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Yaping Wang
,
Xiaopeng Cui
,
Xiaofan Li
,
Wenlong Zhang
, and
Yongjie Huang

Abstract

A set of kinetic energy (KE) budget equations associated with four horizontal flow components was derived to study the KE characteristics during the genesis of Tropical Cyclone (TC) Durian (2001) in the South China Sea using numerical simulation data. The genesis process was divided into three stages: the monsoon trough stage (stage 1), the midlevel mesoscale convective vortex (MCV) stage (stage 2), and the establishment stage of the TC vortex (stage 3). Analysis showed that the KE of the symmetric rotational flow (SRF) was the largest and kept increasing, especially in stages 2 and 3, representing the symmetrization process during TC genesis. The KE of the SRF was mainly converted from the KE of the symmetric divergent flow (SDF), largely transformed from the available potential energy (APE). It was found that vortical hot towers (VHTs) emerged abundantly, aggregated, and merged within the MCV region in stages 1 and 2. From the energy budget perspective, massive moist-convection-produced latent heat was concentrated and accumulated within the MCV region, especially in stage 2, and further warmed the atmosphere, benefiting the accumulation of APE and the transformation from APE to KE. As a result, the midlevel circulation (or MCV) grew strong rapidly. In stage 3, the intensity and number of VHTs both decreased. However, affected by increasing lower-level inward radial wind, latent heat released by the organized convection, instead of disorganized VHTs in the first two stages, continuously contributed to the strengthening of the surface TC circulation as well as the warm core.

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Yongjie Huang
,
Xuguang Wang
,
Christopher Kerr
,
Andrew Mahre
,
Tian-You Yu
, and
David Bodine

Abstract

Phased-array radar (PAR) technology offers the flexibility of sampling the storm and clear-air regions with different update times. As such, the radial velocity from clear-air regions, typically with a lower signal-to-noise ratio, can be measured more accurately. In this work, observing system simulation experiments are conducted to explore the potential value of assimilating clear-air radial velocity observations to improve numerical prediction of supercell thunderstorms. Synthetic PAR observations of a splitting supercell are assimilated at different life cycle stages using an ensemble Kalman filter. Results show that assimilating environmental clear-air radial velocity can reduce wind errors in the near-storm environment and within the precipitation region. Improvements in the forecast are seen at different stages, especially for the forecast after 30 min. After assimilating clear-air radial velocity observations, the probabilities of updraft helicity and precipitation within the corresponding swaths of the truth simulation increase up to 30%–40%. Additional diagnostics suggest that the more accurate track forecast, stronger vertical motion, and better-maintained supercell can be attributed to the better analysis and prediction of the mean environmental winds and linear and nonlinear dynamic forces. Consequently, assimilating clear-air radial velocity produces accurate storm structure (rotating updrafts), updraft size, and storm track, and improves the surface accumulated precipitation forecast. The performance of forecasts with a higher frequency of assimilating clear-air radial velocity does not show systematic improvement. These results highlight the potential of assimilating clear-air radial velocity observations to improve numerical weather prediction forecasts of supercell thunderstorms.

Free access
Yongjie Huang
,
Xuguang Wang
,
Andrew Mahre
,
Tian-You Yu
, and
David Bodine

Abstract

Phased-array radar (PAR) technology can potentially provide high-quality clear-air radial velocity observations at a high spatiotemporal resolution, usually ∼1 min or less. These observations are hypothesized to partially fill the gaps in current operational observing systems with relatively coarse-resolution surface mesonet observations and the lack of high-resolution upper-air observations especially in planetary boundary layer. In this study, observing system simulation experiments are conducted to investigate the potential value of assimilating PAR observations of clear-air radial velocity to improve the forecast of convection initiation (CI) along small-scale boundary layer convergence zones. Both surface-based and elevated CIs driven by meso-γ-scale boundary layer convergence are tested. An ensemble Kalman filter method is used to assimilate synthetic surface mesonet observations and PAR clear-air radial velocity observations. Results show that assimilating only surface mesonet observations fails to predict either surface-based or elevated CI processes. Assimilating clear-air radial velocity observations in addition to surface mesonet observations can capture both surface-based and elevated CI processes successfully. Such an improvement benefits from the better analyses of boundary layer convergence, resulting from the assimilation of clear-air radial velocity observations. Additional improvement is observed with more frequent assimilation. Assimilating clear-air radial velocity observations only from the one radar results in analysis biases of cross-beam winds and CI location biases, and assimilating additional radial velocity observations from the second radar at an appropriate position can reduce these biases while sacrificing the CI timing. These results suggest the potential of assimilating clear-air radial velocity observations from PAR to improve the forecast of CI processes along boundary layer convergence zones.

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