This study analyzes the spatial and temporal distribution characteristics of the in-situ aircraft observations in the middle and higher troposphere in 2019. These aircraft observations are mainly distributed in China, and relatively evenly recorded between 00-15 UTC in time and 6-10 km in height. Based on the 3,395 stronger clear-air turbulence (CAT) events and 4,038 weaker CAT events selected from the observations in the study region (15-55 °N, 70-140 °E), the performances of 24 CAT diagnostics calculated from the ERA5 reanalysis data are evaluated. Results show that the diagnostics connected with vertical wind shear (i.e. version 1 of the North Carolina State University index, negative Richardson number, variant 3 and variant 1 of Ellrod’s turbulence index) have the best performances. However, the performances vary greatly from season to season that best in winter and worst in summer. The annual and seasonal best thresholds for these diagnostics are also listed in this study.
Driven by four global coupled atmosphere–ocean models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble (CNRM‐CM5, GFDL‐ESM2M, EC‐EARTH, and MPI‐ESM‐LR), future changes (2040–2059) of clear‐air turbulence (CAT) in winter over East Asia under Representative Concentration Pathway 8.5 (RCP8.5) scenario are projected with the regional climate model (RCM) RegCM4 and 18 CAT diagnostics based on the second phase of Coordinated Regional Downscaling Experiment East Asia (CORDEX‐EA‐II) framework. Evaluation of RegCM4 with ERA‐Interim shows that RegCM4 and diagnostics can well reproduce the spatial distribution of CAT potential. The probability of CAT potential is expected to increase over most East Asia between 35°N and 50°N, Southeast China, western Pacific, and North India in the future. The CAT potential that significantly affects aviation safety shows a remarkable increase over North and Northeast China, part of East China, and Tibet‐Plateau. In the whole domain of East Asia, the multi‐diagnostics ensemble‐average frequency increase is 6.9% for light CAT (with an intra‐ensemble range of 4.1–18%), 9.1% (5.0–24%) for light‐to‐moderate CAT, 12% (5.9–26%) for moderate CAT, 13% (7.2–29%) for moderate‐to‐severe CAT, and 15% (8.5–33%) for severe CAT. Stronger CAT is more likely to happen, which would be a constant threat, although greater scatter exists among these diagnostics, which implies the uncertainties are also significant in the projection.
On 13 November 2019, seven commercial aircraft of China Eastern Airlines encountered nine severe-or-greater clear-air turbulence (CAT) events over central and eastern China within 12 hours (0000 to 1200 UTC). These events mainly occurred at altitudes between 6.0 and 6.7 km. A high-resolution nested numerical simulation is carried out using the Weather Research and Forecasting (WRF) model to investigate the generation mechanism of these CAT events, with a horizontal resolution of 1 km over the inner domain. In addition, seven CAT diagnostics with outstanding performances are employed for the mechanism analysis. The WRF model can reasonably reproduce both synoptic-scale systems (Siberian high and upper-level jet stream) and local vertical structures (temperature, dewpoint temperature, and wind field). The simulation indicates that an upper-level front-jet system with a remarkable meridional temperature gradient intensifies over central and eastern China, with the maximum wind speed increasing from 59.0 to 67.3 m s−1. The intensification of the front-jet system induces the tropopause folding, and nine localized CAT events occur in the region with large vertical wind shear (VWS) (1.55×10−2−2.53×10−2 s−1) and small Richardson numbers (Ri) (0.42-0.85) below the cyclonic side of the jet stream. Diagnostic analysis reveals that Kelvin-Helmholtz instability plays an important role in CAT generation, while convective and inertial instability is not directly associated with CAT generation in this study. A typical flight case with continuous CAT events also suggests that large VWS (greater than 1.3×10−2 s−1) accompanied with small Ri (less than 1) favors CAT generation in a front-jet system environment.
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