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Theresa K. Andersen
,
David E. Radcliffe
, and
J. Marshall Shepherd

Abstract

Tropical cyclones (TCs) typically weaken or transition to extratropical cyclones after making landfall. However, there are cases of TCs maintaining warm-core structures and intensifying inland unexpectedly, referred to as TC maintenance or intensification events (TCMIs). It has been proposed that wet soils create an atmosphere conducive to TC maintenance by enhancing surface latent heat flux (LHF). In this study, “HYDRUS-1D” is used to simulate the surface energy balance in intensification regions leading up to four different TCMIs. Specifically, the 2-week magnitudes and trends of soil temperature, sensible heat flux (SHF), and LHF are analyzed and compared across regions. While TCMIs are most common over northern Australia, theoretically linked to large fluxes from hot sands, the results revealed that SHF and LHF are equally large over the south-central United States. Modern-Era Retrospective Analysis for Research and Applications (MERRA) 3-hourly LHF data were obtained for the same HYDRUS study regions as well as nearby ocean regions along the TC path 3 days prior (prestorm) to the TC appearance. Results indicate that the simulated prestorm mean LHF is similar in magnitude to that obtained from MERRA, with slightly lower values overall. The modeled 3-day mean fluxes over land are less than those found over the ocean; however, the maximum LHF over the 3-day period is greater over land (HYDRUS) than over the ocean (MERRA) for three of four cases. It is concluded that LHF inland can achieve similar magnitudes to that over the ocean during the daytime and should be pursued as a potential energy source for inland TCs.

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Amanda Schroeder
,
Jeffrey Basara
,
J. Marshall Shepherd
, and
Steven Nelson

Abstract

Flooding is routinely one of the most deadly weather-related hazards in the United States, which highlights the need for more hydrometeorological research related to forecasting these hazardous events. Building upon previous literature, a synergistic study analyzes hydrometeorological aspects of major urban flood events in the United States from 1977 through 2014 caused by locally heavy precipitation. Primary datasets include upper-air soundings and climatological precipitable water (PW) distributions. A major finding of this work is that major urban flood events are associated with extremely anomalous PW values, many of which exceeded the 99th percentile of the associated climatological dataset and all of which were greater than 150% of the climatological mean values. However, of the 40 cases examined in this study, only 15 had PW values that exceeded 50.4 mm (2 in.), illustrating the importance of including the location-specific PW climatology in a PW analysis relevant to the potential for flash floods. Additionally, these events revealed that, despite geographic location and time of year, most had a warm cloud depth of at least 6 km, which is defined here as the layer between the lifting condensation level and the height of the −10°C level. A “composite” flood sounding was also calculated and revealed a characteristically tropical structure, despite cases related to tropical cyclones being excluded from the study.

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Michael Carter
,
J. Marshall Shepherd
,
Steve Burian
, and
Indu Jeyachandran

Abstract

Urban–coastal circulations affect urban weather, dispersion and transport of pollutants and contaminants, and climate. Proper characterization and prediction of thermodynamic and dynamic processes in such environments are warranted. A new generation of observation and modeling systems is enabling unprecedented characterization of the three-dimensionality of the urban environment, including morphological parameters. Urban areas of Houston, Texas, are classified according to lidar-measured building heights and assigned typical urban land surface parameters appropriate to each classification. The lidar data were degraded from 1 m to the model resolution (1 km) with the goal of evaluating the impact of degraded resolution urban canopy parameters (UCPs) and three-dimensionality on the coastal–urban mesoscale circulations in comparison to typical two-dimensional urban slab approaches. The study revealed complex interactions between the sea breeze and urban heat island and offers a novel diagnostic tool, the bulk Richardson shear number, for identifying shallow mesoscale circulation.

Using the Advanced Research Weather Research and Forecasting model (ARW-WRF) coupled to an atmosphere–land surface–urban canopy model, the authors simulated a theoretical sea-breeze day and confirmed that while coastal morphology can itself lead to complex sea-breeze front structures, including preferred areas of vertical motion, the urban environment can have an impact on the evolution of the sea-breeze mesoscale boundary. The inclusion of lidar-derived UCPs, even at degraded resolution, in the model’s land surface representation can lead to significant differences in patterns of skin surface temperature, convergence, and vertical motion, which have implications for many aspects of urban weather.

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Joshua D. Durkee
,
Thomas L. Mote
, and
J. Marshall Shepherd

Abstract

This study uses a database consisting of 330 austral warm-season (October–May) mesoscale convective complexes (MCCs) during 1998–2007 to determine the contribution of MCCs to rainfall across subtropical South America (SSA). A unique precipitation analysis is conducted using Tropical Rainfall Measuring Mission (TRMM) 3B42 version 6 data. The average MCC produces 15.7 mm of rainfall across 381 000 km2, with a volume of 7.0 km3. MCCs in SSA have the largest precipitation areas compared to North American and African systems. MCCs accounted for 15%–21% of the total rainfall across portions of northern Argentina and Paraguay during 1998–2007. However, MCCs account for larger fractions of the total precipitation when analyzed on monthly and warm-season time scales. Widespread MCC rainfall contributions of 11%–20% were observed in all months. MCCs accounted for 20%–30% of the total rainfall between November and February, and 30%–50% in December, primarily across northern Argentina and Paraguay. MCCs also produced 25%–66% of the total rainfall across portions of west-central Argentina. Similar MCC rainfall contributions were observed during warm seasons. An MCC impact factor (MIF) was developed to determine the overall impact of MCC rainfall on warm-season precipitation anomalies. Results show that the greatest impacts on precipitation anomalies from MCC rainfall were located near the center of the La Plata basin. This study demonstrates that MCCs in SSA produce widespread precipitation that contributes substantially to the total rainfall across the region.

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Ryann A. Wakefield
,
Jeffrey B. Basara
,
J. Marshall Shepherd
,
Noah Brauer
,
Jason C. Furtado
,
Joseph A. Santanello Jr.
, and
Roger Edwards

Abstract

Landfalling tropical cyclones (TCs) often decay rapidly due to a decrease in moisture and energy fluxes over land when compared to the ocean surface. Occasionally, however, these cyclones maintain intensity or reintensify over land. Post-landfall maintenance and intensification of TCs over land may be a result of fluxes of moisture and energy derived from anomalously wet soils. These soils act similarly to a warm sea surface, in a phenomenon coined the “brown ocean effect.” Tropical Storm (TS) Bill (2015) made landfall over a region previously moistened by anomalously heavy rainfall and displayed periods of reintensification and maintenance over land. This study evaluates the role of the brown ocean effect on the observed maintenance and intensification of TS Bill using a combination of existing and novel approaches, including the evaluation of precursor conditions at varying temporal scales and making use of composite backward trajectories. Comparisons were made to landfalling TCs with similar paths that did not undergo TC maintenance and/or intensification (TCMI) as well as to TS Erin (2007), a known TCMI case. We show that the antecedent environment prior to TS Bill was similar to other known TCMI cases, but drastically different from the non-TCMI cases analyzed in this study. Furthermore, we show that contributions of evapotranspiration to the overall water vapor budget were nonnegligible prior to TCMI cases and that evapotranspiration along storm inflow was significantly (p < 0.05) greater for TCMI cases than non-TCMI cases suggesting a potential upstream contribution from the land surface.

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Christopher D. Bosma
,
Daniel B. Wright
,
Phu Nguyen
,
James P. Kossin
,
Derrick C. Herndon
, and
J. Marshall Shepherd

Abstract

Recent tropical cyclones (TCs) have highlighted the hazards that TC rainfall poses to human life and property. These hazards are not adequately conveyed by the commonly used Saffir–Simpson scale. Additionally, while recurrence intervals (or, their inverse, annual exceedance probabilities) are sometimes used in the popular media to convey the magnitude and likelihood of extreme rainfall and floods, these concepts are often misunderstood by the public and have important statistical limitations. We introduce an alternative metric—the extreme rain multiplier (ERM), which expresses TC rainfall as a multiple of the climatologically derived 2-yr rainfall value. ERM allows individuals to connect (“anchor,” in cognitive psychology terms) the magnitude of a TC rainfall event to the magnitude of rain events that are more typically experienced in their area. A retrospective analysis of ERM values for TCs from 1948 to 2017 demonstrates the utility of the metric as a hazard quantification and communication tool. Hurricane Harvey (2017) had the highest ERM value during this period, underlining the storm’s extreme nature. ERM correctly identifies damaging historical TC rainfall events that would have been classified as “weak” using wind-based metrics. The analysis also reveals that the distribution of ERM maxima is similar throughout the eastern and southern United States, allowing for both the accurate identification of locally extreme rainfall events and the development of regional-scale (rather than local-scale) recurrence interval estimates for extreme TC rainfall. Last, an analysis of precipitation forecast data for Hurricane Florence (2018) demonstrates ERM’s ability to characterize Florence’s extreme rainfall hazard in the days preceding landfall.

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Elaine M. Prins
,
Christopher S. Velden
,
Jeffrey D. Hawkins
,
F. Joseph Turk
,
Jaime M. Daniels
,
Gerald J. Dittberner
,
Kenneth Holmlund
,
Robbie E. Hood
,
Arlene G. Laing
,
Shaima L. Nasiri
,
Jeffery J. Puschell
,
J. Marshall Shepherd
, and
John V. Zapotocny
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