extreme poleward moisture transport. For CWB, many events occurred in similar geographical regions, but the precipitation and moisture patterns were vastly different between flavors. Our findings suggest that the location, type, and severity of the tropospheric impacts from RWB are strongly dictated by RWB flavor.

Significance Statement

Large-scale atmospheric waves ∼15 km above Earth’s surface are responsible for the daily weather patterns that we experience. These waves can undergo wave breaking, a process that is analogous to ocean waves breaking along the seashore. Wave breaking events have been linked to extreme weather impacts at the surface including cold and heat waves, strong low pressure systems, and extreme precipitation events. Machine learning is used to identify and analyze different flavors, or patterns, of wave breaking events that result in differing surface weather impacts. Some flavors are able to generate notable channels of moisture that result in extreme high precipitation events. This is a crucial insight as forecasting of extreme weather events could be improved from this work.

Open access
Ian C. Cornejo
,
Angela K. Rowe
,
Kristen L. Rasmussen
, and
Jennifer C. DeHart

Abstract

Taiwan regularly receives extreme rainfall due to seasonal mei-yu fronts that are modified by Taiwan’s complex topography. One such case occurred between 1 and 3 June 2017 when a mei-yu front contributed to flooding and landslides from over 600 mm of rainfall in 12 h near the Taipei basin, and over 1500 mm of rainfall in 2 days near the Central Mountain Range (CMR). This mei-yu event is simulated using the Weather Research and Forecasting (WRF) Model with halved terrain as a sensitivity test to investigate the orographic mechanisms that modify the intensity, duration, and location of extreme rainfall. The reduction in WRF terrain height produced a decrease in rainfall duration and accumulation in northern Taiwan and a decrease in rainfall duration, intensity, and accumulation over the CMR. The reductions in northern Taiwan are linked to a weaker orographic barrier jet resulting from a lowered terrain height. The reductions in rainfall intensity and duration over the CMR are partially explained by a lack of orographic enhancements to mei-yu frontal convergence near the terrain. A prominent feature missing with the reduced terrain is a redirection of postfrontal westerly winds attributed to orographic deformation, i.e., the redirection of flow due to upstream topography. Orographically deforming winds converge with prefrontal flow to maintain the mei-yu front. In both regions, the decrease in mei-yu front propagation speed is linked to increased rainfall duration. These orographic features will be further explored using observations captured during the 2022 Prediction of Rainfall Extremes Campaign in the Pacific (PRECIP) field campaign.

Significance Statement

This study examines the impact of terrain on rainfall intensity, duration, and location. A mei-yu front, an East Asian weather front known for producing heavy, long-lasting rainfall, was simulated for an extreme rain event in Taiwan with mountain heights halved as a sensitivity test. Reducing terrain decreased rainfall duration in northern and central Taiwan. Decreases in rainfall duration for both regions is attributed to increased mei-yu front propagation speed. This increase in northern Taiwan is attributed to a weakened barrier jet, a low-level jet induced by flow blocked by the steep mountains of Taiwan. A unique finding of this work is a change in winds north of the front controlling movement of the front near the mountains in central Taiwan.

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Udai Shimada
,
Paul D. Reasor
,
Robert F. Rogers
,
Michael S. Fischer
,
Frank D. Marks
,
Jonathan A. Zawislak
, and
Jun A. Zhang

Abstract

While recent observational studies of intensifying (IN) versus steady-state (SS) hurricanes have noted several differences in their axisymmetric and asymmetric structures, there remain gaps in the characterization of these differences in a fully three-dimensional framework. To address these limitations, this study investigates differences in the shear-relative asymmetric structure between IN and SS hurricanes using airborne Doppler radar data from a dataset covering an extended period of time. Statistics from individual cases show that IN cases are characterized by peak wavenumber-1 ascent concentrated in the upshear-left (USL) quadrant at ∼12-km height, consistent with previous studies. Moderate updrafts (2–6 m s−1) occur more frequently in the downshear eyewall for IN cases than for SS cases, likely leading to a higher frequency of moderate to strong updrafts USL above 9-km height. Composites of IN cases show that low-level outflow from the eye region associated with maximum wavenumber-1 vorticity inside the radius of maximum wind (RMW) in the downshear-left quadrant converges with low-level inflow outside the RMW, forming a stronger local secondary circulation in the downshear eyewall than SS cases. The vigorous eyewall convection of IN cases produces a net vertical mass flux increasing with height up to ∼5 km and then is almost constant up to 10 km, whereas the net vertical mass flux of SS cases decreases with height above 4 km. Strong USL upper-level ascent provides greater potential for the vertical development of the hurricane vortex, which is argued to be favorable for continued intensification in shear environments.

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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.

Restricted 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 Mountains. 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. Reduced mission frequency and reduced dropsonde horizontal spacing both 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.

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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.

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