Atmospheric Column Research Articles

Discriminating between “drizzle or rain” and sea salt aerosols in Cloudnet for measurements over the Barbados Cloud Observatory

Abstract. The highly sensitive Ka-band cloud radar at the Barbados Cloud Observatory (BCO) frequently reveals radar reflectivity signals below −50 dBZ within the convective sub-cloud layer. These so-called haze echoes are signals from hygroscopically grown sea salt aerosols. Within the Cloudnet target classification scheme, haze echoes are generally misclassified as precipitation (target class: “drizzle or rain”). We present a technique to discriminate between “drizzle or rain” and sea salt aerosols in Cloudnet that is applicable to marine Cloudnet sites. The method is based on deriving heuristic probability functions utilizing a combination of cloud radar reflectivity factor, radar mean Doppler velocity, and the ceilometer attenuated backscatter coefficient. The method is crucial for investigating the occurrence of precipitation and significantly improves the Cloudnet target classification scheme for measurements at the BCO. The results are validated against the amount of precipitation detected by the Virga-Sniffer tool. We analyze data for measurements at BCO covering 2 years (July 2021–July 2023). A first-ever statistical analysis of the Cloudnet target classification product including the new “haze echo” target over 2 years at the BCO is presented. In the atmospheric column above the BCO, “drizzle or rain” is on average more frequent during the dry season compared to the wet season due to the higher occurrence of warm clouds contributing to the amount of precipitation. Haze echoes are identified about 4 times more often during the dry season compared to the wet season. The frequency of occurrence of “drizzle or rain” in Cloudnet caused by misclassified haze echoes is overestimated by up to 16 %. Supported by the Cloudnet statistics and the results obtained from the Virga-Sniffer tool, 48 % of detected warm clouds in the dry and wet season precipitate. The proportion of precipitation evaporating fully before reaching the ground (virga) is higher during the dry season.

Hybrid Models of Atmospheric Block Columns of Primary Oil Refining Unit Under Conditions of Initial Information Deficiency

Hybrid Models of Atmospheric Block Columns of Primary Oil Refining Unit Under Conditions of Initial Information Deficiency

Measurement of GPS Derived Precipitable Water Vapour (PWV) in Low and High Altitudes in Nepal

The study of Precipitable Water Vapour (PWV) using satellite data and ground-based observation is crucial for understanding hydrological processes, atmospheric circulation, and weather systems. It is considered the most prominent greenhouse gas in the Earth’s atmosphere. It is highly variable in both space and time across the Earth. Precipitable Water Vapor is a measure of the total amount of water vapour present in a vertical column of the atmosphere from the Earth’s surface to the top of it. This study investigates the potential atmospheric water vapour column at high (JMSM)and low(GRHI) to understand water vapour dynamics. To investigate precipitable water vapour, GNSS/GPS data were downloaded from UNAVCO SAGE. The downloaded data were processed and analyzed using GAMIT/GLOBK software which is a comprehensive GPS analysis package developed at the Massachusetts Institute of Technology (MIT), the Harvard-Smithsonian Center for Astrophysics (CfA), and the Scripps Institution of Oceanography (SIO). The main purpose of this software is to process data for Atmospheric science. This paper’s findings investigate the PWV amount in high and low altitudes over a year. Our finding shows that there is a significant difference in PWV levels between the two stations, with low-altitude areas exhibiting higher humidity and precipitation during the monsoon season, while high altitudes show reduced water vapour concentrations influenced by surrounding climatic variation.

Geometric approximations for global atmospheres on moderately oblate planets

AbstractCertain geometric approximations, such as the widely used traditional shallow‐atmosphere, spherical‐geoid (TSA‐SG) and deep‐atmosphere, spherical‐geoid (DA‐SG) approximations, boil down to the specification of a spatial metric tensor. In order to eliminate the leading‐order errors due to the SG and TSA approximations, a sequence of four geometric approximations of decreasing accuracy at high altitudes is obtained. Their Lagrangians possess a simple, closed‐form analytical expression. The approximations capture to leading order the oblateness of the planet, the widening of atmospheric columns with height, the horizontal and vertical variations of gravity, and the non‐traditional part of the Coriolis force. Furthermore, for the last two approximations, the horizontal metric is conformal (proportional) to the spherical metric, which may simplify analytical and numerical formulations of the equations of motion.

Towards an understanding of uncertainties in the Lagrangian analysis of moisture sources for tropical cyclone precipitation through a study case

Despite the increasing number of atmospheric moisture tracking tools, their validation is challenging due to the lack of observations. This work contributes to a better understanding of uncertainties in the moisture sources analysis for the precipitation of tropical cyclones (TCs) by assessing eight combinations of threshold values in tracking methods based on the Lagrangian water budget equation. We selected as a study case Hurricane Ida that formed in the North Atlantic basin in late August 2021 and extracted the air parcel trajectories from the global outputs of the Lagrangian FLEXPART model. Results indicate that the choice of relative humidity (RH) threshold for filtering precipitating parcels has a noticeable impact on the Lagrangian precipitation estimates. In addition, methods applying the atmospheric boundary layer restriction produce a weaker moisture source pattern than those accounting for moisture uptakes in the whole atmospheric column. In particular, methods imposing an RH restriction along the air parcel trajectories to filter out noise in moisture losses outperform the others, providing more reliable moisture source contributions. We also introduced a simple bias correction approach that further improves the reliability of moisture source representation.

Atmospheric CO2 column concentration over Iran: Emissions, GOSAT satellite observations, and WRF-GHG model simulations

Regarding global warming and climate change, carbon dioxide (CO2) is one of the most important greenhouse gases. Simulating CO2 gas at hourly/weekly time intervals and desired vertical resolution is challenging due to the coarse horizontal resolution of global models. In this study, both column-averaged CO2 mixing ratio (XCO2) and vertical cross sections of CO2 mixing ratio were simulated by the Weather Research and Forecast Green House gas (WRF-GHG) model at spatial resolutions of 30 and 10 km for the Middle East region as the first domain, and Iran as the second domain. Simulations consider the primary CO2 sources (anthropogenic, biogenic, fire, and oceanic) and the Copernicus Atmosphere Monitoring Service (CAMS) dataset. XCO2 retrieved from GOSAT satellite observations was employed to evaluate the simulation results of the column-averaged CO2 concentrations in February and August 2010. The evaluations showed that the spatiotemporal variability of meteorological variables was well simulated by WRF-GHG with correlation coefficients r of 0.86–0.92, 0.67–0.75, and 0.76–0.82 for temperature, wind, and relative humidity, respectively, during February and August 2010. The evaluations also indicated that the WRF-GHG simulations outperformed the global model TM3, with mean bias error values of − 0.79 and 0.45 PPMV for WRF-GHG in February and August, respectively. The percentage contribution of net CO2 emissions from human activities in Iran was calculated as (38.33 % and 23.70 %) of the total emissions, respectively, with values of 4.4 and 0.85 kg/km2 in each month. The net emissions contributions of biogenic, fire, and oceanic sources were evaluated in February and August, with biogenic emissions contributing (31.901 % and 27.66 %), biogenic absorption contributing (24.07 % and 46.63 %), fire emissions contributing (5.7 % and 2.064 %), and oceanic emissions contributing (3.23 × 10−6 % and 2.23 × 10−6 %). Large-scale circulations and biogenic activity are responsible for the major features of the spatial and seasonal distribution of CO2 in the area. In February, column mixing ratios are higher in more northern latitudes; in August, they are higher to the south. Furthermore, the simulated vertical cross sections show high CO2 mixing ratios in the mid-lower troposphere and northerly/northeasterly advection in February; the vertical profile is inverted in August with high concentrations in the lower stratosphere associated with southwesterly advection. However, the interaction between the synoptic and sub-synoptic features with the topography determines the precise dispersion and distribution of CO2. Despite the negligible emissions in central and eastern Iran, these factors play an important role in the observed concentrations in February and August. In August, the areas between the 120-day low-level monsoon flow of Sistan in eastern Iran, and the westerlies over western/southwestern Iran and the Zagros Mountain range, interact with the heat-low in the Iranian plains and with the Arabian subtropical high. In February, the dominant winds in western Asia were west winds, with the main source of pollution coming from the northeastern regions flowing towards central and eastern Iran. The equatorward displacement of the polar jet stream and the passage of low-pressure systems from the west in winter cause a temporary reduction in CO2 concentrations.

ANÁLISE HAZOP DE UMA UNIDADE DE DESTILAÇÃO ATMOSFÉRICA DE PETRÓLEO E SIMILARIDADE EM PROCESSOS DE PRODUÇÃO DE COMBUSTÍVEIS SUSTENTÁVEIS PARA AVIAÇÃO (SAFs)

The production of petroleum products stands out worldwide, among the production processes of non-renewable energies, as the best known worldwide. In this work, an atmospheric distillation column that processed 100,000 barrels/day (662.5 m3/h) of crude oil was simulated using the CHEMCAD® software. From this procedure, the Process Flow Diagram (PFD) and the Piping and Instrumentation Diagram (PI&D) were obtained for the unit, corresponding to its automation. Subsequently, a HAZOP (Hazard and Operability Study) analysis was conducted in order to identify risks in the unit that, although not dangerous, could compromise its ability to achieve its productivity. The main risks of the process were related to fires, explosions and environmental contamination from leaks and ruptures in pipes, pumps, heat exchangers, the column itself, among other equipment. The HAZOP analysis was able, through the use of the guide words, to identify the possible operational risks arising from deviations in the operating intentions, such as the possibility of fires, explosions, environmental contamination and its consequences. It was possible to identify the risks that are associated with the selection of materials, the mechanical design of the equipment and the specifications of the accessories. Therefore, the study carried out is an important survey to reduce possible failures in the oil industry. And, this study being a deepening of the distillation processes for petroleum products. It is understood that its deepening, as a result of the development of new renewable products, especially sustainable aviation fuels (SAFs), due to being similar purification processes, employ the same methodology to identify possible failures in production.

Observing the SO2 and Sulfate Aerosol Plumes From the 2022 Hunga Eruption With the Infrared Atmospheric Sounding Interferometer (IASI)

AbstractThe Hunga volcano violently erupted on 15 January 2022, producing the largest perturbation of the stratospheric aerosol layer since Pinatubo 1991, despite the initially estimated modest injection of SO2. This study presents novel SO2 and sulfate aerosol (SA) co‐retrievals from the Infrared Atmospheric Sounding Interferometer, and uses them to quantify the initial progression of the Hunga plume. These observations are consistent with rapid conversion of SO2 (e‐folding time: 17.1 ± 4.3 days) to SA, with an injected burden of >1.0 Tg SO2. This points at larger SO2 injections than previously thought. A long‐lasting SA plume was observed, with two separate build‐up phases, and with a meridional dispersion of marked anomalies from the tropics to the higher southern hemispheric latitudes. A limited (∼20%) SA removal was observed after 1‐year dispersion. The total injected SA mass burden was estimated at 1.6 ± 0.5 Tg in the total atmospheric column, with a build‐up e‐folding time of about 2 months.

Greenhouse gas column observations from a portable spectrometer in Uganda

Abstract. The extensive terrestrial ecosystems of tropical Africa are a significant store of carbon and play a key but uncertain role in the atmospheric budgets of carbon dioxide and methane. As ground-based observations in the tropics are scarce compared with other parts of the world, recent studies have instead made use of satellite observations assimilated into atmospheric chemistry and transport models to conclude that methane emissions from this geographical region have increased since 2010 as a result of increased wetland extent, accounting for up to a third of global methane growth, and that the tropical Africa region dominates net carbon emission across the tropics. These studies critically rely on the accuracy of satellite datasets, such as those from the Orbiting Carbon Observatory-2 (OCO-2), the Greenhouse gases Observing SATellite (GOSAT), and the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI), along with results from atmospheric transport models, over a geographical region where there are little independent data to test the robustness of published results. In this paper we present the first ground-based observations of greenhouse gas column concentrations over East Africa, obtained using a portable Bruker EM27/SUN Fourier transform infrared (FTIR) spectrometer during a deployment covering the first few months of 2020 in Jinja, Uganda. We operated the instrument near autonomously by way of an automated weatherproof enclosure and observed total atmospheric column concentrations of the greenhouse gases carbon dioxide and methane, as well as carbon monoxide, a useful proxy for emissions from incomplete combustion processes in the region. We discuss the performance of the combined enclosure and spectrometer system that we deployed in Jinja to obtain these data and show comparisons of our ground-based observations with satellite datasets from OCO-2 and Orbiting Carbon Observatory-3 (OCO-3) for carbon dioxide and TROPOMI for methane and carbon monoxide, whilst also comparing our results with concentration data from the GEOS-Chem and Copernicus Atmosphere Monitoring Service (CAMS) atmospheric inversions that provide a means of increasing spatial and temporal coverage where satellite data are not available. For our measurement period, we find mean differences in XCO2 between OCO-2 and the EM27/SUN of −0.29 % and between OCO-3 and the EM27/SUN of −0.28 %. In the case of TROPOMI, the mean difference in XCH4 that we find between TROPOMI and the EM27/SUN is −0.44 %, whilst for XCO the mean difference is −5.65 %. In each of these cases, the mean difference observed between the satellite and ground-based column concentrations is either close to or within the precision and accuracy requirements for the respective missions. With regard to the model and reanalysis comparisons with the EM27/SUN column concentrations, we see mean differences from the EM27/SUN of a global GEOS-Chem inversion for XCO2 of −0.08 %, a regional high-resolution GEOS-Chem inversion for XCH4 of −0.22 %, and the CAMS global reanalysis for XCO of −9.79 %. Our results demonstrate the value of ground-based observations of total column concentrations and show that the combined EM27/SUN and enclosure system employed would be suitable for acquisition of the longer-term observations needed to rigorously evaluate satellite observations and model and reanalysis calculations over tropical Africa.

Medium-Term Monitoring of Greenhouse Gases above Rice-Wheat Rotation System Based on Mid-Infrared Laser Heterodyne Radiometer

The rice-wheat rotation system is a major agricultural practice in China as well as an important source of greenhouse gas (GHG) emissions. In this study, the developed mid-infrared laser heterodyne radiometer (MIR-LHR) was used for the remote sensing of atmospheric CH4 and N2O concentrations above the rice-wheat rotation system. From April 2019 to May 2022, the atmospheric column concentrations of CH4 and N2O above the rice-wheat rotation system were continuously observed in Hefei, China. The peak values of the N2O column concentration appeared 7~10 days after wheat seasonal fertilization, with additional peaks during the drainage period of rice cultivation. During the three-year rice-wheat crop rotation cycle, a consistent trend was observed in the CH4 column concentrations, which increased during the rice-growing season and subsequently decreased during the wheat-growing season. The data reveal different seasonal patterns and the impact of agricultural activities on their emissions. During the observation period, the fluctuations in the CH4 and N2O column concentrations associated with the rice-wheat rotation system were about 40 ppbv and 6 ppbv, respectively. The MIR-LHR developed for this study shows great potential for analyzing fluctuations in atmospheric column concentrations caused by GHG emissions in the rice-wheat rotation system.

Research on simulation and validation methods of aerosol radiative forcing on the Tibetan Plateau based on satellite and ground-based remote sensing observations over the past 20 years

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

Influence of columnar versus vertical distribution of aerosol properties on the modulation of shortwave radiative effects

Quantifying the interaction of atmospheric aerosols with incoming solar radiation remains a challenge owing to the limitations associated with measuring aerosol optical properties. This study investigates how the distribution of aerosol properties, whether columnar or vertical, affects the aerosol radiative forcing (ARF) and heating rates (HRs) across different atmospheric layers under cloud-free conditions in the shortwave region. We also assess the atmospheric parameters, namely, pressure, temperature, water vapour density, and ozone density, from in-situ measurements, reanalysis data, and a standard tropical atmosphere to understand their impact on ARF and HR estimates across seasons. Our findings show that aerosol absorption is highest during monsoon, while it is lowest in the winter. Significant atmospheric warming due to aerosols resulted from the substantial cooling at the surface. Columnar properties of aerosols measured at limited or multiple wavelengths yield similar ARF and HR estimates, provided spectral dependency is considered using the Angstrom exponent across seasons. However, the vertical profiles of aerosol extinction, together with a constant single scattering albedo (SSA) along the atmospheric column versus an actual SSA profile, led to notable differences in ARF and HRs, specifically in pre-monsoon and monsoon periods. Free tropospheric aerosol absorption is underestimated when using columnar properties compared to vertical distribution, while boundary layer absorption is overestimated (> 10 Wm-2). The heterogeneity in aerosol types across atmospheric layers significantly influenced aerosol absorption, highlighting the importance of accurate vertical distribution information. HR profiles obtained with vertical distribution reflect the structure of aerosol extinction, whereas those estimated with columnar properties result in smoother profiles that fail to capture altitude gradients. Aerosol-induced HRs are higher within the boundary layer and free troposphere in the monsoon season for all scenarios of defined aerosol properties. These findings underscore the need for actual vertical profile measurements of aerosol properties to quantify aerosol radiation interaction.

TROPOMI unravels transboundary transport pathways of atmospheric carbon monoxide in Tibetan Plateau

Numerous studies have reported in situ monitoring and source analysis in the Tibetan Plateau (TP), a region crucial for climate systems. However, a gap remains in understanding the comprehensive distribution of atmospheric pollutants in the TP and their transboundary pollution transport. Here, we analyzed the high-resolution satellite TROPOMI observations from 2018 to 2023 in Tibet and its surrounding areas. Our result reveals that, contrary to the results from in situ surface CO monitoring, Tibet exhibits a distinct seasonality in atmospheric carbon monoxide total column average mixing ratio (XCO), with higher levels in summer and lower levels in winter. This distinctive seasonal pattern may be related to the TP's ‘air pump’ effect and the Asia summer monsoon. Before 2022, the annual growth rate of XCO in Tibet was 1.63 %·year−1; however, it declined by 6.88 % in 2022. Source analysis and satellite observations suggest that CO from South Asia may enter Tibet either by crossing the Himalayas or through the Yarlung Zangbo Grand Canyon. We discovered that spring outbreaks of open biomass burning (OBB) in South and Southeast Asia led to an 11.57–27.98 % increase in XCO over Tibet. Favorable wind pattern and unique topography of the canyon promote the high concentrations CO transport to Tibet. Our greater concern is whether the TP will experience more severe transboundary pollution in the future.

A Comparison of Regression Methods for Inferring Near‐Surface NO2 With Satellite Data

AbstractNitrogen dioxide (NO2) is an atmospheric pollutant emitted from anthropogenic and natural sources. Human exposure to high NO2 concentrations causes cardiovascular and respiratory illnesses. The Environmental Protection Agency operates ground monitors across the U.S. which take hourly measurements of NO2 concentrations, providing precise measurements for assessing human pollution exposure but with sparse spatial distribution. Satellite‐based instruments capture NO2 amounts through the atmospheric column with global coverage at regular spatial resolution, but do not directly measure surface NO2. This study compares regression methods using satellite NO2 data from the TROPospheric Ozone Monitoring Instrument (TROPOMI) to estimate annual surface NO2 concentrations in varying geographic and land use settings across the continental U.S. We then apply the best‐performing regression models to estimate surface NO2 at 0.01° by 0.01° resolution, and we term this estimate as quasi‐NO2 (qNO2). qNO2 agrees best with measurements at suburban sites (cross‐validation (CV) R2 = 0.72) and away from major roads (CV R2 = 0.75). Among U.S. regions, qNO2 agrees best with measurements in the Midwest (CV R2 = 0.89) and agrees least in the Southwest (CV R2 = 0.65). To account for the non‐Gaussian distribution of TROPOMI NO2, we apply data transforms, with the Anscombe transform yielding highest agreement across the continental U.S. (CV R2 = 0.77). The interpretability, minimal computational cost, and health relevance of qNO2 facilitates use of satellite data in a wide range of air quality applications.

Synoptic forcing and thermo-dynamical processes during cloudburst event over Sauni Binsar, Uttarakhand, India

Cloud bursts have become a pressing concern with their devastating impact and increasing frequency over the Himalayan region. Therefore, understanding the physical mechanisms associated with their occurrence is essential and urgent. Our investigation into the physical mechanisms of a cloud burst over Sauni Binsar, Uttarakhand, India, which occurred on 10 June 2021 around 06 UTC, is a step towards addressing this urgency. On the day of the cloud burst, there was a continuous accumulation/stagnation (at 850 hPa) of moist air over Sauni Binsar due to the northward propagation of the southwest monsoon, leading to atmospheric column supersaturation. The advection of warm air (dry) from the monsoon heat low at higher (700 hPa) caused potential instability over this region. Orographic lifting and a gradual increase in convergence over this region caused moist convection. Further, the analysis of Richardson's number indicated that turbulence was maximum in the middle and upper troposphere. Just a few hours before the cloud burst event (02–06 UTC 10 June 2021), the decrease in potential vorticity indicates the squashing of the moist columns and the decrease in the vorticity. The sudden squashing of the supersaturated atmospheric column might have caused enormous rainfall (Cloud burst) over the Sauni Binsar region.

Remote sensing of H2O/HDO in the atmospheric column based on a near-infrared laser heterodyne radiometer suppressing local oscillator relative intensity noise

Laser heterodyne radiometer (LHR) exploits the heterodyne signal generated by solar radiation beated with local oscillator (LO) light to extract information on atmospheric species in the atmospheric column. Most of currently reported LHRs are affected by LO-induced relative intensity noise (RIN), which poses a challenge for high-sensitivity detection. In this work, a near-infrared RIN-suppressed LHR is proposed for simultaneous detection of water vapor and HDO in the atmospheric column. The operability of a home-made sun tracker can be obtained from coarse tracking and fine tracking, which offers an excellent opportunity for unattended observation. A tunable distributed feedback (DFB) diode laser centered at 1552.9 nm is employed as LO, where LO-induced RIN is suppressed by a semiconductor optical amplifier (SOA) operating in the dynamic gain saturation regime. By locking LO power and suppressing LO-induced RIN, the SOA-assisted LHR is dominated by 1.27 times shot-noise and the signal-to-ratio (SNR) of heterodyne signal is increased by 5 times. Based on atmospheric transmission spectra measured with the RIN-suppressed LHR in Hefei, China, the total column abundances of water vapor and HDO are retrieved to be 2050 ppm and 0.6 ppm, respectively, with uncertainty of 2 %.

Vertical Variability of Aerosol Pollution in St. Petersburg According to Long-term Lidar Observations

Processing of data obtained using lidar technologies was carried out to identify the vertical variability of the distribution of aerosols in the atmospheric column by month. The results of 227 lidar measurements from 2014 to 2023 were processed in total. It has been established that the concentration and height of compacted aerosol layers begin to increase in spring time, reaches a maximum in July, and from October there is a visible decline in aerosol concentrations in the atmospheric air. It has been established that in the warm season the height of compacted aerosol layers reaches 1200–1800 m, while in the cold season it reaches only heights of 600–1100 m. It was concluded that fine aerosol predominates over the city, based on the calculated Angstrom parameter in the range from 1.95 to 2.91.

Solutions for Tropical Vertical Motion under Convective Quasi-Equilibrium Constraints

Abstract Solutions for tropical convection (vertical motion), including both the first (deep) and the second baroclinic (shallow) modes, subject to convective quasi-equilibrium (CQE) constraints are formulated. Under CQE assumption, tropical convection ω(p, x, y) can be decomposed into a product of height-dependent variable Ωi(p) and space-dependent variable ∇·vi(x, y) with the former constrained by conservation of moist static energy (MSE) or dry static energy (DSE) perturbations, depending on whether the atmospheric column is dominated by ascending or descending motions. We then evaluate the roles of deep and shallow modes of convection in transporting moisture and static energy against observations using the European Centre for Medium-Range Weather Forecasts reanalysis data. The moisture transport by deep mode produces a spatial pattern similar to observations, except for an obvious underestimate of the magnitude over the eastern Pacific convergence zone (EPCZ) and cold tongue areas, where the contribution of shallow mode may account for up to 25% of the total moisture transport. In contrast, the MSE transport by deep mode exhibits a very poor performance, especially over the EPCZ where the observational MSE transport is negative, but a positive value is predicted by deep mode. Including the contribution of shallow mode immediately remedies this deficiency, due to a better representation of the bottom-heavy structure of ascending motions over the EPCZ. These improvements apply to almost the entire tropics, although the correlation tends to decrease away from the convergence zones. Since simple atmospheric models often assume a single heating (forcing) profile to represent the effect of cumulus convection, the present study highlights the importance and feasibility of including both deep and shallow modes in a simple atmospheric model, while at the same time maintaining the simple model framework, to more accurately represent the moisture and MSE transports by convection in the tropics.

Sensitivity analysis of a Martian atmospheric column model with data from the Mars Science Laboratory

Abstract. An extensive sensitivity analysis was performed for a horizontally homogeneous and hydrostatic 1-D column model at the Mars Science Laboratory (MSL) location. Model experiments were compared with observations from the Curiosity Rover Environmental Monitoring Station humidity (REMS-H) device and ChemCam. Based on our earlier column model investigations, model surface temperature and pressure, dust optical depth (τ), and column precipitable water content (PWC) were the parameters that we investigated with our sensitivity analysis. Our analysis suggests that the most sensitive parameters for the column model temperature profile are τ and surface temperature. The initial value of PWC does not affect the temperature profile of the model, but it is the most important parameter for the humidity profile. The fixed value of τ also seems to have some effect on the humidity profile of the model. Based on our analysis, variations in surface pressure initialization are negligible for the model's temperature and almost negligible for the model's humidity predictions. The model simulations are generally in good agreement with the observations. Our additional model experiments with a different shape of the model's initial humidity profile yielded better results compared to the well-mixed assumption in the predicted water vapor volume mixing ratios at 1.6 m.

Benthic habitat mapping for estimating seagrass carbon stock across Takabonerate Islands, Indonesia

Data on benthic habitat cover are essential for monitoring and managing coastal areas, providing valuable ecosystem services for local communities. Moreover, seagrass extent is crucial for estimating carbon stock using Tier-1 calculations. On the other side, remote sensing technology has proven effective in mapping benthic habitat cover, including seagrass, over large local areas. Therefore, this research aims to map specific benthic habitats in a local area to obtain high-accuracy estimates of seagrass extent for carbon stock estimation. The study was conducted in the Takabonerate Islands, Indonesia, using Sentinel-2A imagery. The study involved field data processing, which enabled the mapping of eight benthic habitat classes using Sentinel-2A images, along with the steps for Sentinel-2A image processing for benthic habitat mapping. The benthic habitat map was produced following image correction steps, including atmospheric, sunglint, and water column corrections, followed by image classification using a Neural Net Classifier (NNC). Seagrass carbon stock estimation was performed using the Tier-1 equation from IPCC 2013. The study revealed a total benthic habitat area of 57,538.04 ha, with a seagrass area of 3127.42 ha for carbon stock estimation. The potential seagrass carbon stock in the study area was estimated to range from 337.76 GgC/ha to 31.27 GgC/ha using the Tier-1 equation. The overall accuracy of the benthic habitat map was 80.5 %, calculated using a confusion matrix table. The spatial information from this study can be used by local coastal managers and governments for baseline and monitoring purposes. The key interpretations from this study provide valuable findings that can be adapted and improved for future local mapping purposes.