Beschreibung: The ongoing monitoring of terrestrial carbon fluxes (TCF) goes hand in hand with progress in technical capacities, such as the next-generation Earth observation missions of the Copernicus initiative and advanced machine learning algorithms. Proceeding along this line, we present a physically-based data-driven workflow for quantifying gross primary productivity (GPP) and net primary productivity (NPP) at a global scale from the synergy of Copernicus’ Sentinel-3 (S3) Ocean and Land Color Instrument (OLCI) and the TROPOspheric Monitoring Instrument (TROPOMI) onboard Sentinel-5 Precursor (S5P), along with meteorological variables from Copernicus ERA5-Land. Specifically, we created generic hybrid Gaussian process regression (GPR) retrieval models combining S3-OLCI-derived vegetation products with the TROPOMI solar-induced fluorescence (SIF) product to capture global GPP and NPP. First, the GPR algorithms were trained on theoretical simulations through the Soil-Canopy-Observation of Photosynthesis and Energy fluxes (SCOPE) model, with the final retrieval models termed SCOPE-GPR-TCF. Second, the SCOPE-GPR-TCF models were integrated in Google Earth Engine (GEE) and fed with satellite data and products (coming from Sentinel 3 & 5P and ERA5-Land), producing global and regional (Iberian Peninsula) maps at spatial resolutions of 5 km and 300 m during the year 2019. Moderate relative uncertainties in the range between 10%–40% of the GPP and NPP estimates were achieved by the SCOPE-GPR-TCF models. Analysis of the driving variables revealed that the S3-OLCI vegetation products, i.e., leaf area index (LAI), the fraction of absorbed photosynthetically active radiation (FAPAR), and SIF provided the highest prediction strengths. Validation of GPP temporal estimates from GPR against partitioned GPP estimates at 113 flux towers located in America and Europe highlighted a good overall consistency at the local scale, with performances varying depending on the site and vegetation type. The highest scores emerged for stations located in croplands, grasslands, deciduous broad-leaf and evergreen needle-leaf forests with top and values above 0.8 and below 2 respectively. Further, benchmarking spatiotemporal analysis revealed a strong intra-annual global correlation against reference products for the same year 2019: (i) Cross-comparison against LPJ-GUESS resulted in modal values of = 0.8 and = 1.93 for GPP. (ii) MOD17A2H GPP and NPP estimations cross-correlated with modal values of 0.94 and 0.92 and of 1.26 and 1.05 , respectively. We conclude that the hybrid models integrated into the GEE cloud-computing platform facilitate streamlining the global mapping of TCF products at efficient processing costs. This is particularly promising in preparation for the upcoming Fluorescence Explorer (FLEX) mission, where the SCOPE-GPR-TCF models are foreseen to be customized to 300 m resolution FLEX SIF data streams for high-resolution global productivity monitoring.

Beschreibung: The ongoing monitoring of terrestrial carbon fluxes (TCF) goes hand in hand with progress in technical capacities, such as the next-generation Earth observation missions of the Copernicus initiative and advanced machine learning algorithms. Proceeding along this line, we present a physically-based data-driven workflow for quantifying gross primary productivity (GPP) and net primary productivity (NPP) at a global scale from the synergy of Copernicus’ Sentinel-3 (S3) Ocean and Land Color Instrument (OLCI) and the TROPOspheric Monitoring Instrument (TROPOMI) onboard Sentinel-5 Precursor (S5P), along with meteorological variables from Copernicus ERA5-Land. Specifically, we created generic hybrid Gaussian process regression (GPR) retrieval models combining S3-OLCI-derived vegetation products with the TROPOMI solar-induced fluorescence (SIF) product to capture global GPP and NPP. First, the GPR algorithms were trained on theoretical simulations through the Soil-Canopy-Observation of Photosynthesis and Energy fluxes (SCOPE) model, with the final retrieval models termed SCOPE-GPR-TCF. Second, the SCOPE-GPR-TCF models were integrated in Google Earth Engine (GEE) and fed with satellite data and products (coming from Sentinel 3 & 5P and ERA5-Land), producing global and regional (Iberian Peninsula) maps at spatial resolutions of 5 km and 300 m during the year 2019. Moderate relative uncertainties in the range between 10%–40% of the GPP and NPP estimates were achieved by the SCOPE-GPR-TCF models. Analysis of the driving variables revealed that the S3-OLCI vegetation products, i.e., leaf area index (LAI), the fraction of absorbed photosynthetically active radiation (FAPAR), and SIF provided the highest prediction strengths. Validation of GPP temporal estimates from GPR against partitioned GPP estimates at 113 flux towers located in America and Europe highlighted a good overall consistency at the local scale, with performances varying depending on the site and vegetation type. The highest scores emerged for stations located in croplands, grasslands, deciduous broad-leaf and evergreen needle-leaf forests with top and values above 0.8 and below 2 respectively. Further, benchmarking spatiotemporal analysis revealed a strong intra-annual global correlation against reference products for the same year 2019: (i) Cross-comparison against LPJ-GUESS resulted in modal values of = 0.8 and = 1.93 for GPP. (ii) MOD17A2H GPP and NPP estimations cross-correlated with modal values of 0.94 and 0.92 and of 1.26 and 1.05 , respectively. We conclude that the hybrid models integrated into the GEE cloud-computing platform facilitate streamlining the global mapping of TCF products at efficient processing costs. This is particularly promising in preparation for the upcoming Fluorescence Explorer (FLEX) mission, where the SCOPE-GPR-TCF models are foreseen to be customized to 300 m resolution FLEX SIF data streams for high-resolution global productivity monitoring.

Beschreibung: The Combination Service for Time-variable Gravity fields (COST-G) operationally provides combinations of monthly Earth gravity field models derived from observations of the microwave ranging instrument of the GRACE Follow-on (GRACE-FO) satellite mission, applying the quality control and combination methodology originally developed by the Horizon 2020 project European Gravity Service for Improved Emergency Management for the data of the GRACE satellites. In the frame of the follow-up Horizon 2020 project Global Gravity-based Groundwater Product (G3P), the GRACE-FO combination is used to derive global grids of groundwater storage anomalies. To meet the user requirements and achieve optimal signal-to-noise ratio, the combination has been further developed and extended to incorporate: • new time-series based on the alternative accelerometer transplant product generated in the frame of the project by the Institute of Geodesy at the Graz University of Technology, which specifically improves the estimation of the C30 coefficient and also reduces the noise at medium to short wavelengths, and • the new time-series AIUB–GRACE-FO–RL02 of monthly GRACE-FO gravity fields, which is derived at the Astronomical Institute of the University of Bern by applying empirical noise modelling techniques. The COST-G quality control confirms the consistency of the contributing GRACE-FO time-series concerning the signal amplitude of seasonal hydrology in large river basins and the secular mass change in polar regions, but it also indicates rather diverse noise characteristics. The difference in the noise levels is taken into account in the combination process by relative weights derived by variance component estimation on the solution level. The weights are expected to be inverse proportional to the noise levels of the individual gravity field solutions. However, this expectation is violated when applying the weighting scheme as developed for the GRACE combination. The reason is found in the high-order coefficients of the gravity field, which are poorly determined from the low–low range-rate observations due to the observation geometry and suffer from aliasing due to the malfunctioning accelerometer onboard one of the GRACE-FO satellites. Hence, for the final G3P-combination a revised weighting scheme is applied where the gravity field coefficients beyond order 60 are excluded from the determination of the weights. The quality of the combined gravity fields is assessed by comparison of the noise content and the signal-to-noise ratio with the individual time-series. Independent validation is provided by the COST-G validation centre at the GFZ German Research Centre for Geosciences, where orbit fits of the low-flying Gravity and steady-state Ocean Circulation Explorer satellite are performed that confirm the high quality of the combined GRACE-FO gravity fields. By the end of the G3P project, the new combination scheme is implemented by COST-G as the new COST-G–GRACE-FO–RL02 and continued to be used for the operational GRACE-FO combination.

Beschreibung: Accurate age estimates are crucial for assessing the life-histories of fish and providing management advice, but validation studies are rare for many species. We corroborated age estimates with annual cycles of oxygen isotopes (δ18O) in otoliths of 86 northern pike (Esox lucius) from the southern Baltic Sea, compared results with visual age estimates from scales and otoliths, and assessed bias introduced by different age-estimation structures on von Bertalanffy growth models and age-structured population models. Age estimates from otoliths were accurate, while age estimates from scales significantly underestimated the age of pike older than 6 years compared to the corroborated reference age. Asymptotic length () was larger, and the growth coefficient was lower for scale ages than for corroborated age and otolith age estimates. Consequentially, scale-informed population models overestimated maximum sustainable yield (), biomass at (), relative frequency of trophy fish (), and optimal minimum length limit but underestimated fishing mortality at (). Using scale-based ages to inform management regulations for pike may therefore result in conservative management and lost yield. The overestimated asymptotic length may instill unrealistic expectations of trophy potential in recreational anglers targeting large pike, while the overestimation in MSY would cause unrealistic expectations of yield potential in commercial fishers.

Beschreibung: In the Rafsanjan plain, Iran, the excessive use of groundwater for pistachio irrigation since the 1960s has led to a severe water level decline as well as land subsidence. In this study, the advantages of InSAR analyses and groundwater fow modeling are combined to improve the understanding of the subsurface processes causing groundwater-related land subsidence in several areas of the region. For this purpose, a calibration scheme for the numerical groundwater model was developed, which simultaneously accounts for hydraulic aquifer parameters and sediment mechanical properties of land subsidence and thus considers the impact of water release from aquifer compaction. Simulation results of past subsidence are calibrated with satellite-based InSAR data and further compared with leveling measurements. Modeling results show that land subsidence in this area occurs predominantly in areas with fne-grained sediments and is therefore only partly dependent on groundwater level decline. During the modeling period from 1960 to 2020, subsidence rates of up to 21 cm year−1 are simulated. Due to the almost solely inelastic compaction of the aquifer, this has already led to an irreversible aquifer storage capacity loss of 8.8 km3 . Simulation results of future development scenarios indicate that although further land subsidence cannot be avoided, subsidence rates and the associated aquifer storage capacity loss can be reduced by up to 50 and 36%, respectively, by 2050 through the implementation of improved irrigation management for the pistachio orchards.

Beschreibung: Climate change poses a significant threat to the distribution and composition of forest tree species worldwide. European forest tree species’ range is expected to shift to cope with the increasing frequency and intensity of extreme weather events, pests and diseases caused by climate change. Despite numerous regional studies, a continental scale assessment of current changes in species distributions in Europe is missing due to the difficult task of modeling a species realized distribution and to quantify the influence of forest disturbances on each species. In this study we conducted a trend analysis on the realized distribution of 6 main European forest tree species (Abies alba Mill., Fagus sylvatica L., Picea abies L. H. Karst., Pinus nigra J. F. Arnold, Pinus sylvestris L. and Quercus robur L.) to capture and map the prevalent trends in probability of occurrence for the period 2000–2020. We also analyzed the impact of forest disturbances on each species’ range and identified the dominant disturbance drivers. Our results revealed an overall trend of stability in species’ distributions (85% of the pixels are considered stable by 2020 for all species) but we also identified some hot spots characterized by negative trends in probability of occurrence, mostly at the edges of each species’ latitudinal range. Additionally, we identified a steady increase in disturbance events in each species’ range by disturbance (affected range doubled by 2020, from 3.5% to 7% on average) and highlighted species-specific responses to forest disturbance drivers such as wind and fire. Overall, our study provides insights into distribution trends and disturbance patterns for the main European forest tree species. The identification of range shifts and the intensifying impacts of disturbances call for proactive conservation efforts and long-term planning to ensure the resilience and sustainability of European forests.

Beschreibung: Chromium (Cr) leached from iron (Fe) (oxyhydr)oxide-rich tropical laterites can substantially impact downstream groundwater, ecosystems, and human health. However, its partitioning into mineral hosts, its binding, oxidation state, and potential release are poorly defined. This is in part due to the current lack of well-designed and validated Cr-specific sequential extraction procedures (SEPs) for laterites. To fill this gap, we have (i) first optimized a Cr SEP for Fe (oxyhydr)oxide-rich laterites using synthetic and natural Cr-bearing minerals and laterite references, (ii) used a complementary suite of techniques and critically evaluated existing non-laterite and non-Cr-optimized SEPs, compared to our optimized SEP, and (iii) confirmed the efficiency of our new SEP through analyses of laterites from the Philippines. Our results show that other SEPs inadequately leach Cr host phases and underestimate the Cr fractions. Our SEP recovered up to seven times higher Cr contents because it (a) more efficiently dissolves metal-substituted Fe phases, (b) quantitatively extracts adsorbed Cr, and (c) prevents overestimation of organic Cr in laterites. With this new SEP, we can estimate the mineral-specific Cr fractionation in Fe-rich tropical soils more quantitatively and thus improve our knowledge of the potential environmental impacts of Cr from lateritic areas.

Beschreibung: Cosmic radiation near the Earth's surface is influenced by solar activity, atmospheric conditions, and changes of nearby soil moisture or snow. To better understand how cosmic‐ray neutron measurements should be corrected for meteorological effects, we operated a detector for low‐energy neutrons in a buoy on a lake in Germany for 5 months in 2014. Since the water content in the surroundings is constant, we were able to isolate the signal from almost any ground‐related disturbances. With this instrument, we challenged traditional and recent theories on the neutron response to water, air humidity, and to reference data from high‐energy neutron monitors around the world. We found that in some cases, recent theories showed superior performance over traditional approaches. We also found a stronger response of the neutrons detected by the buoy to a major solar event than was observed by traditional neutron monitors. The concept of a neutron detector on a lake could be useful as a reference station for similar land‐side detectors and help provide more reliable soil moisture products.

Beschreibung: More than 20 yr of measurement data of the gravity missions GRACE (Gravity Recovery And Climate Experiment) and GRACE-FO (GRACE-Follow-On) allow detailed investigations of long-term trends in continental terrestrial water storage (TWS). However, the spatial resolution of conventional GRACE/GRACE-FO data products is limited to a few hundred kilometres which restrains from investigating hydrological trends at smaller spatial scales. In this study GRACE and GRACE-FO data have been used to calculate TWS trends with maximized spatial resolution. Conventionally, GRACE/GRACE-FO is presented as a series of either unconstrained gravity fields post-processed with spatial low pass filters or constrained inversions commonly known as Mascon products. This paper demonstrates that both approaches to suppress spatially correlated noise are mathematically equivalent. Moreover, we demonstrate that readily inverting all available sensor data from GRACE/GRACE-FO for a single TWS trend map, together with annual variations and a mean gravity field, provides additional spatial detail not accessible from the standard products. The variable trade-off between spatial and temporal resolution as a unique feature of satellite gravimetry allows for gravity products that are tailored towards specific geophysical applications. We show additional signal content in terms of long-term water storage trends for four dedicated examples (Lake Victoria, Northwest India, Bugachany Reservoir and High Plains Aquifer) for which external information from other remote sensing instruments corroborates the enhanced spatial resolution of the new mean-field trend product.

Beschreibung: Inorganic geochemistry is a powerful tool in paleolimnology. It has become one of the most commonly used techniques to analyze lake sediments, particularly due to the development and increasing availability of XRF core scanners during the last two decades. It allows for the reconstruction of the continuous processes that occur in lakes and their watersheds, and it is ideally suited to identify event deposits. How earth surface processes and limnological conditions are recorded in the inorganic geochemical composition of lake sediments is, however, relatively complex. Here, we review the main techniques used for the inorganic geochemical analysis of lake sediments and we offer guidance on sample preparation and instrument selection. We then summarize the best practices to process and interpret bulk inorganic geochemical data. In particular, we emphasize that log-ratio transformation is critical for the rigorous statistical analysis of geochemical datasets, whether they are obtained by XRF core scanning or more traditional techniques. In addition, we show that accurately interpreting inorganic geochemical data requires a sound understanding of the main components of the sediment (organic matter, biogenic silica, carbonates, lithogenic particles) and mineral assemblages. Finally, we provide a series of examples illustrating the potential and limits of inorganic geochemistry in paleolimnology. Although the examples presented in this paper focus on lake and fjord sediments, the principles presented here also apply to other sedimentary environments.