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Zhe Feng
,
Xiquan Dong
, and
Baike Xi

Abstract

A decade of collocated Atmospheric Radiation Measurement Program (ARM) 35-GHz Millimeter Cloud Radar (MMCR) and Weather Surveillance Radar-1988 Doppler (WSR-88D) data over the ARM Southern Great Plains (SGP) site have been collected during the period of 1997–2006. A total of 28 winter and 45 summer deep convective system (DCS) cases over the ARM SGP site have been selected for this study during the 10-yr period. For the winter cases, the MMCR reflectivity, on average, is only 0.2 dB lower than that of the WSR-88D, with a correlation coefficient of 0.85. This result indicates that the MMCR signals have not been attenuated for ice-phase convective clouds, and the MMCR reflectivity measurements agree well with the WSR-88D, regardless of their vastly different characteristics. For the summer nonprecipitating convective clouds, however, the MMCR reflectivity, on average, is 10.6 dB lower than the WSR-88D measurement, and the average differences between the two radar reflectivities are nearly constant with height above cloud base. Three lookup tables with Mie calculations have been generated for correcting the MMCR signal attenuation. After applying attenuation correction for the MMCR reflectivity measurements, the averaged difference between the two radars has been reduced to 9.1 dB. Within the common sensitivity range (−10 to 20 dBZ), the mean differences for the uncorrected and corrected MMCR reflectivities have been reduced to 6.2 and 5.3 dB, respectively. The corrected MMCR reflectivities were then merged with the WSR-88D data to fill in the gaps during the heavy precipitation periods. This merged dataset provides a more complete radar reflectivity profile for studying convective systems associated with heavier precipitation than the original MMCR dataset. It also provides the intensity, duration, and frequency of the convective systems as they propagate over the ARM SGP for climate modelers. Eventually, it will be possible to improve understanding of the cloud-precipitation processes, and evaluate GCM predictions using the long-term merged dataset, which could not have been done with either the MMCR or the WSR-88D dataset alone.

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Fiaz Ahmed
,
Courtney Schumacher
,
Zhe Feng
, and
Samson Hagos

Abstract

Radar-based latent heating retrievals typically apply a lookup table (LUT) derived from model output to surface rain amounts and rain type to determine the vertical structure of heating. In this study, a method has been developed that uses the size characteristics of precipitating systems (i.e., area and mean echo-top height) instead of rain amount to estimate latent heating profiles from radar observations. This technique [named the convective–stratiform area (CSA) algorithm] leverages the relationship between the organization of convective systems and the structure of latent heating profiles and avoids pitfalls associated with retrieving accurate rainfall information from radars and models. The CSA LUTs are based on a high-resolution regional model simulation over the equatorial Indian Ocean. The CSA LUTs show that convective latent heating increases in magnitude and height as area and echo-top heights grow, with a congestus signature of midlevel cooling for less vertically extensive convective systems. Stratiform latent heating varies weakly in vertical structure, but its magnitude is strongly linked to area and mean echo-top heights. The CSA LUT was applied to radar observations collected during the DYNAMO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY2011)/ARM MJO Investigation Experiment (AMIE) field campaign, and the CSA heating retrieval was generally consistent with other measures of heating profiles. The impact of resolution and spatial mismatch between the model and radar grids is addressed, and unrealistic latent heating profiles in the stratiform LUT, namely, a low-level heating peak, an elevated melting layer, and net column cooling, were identified. These issues highlight the need for accurate convective–stratiform separations and improvement in PBL and microphysical parameterizations.

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Wenjun Cui
,
Xiquan Dong
,
Baike Xi
, and
Zhe Feng

Abstract

This study uses machine-learning methods, specifically the random-forests (RF) method, on a radar-based mesoscale convective system (MCS) tracking dataset to classify the five types of linear MCS morphology in the contiguous United States during the period 2004–16. The algorithm is trained using radar- and satellite-derived spatial and morphological parameters, along with reanalysis environmental information from a 5-yr manually identified nonlinear mode and five linear MCS modes. The algorithm is then used to automate the classification of linear MCSs over 8 years with high accuracy, providing a systematic, long-term climatology of linear MCSs. Results reveal that nearly 40% of MCSs are classified as linear MCSs, of which one-half of the linear events belong to the type of system having a leading convective line. The occurrence of linear MCSs shows large annual and seasonal variations. On average, 113 linear MCSs occur annually during the warm season (March–October), with most of these events clustered from May through August in the central eastern Great Plains. MCS characteristics, including duration, propagation speed, orientation, and system cloud size, have large variability among the different linear modes. The systems having a trailing convective line and the systems having a back-building area of convection typically move more slowly and have higher precipitation rate, and thus they have higher potential for producing extreme rainfall and flash flooding. Analysis of the environmental conditions associated with linear MCSs show that the storm-relative flow is of most importance in determining the organization mode of linear MCSs.

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Nana Liu
,
L. Ruby Leung
, and
Zhe Feng

Abstract

The distribution of latent heating released by mesoscale convective systems (MCSs) plays a crucial role in global energy and water cycles. To investigate the characteristics of MCS latent heating, five years (2014–19) of Global Precipitation Measurement (GPM) Ku-band Precipitation Radar observations and latent heating retrievals are combined with a newly developed global high-resolution (~10 km, hourly) MCS tracking dataset. The results suggest that midlatitude MCSs are shallower and have a lower maximum precipitation rate than tropical MCSs. However, MCSs occurring in the midlatitudes have larger precipitation areas and higher stratiform rain volume fraction, in agreement with previous studies. With substantial spatial and seasonal variability, MCS latent heating profiles are top-heavier in the middle and high latitudes than those in the tropics. Larger magnitudes of latent heating in the stratiform regions are found over the ocean than over land, which is the case for both the tropics and midlatitudes. The larger magnitude is related to a larger precipitating area/volume rather than a higher storm height or more intense convective core typically associated with land systems. A majority of midlatitude MCSs have a relatively high (>70%) stratiform fraction while this is not the case for tropical MCSs, suggesting that midlatitude MCSs tend to produce more stratiform rain while tropical MCSs are more convective. Importantly, the results of this study indicate that storm intensity, latent heating, and rainfall are different metrics of MCSs that can provide multiple constraints to inform development of convection parameterizations in global models.

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Huancui Hu
,
L. Ruby Leung
, and
Zhe Feng

ABSTRACT

Warm-season rainfall associated with mesoscale convective systems (MCSs) in the central United States is characterized by higher intensity and nocturnal timing compared to rainfall from non-MCS systems, suggesting their potentially different footprints on the land surface. To differentiate the impacts of MCS and non-MCS rainfall on the surface water balance, a water tracer tool embedded in the Noah land surface model with multiparameterization options (WT-Noah-MP) is used to numerically “tag” water from MCS and non-MCS rainfall separately during April–August (1997–2018) and track their transit in the terrestrial system. From the water-tagging results, over 50% of warm-season rainfall leaves the surface–subsurface system through evapotranspiration by the end of August, but non-MCS rainfall contributes a larger fraction. However, MCS rainfall plays a more important role in generating surface runoff. These differences are mostly attributed to the rainfall intensity differences. The higher-intensity MCS rainfall tends to produce more surface runoff through infiltration excess flow and drives a deeper penetration of the rainwater into the soil. Over 70% of the top 10th percentile runoff is contributed by MCS rainfall, demonstrating its important contribution to local flooding. In contrast, lower-intensity non-MCS rainfall resides mostly in the top layer and contributes more to evapotranspiration through soil evaporation. Diurnal timing of rainfall has negligible effects on the flux partitioning for both MCS and non-MCS rainfall. Differences in soil moisture profiles for MCS and non-MCS rainfall and the resultant evapotranspiration suggest differences in their roles in soil moisture–precipitation feedbacks and ecohydrology.

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Huancui Hu
,
Zhe Feng
, and
L. Ruby Leung

Abstract

Mesoscale convective systems (MCSs) that are clustered in time and space can have a broader impact on flooding because they have larger area coverage than that of individual MCSs. The goal of this study is to understand the flood likelihood associated with MCS clusters. To achieve this, floods in the Storm Events Database in April–August of 2007–17 are matched with clustered MCSs identified from a high-resolution MCS dataset and terrestrial conditions in a land surface dataset over the central-eastern United States. Our analysis indicates that clustered MCSs preferentially occurring in April–June are more effective at producing floods, which also last longer due to the greater rainfall per area and wetter initial soil conditions and, hence, produce greater runoff per area than nonclustered MCSs. Similar increases of flood occurrence with cluster-total rainfall size and wetter soils are also observed for each MCS cluster, especially for the overlapping rainfall areas within each cluster. These areas receive rainfall from multiple MCSs that progressively wet the soils and are therefore associated with higher flood likelihood. This study underscores the importance to understand clustered MCSs to better understand flood risks and their future changes.

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Jian-Feng Gu
,
Zhe-Min Tan
, and
Xin Qiu

Abstract

A suite of idealized simulations of tropical cyclones (TCs) with weak to strong vertical wind shear (VWS) imposed during the mature stage was employed to examine the effects of VWS on the inner-core thermodynamics and intensity change of TCs using a three-dimensional full-physics numerical model as well as a budget analysis of moist entropy. For sheared TCs with shear-induced convective asymmetries, VWS tends to reduce moist entropy within the midlevel eyewall and the boundary layer (BL) but supply moist entropy outside the eyewall above the BL. Such changes in moist entropy reduce the radial gradient of moist entropy across the eyewall, resulting in weakening of the TC. Budget analysis showed that the intense eddy fluxes are mainly responsible for the reduction and/or increase in entropy in the sheared TCs. The entropy reduction within the midlevel eyewall is a result of both the radial eddy flux and the vertical eddy flux. These eddy fluxes are effective at introducing low-entropy air into the midlevel eyewall. Accompanying the flushing of midlevel low-entropy air into the BL, there is an increase in moist entropy outside the eyewall above the BL due to the upward transport of moisture from the BL by shear-induced convection. This represents a new potential pathway to further restrain the radial gradient of moist entropy across the eyewall and hence TC intensity in the sheared environmental flow.

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Jian-Feng Gu
,
Zhe-Min Tan
, and
Xin Qiu

Abstract

This study investigates the quadrant-by-quadrant evolution of the low-level tangential wind near the eyewall of an idealized simulated mature tropical cyclone embedded in a unidirectional shear flow. It is found that the quadrant-averaged tangential wind in the right-of-shear quadrants weakens continuously, while that in the left-of-shear quadrants experiences a two-stage evolution: a quasi-steady stage followed by a weakening stage after the imposing of vertical wind shear. This leads to a larger weakening rate in the right-of-shear and a stronger jet in the left-of-shear quadrants. The budget analysis shows that the quadrant-dependent evolution of tangential wind is controlled through the balance between the generalized Coriolis force (GCF; i.e., the radial advection of absolute angular momentum) and the advection terms. The steady decreasing of the GCF is primarily responsible for the continuous weakening of jet strength in the right-of-shear quadrants. For the left-of-shear quadrants, the quasi-steady stage is due to the opposite contributions by the enhanced GCF and negative tendency of advections cancelling out each other. The later weakening stage is the result of both the decreased GCF and the negative tangential advection. The combination of storm-relative flows at vortex scale and the convection strength both within and outside the eyewall determines the evolution of boundary layer inflow asymmetries, which in turn results in the change of GCF, leading to the quadrant-dependent evolution of low-level jet strength and thus the overall storm intensity change.

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Jian-Feng Gu
,
Zhe-Min Tan
, and
Xin Qiu

Abstract

Recent studies have demonstrated the importance of moist dynamics on the intensification variability of tropical cyclones (TCs) in directional shear flows. Here, we propose that dry dynamics can account for many aspects of the structure change of TCs in moist simulations. The change of vortex tilt with height and time essentially determines the kinematic and thermodynamic structure of TCs experiencing directional shear flows, depending on how the environmental flow rotates with height, that is, in a clockwise (CW) or counterclockwise (CC) fashion. The vortex tilt precesses faster and is closer to the left-of-shear (with respect to the deep-layer shear) region, with a smaller magnitude at equilibrium in CW hodographs than in CC hodographs. The low-level vortex tilt and accordingly more low-level upward motions are ahead of the overall vortex tilt in CW hodographs but are behind the overall vortex tilt in CC hodographs. Such a configuration of vortex tilt in CW hodographs is potentially favorable for the continuous precession of convection into the upshear region but in CC hodographs it is unfavorable. Most of the upward motions within a TC undergoing CW shear are concentrated in the downshear-left region, whereas those in the CC shear are located in the downshear-right region. Moreover, the upward (downward) motions are in phase with positive (negative) local helicity in both CW and CC hodographs. Here, we present an alternative mechanism that is associated with balanced dynamics in response to vortex tilt to explain the coincidence and also the distribution variability of vertical motions, as well as local helicity in directional shear flows. The balanced dynamics could explain the overlap of positive helicity and convection in both moist simulations and observations.

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Jian-Feng Gu
,
Zhe-Min Tan
, and
Xin Qiu

Abstract

The coupling of vortex tilt and convection, and their effects on the intensification variability of tropical cyclones (TCs) in directional shear flows, is investigated in this study. The height-dependent vortex tilt controls TC structural differences in clockwise (CW) and counterclockwise (CC) hodographs during their initial stage of development. Moist convection may enhance the coupling between displaced vortices at different levels and thus reduce the vortex tilt amplitude and enhance precession of the overall vortex tilt during the early stage of development. However, differences in the overall vortex tilt between CW and CC hodographs are further amplified by a feedback from convective heating and therefore result in much higher intensification rates for TCs in CW hodographs than those in CC hodographs. In CW hodographs, convection organization in the left-of-shear region is favored because the low-level vortex tilt is ahead of the overall vortex tilt and the TC moves to the left side of the deep-layer shear. This results in a more humid midtroposphere and stronger surface heat flux on the left side (azimuthally downwind) of the overall vortex tilt, thus providing a positive feedback and supporting continuous precession of the vortex tilt into the upshear-left region. In CC hodographs, convection tends to organize on the right side (azimuthally upwind) of the overall vortex tilt because the low-level vortex tilt is behind the overall vortex tilt and the TC moves to the right side of the deep-layer shear. In addition, convection organizes radially outward near the downshear-right region, which weakens convection within the inner region. These configurations lead to a drier midtroposphere and weaker surface heat flux in the downwind region of the overall vortex tilt and also a broader potential vorticity skirt. As a result, a negative feedback is established that prevents continuous precession of the overall vortex tilt.

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