Agricultural sector forms the backbone of India's socioeconomy. Despite consistent efforts to develop the irrigation network for increased agricultural production, approximately 60% of India's cropped area still remains rain fed, thereby functional to the strength of the Indian summer monsoon (ISM). The probability of a weak monsoon is strongly correlated with the occurrence of droughts during the ISM season. The possible influence of atmospheric drivers in initiating these droughts is observed through the dynamics of low-level jets (LLJ) over the northern Arabian Sea forming the core of LLJ during the ISM. Interestingly, since the past 72 years, from 1951 to 2022, the core of LLJ has become dry (increased saturation deficit by 17%) and weak (reduced wind speed by 5%). Additionally, the wind speed (saturation deficit) at the core shares close dependence (75%–80%) with the initiation of dry (wet) extremes exhibiting maximum correlation at a 2-day lag. Furthermore, we observed a 50% (40%) increase in the dry (wet) extremes driven by the lower-atmospheric dynamics of the LLJ core. Consequently, these dry (wet) extremes are characterized by a 6% (12%) enhancement in duration (intensity). Such conditions act as strong precursors for monsoon droughts.
A diverse array of sulfur-containing organic compounds (SOCs) was identified in seasonal snow samples collected from northwestern China, using high-performance liquid chromatography interfaced with an electrospray ionization high-resolution mass spectrometer (HPLC–ESI–HRMS). Hierarchical cluster analysis (HCA) of the HPLC–HRMS data set classified SOCs into distinct clusters based on their molecular characteristics. Substantial differences in SOC composition were observed between urban (U) and rural/remote (R) clusters. In ESI− mode, the SOCs in the U cluster exhibited higher unsaturation degrees, oxidation levels, and larger molecular sizes than the R cluster. These compounds were likely derived from anthropogenic sources, such as transportation and industry, whereas those in the R cluster exhibited signatures of mixed sources, including biomass burning, cooking-related emissions, and local biogenetic inputs. In ESI+ mode, SOCs were scarcely detected in the R cluster but were abundant in the U cluster. These compounds were predominantly reduced and unsaturated SOCs, with more than 85% (by intensity) containing one or no oxygen atoms in their elemental formulas. Tentative assignments for these species include sulfoxides, polycyclic aromatic S-heterocycles, thiols, and sulfides, likely originating from the use and production of heavy oils. Additionally, volatility estimates suggest that the SOCs identified in this study are more volatile than those found in other environmental media. The findings highlight the unique SOCs composition in snowpack of northwestern China, particularly those detected via positive ESI mode, offering new insights into the environmental, climatic, and biogeochemical roles of SOCs.
The Arctic has experienced rapid sea ice loss and a substantial surface albedo decline, altering its radiation budget. CMIP6 (Coupled Model Intercomparison Project Phase 6) models capture these trends but show considerable inter-model spread in the magnitude, distribution, and seasonality of Arctic surface albedo. Over land, spread in AMIP (Atmospheric Model Intercomparison Project) and CMIP6 is associated with snow cover variations, while over the ocean, where sea ice dominates, the sources are less clear. We compare CMIP6 simulations with observations from the Clouds and the Earth's Radiant Energy System (CERES) and develop a decomposition method to quantify contributions from sea ice albedo, concentration, and extent. Over the Arctic Ocean, all three factors contribute to inter-model spread in CMIP6. In AMIP, despite prescribed sea ice concentrations, we were surprised to find an inter-model spread in Arctic Ocean albedo similar to that in CMIP6, driven solely by sea ice albedo. Applying the decomposition to future projections shows that the largest decline occurs in the Central Arctic, driven primarily by reductions in sea ice extent. After 2045, sea ice extent emerges as the dominant driver, highlighting ice edge retreat as key to future albedo decline. These findings pinpoint key sources of inter-model spread in Arctic surface albedo and offer insights into quantifying shortwave (SW) radiative effect associated with sea ice responses in future projections.
Typhoon-induced Compound Flood (TCF), driven by the combined impact of extreme rainfall and increasing coastal water level (CWL), poses a substantial threat to urban safety. This study presents a framework for assessing the future compound flood hazard profiles in a coastal megacity in the Delta region of southern China. A coupled hydrology-hydrodynamic model is applied to simulate the flooding processes of 7 typhoon events. Scenarios are constructed using all possible pairwise combinations of three rainfall and three CWL conditions. These inputs are derived from statistical and dynamical downscaling of climate projections from the Coupled Model Intercomparison Project (CMIP6) ensemble under the SSP5-8.5 pathway. The results show that future CWL rise contributes more to future inundation than increasing rainfall, whereas rainfall contributions exhibit considerable uncertainties due to regional rainfall downscaling. Under extreme warming scenarios, future typhoons may produce increases of up to 230 mm in total rainfall and 28 mm per hour in rainfall intensity, which in turn increase the average urban inundation depth and area by 1.2 cm and 24.7 , respectively. Given an average CWL of 170 cm and a maximum CWL of 440 cm in the future, the inundation depth and area could increase by up to 8.4 cm and 29 , respectively. Within the 7 typhoons in this study, Hagupit (2014) exhibits the most notable compound effect, potentially expanding the medium-to-high risk area (inundation depth above 27 cm) by over 5%. This study demonstrates that climate change may intensify TCF, requiring flood-mitigating measures to consider rainfall-CWL interactions.
Low-level jets (LLJs), as dynamically significant narrow air currents in the lower troposphere, profoundly influence regional weather and anthropogenic activities. Motivated by persistent LLJs detected through Doppler LiDAR observations during March to April 2021, this study systematically characterizes these LLJs over Juehua Island (western Bohai Sea coast) by integrating high-resolution Weather Research and Forecasting Model simulations. Based on a 61-day simulation spanning March to April 2021, this study reveals a notable LLJ occurrence frequency of 25.3%, dominated by two distinct directional modes: southwesterly and northeasterly. The high frequency and pronounced directional dominance of LLJs in this region motivated a systematic investigation combining Empirical Orthogonal Function (EOF) analysis and sensitivity experiments. The LLJ-favorable synoptic patterns were extracted through EOF analysis of the sea-level pressure (SLP) field. The northwest-southeast SLP dipole pattern plays a dominant role, contributing 68% to LLJ formation. Southwesterly and northeasterly LLJs are favored by “high-southeast, low-northwest” and its opposite synoptic dipoles, respectively. Sensitivity experiments quantify the contribution of local geography at 21%, collectively accounted for by the Bohai Sea (16%) and the northwestern highlands (5%). Additionally, the Bohai Sea preferentially enhances southwest LLJs, which exhibit lower LLJ heights. In contrast, the northwestern highlands elevate LLJ heights and align LLJ directions with the terrain orientation, resulting in a more clustered wind direction distribution. This study quantified LLJ-favorable synoptic patterns, Bohai Sea and northwestern high terrain influences. These findings could provide valuable insights for regional LLJ forecasting.
Dialkenes, such as isoprene and 1,3-butadiene (BD), are highly reactive volatile organic compounds (HRVOCs) that undergo rapid atmospheric oxidation driving radical cycles and secondary pollutant formation. Field measurements in Shanghai, China during spring and summer identified distinct characteristics: anthropogenic BD dominated dialkene levels in spring enhancing formaldehyde (HCHO) formation, whereas biogenic isoprene prevailed in summer correlating with elevated glyoxal (CHOCHO). Box model simulations revealed that dialkene chemistry enhanced ROx cycle rates by over 10% under BD-dominant and 40% under isoprene-dominant conditions contributing nearly half of reactive aldehyde formation. Further simulations on O3 indicate that the reactive aldehydes formed from dialkenes exert an influence nearly equivalent to the direct impact of dialkenes. Varying dialkenes composition and abundance modulate ROx activity and secondary aldehydes formation. Accurate identification of these HRVOCs and their oxidative products is crucial for clarifying primary-secondary VOC–O3 interactions and for developing targeted O3 reduction strategies.
Typhoon-induced Compound Flood (TCF), driven by the combined impact of extreme rainfall and increasing coastal water level (CWL), poses a substantial threat to urban safety. This study presents a framework for assessing the future compound flood hazard profiles in a coastal megacity in the Delta region of southern China. A coupled hydrology-hydrodynamic model is applied to simulate the flooding processes of 7 typhoon events. Scenarios are constructed using all possible pairwise combinations of three rainfall and three CWL conditions. These inputs are derived from statistical and dynamical downscaling of climate projections from the Coupled Model Intercomparison Project (CMIP6) ensemble under the SSP5-8.5 pathway. The results show that future CWL rise contributes more to future inundation than increasing rainfall, whereas rainfall contributions exhibit considerable uncertainties due to regional rainfall downscaling. Under extreme warming scenarios, future typhoons may produce increases of up to 230 mm in total rainfall and 28 mm per hour in rainfall intensity, which in turn increase the average urban inundation depth and area by 1.2 cm and 24.7 , respectively. Given an average CWL of 170 cm and a maximum CWL of 440 cm in the future, the inundation depth and area could increase by up to 8.4 cm and 29 , respectively. Within the 7 typhoons in this study, Hagupit (2014) exhibits the most notable compound effect, potentially expanding the medium-to-high risk area (inundation depth above 27 cm) by over 5%. This study demonstrates that climate change may intensify TCF, requiring flood-mitigating measures to consider rainfall-CWL interactions.
Employing the spaceborne observations from scatterometers (QuikSCAT and ASCAT), we quantify the contributions of different mechanisms to the Arctic MYI area changes over two decades (1999/2000–2017/2018). Specifically, the loss mechanisms (export, melt, deformation) and gain mechanism (replenishment) associated with MYI area variations are examined. On average, there was an annual (October-September) MYI area loss of 1,080.3 × 103 km2 due to export, melt, and deformation of 749.2 × 103 km2, 222.5 × 103 km2, and 108.6 × 103 km2, respectively. The substantial MYI depletion was largely offset by replenishment from the aging of first-year ice (FYI) at the end of the melt season, which on average amounted to 993.8 × 103 km2 in the Arctic Ocean. Therefore, a net annual MYI area loss of −86.5 × 103 km2 emerged in the Arctic. The consecutive occurrence of the anomalously low MYI replenishment from 2005 to 2007 was responsible for the dramatic decadal decline of MYI area between the QuikSCAT (P1:2000-2008) and ASCAT (P2: 2009–2018) periods from 3.29 × 106 km2 during P1 dropping a half to 1.61 × 106 km2 during P2. Moreover, the recently enhanced melt and deformation processes were favorable in maintaining the Arctic MYI at the low-level coverage during P2 relative to P1. The thermodynamic (melt and replenishment) and dynamic mechanisms (export) related to MYI variations are linked to Dipole Anomaly (DA), whereas North Atlantic Oscillation (NAO) acts to influence the thermodynamic mechanism (melt and replenishment). On the other hand, no significant connection is identified for Arctic Oscillation (AO) or Barents-Beaufort Oscillation (BBO).
This study investigates the interannual variability in the first occurrence dates of the first Madden Julian Oscillation (FMJO) and the first Boreal Summer Intraseasonal Oscillation (FBSISO) events over the Indian Ocean during 1940–2022. The FMJO typically occurs in November, whereas the FBSISO mainly occurs in early May. The FMJO onset exhibits substantially larger interannual variability. The timing of both phenomena is strongly influenced by the El Niño Southern Oscillation (ENSO), which modulates large scale atmospheric conditions, particularly through column moisture anomalies. The leading Empirical Orthogonal Function (EOF) mode of April column moisture anomalies displays a meridional dipolar pattern over the Indian Ocean. Its associated principal component (PC) time series shows a statistically significant correlation with the FBSISO onset date, indicating that a strong meridional moisture contrast with positive anomalies over the northern Indian Ocean favors an earlier FBSISO onset. The leading EOF mode of November column moisture anomalies exhibits a zonal dipolar pattern extending from the western equatorial Indian Ocean to the Maritime Continent, with a pronounced meridional contrast over the Maritime Continent. The corresponding PC is significantly correlated with the FMJO onset date, suggesting that a zonal moisture contrast with higher moisture over the western Pacific favors an earlier FMJO onset. These moisture anomalies are closely linked to ENSO conditions. Consequently, ENSO also modulates the onset timing of these events, although the onset dates show weaker correlations with ENSO than with monthly moisture anomalies. The physical mechanisms underlying the distinct responses of the FMJO and FBSISO to ENSO remain to be elucidated.
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