Ground-based Measurements Research Articles

Integrating Copernicus LMS with ground measurements data for leaf area index and biomass assessment for grasslands in Poland and Norway

ABSTRACT The integration of satellite data from the Copernicus Land Monitoring Service (CLMS) with ground-based measurements represents a pioneering approach to the assessment of leaf area index (LAI) and in situ biomass at grasslands in Poland and Norway. The aim of this study was to develop a method for assessing grass growth conditions and predicting biomass yield based on Sentinel-2 data and CLMS products. LAI values derived from CLMS were compared with in-situ measurements on grassland plots in the two regions of Podlaskie (PL84) and Wielkopolskie (PL41). Small random statistical errors observed in the differences represent a significant opportunity to use Copernicus data to develop a relationship model for biomass prediction. The NDII index calculated using Sentinel2 was considered important for biomass assessment in the humid areas of Norway. This relational biomass prediction model could provide valuable information to farmers, improving their ability to manage grasslands effectively. As a result of the research, relational models were developed has been developed to predict grassland fresh biomass yield with an R 2 accuracy of 0.72 for the first cut, 0.81 for the second cut and 0.91 for the third cut. This allows farmers to effectively manage and monitor grassland throughout the growing season.

Influence of cloudy and clear-sky partitions, aerosols, and geometry on the recent variability in surface solar irradiance components in northern France

Abstract. Surface solar irradiance (SSI) is a fundamental parameter whose components (direct and diffuse) and variabilities are highly influenced by changes in atmospheric content and scene parameters. The respective importance of cloudy-sky conditions and atmospheric aerosols on SSI evolutions is region dependent and only partially quantified. Here we provide a comprehensive analysis of SSI variabilities recorded in northern France, a region with extensive variability in sky conditions and aerosol loads. Through the application of automatic filtering methods to 1 min resolution SSI ground-based measurements over Lille, sky conditions are classified as clear-sky, 11 %; clear-sun-with-cloud, 22 %; and cloudy-sun situations, 67 % from 2010 to 2022, for which we analyze the statistics and variabilities in the global horizontal irradiance (GHI), beam horizontal irradiance (BHI), and diffuse horizontal irradiance (DHI). Coincident photometric measurements of aerosol properties and radiative-transfer simulations provide the means to conduct a multivariate analysis of the SSI observed trends and year-to-year evolutions and to estimate aerosol and cloud forcings under clear-sun conditions. The analysis of the record value of all-sky GHI in spring 2020 attributes 89 % of the changes to the exceptional sunlight conditions (57 % of clear-sun situations). It highlights also for that season the importance of solar zenith-angle changes, whose positive effects on clear-sun conditions surpass those due to aerosols. Our results show all-sky GHI and BHI positive trends of around +4.0 and +4.4 Wm-2yr-1, respectively, in both spring and summer, which are explained by more than 60 % by an increase in clear-sun occurrences of +1 % yr−1. Additional significant BHI increases under clear-sun conditions are mainly explained in spring by the negative trend in aerosol optical depth (−0.011 yr−1) and partly by angular effects in summer. Moreover, we find that clear-sun-with-cloud situations are frequently marked by irradiance enhancement due to clouds, with 13 % more GHI on a monthly average and 10 % additional diffuse proportion than in clear-sky situations. Under such conditions, clouds add on average 25 W m−2 of diffuse irradiance that sets the GHI at the remarkable level of pristine (aerosol-and-cloud-free) conditions or even higher, by more than +10 W m−2 in summer and for low aerosol loads. Overall, our results highlight the dominant and complex influence of cloudy conditions on SSI, which precedes or combines with that of aerosols and geometrical effects, and leads to a remarkable global level of SSI in clear-sun-with-cloud situations.

Extracting above-ground biomass in areas corresponding to FAO’s definition of “Forest” using open geospatial data: Results for ASEAN

Abstract. In this study, we extracted above-ground biomass (AGB) information for forests in different ecological zones of ASEAN (Association of Southeast Asian Nations) by integrating freely-available global AGB, forest, and ecological zone map products. Our objective was to assess the suitability of the data and proposed approach for national reporting of forest carbon stocks. We compared the satellite-derived AGB values of forests in ASEAN countries with the corresponding AGB values provided by the Intergovernmental Panel for Climate Change (IPCC) in their Guidelines for National Greenhouse Gas Inventories (which are derived from ground-based measurements of forest AGB). For this, we used a map integration approach that ensures that AGB data is extracted from areas corresponding to the Food and Agricultural Association (FAO) of the UN’s definitions of “forest” and “ecological zones”, as recommended by the relevant IPCC Guidelines. We found that the average satellite-derived AGB values extracted for each ecological zone were generally lower than the values for natural forests (but higher than the values for plantation forests) provided in the IPCC Guidelines. Further investigation showed that this was partly due to the presence of many erroneously low AGB values for forests in the extracted results, caused by errors in the data masks applied to the original global AGB map, including masks of cropland, urban areas, bare soil, and water bodies. Our findings suggest that further processing is necessary before using satellite-derived data for national reporting of forest carbon stocks in ASEAN countries, and we give a few possible options for this.

First evaluation of the GEMS glyoxal products against TROPOMI and ground-based measurements

Abstract. The Geostationary Environment Monitoring Spectrometer (GEMS) on board the GEO-KOMPSAT-2B satellite is the first geostationary satellite launched to monitor the environment. GEMS conducts hourly measurements during the day over eastern and southeastern Asia. This work presents glyoxal (CHOCHO) vertical column densities (VCDs) retrieved from GEMS, with optimal settings for glyoxal retrieval based on sensitivity tests involving reference spectrum sampling and fitting window selection. We evaluated GEMS glyoxal VCDs by comparing them to the TROPOspheric Monitoring Instrument (TROPOMI) and multi-axis differential optical absorption spectroscopy (MAX-DOAS) ground-based observations. On average, GEMS and TROPOMI VCDs show a spatial correlation coefficient of 0.63, increasing to 0.87 for northeastern Asia. While GEMS and TROPOMI demonstrate similar monthly variations in the Indochinese Peninsula regions (R > 0.67), variations differ in other areas. Specifically, GEMS VCDs are higher in the winter and either lower or comparable to TROPOMI and MAX-DOAS VCDs in the summer across northeastern Asia. We attributed the discrepancies in the monthly variation to a polluted reference spectrum and high NO2 concentrations. When we correct GEMS glyoxal VCDs as a function of NO2 SCDs, the monthly correlation coefficients substantially increase from 0.16–0.40 to 0.45–0.72 in high NO2 regions. When averaged hourly, GEMS and MAX-DOAS VCDs exhibit similar diurnal variations, especially at stations in Japan (Chiba, Kasuga, and Fukue).

Comparing Airborne and Along-Sidewall Ground-Based Measurements to Retrieve Thermal and PM10 Concentration Profiles in Two Alpine Valleys

Abstract The paper aims at investigating the effectiveness of estimating vertical profiles of air temperature and PM10 concentrations in Alpine valleys through ground stations positioned at different altitudes on one valley sidewall (i.e., pseudovertical profiles). Two case studies in the Italian Alps are investigated: Chiese Valley in Trentino Province and Camonica Valley in the Lombardy region. Vertical profiles of temperature and PM10 concentrations were derived from airborne measurements at the center of the two valleys by means of low-cost sensors installed on a drone during summer 2019 and a tethered balloon during winter 2020. At the same time, five stations, equipped with the same kind of low-cost sensors, simultaneously monitored the same variables on one mountain slope. Comparisons between pseudoprofiles and airborne soundings revealed that ground stations well approximated temperature and PM10 soundings during the night and early morning, while temperatures along the slopes were higher than in the center of the valley during daytime, due to solar radiative heating, with larger differences in summer than in winter. On the contrary, some episodes with PM10 concentrations slightly higher in the valley center than on the slope were recorded, due to transport events and upslope winds. Nonetheless, the pseudoprofiles based on slope ground measurements faithfully reproduced the vertical gradients of both air temperature and PM10 if compared to those assessed from the soundings performed at the center of the two valleys. Results show that pseudovertical profiles can be a reliable and inexpensive method for continuous monitoring of vertical air temperature and PM10 distribution in mountain valleys. Significance Statement The purpose of this study is to understand whether ground-based measurements of air temperature and particulate matter on mountain slopes can be used as suitable surrogates of vertical atmospheric soundings with tethered balloons or drones in mountain environment. This is important because balloon and drone soundings are expensive and regulative constrained. The knowledge of the vertical distribution of air temperature is crucial to predict the distribution of air pollutants in valleys, namely, the particulate matter emitted by wood burning. Our results showed that ground-based measurements on mountain slopes made with low-cost sensors can satisfactorily reproduce vertical gradients of air temperature and distribution of particulate matter in a reliable and inexpensive way.

The effect of Atmospheric Boundary Layer Meteorology in climate-related gases and VOCs concentrations over 3 European cities using an aerial platform

In the frame of the EU Horizon2020 ICARUS project, a N.A.S.A Awarded Light Manned Aircraft equipped with high-tech scientific instrumentation was used to perform an aerial mapping over Athens, Thessaloniki and Ljubljana greater areas. This study aimed to evaluate the effect of Atmospheric Boundary Layer (ABL) on Green House Gases (GHGs) and Volatile Organic Compounds (VOCs) concentrations over urban and rural areas of the above cities. Simultaneous ground-based measurements were performed in the respective regions. Air samples were pressurized with a stainless-steel bellows compressor into electropolished stainless steel canisters and analyzed by the use of a novel gas chromatographic system. The estimation of the mixing height (ΜΗ) of the ABL was based on the synoptic scale atmospheric circulation and the prevailing background wind. It was found that the MH variation, following the prevailing meteorological conditions, results in different concentration profiles in the lower troposphere over the examined regions. The pollutants concentrations were generally decreasing with altitude in the ABL. Under certain meteorological conditions, vertical mixing plus horizontal transport can cause a high pollution level at the top of ABL. The pollutants concentrations were low over less industrialized and upwind regions, suggesting that local emission sources play significant role on the GHGs and VOCs levels over the regions. However, due to the large scale of sampling area that the aircraft covers the above gradients in concentrations are relative low. AQ modelling activities for simulating the cases studied in the current or any relative future work could reduce operating costs and allow projections of potential impacts.

Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements

Abstract. Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation in important air pollutants such as nitrogen dioxide (NO2). The South Korean instrument GEMS (Geostationary Environmental Monitoring Spectrometer), launched in February 2020, is the first geostationary instrument that is able to observe the diurnal variation in NO2. The measurements have a spatial resolution of 3.5 km × 8 km and cover a large part of Asia. This study compares 1 year of tropospheric NO2 vertical column density (VCD) observations from the operational GEMS L2 product, the scientific GEMS IUP-UB (Institute of Environmental Physics at the University of Bremen) product, the operational TROPOspheric Monitoring Instrument (TROPOMI) product, and ground-based differential optical absorption spectroscopy (DOAS) measurements in South Korea. The GEMS L2 tropospheric NO2 VCDs overestimate the ground-based tropospheric NO2 VCDs with a median relative difference of +61 % and a correlation coefficient of 0.76. The median relative difference is −2 % for the GEMS IUP-UB product and −16 % for the TROPOMI product, with correlation coefficients of 0.83 and 0.89, respectively. The scatter in the GEMS products can be reduced when observations are limited to the TROPOMI overpass time. Diurnal variations in tropospheric NO2 VCDs differ by the pollution level of the analyzed site but with good agreement between the GEMS IUP-UB and ground-based observations. Low-pollution sites show weak or almost no diurnal variation. In summer, the polluted sites show a minimum around noon, indicating the large influence of photochemical loss. Most variation is seen in spring and autumn, with increasing NO2 in the morning, a maximum close to noon, and a decrease towards the afternoon. Winter observations show rather flat or slightly decreasing NO2 throughout the day. Winter observations under low-wind-speed conditions at high-pollution sites show enhancements of NO2 throughout the day. This indicates that under calm conditions, dilution and the less effective chemical loss in winter do not balance the accumulating emissions. Diurnal variation observed at a low-pollution site follows seasonal wind patterns. A weekday–weekend effect analysis shows good agreement between the different products. However, the GEMS L2 product, while agreeing with the other data sets on weekdays, shows significantly less reduction on weekends. The influence of the stratospheric contribution and the surface reflectivity product on the satellite tropospheric NO2 VCD products is investigated. While the TM5 model's stratospheric VCDs, used in the TROPOMI product, are too high, resulting in tropospheric NO2 VCDs that are too low and even negative, when used in the GEMS IUP-UB retrieval, the GEMS L2 stratospheric VCD is too low. Surface reflectivity comparisons indicate that the GEMS L2 reflectivity makes a large contribution to the observed overestimation and scatter.

Remote sensing and machine learning algorithms to predict soil salinity in southern Kazakhstan

Salinization and land degradation are significant challenges in the southern regions of Kazakhstan. These issues arise due to climate change, unequal water resource distribution, and human impact. The primary concern revolves around water resources, which are influenced by the area’s trans boundary flow of major rivers. The low level of water and food security has pushed the development of new approaches based on remote sensing monitoring and geographic information systems (GIS) to provide solutions for soil salinity. The research aims to focus on utilizing high-resolution radar images. This data type is effective for cloudy weather and can be useful for continued monitoring of some areas. Machine learning methods can solve the problem of automatic mapping of agricultural land salinity in Kazakhstan’s southern regions. The precise mapping of the salinity area helps prevent or decrease salinity’s impact on agriculture. The experiment realized that complex models such as LightGBM do not have significant accuracy performance over simple models on a small dataset compared with Ridge regression. The results allow us to recommend an approach for further improvement with ground-based measurement data and other deep-learning methods for mapping the salinity of agricultural lands.

Scylla. II. The Spatially Resolved Star Formation History of the Large Magellanic Cloud Reveals an Inverted Radial Age Gradient

The proximity of the Magellanic Clouds provides the opportunity to study interacting dwarf galaxies near a massive host, and spatial trends in their stellar population properties in particular, with a unique level of detail. The Scylla pure parallel program has obtained deep (80% complete to >1 mag below the ancient main-sequence turnoff), homogeneous two-filter Hubble Space Telescope imaging sampling the inner star-forming disk of the Large Magellanic Cloud (LMC), the perfect complement to shallower, contiguous ground-based surveys. We harness this imaging together with extant archival data and fit lifetime star formation histories (SFHs) to resolved color–magnitude diagrams of 111 individual fields, using three different stellar evolutionary libraries. We validate per-field recovered distances and extinctions, as well as the combined global LMC age–metallicity relation and SFH against independent estimates. We find that the present-day radial age gradient reverses from an inside-out gradient in the inner disk to an outside-in gradient beyond ∼2 disk scale lengths, supported by ground-based measurements. The gradients become relatively flatter at earlier look-back times, while the location of the inversion remains constant over an order of magnitude in look-back time, from ∼1 to 10 Gyr. This suggests at least one mechanism that predates the recent intense LMC–Small Magellanic Cloud interaction. We compare observed radial age trends to other late-type galaxies at fixed stellar mass and discuss similarities and differences in the context of potential drivers, implying strong radial migration in the LMC.

Three-dimensional distribution of aerosols of multiple types at daily scale using TROPOMI spaceborne observations

We present new satellite-based daily observations of the 3D distribution of aerosols from most common types and origins, both over land and ocean, derived from TROpospheric Ozone Monitoring Instrument (TROPOMI) measurements. This is done using the so-called AEROS5P (AEROsol Sentinel 5 Precursor) approach which retrieves vertical profiles of aerosol extinction from passive measurements of high-resolution spectral reflectance in the visible and near infrared for cloud-free conditions. Previous work demonstrated the potential of this approach, but it was initially applicable only to biomass burning aerosols with limited spatial coverage over ocean. The new methodology presented here generalizes the method for the most common aerosol types and improves spatial coverage. We take advantage of an operational aerosol type product derived from Visible Infrared Imaging Radiometer Suite (VIIRS) observations, combined with those from TROPOMI, to choose a priori aerosol set of intensive properties (particle size and refractive index). AEROS5P shows good agreement in aerosol optical depth, when compared to observations from AErosol RObotic NETwork and other widely used satellite measurements. Additionally, the vertical distribution of aerosol plumes of different types derived from AEROS5P agrees well with lidar coincident observations from the Advanced Topographic Laser Altimeter System spaceborne sensor and ground-based measurements. We utilize AEROS5P to analyze the three-dimensional distribution of aerosols for four different scenarios. It traces the three-dimensional pathways of smoke from Canadian wildfires reaching the Eastern USA in July 2023, desert dust from the Namibian deserts over the southeast Atlantic Ocean confined near the surface during the same month, fine aerosol pollution over Western Europe during June 2019, and an extreme dust event mixed with fine aerosol pollution over Northern China in March 2021. These observations provide valuable insights into aerosol transport patterns, surface-level air quality impacts, and can potentially be used to assess the radiative effects at various atmospheric layers.

Measurement report: In-flight and ground-based measurements of nitrogen oxide emissions from latest-generation jet engines and 100 % sustainable aviation fuel

Abstract. Nitrogen oxides, emitted from air traffic, are of concern due to their impact on climate by changing atmospheric ozone and methane levels. Using the DLR research aircraft Falcon, total reactive nitrogen (NOy) in-flight measurements were carried out at high altitudes to characterize emissions in the fresh aircraft exhaust from the latest-generation Rolls-Royce Trent XWB-84 engine aboard the long-range Airbus A350-941 aircraft during the ECLIF3 (Emission and CLimate Impact of alternative Fuels 3) experiment. The impact of different engine thrust settings, monitored in terms of combustor inlet temperature, pressure and engine fuel flow, was tested for two different fuel types: Jet A-1 and, for the first time, a 100 % sustainable aviation fuel (SAF) under similar atmospheric conditions. In addition, a range of combustor temperatures and an additional blended SAF were tested during ground-based emission measurements. For the data measured during ECLIF3, we confirm that the NOx emission index increases with increasing combustion temperature, pressure and fuel flow. We find that as expected, the fuel type has no measurable effect on the NOx emission index. These measurements are used to compare to cruise NOx emission index estimates from three engine emission prediction methods. Our measurements thus help to understand the ground to cruise correlation of current engine emission prediction methods while serving as input for climate modelling and extending the extremely sparse data set on in-flight aircraft nitrogen oxide emissions to newer engine generations.

Nebular dust attenuation with the Balmer and Paschen lines based on the MaNGA survey

Dust attenuations observed by stars and ionized gas are not necessarily the same. The lack of observational constraints on the nebular dust attenuation curve leaves a large uncertainty when correcting nebular dust attenuation with stellar continuum-based attenuation curves. Making use of the DAP catalogs of the MaNGA survey, we investigate the nebular dust attenuation of regions traced by the Balmer and Paschen lines. Based on a simple simulation, we find that star-forming regions on kpc scales favor the classic foreground screen dust model rather than the uniform mixture model. We propose a novel approach to fit the dust attenuation curve using the emission-line fluxes directly. For strong hydrogen recombination lines (e.g. and the slopes of the nebular attenuation curve can be well determined and are found to be in good agreement with the Fitzpatrick Milky Way extinction curve with an accuracy of $ 4<!PCT!>$ in terms of the correction factor. However, severe contaminations and/or systematic uncertainties prevent us from obtaining reasonable values of the slopes for weak recombination lines (e.g., the high-order Balmer lines or the Paschen lines). We discuss how the choice of emission line measurement methods affects the results. Our results demonstrate the difficulty of deriving an average nebular dust attenuation curve given the current ground-based emission-line measurements.

3D Surface Velocity Field Inferred from SAR Interferometry: Cerro Prieto Step-Over, Mexico, Case Study

The Cerro Prieto basin, a tectonically active pull-apart basin, hosts significant geothermal resources currently being exploited in the Cerro Prieto Geothermal Field (CPGF). Consequently, natural tectonic processes and anthropogenic activities contribute to three-dimensional surface displacements in this pull-apart basin. Here, we obtained the Cerro Prieto Step-Over 3D surface velocity field (3DSVF) by accomplishing a weighted least square algorithm inversion from geometrically quasi-orthogonal airborne UAVSAR and RADARSAT-2, Sentinel 1A satellite Synthetic Aperture-Radar (SAR) imagery collected from 2012 to 2016. The 3DSVF results show a vertical rate of 150 mm/yr and 40 mm/yr for the horizontal rate, where for the first time, the north component displacement is achieved by using only the Interferometric SAR time series in the CPGF. Data integration and validation between the 3DSVF and ground-based measurements such as continuous GPS time series and precise leveling data were achieved. Correlating the findings with recent geothermal energy production revealed a subsidence rate slowdown that aligns with the CPGF’s annual vapor production.

Global Horizontal Irradiance in Brazil: A Comparative Study of Reanalysis Datasets with Ground-Based Data

Renewable energy sources are increasing globally, mainly due to efforts to achieve net zero emissions. In Brazil, solar photovoltaic electricity generation has grown substantially in recent years, with the installed capacity rising from 2455 MW in 2018 to 47,033 MW in August 2024. However, the intermittency of solar energy increases the challenges of forecasting solar generation, making it more difficult for decision-makers to plan flexible and efficient distribution systems. In addition, to forecast power generation to support grid expansion, it is essential to have adequate data sources, but measured climate data in Brazil is limited and does not cover the entire country. To address this problem, this study evaluates the global horizontal irradiance (GHI) of four global reanalysis datasets—MERRA-2, ERA5, ERA5-Land, and CFSv2—at 35 locations across Brazil. The GHI time series from reanalysis was compared with ground-based measurements to assess its ability to represent hourly GHI in Brazil. Results indicate that MERRA-2 performed best in 90% of the locations studied, considering the root mean squared error. These findings will help advance solar forecasting by offering an alternative in regions with limited observational time series measurements through the use of reanalysis datasets.

Generation and evaluation of energy and water fluxes from the HOLAPS framework: Comparison with satellite-based products during extreme hot weather

Improving our understanding of the energy and water exchanges between the land surface and the lower atmosphere (i.e. land–atmosphere interactions), and how climate change may affect them, is crucial to predict changes in temperature and precipitation extremes. Observations of energy and water fluxes at the land surface are typically retrieved from the eddy covariance method, which presents limitations related to spatial and temporal gaps, and the non-closure of the energy and water balances. Meanwhile, soil moisture (SM) products derived from satellite data have been widely used at regional and global scales, but they are limited to capture only surface soil water content and variations. The combination of remote sensing (RS) data and modelling frameworks is called to be the solution to improve the spatial coverage and vertical resolution of land–atmosphere interactions data, ensuring the energy and water balance closure. Here, we explore the combination of remote sensing and meteorological data with a physical-based modelling framework, the High resOlution Land Atmosphere Parameters from Space (HOLAPS). We used HOLAPS to produce hourly consistent estimates of energy and water fluxes over Europe at 5 km resolution. HOLAPS and other satellite-based evapotranspiration and sensible heat flux products from the literature are evaluated against the water balance method and eddy covariance measurements. HOLAPS SM estimates together with other RS-modelling products are also evaluated against ground-based measurements at the surface and in the root zone. The evaluation of HOLAPS ET estimates show similar performance to the other products with Kling–Gupta efficiency (KGE) ¿ -0.41 in comparison with eddy covariance measurements from FLUXNET in all seasons but in boreal winter. The simulation of H is more uncertain than for ET with KGE values ranging from -2.5 to 0.8 along the products and stations at monthly scales. HOLAPS reaches slightly better results than the rest of ET and H products at daily scales in summer (KGE ¿ 0.3 for ET and KGE ¿ 0.0 for H) and during hot conditions (KGE ¿ 0.2 for ET and KGE ¿-0.2 for H), while the state-of-the-art products show KGE ¿ 0.1 for ET and KGE ¿ -0.41 for H in summer and KGE ¿ -0.1 for ET and KGE ¿ -0.6 for H during hot conditions. All products evaluated here yield a reasonable performance (KGE ¿-0.41 at most sites) in simulating SM at the surface and in the root zone. Our results expose the need for further investigating and improving product performances during extreme conditions. The good performance of HOLAPS together with its inherent advantages (RS data driven, high temporal and spatial resolution, spatial and temporal continuity, soil moisture at different depths and long-term consistent evapotranspiration and sensible heat flux estimates) support its use for agricultural and forest management activities as well as to study land–atmosphere interactions based on Earth Observations.

Thickness of Ruth Glacier, Alaska, and depth of its Great Gorge from ice-penetrating radar and mass conservation

Abstract Ruth Glacier is situated in the Central Alaska Range, with the Don Sheldon Amphitheater comprising much of its broad accumulation area, directly adjacent to North America's tallest mountain, Denali. From there it funnels through the ‘Great Gorge,’ flanked by steep valley walls reaching over 1500 m. We combine airborne and ground-based radar measurements of ice thickness with satellite-derived surface velocities to constrain ice flux above and below the gorge, and employ a mass conservation approach to estimate the glacier's thickness within the gorge. We measure ice thickness in the amphitheater to reach 950 m, and estimate centerline thickness in the gorge to range from 610 to 960 m. Our estimates are up to two times greater than those suggested by global models, and allow us to confirm that the Great Gorge rivals Hells Canyon as the deepest gorge in North America. We found that the geometry of the gorge prevents radar measurements of ice thickness there since returns from the subglacial valley walls would precede and potentially occlude nadir bed returns. The same may be true of other unmapped mountain glaciers; however, thickness may be determined using appropriately located flux gates where radar sounding is feasible, combined with mass conservation methods.

Estimating Global Gross Primary Production Using an Improved MODIS Leaf Area Index Dataset

Remote sensing and process-coupled ecological models are widely used for the simulation of GPP, which plays a key role in estimating and monitoring terrestrial ecosystem productivity. However, most such models do not differentiate the C3 and C4 photosynthetic pathways and neglect the effect of nitrogen content on Vmax and Jmax, leading to considerable bias in the estimation of gross primary productivity (GPP). Here, we developed a model driven by the leaf area index, climate, and atmospheric CO2 concentration to estimate global GPP with a spatial resolution of 0.1° and a temporal interval of 1 day from 2000 to 2022. We validated our model with ground-based GPP measurements at 128 flux tower sites, which yielded an accuracy of 72.3%. We found that the global GPP ranged from 116.4 PgCyear−1 to 133.94 PgCyear−1 from 2000 to 2022, with an average of 125.93 PgCyear−1. We also found that the global GPP showed an increasing trend of 0.548 PgCyear−1 during the study period. Further analyses using the structure equation model showed that atmospheric CO2 concentration and air temperature were the main drivers of the global GPP changes, total associations of 0.853 and 0.75, respectively, while precipitation represented a minor but negative contribution to global GPP.

Summer daily dynamics of the vertical structure of atmospheric aerosol over Baikal coastal area from ground-based lidar measurements

ABSTRACT The spatial structure of atmospheric aerosol over Baikal in summer is studied on a regular basis with the use of ground-based LOSA-M2 lidar measurements at the Boyarsky scientific station of the Institute of Physical Material Science, Siberian Branch, Russian Academy of Sciences (51.83°N, 106.06°E, 456 m a.s.l.), Republic of Buryatia, Russia. The lake is located in a basin surrounded by mountain ranges on all side; its water volume is large. The lidar data are analysed along with the regional meteorological situation and meteorological parameters of the atmosphere. The daily dynamics of aerosol distribution over the atmospheric is examined for the period from 2015 to 2023 accounting the effect of different air masses in the region. Three main typical air circulation types are identified for the coastal zone of southern Baikal in summer, which determine the atmospheric aerosol generation and transport. The first and most common type relates to breeze circulation, where the main changes in the spatial structure of aerosol occur in the 2–3-km layer and are determined by changes in the transport direction within a breeze cell during the day. The main feature of this type is a decrease in the altitude of an air layer which contains most of aerosol in the lower atmosphere up to 1 km. The second type refers to southwestern transport under the presence of an anticyclone over the region. The maximal altitude of the aerosol layers attains 7 km in this case. The most complex and dynamic changes in the daily spatial structure of atmospheric aerosol occurred under transport of cyclones and associated atmospheric fronts over Lake Baikal. Under this third type, the altitude of the aerosol layers decreases throughout the day within the altitude range from the surface to 3–4 km.

The First Validation of Aerosol Optical Parameters Retrieved from the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS) and Its Application

In August 2022, China successfully launched the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS). The primary payload of this satellite is an onboard multi-beam lidar system, which is capable of observing aerosol optical parameters on a global scale. This pioneering study used the Fernald forward integration method to retrieve aerosol optical parameters based on the Level 2 data of the TECIS, including the aerosol depolarization ratio, aerosol backscatter coefficient, aerosol extinction coefficient, and aerosol optical depth (AOD). The validation of the TECIS-retrieved aerosol optical parameters was conducted using CALIPSO Level 1 and Level 2 data, with relative errors within 30%. A comparison of the AOD retrieved from the TECIS with the AERONET and MODIS AOD products yielded correlation coefficients greater than 0.7 and 0.6, respectively. The relative error of aerosol optical parameter profiles compared with ground-based measurements for CALIPSO was within 40%. Additionally, the correlation coefficients R2 with MODIS and AERONET AOD were approximately between 0.5 and 0.7, indicating the high accuracy of TECIS retrievals. Utilizing the TECIS retrieval results, combined with ground air quality monitoring data and HYSPLIT outcomes, a typical dust transport event was analyzed from 2 to 7 April 2023. The results indicate that dust was transported from the Taklamakan Desert in Xinjiang, China, to Henan and Anhui provinces, with a gradual decrease in the aerosol depolarization ratio and backscatter coefficient during the transport process, causing varying degrees of pollution in the downstream regions. This research verifies the accuracy of the retrieval algorithm through multi-source data comparison and demonstrates the potential application of the TECIS in the field of aerosol science for the first time. It enables the fine-scale regional monitoring of atmospheric aerosols and provides reliable data support for the three-dimensional distribution of global aerosols and related scientific applications.

Retrieving hourly aerosol optical depth for geostationary satellite FY-4B/AGRI by surface-related dynamic spectral reflectance ratio method

The Advanced Geostationary Radiation Imager (AGRI) on board Fengyun-4B (FY-4B) has been found to have significant advantages in aerosol dynamic monitoring. This study proposed a surface-related dynamic spectral reflectance ratio (SDSRR) method for FY-4B AGRI to solve the problem of inaccurate surface reflectance estimation in Aerosol Optical Depth (AOD) retrieval. This method introduced Moderate-resolution Imaging Spectroradiometer (MODIS) aerosol product to assist in calculating the surface reflectance of the AGRI blue channel and the spectral reflectance ratio between the shortwave infrared (SWIR) channel and the blue channel, then constructed a surface-related dynamic spectral reflectance ratio series by combining the spectral reflectance ratio, Normalized Difference Vegetation Index (NDVI) and Scattering Angle (SCA) to obtain aerosol retrieval results. To verify the accuracy of the SDSRR method, the AOD dataset of the SDSRR method, the official aerosol products of AGRI (LDA) and Advanced Himawari Imager (AHI) AOD datasets were compared with the ground-based observations of Aerosol Robotic Network (AERONET) and Sun-shy radiometer Observation Network (SONET) in East Asia. The results indicate that the SDSRR method performs more consistently in East Asia compared to the official ARGI aerosol products. The root-mean-square-error (RMSE), mean error (ME), and correlation coefficient (R) between SDSRR AOD and ground-based measurements are 0.286, 0.180 and 0.70, which is better than that of LDA AOD (RMSE = 0.508, ME = 0.292, R = 0.69). Additionally, the RMSE, ME, and R of AHI AOD were 0.253, 0.168, and 0.74, respectively.