Symbiotic Relationship between Meiyu Rainfall and the Morphology of Meiyu Front

Observational evidences from a heavy precipitation event of the 2020 extreme Meiyu season are presented here to reveal a symbiotic relationship between Meiyu rainfall and the morphology of Meiyu front. The two influence each other through dynamical and thermodynamic feedbacks and evolve in a coherent way to generate cyclic behaviors. Specifically, an intense and band-shaped Meiyu front leads to symmetrical instability in the lower atmospheric layer and convective instability in the middle atmospheric layer, forming a rain band along the front. The Meiyu front and its associated instability subsequently weakens as a result of rainfall and the front is bent by the process of tilting frontolysis. Deep convective instability in the middle and lower layers develops in the warm-humid prefrontal area, and triggers isolated heavy rainfall replacing the original rain band south of the bent front. This warm sector precipitation then strengthens the front through tilting and diabatic heating frontogenesis. A stronger front recovers its initial band shape and the associated rainfall also resumes the form of rain band along the front. Analyses of potential energy associated with instability, water vapor convergence, and cross-frontal circulation are carried out to illustrate key processes of this Meiyu front-rainfall cycle. The implications of this symbiotic relationship for simulating and predicting extreme rainfall associated with Meiyu fronts are presented.

Evaluating the Forecast Performance of the Meiyu Front Rainbelt Position: A Case Study of the 30 June to 4 July 2016 Extreme Rainfall Event

An impactful and poorly forecasted heavy rainfall event was observed in association with the Meiyu front over the Yangtze River valley of China from 30 June–4 July 2016. Operational global numerical weather prediction models for almost all forecast lead times beyond 24 h incorrectly forecasted the location and intensity of the precipitation associated with this event. This study presents the first examination of this poleward bias in the operational models for the Meiyu front, which has been frequently noted by meteorologists at the Chinese Meteorological Administration, and explores areas of forecast error and uncertainty in the prediction of the position of the primary frontal rainbelt that is crucial to the placement and intensity of the heavy rainfall. A new zonal mean maximum accumulated precipitation index is introduced and utilized to identify members in the European Centre for Medium-Range Forecasts (ECMWF) Ensemble Prediction System (EPS) that either perform well or perform poorly in forecasting the location of the Meiyu front. Using this new precipitation metric, five-member subgroups representing the EPS members that were most accurate and those that incorrectly displace the Meiyu front the furthest north were identified. An analysis of composite mean fields for the EPS subgroups and the correlation between the rain band placement and the 500 hPa heights was performed for several EPS model runs. We showed that a successful prediction of the location of the Meiyu front rainbelt position by the EPS is most sensitive to the intensity of the 500 hPa trough located over eastern China for the event. The ensemble members that had the largest northward error in the location of the rain band were found to have a more intense 500 hPa trough than the members that more accurately predicted the rainbelt. The more intense upper level trough was found to have enhanced the lower tropospheric southerly flow equatorward of the front and led to a less zonal-oriented Meiyu front, resulting in a northward displacement of both the rainbelt and the regions of more intense precipitation rates. Finally, an examination of the evolution of the differences between the subgroups shows that the primary differences in 500 hPa intensity propagate in-phase with the 500 hPa trough. We show that it is the intensity of the trough, rather than the rate of propagation, that is the most important source of forecast dissimilarities between the successful and failed forecasts.

‘Eastern African Paradox’ rainfall decline due to shorter not less intense Long Rains

An observed decline in the Eastern African Long Rains from the 1980s to late 2000s appears contrary to the projected increase under future climate change. This “Eastern African climate paradox” confounds use of climate projections for adaptation planning across Eastern Africa. Here we show the decline corresponds to a later onset and earlier cessation of the long rains, with a similar seasonal maximum in area-averaged daily rainfall. Previous studies have explored the role of remote teleconnections, but those mechanisms do not sufficiently explain the decline or the newly identified change in seasonality. Using a large ensemble of observations, reanalyses and atmospheric simulations, we propose a regional mechanism that explains both the observed decline and the recent partial recovery. A decrease in surface pressure over Arabia and warmer north Arabian Sea is associated with enhanced southerlies and an earlier cessation of the long rains. This is supported by a similar signal in surface pressure in many atmosphere-only models giving lower May rainfall and an earlier cessation. Anomalously warm seas south of Eastern Africa delay the northward movement of the tropical rain-band, giving a later onset. These results are key in understanding the paradox. It is now a priority to establish the balance of mechanisms that have led to these trends, which are partially captured in atmosphere-only simulations.

Vortex Identification across Different Scales

Vortex identification in atmospheric data remains a challenge. One reason is the general presence of shear throughout the atmosphere that interferes with traditional vortex identification methods based on geopotential height or vorticity. Alternatively, kinematic methods can avoid some of the drawbacks of the traditional methods since they compare the rotational and deformational flow parts. In this work, we apply the kinematic vorticity number method ( W k -method) to atmospheric datasets ranging from the synoptic to the convective scales. The W k -method is tested for winter storm Kyrill, a high-impact extratropical cyclone that affected Germany in January 2007. This case is especially challenging for vortex identification methods since it produced a complex wind occurrence associated with a derecho along a narrow cold-frontal rain band and an area of high winds close to the low pressure center. The W k -method is able to identify vortices in differently-resolved datasets and at different height levels in a consistent manner. Additionally, it is able to determine and visualize the storm characteristics. As a result, we discovered that the total positive circulation of the vortices associated with Kyrill remains of similar order across different data sets though the vorticity magnitude of the most intense vortices increases with increasing resolution.