The 50 most-cited articles in Journal of Geophysical Research Atmospheres, 2024

Abstract The wetland loss rate in Iran is faster than the global average. Comprehending the shrinkage rate in Iranian wetlands and identifying the underlying drivers of these changes is essential for safeguarding their ecosystems' health and services. This study proposes a novel gray‐box modeling framework to quantify the effects of climate change and anthropogenic activities on the wetlands, by combining process‐based and machine learning models. The developed model is utilized to project the Anzali coastal wetland shrinkage by simulating the complex interaction between the meteorological, hydrological, anthropogenic and sea water level characteristics, and the changes in wetland water surface area. Our framework aggregates Soil and Water Assessment Tool model, the 12 General Circulation Models of the Coupled Model Intercomparison Project Phase 6, Landsat imagery, and the Long Short‐Term Memory model to project the shrinkage of the wetland till 2100. A comprehensive range of climate and Land Use/Cover change scenarios are analyzed. The results show that wetland will seasonally…

Abstract The historical global temperature record is an essential data product for quantifying the variability and change of the Earth system. In recent years, better characterization of observational uncertainty in global and hemispheric trends has become available, but the methodologies are not necessarily applicable to analyses at smaller regional areas, or monthly or seasonal means, where station sparsity and other systematic issues contribute to greater uncertainty. This study presents a gridded uncertainty ensemble of historical surface temperature anomalies from the Goddard Institute for Space Studies (GISS) Surface Temperature (GISTEMP) product. This ensemble characterizes the complex spatial and temporal correlation structure of uncertainty, enabling better uncertainty propagation for climate and applied science in applications of historical temperature products at spatial scales from global to regional and temporal scales from centennial to monthly. This work details the methodology for generating the uncertainty ensemble, presents key statistics of the uncertainty…

Abstract This study focuses on a new compounding concern, the sudden turn from drought to flood (STDF), that is becoming increasingly prominent. This study investigates the long‐term trends and variability of STDFs in China during 1961–2020. The findings indicate that STDFs are prevalent in north and northeast China, and the Yangtze River Delta (YRD). The probability of a drought being followed by a severe flood is approaching 35% in northern and northeastern China. Since 1961, the number of STDFs in China has increased at a rate of average 2.8 events per decade. This increase mainly has occurred in late spring and early summer. The likelihood that a drought being followed by a significant pluvial is also increasing. The increasing STDF in northern China is mainly attributable to the increasing flood frequency and volatility of precipitation. Changes in the STDF trend is more dependent on the drought frequency in the YRD.

Abstract Understanding the present and future features of atmospheric rivers (ARs) is critical for effective disaster prevention and mitigation efforts. This study comprehensively assesses the performance of ARs in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) models on both seasonal and interannual timescales within the historical period and investigates the future projection of ARs under different emission scenarios on a global scale. The multi‐model mean results obtained using the PanLu detection algorithm consistently exhibit agreement with the observational AR climatology and capture interannual fluctuations as well as the relationships with large‐scale drivers. The future projections reveal increased AR frequency, intensity, duration, and spatial extent and decreased landfall intervals with regional variations and seasonal fluctuations. Besides, the AR frequency increase will accelerate around the middle of the century, attributed to a non‐linear rise in surface temperature. Furthermore, mid‐latitude ARs are gradually shifting toward higher latitudes in both…

Abstract The January 2022 eruption of the Hunga Tonga‐Hunga Ha'apai underwater volcano injected a large amount of water vapor into the mid‐stratosphere. This study uses model simulations to investigate the resulting stratospheric impacts out to 2031. Maximum radiatively‐driven model temperature changes occur in the Southern Hemisphere (SH) subtropics in April–May 2022, with warming of ∼1 K in the lower stratosphere and cooling of 3 K in the mid‐stratosphere. The radiative cooling combined with adiabatic cooling driven by the quasi‐biennial oscillation meridional circulation explains the near‐record cold anomaly observed in the SH subtropical mid‐stratosphere. Projected ozone responses maximize in 2023–2024 as the water vapor plume is transported globally throughout the stratosphere and mesosphere. The excess H2O increases the OH radical, causing a negative global ozone response (2%–10%) in the upper stratosphere and mesosphere due to increased odd hydrogen‐ozone loss, and a small positive ozone response (0.5%–1%) in the mid‐stratosphere due to interference of the NOx catalytic loss…

Abstract Mesoscale convective systems (MCSs) are clusters of thunderstorms that are important in Earth's water and energy cycle. Additionally, they are responsible for extreme events such as large hail, strong winds, and extreme precipitation. Automated object‐based analyses that track MCSs have become popular since they allow us to identify and follow MCSs over their entire life cycle in a Lagrangian framework. This rise in popularity was accompanied by an increasing number of MCS tracking algorithms, however, little is known about how sensitive analyses are concerning the MCS tracker formulation. Here, we assess differences between six MCS tracking algorithms on South American MCS characteristics and evaluate MCSs in kilometer‐scale simulations with observational‐based MCSs over 3 years. All trackers are run with a common set of MCS classification criteria to isolate tracker formulation differences. The tracker formulation substantially impacts MCS characteristics such as frequency, size, duration, and contribution to total precipitation. The evaluation of simulated MCS…

Abstract Climate models are essential to understand and project climate change, yet long‐standing biases and uncertainties in their projections remain. This is largely associated with the representation of subgrid‐scale processes, particularly clouds and convection. Deep learning can learn these subgrid‐scale processes from computationally expensive storm‐resolving models while retaining many features at a fraction of computational cost. Yet, climate simulations with embedded neural network parameterizations are still challenging and highly depend on the deep learning solution. This is likely associated with spurious non‐physical correlations learned by the neural networks due to the complexity of the physical dynamical system. Here, we show that the combination of causality with deep learning helps removing spurious correlations and optimizing the neural network algorithm. To resolve this, we apply a causal discovery method to unveil causal drivers in the set of input predictors of atmospheric subgrid‐scale processes of a superparameterized climate model in which deep convection is…

Abstract The response of tropical high clouds to surface warming and their radiative feedbacks are uncertain. For example, it is uncertain whether their coverage will contract or expand in response to surface warming and whether such changes entail a stabilizing radiative feedback (iris feedback) or a neutral feedback. Global satellite observations with passive and active remote sensing capabilities over the last two decades can now be used to address such effects that were previously observationally limited. Using these observations, we show that the vertically averaged coverage exhibits no significant contraction or expansion. However, we find a reduction in coverage at the altitude where high clouds peak and are particularly radiatively‐relevant. This results in a negative longwave (LW) feedback and a positive shortwave (SW) feedback which cancel to yield a near‐zero high‐cloud amount feedback, providing observational evidence against an iris feedback. Next, we find that tropical high clouds have risen but have also warmed, leading to a positive, but small, high‐cloud altitude…

Abstract The products from the Stable Water Isotope Intercomparison Group, Phase 2, are currently used for numerous studies, allowing water isotope model‐data comparisons with various isotope‐enabled atmospheric general circulation model (AGCMs) outputs. However, the simulations under this framework were performed using different parameterizations and forcings. Therefore, a uniform experimental design with state‐of‐the‐art AGCMs is required to interpret isotope observations rigorously. Here, we evaluate the outputs from three isotope‐enabled numerical models nudged by three different reanalysis products and investigate the ability of the isotope‐enabled AGCMs to reproduce the spatial and temporal patterns of water isotopic composition observed at the surface and in the atmospheric airborne water. Through correlation analyses at various spatial and temporal scales, we found that the model's performance depends on the model or reanalysis we use, the observations we compare, and the vertical levels we select. Moreover, we employed the stable isotope mass balance method to conduct…

Abstract Streamflow flash droughts (SFDs), characterized by a rapid decline in streamflow over a relatively short period, affect water availability, hydropower generation, and the ecosystem. However, atmospheric and land processes that drive SFDs in the monsoonal climate of India remain unexplored. Using observations, reanalysis data sets, and model simulations, we examined the critical drivers of SFDs in 64 catchments in India during the 1971–2018 period. We identified meteorological flash droughts (MFDs) using precipitation and SFDs using in situ observations and model simulations of streamflow. We show that precipitation deficit and anomalous high temperature, driven mainly by the summer monsoon breaks, lead to the development of MFDs. Antecedent baseflow conditions play a major role in the propagation of MFDs to SFDs. Favorable atmospheric conditions (driven by the monsoon breaks) cause MFDs, which translate to SFDs. High and low baseflow conditions limit the rapid decline in streamflow, which controls the occurrence of streamflow flash drought. On the other hand, favorable…

Abstract The Mediterranean region is experiencing pronounced aridification and in certain areas higher occurrence of intense precipitation. In this work, we analyze the evolution of the precipitation probability distribution in terms of precipitating days (or “wet‐days”) and all‐days quantile trends, in Europe and the Mediterranean, using the ERA5 reanalysis. Looking at the form of wet‐days quantile trends curves, we identify four regimes. Two are predominant: in most of northern Europe the precipitation quantiles all intensify, while in the Mediterranean the low‐medium quantiles are mostly decreasing as extremes intensify or decrease. The wet‐days distribution is then modeled by a Weibull law with two parameters, whose changes capture the four regimes. Assessing the significance of the parameters' changes over 1950–2020 shows that a signal on wet‐days distribution has already emerged in northern Europe (where the distribution shifts to more intense precipitation), but not yet in the Mediterranean, where the natural variability is stronger. We extend the results by describing the…

Abstract The present study assesses the climate of the Middle East and North Africa (MENA) in detail, focusing on the historical and future warming trends in the region. The assessment incorporates data from observations, reanalyses, and statistically downscaled climate models from the Coupled Model Intercomparison Project Phases 5 and 6. Since the pre‐industrial era, the observed average climate in the MENA has warmed by 1.5°C and is on the brink of exceeding 2°C. The reanalysis data suggest that the regional warming over some MENA sub‐regions is three times faster than the global average. By the end of the 21st century, the Arabian Peninsula is projected to warm to 2.6°C ± 0.57°C and 7.6°C ± 1.53°C under low and high greenhouse gas emission scenarios, respectively. Distinct warming hotspots emerge over the Arabian Peninsula and Algeria in summer and over Mauritania in West Africa and the Elburz Mountains in Iran in winter. The summer hotspot over the Arabian Peninsula has already warmed by more than 2°C and can potentially warm to approximately 9°C under the high‐emission…

Abstract We calculate the climate forcing for the 2 ys after the 15 January 2022, Hunga Tonga‐Hunga Ha'apai (Hunga) eruption. We use satellite observations of stratospheric aerosols, trace gases and temperatures to compute the tropopause radiative flux changes relative to climatology. Overall, the net downward radiative flux decreased compared to climatology. The Hunga stratospheric water vapor anomaly initially increases the downward infrared radiative flux, but this forcing diminishes as the anomaly disperses. The Hunga aerosols cause a solar flux reduction that dominates the net flux change over most of the 2 yrs period. Hunga induced temperature changes produce a decrease in downward long‐wave flux. Hunga induced ozone reduction increases the short‐wave downward flux creating small sub‐tropical increase in total flux from mid‐2022 to 2023. By the end of 2023, most of the Hunga induced radiative forcing changes have disappeared. There is some disagreement in the satellite measured stratospheric aerosol optical depth (SAOD) observations which we view as a measure of the…

Abstract NASA's Deep Blue aerosol project has developed global aerosol data records using consistent retrieval algorithms applied to various satellite sensors. The primary components of these data records are derived from the series of Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar‐orbiting Partnership (SNPP) and the National Oceanic and Atmospheric Administration or NOAA‐20+ satellites as well as the Moderate Resolution Imaging Spectroradiometer (MODIS), among others. These instruments provide over 23 years of measurements with similar radiometric characteristics for aerosol retrievals. The algorithms used for the initial Version 1 SNPP VIIRS data set were based on the MODIS Collection 6.1 Deep Blue algorithm over land and Satellite Ocean Aerosol Retrieval (SOAR) algorithm over water. For VIIRS Version 2 data reprocessing, major updates have been made to the algorithm suite, including better accounting for effects of surface pressure, improved determination of surface reflectance, and the inclusion of fine‐mode aerosol optical models to better…

Abstract Mesoscale convective systems (MCSs) are crucial components of the hydrological cycle and often produce flash floods. Given their impact, it is important to understand how they will change under a warming climate. This study uses a satellite‐ and radar‐based MCS tracking algorithm on convection‐permitting climate model simulations and examines changes in MCS properties and precipitation structures between historical and future simulations. An underestimation in MCS total precipitation is evident in historical simulation compared to observations, due to model's depiction of MCS precipitation area and summertime occurrence frequency. Under pseudo‐global warming, increases in MCS frequency and total warm season precipitation are observed, most notably in the southern U.S. The precipitation intensity and precipitating area generated by future MCSs also rises and results in an increase in precipitation volume. MCS precipitation structures are further classified into convective core and stratiform regions to understand how change in these structures contributes to future rainfall…

Abstract An independent evaluation of methane emissions data from GHGSat, a private company that operates a constellation of small microsatellites flying Fabry‐Perot spectrometers operating at 1.6 µm, was performed. Data from multiple GHGSat commercial satellites, consisting of retrieved methane, diagnostics, and, where detected, plume and emissions information from roughly 250 scenes across Canada were analyzed. From these, 10 scenes contained methane plumes with a 2% detection rate for oil and gas scenes, and 10% for landfills. Methane precision was found to be 5%/2% on average for the C1/C2–C5 designs, with some variability due to scene albedo, terrain roughness, and airmass. Synthetic GHGSat plumes, generated using Lagrangian plume dispersion model and GHGSat characteristics, indicates typical detection limits of 240/180 kg/hr(C1/C2–C5), with a best case of roughly 100 kg/hr. Emissions and their uncertainties calculated using an alternative approach were in broad agreement with GHGSat‐reported emissions. Overall, the performance of the GHGSat C2 design (also used for C3 onward)…

Abstract In the past decade, dynamical downscaling using “pseudo‐global‐warming” (PGW) techniques has been applied frequently to project regional climate change. Such techniques generate signals by adding mean global climate model (GCM)‐simulated climate change signals in temperature, moisture, and circulation to lateral and surface boundary conditions derived from reanalysis. An alternative to PGW is to downscale GCM data directly. This technique should be advantageous, especially for simulation of extremes, since it incorporates the GCM's full spectrum of changing synoptic‐scale dynamics in the regional solution. Here, we test this assumption, by comparing simulations in Europe and Western North America. We find that for warming and changes in temperature extremes, PGW often produces similar results to direct downscaling in both regions. For mean and extreme precipitation changes, PGW generally also performs surprisingly well in many cases. Moisture budget analysis in the Western North America domain reveals why. Large fractions of the downscaled hydroclimate changes arise from…

Abstract Given the important role of Atmospheric River precipitation (ARP) in the global hydrological cycle, accurate representation of ARP is significant. However, general circulation models (GCMs) demonstrate bias in simulating ARP. The target of this study is to quantify the performance of ARP intensity/frequency for CMIP6 simulations, and further to improve ARP estimation of CMIP6 using Cycle‐Consistent Generative Adversarial Networks (CycleGAN) with highlighting the more accurate ARP features under the global warming background. The findings of this study are as follows: (a) although ARP intensity/frequency in reserved‐optimal CMIP6 overall reproduces the observation, it is still underestimated at the stronger Atmospheric river (AR) scales, particularly for the AR highly active mid‐latitude regions. (b) The CycleGAN‐based bias correction approach markedly diminishes the bias of the CMIP6 simulations within most of the AR scales among both global and the four AR highly active regions. Moreover, the performance of the ARP in AR highly active regions is significant improvement,…

Abstract Large uncertainty exists in the sign of long‐term changes in regional scale mean precipitation across the current generation of global climate models. To explore the physical drivers of this uncertainty for New Zealand, here we adopt a storyline approach applying cluster analysis to spatial patterns of future projected seasonal mean precipitation change across CMIP6 models (n = 43). For the winter precipitation change signal, the models split roughly into two main groups: both groups have a very robust wet signal across the west coast of the South Island but differ notably in terms of the sign of precipitation change across the north of the North Island. These far north winter precipitation differences appear related to how far the Hadley cell edge and regional eddy‐driven jet shift across the models relative to their historical positions. In contrast, for summer, most models have a markedly weaker and spatially non‐uniform response, where internal variability often plays a large role. However, a small group of models predict a robust wet signal across most of the country…

Abstract The source of dust in the global atmosphere is an important factor to better understand the role of dust aerosols in the climate system. However, it is a difficult task to attribute the airborne dust over the remote land and ocean regions to their origins since dust from various sources are mixed during long‐range transport. Recently, a multi‐model experiment, namely the AeroCom‐III Dust Source Attribution (DUSA), has been conducted to estimate the relative contribution of dust in various locations from different sources with tagged simulations from seven participating global models. The BASE run and a series of runs with nine tagged regions were made to estimate the contribution of dust emitted in East‐ and West‐Africa, Middle East, Central‐ and East‐Asia, North America, the Southern Hemisphere, and the prominent dust hot spots of the Bodélé and Taklimakan Deserts. The models generally agree in large scale mean dust distributions, however models show large diversity in dust source attribution. The inter‐model differences are significant with the global model dust diversity…

Abstract The environmental effects of airborne micro‐ and nano‐size plastic particles are poorly understood. Microscopy and chemical analyses of atmospherically deposited particles on snow surfaces at high elevation (2,865–3,690 m) in the Upper Colorado River basin (UCRB; Colorado Rocky Mountains) revealed the presence of black substances intimately associated with microplastic fibers, particles interpreted to have originated as tire matter. Identical and similar particles occur in shredded tires and road‐surface samples. The substance responsible for the black color of all tires is carbon black, a graphitic light‐absorbing tire additive produced by hydrocarbon combustion that homogeneously permeates the mixture of tire polymers and other additives. Such black tire matter may thus exert radiative effects closely similar to those of black carbon. The presence in snow of many organic compound types common to tires, measured by two‐dimensional gas chromatography, suggests that atmospherically deposited black road‐tire‐wear matter is among the light‐absorbing particulates that advance…

Abstract The unprecedented 2022 Yangtze River Basin (YRB) heatwave is a threat to human society and natural ecology, so the understanding of its underlying drivers is critical to regional climate adaptation and resilience. Here we conducted a multi‐method attribution analysis on the contribution of atmospheric circulation change and anthropogenic impacts to the occurrence probability and intensity of this extreme heatwave. Based on the nonstationary statistical analysis, the 2022 YRB heatwave is a 1‐in‐900‐year event and a 1‐in‐110‐year event with and without considering the 2022 YRB heatwave in the fitting, respectively. The large‐scale meteorological condition analysis shows that the 2022 YRB heatwave is featured with an anomalous high‐pressure system that favors a hot and dry atmospheric column, overlaid by anomalous subsidence and clear skies which leads to warming and greater solar heating. The ensemble constructed circulation analogue analyses show that the circulation anomaly fails to explain the observed 2022 YRB SAT anomalies fully. Specifically, 46% (0.132 ± 0.027°C decade…

Abstract Regional climate models (RCMs) are widely used to assess future impacts associated with climate change at regional and local scales. RCMs must represent relevant climate variables in the present‐day climate to be considered fit‐for‐purpose for impact assessment. This condition is particularly difficult to meet over complex regions such as the Andes‐Amazon transition region, where the Andean topography and abundance of tropical rainfall regimes remain a challenge for numerical climate models. In this study, we evaluate the ability of 30 regional climate simulations (6 RCMs driven by 10 global climate models) to reproduce historical (1981–2005) rainfall climatology and temporal variability over the Andes‐Amazon transition region. We assess spatio‐temporal features such as spatial distribution of rainfall, focusing on the orographic effects over the Andes‐Amazon “rainfall hotspots” region, and seasonal and interannual precipitation variability. The Eta RCM exhibits the highest spatial correlation (up to 0.6) and accurately reproduces mean annual precipitation and orographic…

Abstract Accurate and fine‐scaled prediction of ozone concentrations across space and time, as well as the assessment of associated human risks, is crucial for protecting public health and promoting environmental conservation. This paper introduces NetGBM, an innovative machine‐learning model designed to comprehensively model ozone levels across China's diverse topography and analyze the spatiotemporal distribution of ozone and exposure. Our model focuses on daily, weekly, and monthly predictions, achieving commendable coefficients of 0.83, 0.77, and 0.79, respectively. By constructing a gridded map of ozone and incorporating both land use and meteorological features into each grid, we achieved ozone prediction at a high spatiotemporal resolution, outperforming previous research in terms of performance and scale, particularly in regions with limited monitoring stations. The results can be further improved when applied to regional research using meteorological and ozone data from regional stations. Additionally, our research revealed that temperature is the most significant factor…

Abstract This study quantifies the contribution of individual cloud feedbacks to the total short‐term cloud feedback in satellite observations over the period 2002–2014 and evaluates how they are represented in climate models. The observed positive total cloud feedback is primarily due to positive high‐cloud altitude, extratropical high‐ and low‐cloud optical depth, and land cloud amount feedbacks partially offset by negative tropical marine low‐cloud feedback. Seventeen models from the Atmosphere Model Intercomparison Project of the sixth Coupled Model Intercomparison Project are analyzed. The models generally reproduce the observed moderate positive short‐term cloud feedback. However, compared to satellite estimates, the models are systematically high‐biased in tropical marine low‐cloud and land cloud amount feedbacks and systematically low‐biased in high‐cloud altitude and extratropical high‐ and low‐cloud optical depth feedbacks. Errors in modeled short‐term cloud feedback components identified in this analysis highlight the need for improvements in model simulations of the…

Abstract Upscaling flux tower measurements based on machine learning (ML) algorithms is an essential approach for large‐scale net ecosystem CO 2 exchange (NEE) estimation, but existing ML upscaling methods face some challenges, particularly in capturing NEE interannual variations (IAVs) that may relate to lagged effects. With the capacity to characterize temporal memory effects, the Long Short‐Term Memory (LSTM) networks are expected to help solve this problem. Here we explored the potential of LSTM for predicting NEE across various ecosystems using flux tower data over 82 sites in North America. The LSTM model with differentiated plant function types (PFTs) demonstrates the capability to explain 79.19% ( R 2 = 0.79) of the monthly variations in NEE within the testing set, with RMSE and Mean Absolute Error values of 0.89 and 0.57 g C m −2 d −1 respectively ( r = 0.89, p < 0.001). Moreover, the LSTM model performed robustly in predicting cross‐site variability, with 67.19% of the sites that can be predicted by both LSTM models with and without distinguished PFTs showing improved…

Abstract The National Oceanic and Atmospheric Administration (NOAA)’s National Water Model (NWM) provides analyses and predictions of hydrologic variables relevant to drought monitoring and forecasts at fine time and space scales (hourly, 0.25–1 km). We present results exploring the potential for NWM soil moisture and streamflow analyses to inform operational drought monitoring. Both agricultural and hydrologic drought monitoring rely either explicitly or implicitly on an accurate representation of anomalous soil moisture values. Much of our analysis focuses on comparisons of soil moisture anomalies in the NWM to those from in‐situ observations. To establish benchmarks for NWM soil moisture skill, we also include other gridded data sets currently used to inform the US Drought Monitor, specifically those from the North American Land Data Assimilation System phase 2 (NLDAS‐2) land surface models. We then compare NWM streamflow low flows with ∼500 stream gauges from the United States Geological Survey (USGS) Hydro‐Climatic Data Network of undisturbed basins. The NWM soil moisture…

Abstract Extreme precipitation events associated with atmospheric rivers (ARs) trigger floods, landslides, and avalanches that threaten lives and livelihoods in Southeast Alaska. Six rural and indigenous communities (Hoonah, Klukwan, Skagway, Yakutat, Craig, and Kasaan) identified specific needs regarding these hazards and joined the Southeast Alaska Coastlines and People (CoPe) K utí Hub to address the shared challenge of understanding and predicting these events. This study presents a climatology (1980–2019) of synoptic, mesoscale, and local meteorological characteristics of ARs and heavy precipitation across this region. High‐amplitude upper‐level patterns across the northeastern Pacific Ocean favor ARs reaching Southeast Alaska, where moisture is orographically lifted, resulting in heavy precipitation. In the six communities, ARs occur 8–15 days per month, yet only 6 AR days per year account for up to 68%–91% of precipitation extremes. Furthermore, 80%–96% of days with extreme precipitation have >75th percentile integrated water vapor transport (IVT), demonstrating the strong…

Abstract Supercooled liquid clouds are ubiquitous over the Southern Ocean (SO), even to temperatures below −20°C, and comprise a large fraction of the marine boundary layer (MBL) clouds. Earth system models and reanalysis products have struggled to reproduce the observed cloud phase distribution and occurrence of cloud ice in the region. Recent simulations found the microphysical representation of ice nucleation and growth has a large impact on these properties, however, measurements of SO ice nucleating particles (INPs) to validate simulations are sparse. This study presents measurements of INPs from simultaneous aircraft and ship campaigns conducted over the SO in austral summer 2018, which include the first in situ observations in and above cloud in the region. Our results confirm recent observations that INP concentrations are uniformly lower than measurements made in the late 1960s. While INP concentrations below and above cloud are similar, higher ice nucleation efficiency above cloud supports model simulations that the dominant INP composition varies with height. Model…

Abstract Researchers have recently focused on the interplay of the urban heat island (UHI) effect and heat waves (HWs). However, the synergies of these two phenomena remains inconclusive at present. To address this gap, this study investigated UHIs and HWs synergies during the last 30 years in the Tokyo metropolitan area, through a unique and novel approach named Land‐Surface‐Physics‐Based Downscaling (LSP‐DS). LSP‐DS integrates the widely used Noah‐Multiparameterization (Noah‐MP) land‐surface model coupled with urban canopy‐process physics, aiming to conduct high‐resolution, long‐term urban‐specific simulations with much less computational resources. Our comprehensive analysis combining observation data and numerous LSP‐DS simulations confirms exacerbated UHIs during HWs. Specifically, HWs amplify the temperature differences between urban and rural environments, which is quantified by UHI intensity (UHII). During HWs, UHII increased more at night in inland areas and more during daytime in coastal areas. HWs present especially a heightened threat to coastal regions where daytime…

Abstract Low‐level jets (LLJs), vertical profiles with a wind speed maxima in the lowest hundred meters of the troposphere, have multiple impacts in the Earth system, but a global present‐day climatology based on contemporary data does not exist. We use the spatially and temporally complete data set from ERA5 reanalysis to compile a global climatology of LLJs for studying the formation mechanisms, characteristics, and trends during the period of 1992–2021. In the global mean, LLJs are detected 21% of the time with more cases over land (32%) than over the ocean (15%). We classified the LLJs into three categories: non‐polar land (LLLJ), polar land (PLLJ), and coastal (CLLJ) LLJs. For LLLJ, the averaged frequency of occurrence is 20% and 75% of them are associated with a near‐surface temperature inversion as a prerequisite for an inertial oscillation. PLLJs are also associated with a temperature inversion and occur even more frequently with 59% of the time. These are also the lowest and the strongest LLJs among the three categories. CLLJs are particularly frequent in some marine…

Abstract Modeling atmospheric black carbon (BC) aerosol optical properties remains largely uncertain due to their complex mixing states, nonsphericity, and heterogeneity of coating distribution. Although there exist numerical models with realistic BC morphologies, these models are mostly limited to particle‐scale studies and have not been coupled to large‐scale atmospheric or climate models. In this study, a multidimensional parameterization scheme is developed by an accurate numerical algorithm for BC optical property calculation in global climate models, by incorporating their mixing state and nonspherical structure as well as heterogeneous coating distribution. The scheme was coupled and tested with the Community Atmosphere Model version 6 (CAM6) by a weighted averaging algorithm for individual particles and integration for particle ensembles. The simulation results indicate that BC morphology has a limited influence on the aerosol absorption cross section (Cabs), and the differences in Cabs between irregularly coated fractal aggregates and ideal core‐shell spherical (CS)…

Abstract For the first‐time, analysis of a decade long measurement of Black Carbon mass concentration (BC) was carried out at a representative central Indo‐Gangetic Plain (IGP) location, Varanasi (25.30°N, 83.03°E, 79 m asl), from 2009 to 2021 to understand its physical, optical, and radiative impacts. During the 13‐year study period, the daily BC mass concentration was found to vary between 0.07 and 46.23 μg m −3 (mean 9.18 ± 6.53 μg m −3 ) and showed a strong inter‐annual and intra‐annual variations. The inter‐annual variability of BC showed a significant decreasing trend (−0.47 μg m −3 yr −1 ), with a maximum during the post‐monsoon (−1.86 μg m −3 yr −1 ) and minimum during the pre‐monsoon season (−0.31 μg m −3 yr −1 ). The Black Carbon Aerosol Radiative Forcing (BC‐ARF) at the top of the atmosphere (BC‐ARFT), surface (BC‐ARFS), and within the atmosphere (BC‐ARFA) was found to be 10.3 ± 6.4, −30.1 ± 18.9, and 40.5 ± 25.2 W m −2 , respectively. BC‐ARF also showed a strong inter‐annual variability with a decreasing trend for BC‐ARFT (−0.47 W m −2 yr −1 ) and BC‐ARFA (−1.94 W m −2…

Abstract Accurately predicting fog is challenging due to interplay of myriad processes in its formation and high spatiotemporal variability. This study compares the performance of the Weather Research and Forecasting model with control (CNTL‐WRF) and assimilated fine‐grid (HRLDAS‐WRF) soil fields in the Ingo‐Gangetic Plain (IGP) over a 2‐years winter period (2019–2020 and 2020–2021). Results show HRLDAS‐WRF enhances accuracy in representing surface fog's heterogeneity and lifecycle across the IGP, demonstrating a spatial skill improvement of approximately 18% with a Fraction Skill Score of 0.44, compared to CNTL‐WRF's (0.36). Employing fog classification algorithm identifies 25 dense fog episodes (Vis < 500 m) over Delhi's urban boundary layer, including 14 radiation (RAD), 5 cloud‐base lowering (CBL), 3 advection + radiation (ADV + RAD), and 3 evaporation (EVA) episodes. CNTL‐WRF predicts 20 episodes but misses five due to a dry bias in the initial moisture conditions. However, HRLDAS‐WRF demonstrates limited vertical fog growth in various occurrences, highlighting the crucial role…

Abstract The Hengduan Mountains (HM) are located on the southeastern edge of the Tibetan Plateau and feature high mountain ridges (>6,000 m MSL) separated by deep valleys. The HM region also features an exceptionally high biodiversity, believed to have emerged from the topography interacting with the climate. To investigate the role of the HM topography on regional climate, we conduct simulations with the regional climate model COSMO at high horizontal resolutions (at ∼12 km and a convection‐permitting scale of ∼4.4 km) for the period 2001–2005. We conduct one control simulation with modern topography and two idealized experiments with modified topography, inspired by past geological processes that shaped the mountain range. In the first experiment, we reduce the HM's elevation by applying a spatially non‐uniform scaling to the topography. The results show that, following the uplift of the HM, the local rainy season precipitation increases by ∼25%. Precipitation in Indochina and the Bay of Bengal (BoB) also intensifies. Additionally, the cyclonic circulation in the BoB extends…

Abstract Investigating lightning is of key significance in understanding the lightning mechanism and mitigating lightning hazards. We reported an experiment of investigating lightning through three‐dimensional (3D) thunder locating using a Distributed Acoustic Sensing (DAS) array in Hefei, China. In this experiment, we recast a 7.7 km long urban telecom optical fiber cable as 3,850 sensors using the DAS technique. From dense DAS recording, we manually identified 101 thunder events during six positive cloud‐to‐ground (CG) lightning flashes within 20 min. The DAS recorded thunder signals are dominated by direct acoustic waves rather than air‐ground coupled surface waves. The thunder events were then located using the arrival times of thunder signals. The locations and amplitudes of thunder events are generally consistent with those from the conventional lightning detection data set and broadband magnetic field. There is likely a correlation between the maximum strength of thunder events and the highest peak current for individual CG flashes. Moreover, the comparison with weather radar…

Abstract Permafrost in the Qinghai‐Tibet Plateau (QTP) is sensitive to climate warming, but the associated degradation risk still lacks accurate evaluation. To address this issue, machine learning (ML) models are established to simulate the mean annual ground temperature (MAGT) and active layer thickness (ALT), and climate data from shared socioeconomic pathways (SSPs) are prepared for evaluation in the future period. Based on the projections, permafrost is expected to remain relatively stable under the SSP1‐2.6 scenario, and large‐scale permafrost degradation will occur after the 2050s, resulting in area losses of 30.15% (SSP2‐4.5), 58.96% (SSP3‐7.0), and 65.97% (SSP5‐8.5) in the 2090s relative to the modeling period (2006–2018). The average permafrost MAGT (ALT) is predicted to increase by 0.50°C (59 cm), 0.67°C (89 cm), and 0.79°C (97 cm) in the 2090s with respect to the modeling period under the SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5 scenarios, respectively. Permafrost in the Qilian Mountains and Three Rivers Source region are fragile and vulnerable to degradation. In the future…

Abstract Large reductions in anthropogenic emissions of particulate matter and its precursor emissions have occurred since the enactment of the Clean Air Act Amendments of 1990. The Interagency Monitoring of Protected Visual Environments network has measured PM 2.5 gravimetric mass (mass of particles with aerodynamic diameters less than 2.5 μm, also referred to here as fine mass, “FM”) and speciated PM 2.5 aerosol composition at remote sites since 1988. Measured species include inorganic anions such as sulfate, nitrate, and chloride, carbonaceous aerosols such as organic (OC) and elemental carbon (EC), and elemental concentrations used to estimate fine dust (FD). Trends in seasonal and annual mean mass concentrations were calculated from 2000 through 2021, a period that includes the largest reductions in emissions. On average, annual mean FM at remote sites in the continental United States has decreased at a rate of −1.8% yr −1 . This reduction is largely due to annual mean trends in sulfate (−6.1% yr −1 ), nitrate (−2.7% yr −1 ), EC (−2.2% yr −1 ), FD (−1.3% yr −1 ), and OC (−0.9%…

Abstract Recent climatic trends have increased forest fire activity in Canada. This study aimed to evaluate how forest fire conditions might evolve across the Canadian boreal forests in the future and to inform discussions about the impact of climate change on fire danger and severity. I generated surfaces of daily climate conditions using daily observational data from meteorological stations across Canada from 1976 to 2014. Simulated daily values of the same climatic variables were obtained from four earth system models of the Coupled Model Intercomparison Project Phase 5 project (CMIP5) for the historical period 1976–2005. Daily climate values for 2006–2100, forced by three climate change scenarios, Representative Concentration Pathway (RCP) 2.6, RCP 4.5, and RCP 8.5, were also simulated by the models. The simulated data were bias‐corrected and delta‐downscaled to project future trends in fire activity to assess the spatiotemporal variations of the potential impacts of climate change on forest fires. My results suggest fire danger and severity would increase in many Canadian…

Abstract Accurate forecasting of wind speed is essential for daily life and social production. While numerical weather prediction products are widely used, they rely on global data and mathematical models to solve atmospheric dynamics' equations, often failing to capture localized micrometeorological phenomena accurately. Factors such as surface conditions, land‐sea differences, and topography, particularly in coastal areas, further impact the accuracy of wind speed forecasts. This study presents a new method to enhance short‐term wind speed forecasting along China's coast by incorporating local and neighborhood spatiotemporal information. The approach integrates meteorological data from adjacent grid points as new inputs in the LightGBM, CatBoost, and XGBoost algorithms. Stacking ensemble technique is then employed to effectively combine with the aforementioned foundational models. Two sets of experiments are conducted: Experiments 1 exclude surrounding information, while Experiments 2 include it. Each set consists of five experiment groups: annual, spring, summer, autumn, and…

Abstract This study investigates the physical processes behind extreme precipitation events (EPEs) in the Himalayas, notorious for causing frequent floods and significant loss of life and property. Due to the presence of complex terrain, understanding the driving factors of these EPEs is challenging. Here, we decipher the precipitation characteristics and their driving factors responsible for the occurrence of EPEs in the Western Himalayas (WH) for the period 1979–2020. EPEs are defined as events exceeding the 99th percentile threshold. The extreme precipitation in the WH is contributed by both large‐scale precipitation (accounting for 61%) and convective precipitation (39%). Moreover, 25.49% of EPEs in this region are directly associated with monsoon depressions. The presence of distinct upper‐tropospheric gyres flanking the WH, along with a prominent zonal wave pattern, promotes a southward extension of the trough. This intensifies the low‐level convergence of moisture‐laden winds from the adjoining seas, resulting in substantial moisture availability for the EPEs. An omega‐type…

A Perturbed Parameter Ensemble (PPE) with the Community Atmosphere Model version 6 (CAM6) is used to better understand the sensitivity of simulated clouds to both aerosol forcing and cloud feedbacks and the interactions between them. Aerosol forcing through aerosol-cloud interactions is mostly negative (a cooling) due to shortwave radiation, while feedbacks are positive or negative in different regions due to contrasting longwave and shortwave effects. Both forcing and feedbacks are related to the mean climate state. Higher magnitude cloud radiative effects generally mean larger net forcing and larger net feedback. Aerosol forcing is broadly related to the susceptibility of clouds to drop number. Feedbacks are less related to susceptibility, and in different regions. Aerosol forcing and cloud feedbacks are anti-correlated in the CAM6 PPE such that stronger negative forcing is associated with stronger positive feedbacks. Even the processes governing forcing and feedback sensitivity in the PPE are similar. These include the warm rain formation process, ice loss processes and deep…

Abstract The South China coast (SCC) experiences frequent heavy rainfall during the warm season (May–September). Objective classification analysis on 925‐hPa geopotential height shows that the majority of warm‐season precipitation (>80%) occurs under three typical synoptic patterns: the southerly monsoon pattern (P1), the southwesterly monsoon pattern (P2), and the low‐level vortex pattern (P3). Using 20 years of satellite observations and cloud tracking, this study highlights that mesoscale convective systems (MCSs) play a pivotal role in generating precipitation under all three synoptic patterns, while the initiation and rainfall characteristics of MCSs are strongly modulated by the background synoptic circulations. The diurnal MCS precipitation under P1 and P2 is predominantly influenced by land‐sea breeze circulation, which is characterized by a morning offshore propagation and an afternoon onshore propagation. The rainfall propagation speeds, however, are strongly modulated by the prevailing low‐level monsoonal flows. Under P3, MCS precipitation initiates near the coast around…

Abstract We use the GEOS‐Chem chemistry transport model to quantify the factors in the diel discrepancy of Aerosol Optical Depth (AOD) retrieved from Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite observations over eastern China. The GEOS‐Chem simulation reveals that the AOD below 1 km is 58.5% larger at night than during the daytime, which is comparable to the counterpart of 41.3% from CALIOP (v4.2). Model sensitivity simulations show that the diurnal variation in wind barely impacts the AOD difference between daytime and nighttime, and the increase in AOD at nighttime is primarily caused by the lower temperature at nighttime compared to daytime. Further simulations demonstrate that the low temperature at night increases AOD primarily by increasing relative humidity, and hence particle hygroscopic growth, while the effect of temperature on chemical rate barely influences AOD. CALIOP also observes that the absolute difference in AOD above 1 km between nighttime and daytime is 0.105, while the counterpart in GEOS‐Chem simulations is −0.031. This contrast can be…

Abstract Arid and semiarid ecosystems around the world are often prone to both soil salinization and accelerated soil erosion by wind. Soil salinization, the accumulation of salts in the shallow portions of the soil profile, is known for its ability to decreases soil fertility and inhibit plant growth. However, the effect of salts on soil erodibility by wind and the associated dust emissions in the early stages of soil salinization (low salinity conditions) remains poorly understood. Here we use wind tunnel tests to detect the effects of soil salinity on the threshold velocity for wind erosion and dust production in dry soils with different textures treated with salt‐enriched water at different concentrations. We find that the threshold velocity for wind erosion increases with soil salinity. We explain this finding as the result of salt‐induced (physical) aggregation and soil crust formation, and the increasing strength of surface soil crust with increasing soil salinity, depending on soil texture. Even though saline soils showed resistance to wind erosion in the absence of…

Abstract Our basic knowledge of downward positive lightning leaders is incomplete due to their rarity and limited ability of VHF mapping systems to image positive streamers. Here, using high‐speed optical records and wideband electric field and magnetic field derivative signatures, we examine in detail the development of a descending positive leader, which extended intermittently via alternating branching at altitudes of 4.2 to 1.9 km and involved luminosity transients separated by millisecond‐scale quiet intervals. We show that the transients (a) are mostly initiated in previously created but already decayed branches, at a distance of the order of 100 m above the branch lower extremity, (b) extend bidirectionally with negative charge moving up, (c) establish a temporary (1 ms or so) steady‐current connection to the negative part of the overall bidirectional leader tree, and (d) exhibit brightening accompanied by new breakdowns at the positive leader end. One of the transients unexpectedly resulted in a negative cloud‐to‐ground discharge. Both positive and negative ends of the…

Abstract In July 2023, an extreme precipitation event (EPE) caused severe damage and nearly 100 fatalities in the Hai River basin, North China. Using a Lagrangian approach, we investigated the moisture transport regime and identified the circulation pattern responsible for the EPE. The primary moisture sources were the northwest Pacific (24%), southeast China (21%), and the South China Sea (20%). The circulation pattern, featuring the western Pacific subtropical high to the northeast, tropical cyclone KHANUN in the northwest Pacific, and a low‐pressure system southwest of the Hai River Basin, predominantly controlled the moisture transport. We discovered that an unprecedented EPE in 1963 exhibited a similar circulation pattern. By classifying historical EPEs into three categories based on seven atmospheric predictors, we identified circulation patterns associated with disaster‐prone events. The most frequent category is characterized by a circulation pattern with positive geopotential height anomalies in northeast Asia and negative anomalies to the south, extending from the…

Abstract Emission sources influencing high particulate air pollution levels and related mortality in India have been studied earlier on country‐wide and sub‐national scales. Here, we use novel data sets of emissions (for 2019) and observations created under the Carbonaceous Aerosol Emissions, Source Apportionment, and Climate Impacts network in India (Venkataraman et al., 2020, https://doi.org/10.1175/bams‐d‐19‐0030.1 ) in WRF‐Chem simulations to evaluate drivers of high PM2.5 levels during episodes and in airsheds with different pollution levels. We identify airsheds in “extreme” (110–140 μg/m3), “severe” (80–110 μg/m3) and “significant” (40–80 μg/m3) exceedance of the Indian annual ambient air quality standard (National Ambient Air Quality Standards [NAAQS]) of 40 μg/m3 for PM2.5. We find that primary organic matter and anthropogenic mineral matter (largely coal fly‐ash) drive high PM2.5 levels, both annually and during high PM2.5 episodes. PM2.5 episodes are driven by organic aerosol in north India (Mohali) in wintertime but are additionally influenced by mineral matter and…

Abstract Clear‐Air Turbulence (CAT) is associated with wind shear in the vicinity of jet streams in upper atmospheric levels. This turbulence occurs in cloudless regions and causes most weather‐related aircraft accidents. Recent studies have shown that in response to climate change, CAT could significantly increase over certain regions as a consequence of strengthening of jet streams. In this study we use several atmospheric reanalyses and coupled model experiments database to evaluate CAT recent and future changes in the Northern Hemisphere. Several CAT diagnostics are computed to assess the sensitivity of the results to different turbulence representations. A significant positive trend in CAT frequency is found in the reanalyses in different Northern Hemisphere regions over the period 1980–2021. The signal‐to‐noise analysis shows that over North Africa, East Asia and Middle East the increase of CAT occurrence in the last decades is likely attributed to the response to anthropogenic forcing. In contrast, over the North Atlantic and North Pacific the response to external forcing is…

Abstract Over the past century, rapid urbanization has greatly altered landscapes and affected atmospheric conditions causing impacts across a wide range of sectors including human welfare, infrastructure, and ecosystems. As a result, there is a growing imperative to improve understanding of urbanization impacts on local and regional weather events and hydroclimates. This study investigates how urbanization affects precipitation and cloud fraction (CF) in the vicinity of Indianapolis. We employ multi‐month simulations using the Weather Research and Forecasting model to: (a) assess the impact of an urban area on precipitation and CF, (b) quantify how this impact varies with urban growth, and (c) examine the main mechanisms through which the city alters the local hydroclimate. Specifically, two perturbed simulations, where the urban land cover is either replaced by croplands or is increased in size, are also performed for the two rainiest months. Comparisons of the control run with no city against the perturbed runs indicate statistically significant impacts of the urban area in…