Toward Understanding the Extreme Floods over Yangtze River Valley in June−July 2020:Role of Tropical Oceans

The extreme floods in the Middle/Lower Yangtze River Valley(MLYRV)during June−July 2020 caused more than 170 billion Chinese Yuan direct economic losses.Here,we examine the key features related to this extreme event and explore relative contributions of SST anomalies in different tropical oceans.Our results reveal that the extreme floods over the MLYRV were tightly related to a strong anomalous anticyclone persisting over the western North Pacific,which brought tropical warm moisture northward that converged over the MLYRV.In addition,despite the absence of a strong El Niño in 2019/2020 winter,the mean SST anomaly in the tropical Indian Ocean during June−July 2020 reached its highest value over the last 40 years,and 43%(57%)of it is attributed to the multi-decadal warming trend(interannual variability).Based on the NUIST CFS1.0 model that successfully predicted the wet conditions over the MLYRV in summer 2020 initiated from 1 March 2020(albeit the magnitude of the predicted precipitation was only about one-seventh of the observed),sensitivity experiment results suggest that the warm SST condition in the Indian Ocean played a dominant role in generating the extreme floods,compared to the contributions of SST anomalies in the Maritime Continent,central and eastern equatorial Pacific,and North Atlantic.Furthermore,both the multi-decadal warming trend and the interannual variability of the Indian Ocean SSTs had positive impacts on the extreme floods.Our results imply that the strong multi-decadal warming trend in the Indian Ocean needs to be taken into consideration for the prediction/projection of summer extreme floods over the MLYRV in the future.

Effects of diurnal adjustment on biases and trends derived from inter-sensor calibrated AMSU-A data

Measurements of brightness temperatures from Advanced Microwave Sounding Unit-A （AMSU-A） temperature sounding instruments onboard NOAA Polar- orbiting Operational Environmental Satellites （POES） have been extensively used for studying atmospheric temperature trends over the past several decades. Inter- sensor biases, orbital drifts and diurnal variations of atmospheric and surface temperatures must be considered before using a merged long-term time series of AMSU-A measurements from NOAA- 15, - 18, - 19 and MetOp-A. We study the impacts of the orbital drift and orbital differences of local equator crossing times （LECTs） on temperature trends derivable from AMSU-A using near-nadir observa- tions from NOAA-15, NOAA-18, NOAA-19, and MetOp-A during 1998 - 2014 over the Amazon rainforest. The double difference method is firstly applied to estimation of inter-sensor biases between any two satellites during their overlapping time period. The inter-calibrated observations are then used to generate a monthly mean diurnal cycle of brightness temperature for each AMSU-A channel. A diurnal correction is finally applied each channel to obtain AMSU-A data valid at the same local time. Impacts of the inter-sensor bias correction and diurnal correction on the AMSU-A derived long-term atmospheric temperature trends are separately quantified and compared with those derived from original data. It is shown that the orbital drift and differences of LECT among different POESs induce a large uncertainty in AMSU-A derived long-term warming/cooling trends. After applying an inter-sensor bias correction and a diurnal correction, the warming trends at different local times, which are approximately the same, are smaller by half than the trends derived without applying these corrections.

中东沙尘活动年代际趋势的转变归因于热带大西洋的海温变率

中东作为世界第二大沙尘源区,其沙尘的排放影响了从北美到南亚的众多人口稠密地区.在过去20年中,中东地区的沙尘活动呈现出明显的趋势转变,即在2010年左右,其趋势由增长变为下降.而目前造成这种趋势转变的原因尚不清楚.本研究结合多源数据分析和全球气候模式模拟,揭示了中东沙尘的年代际趋势转变与热带北大西洋海表面温度的变化密切相关.具体而言,偏暖的热带北大西洋产生了异常的局地纬向环流,促进了气流在热带北大西洋的上升和在中东的下沉.由此产生的地表高压和北部更强的沙马尔风为中东创造了炎热和干燥的环境,这都有利于沙尘的排放和运输.因此,2010年前后热带北大西洋趋势由正转负是中东沙尘趋势变化的主要原因.该机制对预测中东地区的年代际沙尘变化乃至全球环境都具有重要意义.

Evaluation of the influence of El Niño–Southern Oscillation on air quality in southern China from long-term historical observations

Previous studies demonstrated that the El Niño–Southern Oscillation(ENSO)could modulate regional climate thus influencing air quality in the low-middle latitude regions like southern China.However,such influence has not been well evaluated at a long-term historical scale.To filling the gap,this study investigated two-decade(2002 to 2020)aerosol concentration and particle size in southern China during the whole dynamic development of ENSO phases.Results suggest strong positive correlations between aerosol optical depth(AOD)and ENSO phases,as low AOD occurred during El Niño while high AOD occurred during La Niña event.Such correlations are mainly attributed to the variation of atmospheric circulation and precipitation during corresponding ENSO phase.Analysis of the angstrom exponent(AE)anomalies further confirmed the circulation pattern,as negative AE anomalies is pronounced in El Niño indicating the enhanced transport of sea salt aerosols from the South China Sea,while the La Niña event exhibits positive AE anomalies which can be attributed to the enhanced import of northern fine anthropogenic aerosols.This study further quantified the AOD variation attributed to changes in ENSO phases and anthropogenic emissions.Results suggest that the long-term AOD variation from 2002 to 2020 in southern China is mostly driven(by 64.2%)by the change of anthropogenic emissions from 2002 to 2020.However,the ENSO presents dominant influence(70.5%)on year-to-year variations of AOD during 2002–2020,implying the importance of ENSO on varying aerosol concentration in a short-term period.