Advances in Atmospheric Sciences最新文献

The impacts of hydrometeor-related processes on the development and evolution of the “21·7” extremely heavy rainfall in Zhengzhou were investigated using WRF simulations. Surface precipitation was determined by the hydrometeor microphysical processes (all microphysical source sink terms of hydrometeors) and macrophysical processes (local change and flux convergence of hydrometeors). The contribution of hydrometeor macrophysical processes was commonly less than 10%, but could reach 30%–50% in the early stage of precipitation, which was largely dependent on the size of the study area. The macrophysical processes of liquid-phase hydrometeors always presented a promotional effect on rainfall, while the ice-phase hydrometeors played a negative role in the middle and later stages of precipitation. The distributions of microphysical latent heat corresponded well with those of buoyancy and vertical velocity (tendency), indicating that the phase-change heating was the major driver for convective development. Reasonable diagnostic buoyancy was obtained by choosing an area close to the convective size for getting the reference state of air. In addition, a new dynamic equilibrium involving hydrometeors with a tilted airflow was formed during the heavy precipitation period (updraft was not the strongest). The heaviest instantaneous precipitation was mainly produced by the warm-rain processes. Sensitivity experiments further pointed out that the uncertainty of latent heat parameterization (±20%) did not significantly affect the convective rainfall. While when the phase-change heating only altered the temperature tendency, its impact on precipitation was remarkable. The results of this study help to deepen our understanding of heavy rainfall mechanisms from the perspective of hydrometeor processes.

Quantifying differences in secondary organic aerosols (SOAs) between the preindustrial period and the present day is crucial to assess climate forcing and environmental effects resulting from anthropogenic activities. The lack of vegetation information for the preindustrial period and the uncertainties in describing SOA formation are two leading factors preventing simulation of SOA. This study calculated the online emissions of biogenic volatile organic compounds (VOCs) in the Aerosol and Atmospheric Chemistry Model of the Institute of Atmospheric Physics (IAP-AACM) by coupling the Model of Emissions of Gases and Aerosols from Nature (MEGAN), where the input vegetation parameters were simulated by the IAP Dynamic Global Vegetation Model (IAP-DGVM). The volatility basis set (VBS) approach was adopted to simulate SOA formation from the nontraditional pathways, i.e., the oxidation of intermediate VOCs and aging of primary organic aerosol. Although biogenic SOAs (BSOAs) were dominant in SOAs globally in the preindustrial period, the contribution of nontraditional anthropogenic SOAs (ASOAs) to the total SOAs was up to 35.7%. In the present day, the contribution of ASOAs was 2.8 times larger than that in the preindustrial period. The contribution of nontraditional sources of SOAs to SOA was as high as 53.1%. The influence of increased anthropogenic emissions in the present day on BSOA concentrations was greater than that of increased biogenic emission changes. The response of BSOA concentrations to anthropogenic emission changes in the present day was more sensitive than that in the preindustrial period. The nontraditional sources and the atmospheric oxidation capability greatly affect the global SOA change.

There is limited understanding regarding the formation of multiple tropical cyclones (MTCs). This study explores the environmental conditions conducive to MTC formation by objectively determining the atmospheric circulation patterns favorable for MTC formation over the western North Pacific. Based on 199 MTC events occurring from June to October 1980–2020, four distinct circulation patterns are identified: the monsoon trough (MT) pattern, accounting for 40.3% of occurrences, the confluence zone (CON) pattern at 26.2%, the easterly wave (EW) pattern at 17.8%, and the monsoon gyre (MG) pattern at 15.7%. The MT pattern mainly arises from the interaction between the subtropical high and the monsoon trough, with MTCs forming along the monsoon trough and its flanks. The CON pattern is affected by the subtropical high, the South Asian high, and the monsoon trough, with MTCs emerging at the confluence zone where the prevailing southwesterly and southeasterly flows converge. The EW pattern is dominated by easterly flows, with MTCs developing along the easterly wave train. MTCs in the MG pattern arise within a monsoon vortex characterized by strong southwesterly flows. A quantitative analysis further indicates that MTC formation in the MT pattern is primarily governed by mid-level vertical velocity and low-level vorticity, while mid-level humidity and vertical velocity are significantly important in the other patterns. The meridional shear and convergence of zonal winds are essential in converting barotropic energy from the basic flows to disturbance kinetic energy, acting as the primary source for eddy kinetic energy growth.

Besides the rapid retreating trend of Arctic sea-ice extent (SIE), this study found the most outstanding low-frequency variation of SIE to be a 4–6-year periodic variation. Using a clustering analysis algorithm, the SIE in most ice-covered regions was clustered into two special regions: Region-1 around the Barents Sea and Region-2 around the Canadian Basin, which were located on either side of the Arctic Transpolar Drift. Clear 4–6-year periodic variation in these two regions was identified using a novel method called “running linear fitting algorithm”. The rate of temporal variation of the Arctic SIE was related to three driving factors: the regional air temperature, the sea-ice areal flux across the Arctic Transpolar Drift, and the divergence of sea-ice drift. The 4–6-year periodic variation was found to have always been present since 1979, but the SIE responded to different factors under heavy and light ice conditions divided by the year 2005. The joint contribution of the three factors to SIE variation exceeded 83% and 59% in the two regions, respectively, remarkably reflecting their dynamic mechanism. It is proven that the process of El Niño–Southern Oscillation (ENSO) is closely associated with the three factors, being the fundamental source of the 4–6-year periodic variations of Arctic SIE.

Various approaches have been proposed to minimize the upper-level systematic biases in global numerical weather prediction (NWP) models by using satellite upper-air sounding channels as anchors. However, since the China Meteorological Administration Global Forecast System (CMA-GFS) has a model top near 0.1 hPa (60 km), the upper-level temperature bias may exceed 4 K near 1 hPa and further extend to 5 hPa. In this study, channels 12–14 of the Advanced Microwave Sounding Unit A (AMSU-A) onboard five satellites of NOAA and METOP, whose weighting function peaks range from 10 to 2 hPa are all used as anchor observations in CMA-GFS. It is shown that the new “Anchor” approach can effectively reduce the biases near the model top and their downward propagation in three-month assimilation cycles. The bias growth rate of simulated upper-level channel observations is reduced to ±0.001 K d⁻¹, compared to −0.03 K d⁻¹ derived from the current dynamic correction scheme. The relatively stable bias significantly improves the upper-level analysis field and leads to better global medium-range forecasts up to 10 days with significant reductions in the temperature and geopotential forecast error above 10 hPa.

This study investigates the dominant modes of interannual variability of snowfall frequency over the Eurasian continent during autumn and winter, and explores the underlying physical mechanisms. The first EOF mode (EOF1) of snowfall frequency during autumn is mainly characterized by positive anomalies over the Central Siberian Plateau (CSP) and Europe, with opposite anomalies over Central Asia (CA). EOF1 during winter is characterized by positive anomalies in Siberia and negative anomalies in Europe and East Asia (EA). During autumn, EOF1 is associated with the anomalous sea ice in the Kara–Laptev seas (KLS) and sea surface temperature (SST) over the North Atlantic. Increased sea ice in the KLS may cause an increase in the meridional air temperature gradient, resulting in increased synoptic-scale wave activity, thereby inducing increased snowfall frequency over Europe and the CSP. Anomalous increases of both sea ice in the KLS and SST in the North Atlantic may stimulate downstream propagation of Rossby waves and induce an anomalous high in CA corresponding to decreased snowfall frequency. In contrast, EOF1 is mainly affected by the anomalous atmospheric circulation during winter. In the positive phase of the North Atlantic Oscillation (NAO), an anomalous deep cold low (warm high) occurs over Siberia (Europe) leading to increased (decreased) snowfall frequency over Siberia (Europe). The synoptic-scale wave activity excited by the positive NAO can induce downstream Rossby wave propagation and contribute to an anomalous high and descending motion over EA, which may inhibit snowfall. The NAO in winter may be modulated by the Indian Ocean dipole and sea ice in the Barents-Kara-Laptev Seas in autumn.

This paper presents a method for retrieving optical parameters from volcanic sulfate aerosols from the AHI radiometer on board the Himawari-8 satellite. The proposed method is based on optical models for various mixtures of aerosol components from volcanic clouds, including ash particles, ice crystals, water drops, and sulfate aerosol droplets. The application of multi-component optical models of various aerosol compositions allows for the optical thickness and mass loading of sulfate aerosol to be estimated in the sulfuric cloud formed after the Karymsky volcano eruption on 3 November 2021. A comprehensive analysis of the brightness temperatures of the sulfuric cloud in the infrared bands was performed, which revealed that the cloud was composed of a mixture of sulfate aerosol and water droplets. Using models of various aerosol compositions allows for the satellite-based estimation of optical parameters not only for sulfate aerosol but also for the whole aerosol mixture.

Under global warming, understanding the long-term variation in different types of heatwaves is vital for China’s preparedness against escalating heat stress. This study investigates dry and wet heatwave shifts in eastern China over recent decades. Spatial trend analysis displays pronounced warming in inland midlatitudes and the Yangtze River Valley, with increased humidity in coastal regions. EOF results indicate intensifying dry heatwaves in northern China, while the Yangtze River Valley sees more frequent dry heatwaves. On the other hand, Indochina and regions north of 25°N also experience intensified wet heatwaves, corresponding to regional humidity increases. Composite analysis is conducted based on different situations: strong, frequent dry or wet heatwaves. Strong dry heatwaves are influenced by anticyclonic circulations over northern China, accompanied by warming SST anomalies around the coastal midlatitudes of the western North Pacific (WNP). Frequent dry heatwaves are related to strong subsidence along with a strengthened subtropical high over the WNP. Strong and frequent wet heatwaves show an intensified Okhotsk high at higher latitudes in the lower troposphere, and a negative circumglobal teleconnection wave train pattern in the upper troposphere. Decaying El Niño SST patterns are observed in two kinds of wet heatwave and frequent dry heatwave years. Risk analysis indicates that El Niño events heighten the likelihood of these heatwaves in regions most at risk. As global warming continues, adapting and implementing mitigation strategies toward extreme heatwaves becomes crucial, especially for the aforementioned regions under significant heat stress.

Changes in the activities of the Boreal Summer Intraseasonal Oscillation (BSISO) at the end of 21st century under the SSP5-8.5 scenario are assessed by adopting 17 CMIP6 models and the weak-temperature-gradient assumption. Results show that the intraseasonal variations become more structured. The BSISO-related precipitation anomaly shows a larger zonal scale and propagates further northward. However, there is no broad agreement among models on the changes in the eastward and northward propagation speeds and the frequency of individual phases.

In the western North Pacific (WNP), the BSISO precipitation variance is significantly increased, at 4.62% K⁻¹, due to the significantly increased efficiency of vertical moisture transport per unit of BSISO apparent heating. The vertical velocity variance is significantly decreased, at −3.51% K⁻¹, in the middle troposphere, due to the significantly increased mean-state static stability. Changes in the lower-level zonal wind variance are relatively complex, with a significant increase stretching from the northwestern to southeastern WNP, but the opposite in other regions. This is probably due to the combined impacts of the northeastward shift of the BSISO signals and the reduced BSISO vertical velocity variance under global warming.

Changes in strong and normal BSISO events in the WNP are also compared. They show same-signed changes in precipitation and large-scale circulation anomalies but opposite changes in the vertical velocity anomalies. This is probably because the precipitation anomaly of strong (normal) events changes at a rate much larger (smaller) than that of the mean-state static stability, causing enhanced (reduced) vertical motion.

Due to the considerable uncertainties inherent in the datasets describing the spatiotemporal distributions of precipitation in the drylands of China, this study presents a new merged monthly precipitation product with a spatial resolution of approximately 0.2° × 0.2° during 1980–2019. The newly developed precipitation product was validated at different temporal scales (e.g., monthly, seasonally, and annually). The results show that the new product consistently aligns with the spatiotemporal distributions reported by the Chinese Meteorological Administration Land Data Assimilation System (CLDAS) product and Multi-Source Weighted Ensemble Precipitation (MSWEP). The merged product exhibits exceptional quality in describing the drylands of China, with a bias of −2.19 mm month⁻¹ relative to MSWEP. In addition, the annual trend of the merged product (0.09 mm month⁻¹ yr⁻¹) also closely aligns with that of the MSWEP (0.11 mm month⁻¹ yr⁻¹) during 1980–2019. The increasing trend indicates that the water cycle and wetting process intensified in the drylands of China during this period. In particular, there was an increase in wetting during the period from 2001–2019. Generally, the merged product exhibits potential value for improving our understanding of the climate and water cycle in the drylands of China.