JGR–Atmospheres

Rising Arctic temperatures pose a threat to the large carbon stores trapped in Arctic permafrost. To assess methane emissions in high-Arctic regions, we analyzed atmospheric data from Alaska and Siberia using two methods: (a) a wind sector approach to calculate emission changes based on concentration enhancements using wind direction, and (b) an inversion method utilizing a high-resolution atmospheric transport model. Incorporating data after 2015, we observed a significant rise in methane emissions (0.018 ± 0.005 Tg yr−2 from 2000 to 2021) from Alaska's North Slope, indicating a shift from previous analyses. We find 34%–50% of yearly emissions occurred in the late season (September–December) consistently across multiple years and regions, which is historically underestimated in models and inventories. Our findings reveal significant changes occurring in the Arctic, highlighting the crucial role of long-term atmospheric measurements in monitoring the region, especially during the cold season.

Vegetation responses to rising atmospheric CO2 levels can significantly affect water availability (defined as precipitation minus evapotranspiration (ET)). While this effect has long been recognized and assessed for the mean state, its influence on interannual variability, which is more closely associated with extreme events, has yet to be comprehensively quantified. In this study, our primary focus is to evaluate the impacts of ET by plant physiology (denoted as ET Phy ) on the mean and interannual variability of water availability under elevated CO2 using multiple CO2 sensitivity experiments from the coupled model intercomparison project phase 6. We show that the contribution of vegetation physiological effects to the mean water availability varies among regions, while it consistently contributes to variability by about 33%. Considering CO2 physiological effects alone, ET Phy exerts a more significant influence on the mean state than on variability, particularly in humid regions. Consequently, ET Phy contributes less than 5% to the variability of water availability in humid regions under rising CO2, whereas it accounts for about 20% of the mean state. This distinction could be attributed to the different mechanisms governing the mean and variability of ET Phy . Specifically, evaporation from CO2 physiological forcing is the most critical contributor to the variability of ET Phy in most regions while showing minimal impacts on the mean state. Our findings identify the divergent effects of ET Phy on the mean state and interannual variability of water availability under elevated CO2, as important in future climate projections.

Forecasts of tropical cyclone (TC) tornadoes are less skillful than their non-TC counterparts at all lead times. The development of a convection-allowing regional ensemble, known as the Warn-on-Forecast System (WoFS), may help improve short-fused TC tornado forecasts. As a first step, this study investigates the fidelity of convective-scale kinematic and thermodynamic environments to a preliminary set of soundings from WoFS forecasts for comparison with radiosondes for selected 2020 landfalling TCs. Our study shows reasonable agreement between TC convective-scale kinematic environments in WoFS versus observed soundings at all forecast lead times. Nonetheless, WoFS is biased toward weaker than observed TC-relative radial winds, and stronger than observed near-surface tangential winds with weaker winds aloft, during the forecast. Analysis of storm-relative helicity (SRH) shows that WoFS underestimates extreme observed values. Convective-scale thermodynamic environments are well simulated for both temperature and dewpoint at all lead times. However, WoFS is biased moister with steeper lapse rates compared to observations during the forecast. Both CAPE and, to a lesser extent, 0–3-km CAPE distributions are narrower in WoFS than in radiosondes, with an underestimation of higher CAPE values. Together, these results suggest that WoFS may have utility for forecasting convective-scale environments in landfalling TCs with lead times of several hours.

The dominant fraction of anthropogenic volatile organic compound (VOC) emissions shifted from transportation fuels to volatile chemical products (VCP) in Los Angeles (LA) in 2010. This shift in VOC composition raises the question about the importance of VCP emissions for ozone (O3) formation. In this study, O3 chemistry during the CalNex 2010 was modeled using the Master Chemical Mechanism (MCM) version 3.3.1 and a detailed representation of VCP emissions based on measurements combined with inventory estimates. The model calculations indicate that VCP emissions contributed to 23% of the mean daily maximum 8-hr average O3 (DMA8 O3) during the O3 episodes. The simulated OH reactivity, including the contribution from VCP emissions, aligns with observations. Additionally, this framework was employed using four lumped mechanisms with simplified representations of emissions and chemistry. RACM2-VCP showed the closest agreement with MCM, with a slight 4% increase in average DMA8 O3 (65 ± 13 ppb), whereas RACM2 (58 ± 13 ppb) and SAPRC07B (59 ± 14 ppb) exhibited slightly lower levels. CB6r2, however, recorded reduced concentrations (37 ± 10 ppb). Although emissions of O3 precursors have declined in LA since 2010, O3 levels have not decreased significantly. Model results ascribed this trend to the rapid reduction in NOX emissions. Moreover, given the impact of COVID-19, an analysis of 2020 reveals a shift to a NOX-limited O3 formation regime in LA, thereby diminishing the influence of VCPs. This study provides new insights into the impact of VCP emissions on O3 pollution from an in-depth photochemical perspective.

Eighteen lightning flash rate parameterization schemes (FRPSs) were investigated in a Weather Research and Forecasting model coupled with chemistry cloud-resolved simulation of the 29–30 May 2012 supercell storm system observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. Most of the observed storm's meteorological conditions were well represented when the model simulation included both convective damping and lightning data assimilation techniques. Newly-developed FRPSs based on DC3 radar observations and Lightning Mapping Array data are implemented in the model, along with previously developed schemes from the literature. The schemes are based on relationships between lightning and various kinematic, structural, and microphysical thunderstorm characteristics (e.g., cloud top height, hydrometeors, reflectivity, and vertical velocity) available in the model. The results suggest the model-simulated graupel and snow/ice hydrometeors require scaling factors to more closely represent proxy observations. The model-simulated lightning flash trends and total flashes generated by each scheme over the simulation period are compared with observations from the central Oklahoma Lightning Mapping Array. For this supercell system, 13 of the 18 schemes overpredicted flashes by >100% with the group of FRPSs based on storm kinematics and structure (particularly updraft volume) performing slightly better than the hydrometeor-based schemes. During the storm's first 4 hr, the upward cloud ice flux FRPS, which is based on the combination of vertical velocity and hydrometeors, well represents the observed total flashes and flash rate trend; while, the updraft volume scheme well represents the observed flash rate peak and subsequent sharp decline in flash rate.

Understanding the impacts of high-resolution ocean model provides valuable insights for future research. However, the outcomes of sea surface state changes in both the tropics and mid-latitudes remain unclear, and initialized seasonal forecasts have not been studied extensively. This study investigates the impact of ocean model resolution with the first long-term hindcast experiment of an eddy-resolving (0.1°) ocean model used for global seasonal forecasting. We show that using the high-resolution ocean model significantly changes boreal winter jet streams in the atmosphere, based on the comparison of 30-year hindcasts with ocean resolutions ranging from 1° to 0.1° for the Japan Meteorological Agency/Meteorological Research Institute Coupled Prediction System version 3. In boreal winters, the cold sea surface bias in the equatorial Pacific is significantly reduced, leading to an equatorward shift in the intertropical convergence zone (ITCZ) and enhanced convective activity in the western equatorial Pacific. The subtropical jet shifts equatorward due to the ITCZ shift and the weakening of equatorward propagation of mid-latitude atmospheric eddies. The enhanced convective activity in the tropics has a remote influence in the mid-latitudes, significantly reducing the upward eddy propagation of zonal wavenumber 1. Sea surface warm-up in the mid-latitudes partially cancels the reduction impact by enhancing the zonal wavenumber 2. Overall, the polar night jet accelerates due to the reduced supply of eddy forcing.

A cloud-resolved storm and chemistry simulation of a severe convective system in Oklahoma constrained by anvil aircraft observations of NO x was used to estimate the mean production of NO x per flash in this storm. An upward ice flux scheme was used to parameterize flash rates in the model. Model lightning was also constrained by observed lightning flash types and the altitude distribution of flash channel segments. The best estimate of mean NO x production by lightning in this storm was 80–110 mol per flash, which is smaller than many other literature estimates. This result is likely due to the storm having been a high flash rate event in which flash extents were relatively small. Over the evolution of this storm a moderate negative correlation was found between the total flash rate and flash extent and energy per flash. A longer-term simulation at 36-km horizontal resolution with parameterized convection was used to simulate the downwind transport and chemistry of the anvil outflow from the same storm. Convective transport of low-ozone air from the boundary layer decreased ozone in the anvil outflow by up to 20–40 ppbv compared with the initial conditions, which contained stratospheric influence. Photochemical ozone production in the lightning-NO x enhanced convective plume proceeded at a rate of 10–11 ppbv per day in the 9–11 km outflow layer over the 24-hr period of downwind transport to the Southern Appalachians. Photochemical production plays a large role in the restoration of upper tropospheric ozone following deep convection.

Recent research has described a ‘moist margin’ in the tropics, defined through a total column water vapor (TCWV) value of 48 kg m−2, that encloses most of the rainfall over the tropical oceans. Diagnosing the moist margin in the ERA5 reanalysis reveals that it varies particularly on synoptic time scales, which this study aims to quantify. We define ‘wet and dry perturbation’ objects based on the margin's movement relative to its seasonal climatology. These perturbations are associated with a variety of synoptic weather systems. Wet (dry) perturbations produce substantially more (less) rainfall compared to the seasonal average, confirming the clear link between moisture and precipitation. On synoptic scales we suggest that mid-tropospheric humidity plays a key role in creating these perturbations, while sea surface temperatures (SSTs) are relatively unimportant.

Although afforestation is a potential strategy to mitigate climate change by sequestering carbon, its potential biophysical effects on climate, such as regulating surface albedo, evapotranspiration, and energy balance, have not been fully incorporated into climate change mitigation strategies. This is partly due to the challenges associated with modeling the complex bidirectional interactions between vegetation and climate. In this study, we assess the impact of afforestation on low cloud cover using a regional climate model (RCM) and Earth observation data, applying a space-for-time approach to overcome limitations that may arise from comparing satellite and RCM results, such as different background climate conditions or different extents of land cover change. Our results show a consistent increase in low cloud cover in Europe due to afforestation in both datasets (3.71% and 3.56% on average, respectively), but the magnitude and direction of this effect depend on various factors, including location, seasonality, and forest type. These results suggest that afforestation can have important feedbacks on the climate system, and that its biophysical effects must be considered in climate change mitigation strategies. Furthermore, we emphasize the role of the modeling community in developing accurate and reliable approaches to assess the biophysical effects of land cover change on climate.

The manifestation of extreme solar proton events (SPEs) in Beryllium-10 (10Be) ice core data contains valuable information about the strength and incidence of SPEs or local characteristics of the atmosphere. To extract this information, the signals of enhanced production of cosmogenic 10Be due to the SPEs have to be detected, hence distinguished from the variability of the background production by galactic cosmic rays (GCRs). Here, we study the transport and deposition of 10Be from GCRs, using the ECHAM/MESSy Atmospheric Chemistry climate model, and discuss the detectability of extreme SPEs (similar to the CE 774/775 SPE) in 10Be ice core data depending on the ice core location, seasonal appearance of the SPE, atmospheric aerosol size distribution and phase of the 11-year solar cycle. We find that sedimentation can be a major deposition mechanism of GCR generated 10Be, especially at high latitudes, depending on the aerosols to which 10Be attaches after production. The comparison of our results to four ice core records of 10Be from Greenland and Antarctica shows good agreement for both 10Be from GCRs and solar energetic particles (SEP). From our results we deduce that the location of detection and the season of occurrence of the SPE have a considerable effect on its detectability, as well as the aerosol size distribution the produced cosmogenic nuclides meet in the atmosphere. Furthermore, we find that SPEs occurring in the phase of highest activity during the 11-year solar cycle are more detectable than SPEs that arise in the phase of lowest activity.

This study evaluated the precipitation forecast produced by the operational China Meteorological Administration Mesoscale model (CMA-MESO) during the “super violent” Meiyu season of 2020. Generally, CMA-MESO, which runs with ∼3-km-grid resolution, is able to reproduce the distribution and diurnal variation of precipitation. However, the precipitation amount is greatly overestimated, especially in eastern coastal areas of China. Precipitation in that region usually occurs with two peaks: one in the morning that mostly reflects organized precipitation systems, and the other in the afternoon generated mostly by local convection. Analyses showed that overestimation of low-level wind speed is the main reason for the overestimation of precipitation. CMA-MESO produces low-level winds that are overly strong, which greatly enhance the predicted convergence at night, leading to overestimation of precipitation. Additionally, the stronger wind speed increases the estimated transport of water vapor to the eastern coastal area, producing fake convection near the coastal mountains as the perturbed wind direction turns toward the mountain area in the afternoon. In comparison with ERA5, CMA-MESO tends to overestimate (underestimate) the temperature in the northwest (southeast), and the larger temperature gradient increases the pressure gradient, resulting in the stronger low-level wind speed.

The Planetary Boundary Layer height (PBLH) is essential for studying PBL and ocean-atmosphere interactions. Marine PBL is usually defined to include a mixed layer (ML) and a capping inversion layer. The ML height (MLH) estimated from the measurements of aerosol backscatter by a lidar was usually compared with PBLH determined from radiosondes/dropsondes in the past, as the PBLH is usually similar to MLH in nature. However, PBLH can be much greater than MLH for decoupled PBL. Here we evaluate the retrieved MLH from an airborne lidar (HSRL-2) by utilizing 506 co-located dropsondes during the ACTIVATE field campaign over the Northwest Atlantic from 2020 to 2022. First, we define and determine the MLH and PBLH from the temperature and humidity profiles of each dropsonde, and find that the MLH values from HSRL-2 and dropsondes agree well with each other, with a coefficient of determination of 0.66 and median difference of 18 m. In contrast, the HSRL-2 MLH data do not correspond to dropsonde-derived PBLH, with a median difference of −47 m. Therefore, we modify the current operational and automated HSRL-2 wavelet-based algorithm for PBLH retrieval, decreasing the median difference significantly to −8 m. Further data analysis indicates that these conclusions remain the same for cases with higher or lower cloud fractions, and for decoupled PBLs. These results demonstrate the potential of using HSRL-2 aerosol backscatter data to estimate both marine MLH and PBLH and suggest that lidar-derived MLH should be compared with radiosonde/dropsonde-determined MLH (not PBLH) in general.

Sub-seasonal to seasonal (S2S) prediction provides an extended range of lead time for decision-makers across multiple sectors. S2S forecast is crucial for a country that are susceptible to hydro-meteorological disasters like Nepal. However, S2S forecast requires assessment with reliable datasets before its application. Since, Nepal lacks a dense station network, multi-source precipitation estimates (MPEs) are the obvious alternatives. Therefore, using classical evaluation metrics and extreme precipitation indices, this study assessed eleven high-resolution datasets against 159-gauge stations over Nepal for the 2001–2020 period. These datasets are classified as gauge-interpolated (APHRODITE), merged (TPMFD, MSWEP, CLDAS, and CHIRPS), satellite-based (IMERGV7, IMERGV6, CMORPH, and PERSIANN), and reanalysis (ERA5-L and HAR). Satellite datasets (except IMERGV7) failed to capture the spatial pattern of mean annual precipitation, while others broadly captured it. Most MPEs struggled to accurately estimate wet season precipitation compared to dry season. Furthermore, increasing estimation error from light to extreme precipitation and decreasing skill metrics from flat to complex terrain, demonstrate the intensity and terrain-specific limitations of MPEs. In terms of precipitation extremes, APHRODITE exhibits the highest skill, followed by MSWEP, TPMFD, HAR, ERA5-L, IMERGV7, CLDAS, IMERGV6, CHIRPS, CMORPH, and PERSIANN. IMERGV7 exhibits increased skill in detecting extreme precipitation and precipitation over orography against IMERGV6. APHRODITE and TPMFD datasets performed consistently well in all scales, including weekly anomaly, with an average anomaly correlation of 0.84 and 0.66 respectively. However, since APHRODITE is not widely available, TPMFD can serve as a benchmark dataset for evaluating high-resolution S2S forecasts within the study region.

A continuous decrease in aerosols over the Western North Atlantic Ocean (WNAO) on a decadal timescale provides a long-term benchmark to evaluate how various natural and anthropogenic processes affect the manifestation of aerosol-cloud interactions in this region. Furthermore, the WNAO serves as a natural laboratory with diverse aerosol sources, marine boundary layer clouds more variable than those in marine stratocumulus deck regions, and unique flow regimes established by the Gulf Stream and the semi-permanent Bermuda High. We investigate how satellite-retrieved macrophysical and microphysical properties of low clouds and the surface shortwave irradiance changed from 2003 to 2020, in tandem with this aerosol decrease. The decadal changes in large-scale meteorology related to the North Atlantic Oscillation (NAO) are also examined. We find a reduction in low-cloud optical thickness, accompanied by fewer and larger cloud droplets, yet observe no significant changes in low-cloud fraction and liquid water path. Despite the reduction in low-cloud optical thickness together with aerosol decrease, a corresponding increase in the trends of surface shortwave irradiance, also known as surface brightening, is lacking. This absence of brightening is potentially related to concomitant changes found in large-scale meteorology associated with NAO—Bermuda High strengthening, sea surface warming, and atmospheric moistening— as well as an increase in high-level cloud fraction that can counteract the surface brightening. Ultimately, our findings suggest that spatial patterns of decadal meteorological variability introduce complexities in the surface cloud radiative effect over the WNAO, thereby complicating the isolation and examination of aerosol-cloud interactions.

Gas flaring (GF) has the negative impact on the environment, climate, and human health. So, regular monitoring of flares and quantification of their volume is necessary. Iran has many natural oil/gas processing plants and petrochemical companies which are concentrated in the southern region. Pars Special Economic Energy Zone (PSEEZ) is an industry part with different kinds of active flares, thus a significant potential source of environmental impacts due to gas flaring. Remotely sensed data are used in gas-flaring detection, volume estimation, and pollution emission. In this study, we applied day/nighttime radiation and air pollutant data to estimate gas flaring volumes. We developed artificial neural network models (ANN) for finding the relationship between the field measurement of GF volume as the dependent variable and shortwave infrared and thermal infrared bands of Landsat 8, M10 band of Visible Infrared Imaging Radiometer Suite, and air pollutant (NO2, CO, O3, and SO2) of TROPOMI as independent variables. Results showed that R2 values were 0.73 for the ANN model from 2018 to 2019. The sensitivity analysis demonstrated that the thermal infrared bands of B10 and B11 of Landsat 8 had the most important role in the estimation of gas flaring volume. In contrast, the SWIR bands of Landsat 8 and all TROPOMI products were insignificant. The findings of this research help to shed light on the use of remotely sensed data in estimating the volume of gas flaring at the regional/global scale by integration of the ANN model.

Soil moisture can significantly influence weather and climate via land‒atmosphere interactions over the Tibetan Plateau. However, the temporal and spatial preferences of precipitation for soil moisture anomalies and the underlying mechanisms over the plateau have not been determined. Using multiple satellite data sets (including Global Precipitation Measurement precipitation data and Soil Moisture Active Passive and Advanced SCATterometer soil moisture data) and ERA5 reanalysis data, the temporal and spatial soil moisture–precipitation coupling (SMPC) relationships in seven summers during 2015–2021 over the plateau are quantified based on a percentile-based method. The satellite observations show prevalent positive temporal SMPC across the plateau, indicating that wetter-than-normal soil conditions tend to lead to more afternoon precipitation. While ERA5 generally aligns with satellite findings, it underestimates areas with positive temporal SMPC. Both the satellite and ERA5 data show that spatial SMPC relationships are usually statistically insignificant, but a few regions show significant positive relationships, that is, precipitation is more likely to occur over soils wetter than the surrounding soils. Moreover, the satellite observations suggest an inter-event positive correlation between the temporal and spatial SMPC relationships. ERA5 agrees with the satellite-based results over the western plateau but shows discrepancies over the eastern plateau. The temporal and spatial variations in soil moisture modulate the partitioning of surface heat fluxes, planetary boundary layer height, and lifting condensation level, promoting moist convection and afternoon precipitation. The findings from this study shed new light on SMPC and have important implications for precipitation forecasting over the plateau.

The variability of the shortwave radiative fluxes at the surface and top of atmosphere (TOA) is examined in a pre-industrial modeling setup using the Pacific Decadal Oscillation (PDO) as a possible pacemaker of atmospheric decadal-scale variability. Within models from the Coupled Model Intercomparison Project—Phase 6, downwelling shortwave radiation at the surface, the net shortwave fluxes at the surface and TOA, as well as cloud radiative effects show remarkably similar patterns associated with the PDO. Through ensemble simulations designed with a pure PDO pattern in the North Pacific only, we show that the PDO relates to about 20%–40% of the unforced year-to-year variability of these shortwave fluxes over the Northern Hemispheric continents. The sea surface temperature imprint on shortwave-flux variability over land is larger for spatially aggregated time series as compared to smaller areas, due to the blurring effect of small-scale atmospheric noise. The surface and TOA radiative flux anomalies associated with the PDO index range of [−1.64; 1.64] are estimated to reach up to ±6 Wm−2 for North America, ∓3 Wm−2 for India and ±2 Wm−2 for Europe. We hypothesize that the redistribution of clouds in response to a North Pacific PDO anomaly can impact the South Pacific and North Atlantic SSTs.

We present the first continuous observations of three-dimensional spatially resolved wind fields and atmospheric motions in the mesosphere and lower thermosphere in the mid-latitudes of the Northern Hemisphere. Our observations were performed during a 19-month campaign from January 2022 to July 2023 and exploited the composite data from the first multistatic meteor radar system in China and an adjacent monostatic meteor radar. To retrieve the atmospheric kinetic properties, we introduce an improved volume velocity processing method including coordinate transformations and non-linear constraints to minimize errors. The vertical winds are estimated separately from the iteration of the horizontal divergence to avoid potential biases or contamination from the horizontal winds. The winds and air motions show annual/semiannual variation characteristics within certain altitudes, usually more variable around the equinoxes. The vertical winds are basically within the magnitude of 1 m/s and are upward as expected at the mesopause during the summer, which corresponds to the adiabatic cooling.

No abstract is available for this article.