JGR–Atmospheres

Aerosol-cloud-precipitation interactions are a leading source of uncertainty in estimating climate sensitivity. Remote marine boundary layers where accumulation mode (∼100–400 nm diameter) aerosol concentrations are relatively low are very susceptible to aerosol changes. These regions also experience heightened Aitken mode aerosol (∼10–100 nm) concentrations associated with ocean biology. Aitken aerosols may significantly influence cloud properties and evolution by replenishing cloud condensation nuclei and droplet number lost through precipitation (i.e., Aitken buffering). We use a large-eddy simulation with an Aitken-mode enabled microphysics scheme to examine the role of Aitken buffering in a mid-latitude decoupled boundary layer cloud regime observed on 15 July 2017 during the Aerosol and Cloud Experiments in the Eastern North Atlantic flight campaign: cumulus rising into stratocumulus under elevated Aitken concentrations (∼100–200 mg−1). In situ measurements are used to constrain and evaluate this case study. Our simulation accurately captures observed aerosol-cloud-precipitation interactions and reveals time-evolving processes driving regime development and evolution. Aitken activation into the accumulation mode in the cumulus layer provides a reservoir for turbulence and convection to carry accumulation aerosols into the drizzling stratocumulus layer above. Further Aitken activation occurs aloft in the stratocumulus layer. Together, these activation events buffer this cloud regime against precipitation removal, reducing cloud break-up and associated increases in heterogeneity. We examine cloud evolution sensitivity to initial aerosol conditions. With halved accumulation number, Aitken aerosols restore accumulation concentrations, maintain droplet number similar to original values, and prevent cloud break-up. Without Aitken aerosols, precipitation-driven cloud break-up occurs rapidly. In this regime, Aitken buffering sustains brighter, more homogeneous clouds for longer.

This study investigates the anthropogenic contribution to the summer precipitation changes over southern China and the underlying physical mechanisms. Observations show a wetting trend over southeastern China (SEC) but a drying trend over southwestern China (SWC) in summer of 1961–2014. The dipole pattern can be reasonably reproduced by the anthropogenic forcing simulations of CMIP6 models but with weak trends under the external natural forcing simulations, suggesting the vital human contribution to the observed changes. Particularly, anthropogenic greenhouse gases (GHG) dominate the wetting trend over SEC, while the drying trend over SWC is primarily attributed to anthropogenic aerosol (AA) emissions. Further analysis shows that the GHG concentrations enhance the subtropical high over the western North Pacific (WNP) via the heterogeneous warming of the sea surface temperature, decrease the sea level pressure over eastern China, and increase the atmospheric moisture, facilitating the moisture flux convergence (MFC) and the precipitation over SEC. The GHG-induced wetting trend is somewhat offset by the inhibited evaporation due to the AA forcing. For SWC, the decreased precipitation is influenced by the anomalous high pressure from India to WNP, which is closely associated with the enhanced Asian AA emission and the interhemispheric asymmetrical distribution of AA emissions. In the upper troposphere, the uneven AA emissions between South and East Asia and Europe weaken the East Asian summer subtropical jet, resisting the western moisture to SWC. Both factors in the low-and-high levels suppress the MFC and precipitation over SWC, counteracted by the thermodynamical effects of GHG forcing.

The dynamic variations of agricultural drought can reflect the water shortage situation of the agricultural system, and there is a progressive relationship in the response of agricultural drought to meteorological drought on a spatiotemporal scale. In this study, the vegetation health index and the standardized precipitation evapotranspiration index were adopted as agricultural and meteorological drought indicators, respectively. Additionally, using the three-dimensional spatiotemporal clustering technology, the dynamic evolutions of typical drought events were clarified, and the spatiotemporal response characteristics of agricultural drought to meteorological drought were revealed. The results indicated that: (a) there were 81 agricultural drought events in the North China Plain (NCP) during 1982–2020, with a largest drought severity (12.82 × 104 month km2), a 6-month duration, and a 23.24 × 104 km2 affected area occurring in the No. 4 event; (b) from the 1980s to the 2010s, the agricultural drought gradually decreased and large-scale droughts mainly concentrated in the border areas of Hebei, Shandong, and Henan; and (c) a total of 13 drought event pairs were successfully matched in the NCP, including 7 pairs of “one-to-one,” 4 pairs of “one-to-many,” 1 pair of “many-to-one,” and 1 pair of “many-to-many.” The spatiotemporal responses of agricultural drought were elucidated in a three-dimensional perspective, which can propose a new approach for establishing drought propagation model, predicting future agricultural drought conditions, improving ecological environment quality, and can also be applied for the investigation of other drought types.

Planetary boundary layer (PBL) modeling is a primary contributor to uncertainties in a numerical weather prediction (NWP) model due to difficulties in modeling the turbulent transport of surface fluxes. The Weather Research and Forecasting model (WRF) has provided many PBL schemes that may feature a non-local transport component driven by large eddies or a one-and-half order turbulence closure model, but few of them possess the two features at once. In the present study, a turbulent kinetic energy (TKE)-based eddy diffusivity/viscosity method is integrated into the non-local Asymmetric Convective Model version 2 (ACM2) PBL scheme and implemented in WRF. The original first-order eddy-diffusivity term in ACM2 is discarded and an extra prognostic equation for TKE, which considers the tendency of TKE by buoyancy, wind shear, vertical transport, and dissipative processes, is supplied to calculate the diffusivity/viscosity. Non-local transport is modeled the same as ACM2 using the transilient matrix method. Idealized tests using prescribed surface heat flux and roughness length are performed. TKE-ACM2 displays advantages over the PBL scheme developed by Bougeault and Lacarrère (hereinafter referred to as Boulac) and ACM2 in the wind speeds (WS) profile because it better matches large-eddy simulations results in the surface momentum flux. Real case simulations show that TKE-ACM2 generally outperforms in the diurnal vertical profiles of WS under stable conditions. TKE-ACM2 also produces a better alignment under moderately unstable conditions in the early nighttime at the urban LiDAR station. However, the model exhibits discrepancies more apparently under a more unstable condition during the winter daytime.

A Cimel Sun-sky-lunar photometer (CE318-T) is designed to perform daytime and nighttime photometric measurements and calculate diurnal cycle of aerosol optical depth (AOD). Nevertheless, the determination of nocturnal AOD from CE318-T requires a precise knowledge of extraterrestrial lunar irradiance, which significantly changes with moon's phase angle (MPA) and lunar libration in a single night. This study evaluated the 1-year nocturnal AODs at Lanzhou by using three different methods, which were validated by collocated measurements of DIAL Lidar (as a reference) and Cimel software (as a proxy). The results indicated that three independent approaches could implement a similar performance to compute nocturnal AOD near full moon phase (i.e., MPA = 0°) under moderate aerosol loading. The spectral AOD values at nighttime calculated by ROLO Lunar Langley (Robotic Lunar Observatory model) and Sun-moon Gain Factor (SMGF) methods are significantly underestimated under low moon's illumination or high MPA (MPA < −47° or MPA > 47°) and distinctly dependent on MPA. The RIMO correction factor (RCF) (ROLO Implementation for Moon photometry Observation correction factor) method could compensate the underestimated extraterrestrial lunar irradiances of ROLO model for about 6.76%–9.78%, and thus greatly improve the calculation accuracy of nighttime AOD. The day/night coherence transition test has demonstrated that we would obtain a good diurnal variation of AODs at Lanzhou after RCF correction. The overall averages of nocturnal AOD440nm differences between Cimel software and ROLO model and SMGF method are 0.064 ± 0.024 and 0.052 ± 0.022, respectively, while the corresponding difference of RCF is less than 0.021 ± 0.014 for all wavelengths, falling within uncertainty range of AERONET AOD products (∼±0.02). The diurnal variations of AODs determined from RCF method agree well with synchronous results of DIAL Lidar, with total mean AOD532nm differences of 0.038 ± 0.024 and 0.023 ± 0.017 in daytime and nighttime, respectively. The spectral AODs computed from RCF method are well consistent with Cimel software, although there are some discrepancies under low AOD cases (AOD440nm < 0.30), and the overall average of AOD440nm differences are less than −0.0053 ± 0.002 and −0.0185 ± 0.013 in daytime and nighttime, respectively. Our results confirmed that the CE318-T photometer can be reasonably calculated nighttime AOD and Ångström exponent (AE440–870nm) at urban Lanzhou by using three independent methods, although the former two need to be greatly improved under low moon's illumination. The RCF method was proved to reliably calculate nocturnal AOD from moonlight irradiance, which didn't rely on MPA. A more accurate lunar irradiance model needs to be developed to improve the underestimation of current ROLO model. Long-term climatological information of nocturnal AOD is crucial for comprehensively characterizing the diurnal variations of aerosol optical properties and atmospheric boundary layer structure during the winter at typical northern city of China, which deserves to be further investigated in the future.

The planetary boundary layer height (PBLH) is a crucial indicator reflecting the region of the atmosphere characterized by continuous turbulence. Here, we use radiosonde and surface meteorological observations (4–7 times per day, year-round measurements) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition to derive the PBLH (PBLH MOSAiC ), and further evaluate the PBLH from the ERA5 reanalysis (PBLH ERA5 ). Comparisons between PBLH MOSAiC and PBLH ERA5 from different perspectives reveal that: (a) The overestimation of PBLH ERA5 when the sea ice concentration is >90% is significant with the centered root mean squared error reaching up to 201 m; (b) The difference between the two products is notably pronounced in cold seasons, while it is comparatively diminished in warm seasons; (c) In neutral boundary layers, differences in PBLH ERA5 are larger compared with stable and convective boundary layers. In addition, the analysis of error sources indicates that the bias of PBLH ERA5 is sensitive to the bias of vertical thermal structure and wind speed profiles in ERA5 data sets in all conditions. Finally, we find a Random Forest model effectively reduces the bias of PBLH ERA5 with the index of agreement reaching up to 0.71 in the test data set, while a multiple linear regression demonstrates comparable performance to the Random Forest model.

Aerosol optical depth (AOD) is a vital parameter in atmospheric research. Using observations of the Visible Infrared Imaging Radiometer Suite (VIIRS), onboard Suomi National Polar-orbiting Partnership (Suomi-NPP) and NOAA-20 satellites, National Oceanic and Atmospheric Administration (NOAA) produces near-real time AOD product with high pixel resolution (750 m), wide swath width (3,040 km), and a 16-day repeat cycle. Here we report the evaluation of the NOAA/VIIRS AOD using a comprehensive aerosol data set, derived from a global-scale, multi-seasonal airborne mission, the NASA Atmospheric Tomography Mission (ATom). This data set includes rich physical and chemical information, such as size distributions, chemical compositions, optical properties, and hygroscopicities of major aerosol types, including dust, sea salt, smoke, internally mixed sulfate/nitrate/organics particles (non-smoke), black carbon, etc. Globally, VIIRS AOD (Suomi-NPP and NOAA-20) shows good agreement with the ATom AOD in the moderate to high AOD range (>0.3), with respect to measurement uncertainties (orthogonal distance regression fitting slope: 1.5 ± 0.2 for Suomi-NPP and 1.6 ± 0.5 for NOAA-20; correlation coefficient: 0.85 for Suomi-NPP and 0.73 for NOAA-20). There is a persistent bias in the low AOD range (<0.3) on the order of 0.03, likely reflecting systematic errors on VIIRS and/or the ATom AOD product. Ångström exponent reported by VIIRS shows excellent agreement with ATom results within expected uncertainties. Given the unique insights revealed by the ATom AOD and aerosol property data set, it is desirable to have ATom-like comprehensive payloads in future airborne satellite validation programs.

In June–July 2020, the middle and lower reaches of the Yangtze River (MLYR) were hit by a Meiyu event characterized by a long duration, abundant precipitation, and frequent heavy rainfall, resulting in destructive flooding. We found that the extreme cumulative precipitation in 2020 was mainly contributed by more moderate to heavy daily precipitation rather than extreme daily events. Although some previous studies have been conducted to attribute the 2020 Meiyu event in the MLYR, most of them focused on the cumulative precipitation amount. This attribution case study complements previous attribution analyses and reveals many new features. Our results show that anthropogenic climate change—primarily driven by greenhouse gas (GHG) forcing, anthropogenic aerosol (AA) forcing, and land-use—has led to a decrease in the number of light to heavy precipitation days, while concurrently increasing the number of extreme precipitation days in the MLYR. Specifically, GHG and AA forcings decreased the frequency of light and moderate precipitation, but only GHG increased the frequency of extreme precipitation. An increasing trend in very heavy precipitation days has been observed. The competitive effects of GHG and AA forcings make it challenging to detect the signal of human activities, which could be intermingled with effects from natural variability. Under the SSP5-8.5 scenario, the probability of experiencing both light and extreme precipitation events will significantly increase in the MLYR. By 2050–2100, these events are projected to be nearly 4 times more frequent compared to the current climate, which poses significant challenges to water security and economic development decision makers.

The interactions of clouds with radiation influence climate. Many of these impacts appear to be related to the radiative heating and cooling from high-level clouds, but few studies have explicitly tested this. Here, we use simulations with the ICON-ESM model to understand how high-level clouds, through their radiative heating and cooling, influence the large-scale atmospheric circulation and precipitation in the present-day climate. We introduce a new method to diagnose the radiative heating of high-level clouds: instead of defining high-level clouds as all clouds at temperatures colder than −35°C, we define them as all clouds with a cloud top at temperatures colder than −35°C. The inclusion of the lower cloud parts at temperatures warmer than −35°C circumvents the creation of artificial cloud boundaries and strong artificial radiative heating at the temperature threshold. To isolate the impact of high-level clouds, we analyze simulations with active cloud-radiative heating, with the radiative heating from high-level clouds set to zero, and with the radiative heating from all clouds set to zero. We show that the radiative interactions of high-level clouds warm the troposphere and strengthen the eddy-driven jet streams, but have no impact on the Hadley circulation strength and the latitude of the Intertropical Convergence Zone. Consistent with their positive radiative heating and energetic arguments, high-level clouds reduce precipitation throughout the tropics and lower midlatitudes. Overall, our results confirm that the radiative interactions of high-level clouds have important impacts on climate and highlight the need for better representing their radiative interactions in models.

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 enhancing precipitation amounts, frequency and low-level CF, particularly within the first 100 km radius downwind of the city boarder. The urban environment is found to increase precipitation efficiency over the city and in downwind regions. Temperature at 2 m height, planetary boundary layer height, turbulent kinetic energy, and convective available potential energy, are also enhanced in the perturbed runs and drive changes in vertical mixing, downwind precipitation amounts, frequency and low-level height CF. All these changes appear to be a non-linear function of the city size.

While the Department of Defense (DoD) infrastructure is no stranger to extremes, recent events have been unprecedented, with climate change acting as a growing risk multiplier. To assess the level of exposure of DoD installations to extreme weather and climate events, site-specific climate information is needed. One way to bridge the scale gap between outputs from existing global climate models (GCMs) and sites is climate downscaling. This makes the information more relevant for impact assessment at the DoD installation and facility scale. However, downscaling GCMs is beset by a myriad of challenges and sources of uncertainty, and downscaling methods were not designed with specific infrastructure planning and design needs in mind. Here, we evaluate state-of-the-science dynamical downscaling and statistical downscaling and bias correction for climate variables (i.e., temperature and precipitation) at the daily scale. We also combine downscaling approaches in novel ways to optimize computational efficiency and reduce uncertainty. Furthermore, we examine the sensitivity of the downscaled outputs to the choice of reference data and quantify the relative uncertainty related to downscaling approach, reference data, and other factors across the climate variables and aggregation scales. Results show that empirical quantile mapping (EQM), a statistical downscaling, consistently performs well and has less sensitivity to the choice of reference data. Moreover, the hybrid downscaling that leverages EQM improves the performance of dynamical downscaling. Our findings highlight that the choice of reference data dominates uncertainties in temperature downscaling, while their role is more muted for precipitation but still non-negligible.

Despite the importance of understanding the urban emission characteristics of greenhouse gases (GHGs) and air pollutants, few studies have conducted integrated assessments across diverse urban environments. Herein, we conducted a comprehensive evaluation of the emission characteristics of GHGs and air pollutants in seven cities in the Northern Hemisphere using ground-based Fourier transform spectrometers. Our analysis primarily focused on emission ratios of excess column-averaged dry-air mole fractions of carbon monoxide (CO) to carbon dioxide (CO2) (∆XCO:∆XCO2) and those of methane (CH4) to CO2 (∆XCH4:∆XCO2). We found that the emission ratios varied significantly across cities. Xianghe (China) and Pasadena (USA), known for severe air pollution, showed the highest emission ratios. Notably, Seoul (South Korea) showed lower ∆XCO:∆XCO2 (3.32 ± 0.10 ppb/ppm) but relatively higher ∆XCH4:∆XCO2 (4.85 ± 0.04 ppb/ppm), which was comparable to the ∆XCH4:∆XCO2 value of Xianghe (5.15 ± 0.10 ppb/ppm), suggesting that targeted CH4 reduction strategies may be required for climate change mitigation in Seoul.

Deciphering how modern precipitation patterns became established in monsoon-dominated East Asia and the arid interior Asia is crucial for predicting future precipitation trends under accelerated global warming and increased climate extremes. However, this effort is hindered by a scarcity of quantitative paleo-precipitation data in this region. Here we reconstruct the pattern of Middle to Late Miocene paleo-precipitation across an east-to-west transect from the summer monsoon-dominated East Asian region through the transition zone and into interior Asia. Our work is based on a newly established precipitation calculation equation and quantitative pollen-based precipitation conversion. Analysis indicates a common trend of precipitation across the studied region prior to ca, 11 Ma, followed by a clear divergence of precipitation variations between East and interior Asia since at least 11–9 Ma. This divergence is characterized by increasing precipitation in East Asia, but a coeval decrease in rainfall in the transition zone and interior Asia. The timing of this precipitation divergence was contemporaneous with intense tectonic activity in the northern Tibetan Plateau, which differentially affected the efficacy of water vapor transport into East and interior Asia. Modeling work using different topographic settings corroborates this tectonic influence. Our study demonstrates the early establishment of modern-like precipitation patterns in East-interior Asia at least in the early Late Miocene.

Changes in precipitation and its causes under future warming scenarios in Northwest China are of great concern. Based on the dynamical downscaling results of the Weather Research and Forecasting model (WRF), this study quantitatively identified the contribution of local evaporation and external moisture transport to future precipitation changes in western and eastern Northwest China (WNWC and ENWC) by calculating the precipitation recycling ratio (PRR). The results showed that the WRF could reasonably reproduce the observed spatial and temporal distribution of precipitation and evaporation during the historical reference period of 1985–2014. Under the 1.5 and 2.0°C stabilized warming scenarios from 2071 to 2100, there is a stronger precipitation growth in WNWC than in ENWC, and the PRR generally increases in WNWC and decreases in ENWC. Further analysis indicates that external moisture transport is the dominant contributor to the increased precipitation in all cases with its contribution exceeding 70%, while the difference of precipitation growth in two sub-regions arises from the summer moisture transport at the southern boundary as the inflow in WNWC and outflow in ENWC. Compared to the negligible contribution of evaporation in ENWC (less than 7%), evaporation contributes more than 23% to the precipitation increase in WNWC under future warming scenarios, which may be related to the strong land-atmosphere coupling there. Furthermore, an additional warming of 0.5°C leads to an increase in precipitation for both sub-regions, which is mainly due to the contribution of external moisture transport.

Agricultural soils containing nitrogen-rich fertilizers are a substantial source of reactive nitrogen to the atmosphere with potential to impact air quality. One form of reactive nitrogen, nitrogen oxides (NOx = NO + NO2), are a harmful air pollutant and form secondary pollutants, including particulate matter (PM) and ozone (O3). Soil nitrogen oxide emissions (SNOx) are heavily influenced by environmental conditions, however the understanding of the influence of environmental drivers on the behavior of SNOx is limited. Here, we implement a modified soil moisture-dependent SNOx parameterization into the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and investigate the impact on regional air quality in the central U.S. Evaluating against TROPOspheric Monitoring Instrument (TROPOMI) column NO2 observations, WRF-Chem columns better capture the TROPOMI column magnitudes earlier in the growing season when using the updated SNOx parametrization, with modeled column bias improved to −1.1% over the most heavily fertilized regions. Evaluating against Environmental Protection Agency (EPA) surface NO2 observations, the relationship between surface NO2 and soil moisture is better represented in agriculturally-dominant regions when using the updated parameterization, with greatest surface NO2 concentrations at moderate soil moisture and lower concentrations at wetter or drier soil conditions. In simulations, these SNOx lead to increased O3 in select urban regions, with more than double the occurrences of O3 exceeding the EPA 8-hr O3 standard of 70 ppb.

Strong surface winds induced by polar lows (PLs) may affect the upper ocean. However, understanding of the oceanic responses and feedback processes associated with PLs remains insufficient, especially for observations. Using a combined analysis of satellite-based sea surface temperature (SST) and PL tracking data, we investigated the oceanic response to 380 PL passages over the Nordic Sea occurring between 1999 and 2018. Consequently, two types of oceanic responses—warming and cooling—occurred in 32% and 40% of the total occurrences, respectively. The average magnitude of SST response was approximately ±0.2 K. Significant differences in upward surface turbulent heat flux (THF) between warming and cooling response cases were found, causing a significant difference in the decay rate after maximum PL development. By analyzing changes in the state variables of the THF, we identified two different feedback processes depending on the oceanic warming/cooling response. During a warming (cooling) response, the atmosphere near the surface becomes more unstable (stable), and the turbulence of the marine atmospheric boundary layer increases (decreases), which strengthens (weakens) the ocean surface wind and decreases (increases) temperature and specific humidity. These changes contribute to increasing (decreasing) the upward THF that influences PL development. The differences between these two responses may be caused by the state of the upper ocean layer, including temperature inversion. The analysis of the in situ observations of the upper ocean supports the hypothesis that a warming response occurs when inversion is strong. This study emphasizes the importance of feedback through oceanic responses for understanding and predicting PL.

This study characterizes moisture source regions for wintertime precipitation across the Salt-Verde watershed and Arizona (USA) through use of convection-permitting numerical experiments. We dynamically downscale three four-month-long (i.e., December-January-February-March, or DJFM) winter periods: a representative warm (DJFM 1997–1998), cold (DJFM 1999–2000), and neutral (DJFM 2016–2017) winter, as diagnosed by the mean Sea Surface Temperature (SST) across the El Niño 3.4 region compared to a 1995 to 2019 baseline. We utilize the Weather Research and Forecasting (WRF) model with water vapor tracers (WVTs) to distinguish moisture source contributions to total precipitation across Arizona, as originating from land evapotranspiration, sea evaporation, and external advection. Analysis of our numerical experiments demonstrates that WRF is able to capture the day-to-day precipitation events across the complex terrain that is characteristic of the Salt-Verde watershed, but seasonal accumulated precipitation is consistently overestimated compared to individual station observations. The spatial distribution of wintertime monthly accumulated precipitation across Arizona is well captured by WRF, although the total amount of rainfall is overestimated in some confined areas across the highlands of Arizona. Our convection-permitting WRF experiments also demonstrate that WVT contributions to total wintertime precipitation are apportioned roughly equally between sea evaporation (contributing 45.6%) across the North America west coast and external advection (contributing 48.1%), with land evapotranspiration playing a minimal role (i.e., the remaining 6.3%). We further conduct single-domain WRF experiments at non-convection-permitting resolution and conclude that local sea evaporation, bounded by 140°W and 100°W, is the primary moisture source region to total wintertime precipitation across the Salt-Verde watershed and Arizona independent of the remote tropical SST across the El Niño 3.4 region.

The direct radiative forcing (RF) from halocarbons is reasonably well characterized. However, the forcing due to polyatomic halogen reservoir and halocarbon breakdown products has not previously been quantified and it is important to estimate this contribution. Four gases, ClONO2, COCl2, COF2 and COClF, are considered; their stratospheric abundances mostly originate from the breakdown of chlorofluorocarbons, hydrochlorofluorocarbons and CCl4. They have significant mid-infrared absorption bands and peak stratospheric mole fractions ranging from around 20 ppt to over 1 ppb, which are large compared to typical abundances of many emitted halocarbons. Using satellite observations of stratospheric abundance, observed infrared spectra, and a narrow-band radiation code, the stratosphere-adjusted radiative forcings (SARF) is computed. The global-annual mean SARF is estimated to be 7 ± 0.8 mW m−2 based on measured abundances in the period 2004–2019, with ClONO2 contributing about 50%. Whilst not a major contributor to anthropogenic RF, only six individual halocarbon gases cause a significantly greater forcing. This forcing is then approximately attributed to their source gases; for most, it modestly enhances (by 1%–3%) both their direct RF and their global warming potentials. The most significant enhancement (5%–15%) is to CCl4, the principal source of stratospheric COCl2 and contributor to ClONO2 abundances; disagreement in recent satellite-based COCl2 retrievals is a significant source of uncertainty. These additional gases enhance the available best estimate of the total forcing due to halocarbon source gases (including e.g., ozone depletion) by about 3%; notably, this is the only identified indirect mechanism that increases, rather than decreases, total halocarbon forcing.

The orographic effect on the spatial structure of precipitation is a fundamental problem in hydrometeorology that still requires a better understanding of the physical processes involved in the emergence of rainfall patterns and their complex statistical structure. In tropical regions, where meteorological measurements are notoriously sparse and data quality control is often poor or missing, the study of precipitation modeling and prediction is challenging. This research aims to show an innovative approach based on a random cascade downscaling method to generate high-resolution precipitation products from coarse-scale precipitation products. This approach also includes a topographic enhancement function for describing the altitudinal variability of precipitation and a numerical diffusion filter to lessen the blockiness problem of random cascades. The suggested approach was applied to analyze some long-term precipitation statistics in the metropolitan area of Mexico City. The model result agrees closely with the temporal statistics of the selected precipitation products and reflects complex orographic constraints. The proposed downscaling approach becomes an alternative to expensive computational methods and allows urban hydrology applications and analysis of small watersheds to incorporate the effects of complex orography.

Fog processing has a significant impact on sulfur chemistry in the atmosphere. This study analyzed three winter fog events in Hong Kong using single-particle aerosol mass spectrometry (SPAMS) and a Monitor for AeRosols and GAses in ambient air (MARGA). Black carbon (BC)-related carbonaceous particles with substantial sulfate amounts comprised the largest particle number fraction (56.7%). Sulfate mass concentration decreased during fog due to the cloud's effective scavenging, but fog processing notably promoted sulfate formation at the single-particle level (average peak area increases of 31.2%). Hydroxymethanesulfonate (HMS), an important S(IV) compound and fog tracer, was identified accounting for up to 12% by particle number fraction. Although pH showed a positive correlation (r = 0.53–0.69) with HMS particles in each fog scenario, a negative overall correlation (r = −0.51) was observed. Further analysis revealed that the higher aerosol acidity (pH 0.65–3.11), promoted Fe dissolution, leading to 49% of HMS particles being mixed with Fe, which potentially facilitated sulfate formation via the Fenton reaction. Additionally, around 40% of HMS-Fe particles are mixed with oxalate, thereby warranting further attention for their potential to cause more intricate sulfur oxidation processes. This study reveals the initial identification of a high mixed-state of HMS-Fe, which could potentially serve as a crucial avenue for the formation of sulfate on individual particulate matter. Considering the persistent augmentation of aerosol acidity in the Asian region, this phenomenon necessitates further investigation and attention.