A Review of Research on the Record-Breaking Precipitation Event in Henan Province,China,July 2021

A record-breaking precipitation event,with a maximum 24-h(1-h)precipitation of 624 mm(201.9 mm)observed at Zhengzhou Weather Station,occurred in Henan Province,China,in July 2021.However,all global operational forecast models failed to predict the intensity and location of maximum precipitation for this event.The unexpected heavy rainfall caused 398 deaths and 120.06 billion RMB of economic losses.The high-societal-impact of this event has drawn much attention from the research community.This article provides a research review of the event from the perspectives of observations,analysis,dynamics,predictability,and the connection with climate warming and urbanization.Global reanalysis data show that there was an anomalous large-scale circulation pattern that resulted in abundant moisture supply to the region of interest.Three mesoscale systems(a mesoscale low pressure system,a barrier jet,and downslope gravity current)were found by recent high-resolution model simulation and data assimilation studies to have contributed to the local intensification of the rainstorm.Furthermore,observational analysis has suggested that an abrupt increase in graupel through microphysical processes after the sequential merging of three convective cells contributed to the record-breaking precipitation.Although these findings have aided in our understanding of the extreme rainfall event,preliminary analysis indicated that the practical predictability of the extreme rainfall for this event was rather low.The contrary influences of climate warming and urbanization on precipitation extremes as revealed by two studies could add further challenges to the predictability.We conclude that data sharing and collaboration between meteorological and hydrological researchers will be crucial in future research on high-impact weather events.

High-resolution Simulation of an Extreme Heavy Rainfall Event in Shanghai Using the Weather Research and Forecasting Model: Sensitivity to Planetary Boundary Layer Parameterization

In this study,an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model,with a focus on the effects of planetary boundary layer(PBL)physics using double nesting with large grid ratios(15:1 and 9:1).The sensitivity of the precipitation forecast was examined through three PBL schemes:the Yonsei University Scheme,the Mellor−Yamada−Nakanishi Niino Level 2.5(MYNN)scheme,and the Mellor−Yamada−Janjic scheme.The PBL effects on boundary layer structures,convective thermodynamic and large-scale forcings were investigated to explain the model differences in extreme rainfall distributions and hourly variations.The results indicated that in single coarser grids(15 km and 9 km),the extreme rainfall amount was largely underestimated with all three PBL schemes.In the inner 1-km grid,the underestimated intensity was improved;however,using the MYNN scheme for the 1-km grid domain with explicitly resolved convection and nested within the 9-km grid using the Kain−Fritsch cumulus scheme,significant advantages over the other PBL schemes are revealed in predicting the extreme rainfall distribution and the time of primary peak rainfall.MYNN,with the weakest vertical mixing,produced the shallowest and most humid inversion layer with the lowest lifting condensation level,but stronger wind fields and upward motions from the top of the boundary layer to upper levels.These factors all facilitate the development of deep convection and moisture transport for intense precipitation,and result in its most realistic prediction of the primary rainfall peak.

The impacts of the East Asian subtropical westerly jet on weather extremes over China in early and late summer

东亚副热带西风急流是影响中国极端天气的重要原因之一,然而之前的研究主要关注整个夏季急流的变率,对其早夏和晚夏变率的区别及其对极端天气的影响关注较少.本文研究了早夏和晚夏东亚副热带西风急流季节内变化特征的区别,以及这种区别带来的极端天气的差异及其可能的动力学机制.研究结果表明,相比于早夏,晚夏急流季节内变化中心位置偏西偏北,通过改变垂直运动和水汽输送可以影响极端降水和湿热浪在相应区域的发生概率.

Development of a hybrid photo-bioreactor and nanoparticle adsorbent system for the removal of CO2,and selected organic and metal co-pollutants

Fossil fuel combustion and many industrial processes generate gaseous emissions that contain a number of toxic organic pollutants and carbon dioxide（CO_2） which contribute to climate change and atmospheric pollution.There is a need for green and sustainable solutions to remove air pollutants,as opposed to conventional techniques which can be expensive,consume additional energy and generate further waste.We developed a novel integrated bioreactor combined with recyclable iron oxide nano/micro-particle adsorption interfaces,to remove CO_2,and undesired organic air pollutants using natural particles,while generating oxygen.This semi-continuous bench-scale photo-bioreactor was shown to successfully clean up simulated emission streams of up to 45% CO_2 with a conversion rate of approximately 4%CO_2 per hour,generating a steady supply of oxygen（6 mmol/hr）,while nanoparticles effectively remove several undesired organic by-products.We also showed algal waste of the bioreactor can be used for mercury remediation.We estimated the potential CO_2 emissions that could be captured from our new method for three industrial cases in which,coal,oil and natural gas were used.With a 30% carbon capture system,the reduction of CO_2 was estimated to decrease by about 420,000,320,000 and 240,000 metric tonnes,respectively for a typical 500 MW power plant.The cost analysis we conducted showed potential to scale-up,and the entire system is recyclable and sustainable.We further discuss the implications of usage of this complete system,or as individual units,that could provide a hybrid option to existing industrial setups.