Atmospheric Research最新文献

The study explores Hurricane Michael's impact on Hurricane Leslie's trajectory predictability using ECMWF and NCEP ensemble systems. A clustering method focused on tropical cyclones is used to identify potential paths for Leslie: Cluster 1 accurately predicted Leslie's direction towards the Iberian Peninsula, whereas Clusters 2 and 3 indicated a southern recurve near the Canary Islands. Analysis of potential vorticity and irrotational wind at upper levels showed a significant interaction between Michael, ridge, and trough across the jet stream from +12 h after initialization. Cluster 1 showed a stronger Michael promoting upper-level wind divergence greatest, modifying the jet stream configuration around the ridge and downstream. Alterations in the jet stream's configuration, functioning as a waveguide, propagated downstream, guiding Leslie towards the Iberian Peninsula. Clusters 2 and 3 indicated the trough's failure to incorporate Leslie, resulting in a recurve of the trajectory around the Azores anticyclone. This research enhances comprehension of the interaction between two tropical cyclones via synoptic Rossby wave flow. Moreover, the conceptual framework can aid operational meteorologists in identifying the sources of uncertainty, particularly in track forecasts under synoptic conditions analogous to those examined in this study.

The Beijing-Tianjin-Hebei urban agglomeration(BTH) has successively witnessed the extraordinary precipitation extremes (PEs) with huge economic losses and death-toll in the recent decade. To timely and comprehensively understand the PEs in the urban agglomeration, we investigate the characteristic and mechanism of PEs variation based on six extreme precipitation indices (EPIs) including maximum daily precipitation(Rx1day), maximum consecutive 5-day precipitation(Rx5day), total precipitation with daily precipitation more than the 95th percentile (R95P), average daily precipitation on wet days (SDII), heavy precipitation days(R25) and very heavy precipitation days(R50). Our results suggest that the PEs of summertime over the BTH has significantly amplified since 21st century. During 2001–2023, the Rx1day, Rx5day, R95p, SDII, R25 and R50 significantly increased at a rate of 13.5 mm/10a, 26.3 mm/10a, 49.4 mm/10a, 2.2 mm/10a, 0.78d/10a and 0.46d/10a, respectively. The average contribution of urbanization to the increased EPIs is estimated by 21 %. The strengthened East Asian Summer Monsoon, intensified and northward extended West Pacific Subtropical High may increase occurrence and severity of PEs in the era of rapid global warming. Three case studies of PEs in 2012, 2016 and 2023 verify our finding. We hope this study can help policy makers to shape strategies to mitigate or reduce societal impact of PEs under global warming crisis and rapid urbanization.

This study analyzes the performance of the Climate–Weather Research and Forecasting (CWRF) model in predicting the summer temperature and precipitation in northwestern China (NWC) for the 1991–2021 period. It also examines the improvements in prediction resulting from the implementation of convolutional neural network (CNN) and long short-term memory (LSTM) downscaling methods. The results indicate that the CWRF model demonstrates reasonable ability in capturing the characteristics of climatological temperature and precipitation in NWC. Both the climatological temperature and precipitation predictions consistently demonstrate a systematic underestimation, revealing evident biases in regions characterized by complex terrain. In terms of interannual variation, the temperature prediction outperforms the precipitation prediction, whereas there is no significant difference in the temperature predictions for lead Months 1–3. However, uncertainties increase as the lead time is extended in precipitation prediction. Therefore, the combination of dynamical and statistical downscaling is employed to the summer temperature and precipitation prediction over NWC. It is shown both the CNN and LSTM downscaling methods can improve the prediction ability of the CWRF model for summer climatological temperature and precipitation. The LSTM method significantly reduces the root mean square error (RMSE) of precipitation and temperature predictions, indicating an improvement in predicting the spatial structure. At the interannual scale, the CNN method is less dependent on the lead time of prediction than the LSTM method is, and the interannual correlation coefficient of precipitation and temperature is greater than 0.1 compared with that of the raw CWRF model. These results provide valuable insights into understanding the prediction capabilities of the CWRF model in NWC and highlight the necessity of applying downscaling methods to the CWRF model to increase its prediction ability.

Intensity of different precipitation types (convective, stratiform and shallow) and associated cloud vertical microphysical and radiative heating features are analyzed considering typhoon development, maturity, and decaying stages over the western North Pacific using the CloudSat Tropical Cyclone and China Meteorological Administration tropical cyclone best-track datasets from 2 June 2006 to 31 December 2015. At all three stages, the convective precipitation intensity, approximately twice that of stratiform precipitation, is the highest and peaks at development stage. The strongest stratiform precipitation occurs at typhoon maturity stage. Shallow precipitation is the weakest throughout the typhoon lifespan. Although the cloud microphysical parameters (radar reflectivity, cloud ice particle number concentration and effective radius) of both convective and stratiform precipitation tend to increase with precipitation intensity, convective precipitation contains more ice water of larger sizes in upper layers than stratiform precipitation. Unlike convective and stratiform precipitation, dominated by cold clouds, shallow precipitation is dominated by warm clouds with weak vertical contrast in the radiative distribution but strong radiation nearby 5 km. Our results show that cloud ice particle number concentration is important not only in precipitation intensity enhancement but also in determining the shortwave radiative heating center vertical location. More and larger ice particles in convective precipitation profiles result in stronger or comparable shortwave radiative heating than those in stratiform precipitation profiles, while the longwave radiative cooling rates in convective and stratiform precipitation profiles exhibit very similar features, likely attributable to similar infrared radiation levels due to comparable temperatures in these profiles.

In this study, we report significant biennial variability or oscillation (BO) in the boreal spring (March–May) Surface Air Temperature (SAT) over India and unravelled the causative mechanisms. The positive phase of the BO exhibit significant seasonal warming over India, whereas seasonal cooling is observed during the negative phase of BO. Heat wave days are more during the positive phase of BO compared to negative or neutral phase. The positive (negative) phase of BO is generally coherent with the central (eastern) Pacific warming (cooling) years. The anomalous low-level divergence associated with low-level anticyclonic circulation induces less cloudiness and intense surface solar radiation ovr India during the positive phase, favouring surface warming. The evolution of some positive and/or negative phases of BO without any large scale forcing from the equatorial Pacific suggested the possibility of alternate pathways. The strong anomalous upper-level (at 200 hPa) anticyclonic circulation provoked by mid-latitude Rossby waves is found contributing to the positive phase, thereby highlighting the role of dominant mid-latitude pathways in the biennial SAT variability in addition to El Niño forcing. The sinking motion associated with persistent high, and the associated adiabatic compression also supported surface heating during the positive phase of BO. On the other hand, the mid-latitude Rossby wave induced upper-level cyclonic circulation is found contributing to the negative phase. The sinking motion associated with persistent high, and the associated adiabatic compression also supported surface heating during the positive phase of BO. In contrast, negative soil temperature anomalies and high latent heat flux release to the atmosphere supported surface cooling during the negative phase.

Atmospheric radiative changes induced by aerosol radiative forcing are the most uncertain factors in climate change, affecting a comprehensive understanding of aerosol's role in the climate system and ecosystem, with current research mainly focused on densely populated and heavily polluted regions. This study utilizes satellite and ground-based remote sensing data to establish a multi-source data processing and analysis workflow suitable for the Qinghai-Tibet Plateau region, and based on atmospheric radiative transfer models, constructs methods for simulating and validating regional aerosol radiative forcing, optimizing the long-term observational, simulation, and variation studies of aerosol radiative forcing at regional scales. The results indicate: (1) Key input parameters for simulating aerosol radiative forcing regions were determined through sensitivity tests of radiative transfer model parameters to be AOD, surface albedo, atmospheric column water vapor content, and total atmospheric ozone. A method for simulating aerosol direct radiative forcing regions was constructed. Comparison and validation against aerosol radiative forcing site simulations based on ground-based remote sensing observations at the Yangbajing station in Tibet showed R² values above 0.8 and NRMSE values between 0.25 and 0.39, indicating high accuracy of the method, suitable for the Qinghai-Tibet Plateau. (2) Utilizing satellite remote sensing data, aerosol direct radiative forcing simulations for the Qinghai-Tibet Plateau region over the past 20 years were conducted based on the constructed method. Results showed: ① The annual mean aerosol radiative forcing at the top of the atmosphere was −3.03 W/m², gradually increasing from west to east; monthly means were negative, decreasing by an average of 0.0025 W/m² per year, with decreases mainly in February to May. ② The annual mean surface aerosol radiative forcing was −13.56 W/m², gradually increasing from west to east; monthly means were negative, decreasing by an average of 0.015 W/m² per year, with decreases mainly in February, June to July, and October to December. ③ The annual mean atmospheric aerosol radiative forcing was 10.6 W/m², gradually increasing from southwest to northeast; monthly means were positive, increasing by 0.007 W/m² per year, with increases mainly in October to December. Overall, the annual and monthly mean aerosol direct radiative forcing values at the top of the atmosphere and surface were negative, indicating a cooling effect, while those in the atmosphere were positive, indicating a heating effect; the strongest aerosol radiative forcing occurred in summer at the top of the atmosphere, and in spring for both surface and atmosphere; April showed the fastest variation.

Utilizing the reanalysis data and model simulations, we explore the interannual variations of extreme high temperatures over the Indochina Peninsula during 1960–2022, as well as their responses to critical oceanic systems and corresponding mechanisms. Given the intricate interactions among oceanic regions, this study employs the Generalized Equilibrium Feedback Analysis method to extract the atmospheric responses to key ocean systems, including the tropical Indian Ocean (TIO), El Niño–Southern Oscillation (ENSO), and tropical Atlantic. Results highlight the significant contributions of TIO and ENSO. It is suggested that the anomalous anticyclonic circulation located over the Indochina Peninsula, as a response to the warm TIO and ENSO, favors the local anomalous downward motions, resulting in reduced cloud cover, diminished precipitation, increased net radiative energy to the surface and increased sensible and latent heat flux from the surface to the atmosphere, and finally inducing an increase in extreme high temperatures. These observed patterns are also well simulated by the Community Earth System Model tropical Indian Ocean and tropical Pacific Ocean pacemaker experiments, indicating that the warmer tropical Indian Ocean and ENSO could induce anomalous anticyclonic (cyclonic) patterns at the lower (upper) troposphere over the South China Sea, thereby promoting the subsidence and occurrence of extreme high temperatures over the Indochina Peninsula.

Significant vegetation increase in the Loess Plateau (LP) of China could strongly affect the surface water budget. Through the WRF model with the Water Vapor Tracer (WVT) method tracking moisture within the LP, this study conducted three sets of experiments from 1999 to 2018 with GLASS Fractional Vegetation Cover (FVC) data. The results indicate that vegetation has a critical role in partitioning evapotranspiration (ET) into transpiration (Et), canopy evaporation (Ecan), and soil evaporation (Edir), thus regulating terrestrial internal convective precipitation (P). The local P response largely depends on external P (E_P), while the internal P (I_P) contribution remains minor. In summer, the total wet difference of I_P in the LP is about 0.03 mm/day, almost 5 times that of E_P. Greening also causes surface runoff reduction. Thus, in spring and summer, surface water storage (W) decreases due to the greater increase in ET than in P. In autumn, W increases by about 0.06 mm/day due to a large decrease in Ecan, implying confining the increased W to shallower soils, resulting in accelerated loss of deep soil moisture. The greening trend of 2000–2018 contributed to an increase in I_P, which could not offset increased ET and reduced E_P, leading to terrestrial water storage reduction.

This study explores the uncertainty of future summer warming over Iberia using storylines constructed from climate model simulations of the Climate Model Intercomparison Project Phase 6. Unlike prior storyline approaches focusing on remote drivers and global teleconnections of atmospheric circulation, we use regional factors that directly influence summer temperatures: ridging activity, soil moisture and Mediterranean sea surface temperature. These drivers explain a substantial portion of the observed variability across climate models, with ridging activity and soil moisture showing the strongest influence on Iberian warming. Under a high radiative forcing scenario (SSP5–8.5), the storylines of Iberian warming based on these two drivers range between 7 and 9 °C for the end of the 21st century. The storyline leading to the largest warming is characterised by a drying out of the soil conditions and an increase in the anticyclonic activity over Iberia. We find similar conclusions for simple extreme heat indicators, though the approach struggles with more complex heatwave metrics. We also propose a novel modification of the storyline approach to increase the data sample of climate responses by using different time intervals throughout the 21st century. This modification would allow the application of more complex statistical models, the exploration of non-linear relationships and the identification of other drivers shaping the regional climate projections.