Trend and Multi‐Frequency Analysis Through Empirical Mode Decomposition: An Application to a 20‐Year Record of Atmospheric Carbonyl Sulfide Measurements

The Empirical Mode Decomposition (EMD) is a fully non-parametric analysis of frequency modes and trends in a given series that is based on the data alone. We have devised an improved strategy based on a series of best practices to use EMD successfully in the analysis of the monthly time series of carbonyl sulfide (OCS) atmospheric mole fractions measured at NOAA network stations (2000–2020). Long-term trends and intra- and inter-annual variability has been assessed. After a phase of generally increasing mole fractions up to 2015, with a temporary decline around 2009, we found that the OCS atmospheric mole fraction subsequently decreased at all stations, reflecting a recent imbalance in its total sources and losses. Our analysis has revealed a characteristic time scale for variation of 8–10 years. The variance associated with this long-term behavior ranges from urn:x-wiley:2169897X:media:jgrd58461:jgrd58461-math-000115% to 40% of the total strength of the signal, depending on location. Apart from this complex long-term behavior, the OCS time series show a strong annual cycle, which primarily results from the well-known OCS uptake by vegetation. In addition, we have also found one more frequency of minor variance intensity in the measured mole fraction time-history, which corresponds to periods in the range of 2–3 years. This inter-annual variability of OCS may be linked to the Quasi-Biennial Oscillation

Increasing concentrations of dichloromethane, CH2Cl2, inferred from CARIBIC air samples collected 1998–2012

Atmospheric concentrations of dichloromethane, CH2Cl2, a regulated toxic air pollutant and minor contributor to stratospheric ozone depletion, were reported to have peaked around 1990 and to be declining in the early part of the 21st century. Recent observations suggest this trend has reversed and that CH2Cl2 is once again increasing in the atmosphere. Despite the importance of ongoing monitoring and reporting of atmospheric CH2Cl2, no time series has been discussed in detail since 2006. The CARIBIC project (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container) has analysed the halocarbon content of whole-air samples collected at altitudes of between ~10–12 km via a custom-built container installed on commercial passenger aircraft since 1998, providing a long-term record of CH2Cl2 observations. In this paper we present this unique CH2Cl2 time series, discussing key flight routes which have been used at various times over the past 15 years. Between 1998 and 2012 increases were seen in all northern hemispheric regions and at different altitudes, ranging from ~7–10 ppt in background air to ~13–15 ppt in regions with stronger emissions (equating to a 38–69% increase). Of particular interest is the rising importance of India as a source of atmospheric CH2Cl2: based on CARIBIC data we provide regional emission estimates for the Indian subcontinent and show that regional emissions have increased from 3–14 Gg yr^-1 (1998–2000) to 16–25 Gg yr^-1 (2008). Potential causes of the increasing atmospheric burden of CH2Cl2 are discussed. One possible source is the increased use of CH2Cl2 as a feedstock for the production of HFC-32, a chemical used predominantly as a replacement for ozone-depleting substances in a variety of applications including air conditioners and refrigeration

A new multi-gas constrained model of trace gas non-homogeneous transport in firn: evaluation and behaviour at eleven polar sites

Insoluble trace gases are trapped in polar ice at the firn-ice transition, at approximately 50 to 100 m below the surface, depending primarily on the site temperature and snow accumulation. Models of trace gas transport in polar firn are used to relate firn air and ice core records of trace gases to their atmospheric history. We propose a new model based on the following contributions. First, the firn air transport model is revised in a poromechanics framework with emphasis on the non-homogeneous properties and the treatment of gravitational settling. We then derive a nonlinear least square multi-gas optimisation scheme to calculate the effective firn diffusivity (automatic diffusivity tuning). The improvements gained by the multi-gas approach are investigated (up to ten gases for a single site are included in the optimisation process). We apply the model to four Arctic (Devon Island, NEEM, North GRIP, Summit) and seven Antarctic (DE08, Berkner Island, Siple Dome, Dronning Maud Land, South Pole, Dome C, Vostok) sites and calculate their respective depth-dependent diffusivity profiles. Among these different sites, a relationship is inferred between the snow accumulation rate and an increasing thickness of the lock-in zone defined from the isotopic composition of molecular nitrogen in firn air (denoted d15N). It is associated with a reduced diffusivity value and an increased ratio of advective to diffusive flux in deep firn, which is particularly important at high accumulation rate sites. This has implications for the understanding of d15N of N2 records in ice cores, in relation with past variations of the snow accumulation rate. As the snow accumulation rate is clearly a primary control on the thickness of the lock-in zone, our new approach that allows for the estimation of the lock-in zone width as a function of accumulation may lead to a better constraint on the age difference between the ice and entrapped gases

An empirical vegetation correction for soil water content quantification using cosmic ray probes

Cosmic ray probes are an emerging technology to continuously monitor soil water content at a scale significant to land surface processes. However, the application of this method is hampered by its susceptibility to the presence of aboveground biomass. Here we present a simple empirical framework to account for moderation of fast neutrons by aboveground biomass in the calibration. The method extends the N0-calibration function and was developed using an extensive data set from a network of 10 cosmic ray probes located in the Rur catchment, Germany. The results suggest a 0.9% reduction in fast neutron intensity per 1 kg of dry aboveground biomass per m2 or per 2 kg of biomass water equivalent per m2. We successfully tested the novel vegetation correction using temporary cosmic ray probe measurements along a strong gradient in biomass due to deforestation, and using the COSMIC, and the hmf method as independent soil water content retrieval algorithms. The extended N0-calibration function was able to explain 95% of the overall variability in fast neutron intensity

Simulation of spatial variability in crop leaf area index and yield using agroecosystem modeling and geophysics-based quantitative soil information

Agroecosystem models that simulate crop growth as a function of weather conditionsand soil characteristics are among the most promising tools for improving crop yield and achieving more sustainable agricultural production systems. This study aims at using spatially distributed crop growth simulations to investigate how field-scale patterns in soil properties obtained using geophysical mapping affect the spatial variability of soil water content dynamics and growth of crops at the square kilometer scale. For this, a geophysics-based soil map was intersected with land use information. Soilhydraulic parameters were calculated using pedotransfer functions. Simulations of soilwater content dynamics performed with the agroecosystem model AgroC were com-pared with soil water content measured at two locations, resulting in RMSE of 0.032and of 0.056 cm3cm−3, respectively. The AgroC model was then used to simulate thegrowth of sugar beet (Beta vulgaris L.), silage maize (Zea maysL.), potato (SolanumtuberosumL.), winter wheat (Triticum aestivumL.), winter barley (Hordeum vulgareL.), and winter rapeseed (Brassica napusL.) in the 1- by 1-km study area. It was found that the simulated leaf area index (LAI) was affected by the magnitude of simulated water stress, which was a function of both the crop type and soil characteristics. Simulated LAI was generally consistent with the observed LAI calculated from normalized difference vegetation index (LAINDVI) obtained from RapidEye satellite data. Finally, maps of simulated agricultural yield were produced for four crops, and it was found that simulated yield matched well with actual harvest data and literature values. Therefore, it was concluded that the information obtained from geophysics-based soilmapping was valuable for practical agricultural applications

Modelling marine emissions and atmospheric distributions of halocarbons and dimethyl sulfide: the influence of prescribed water concentration vs. prescribed emissions

Marine-produced short-lived trace gases such as dibromomethane (CH2Br2), bromoform (CHBr3), methyliodide (CH3I) and dimethyl sulfide (DMS) significantly impact tropospheric and stratospheric chemistry. Describing their marine emissions in atmospheric chemistry models as accurately as possible is necessary to quantify their impact on ozone depletion and Earth's radiative budget. So far, marine emissions of trace gases have mainly been prescribed from emission climatologies, thus lacking the interaction between the actual state of the atmosphere and the ocean. Here we present simulations with the chemistry climate model EMAC (ECHAM5/MESSy Atmospheric Chemistry) with online calculation of emissions based on surface water concentrations, in contrast to directly prescribed emissions. Considering the actual state of the model atmosphere results in a concentration gradient consistent with model real-time conditions at the ocean surface and in the atmosphere, which determine the direction and magnitude of the computed flux. This method has a number of conceptual and practical benefits, as the modelled emission can respond consistently to changes in sea surface temperature, surface wind speed, sea ice cover and especially atmospheric mixing ratio. This online calculation could enhance, dampen or even invert the fluxes (i.e. deposition instead of emissions) of very short-lived substances (VSLS). We show that differences between prescribing emissions and prescribing concentrations (−28 % for CH2Br2 to +11 % for CHBr3) result mainly from consideration of the actual, time-varying state of the atmosphere. The absolute magnitude of the differences depends mainly on the surface ocean saturation of each particular gas. Comparison to observations from aircraft, ships and ground stations reveals that computing the air–sea flux interactively leads in most of the cases to more accurate atmospheric mixing ratios in the model compared to the computation from prescribed emissions. Calculating emissions online also enables effective testing of different air–sea transfer velocity (k) parameterizations, which was performed here for eight different parameterizations. The testing of these different k values is of special interest for DMS, as recently published parameterizations derived by direct flux measurements using eddy covariance measurements suggest decreasing k values at high wind speeds or a linear relationship with wind speed. Implementing these parameterizations reduces discrepancies in modelled DMS atmospheric mixing ratios and observations by a factor of 1.5 compared to parameterizations with a quadratic or cubic relationship to wind spee

Unmanned aircraft systems (UAS) evapotranspiration estimates evaluated in comparison with TERENO eddy covariance measurements

editorial reviewe

Comparison of UAS LiDAR LAI retrieval methods for vineyards

editorial reviewe

Long-term and high-resolution global time series of brightness temperature from copula-based fusion of SMAP enhanced and SMOS data

Long and consistent soil moisture time series at adequate spatial resolution are key to foster the application of soil moisture observations and remotely-sensed products in climate and numerical weather prediction models. The two L-band soil moisture satellite missions SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity) are able to provide soil moisture estimates on global scales and in kilometer accuracy. However, the SMOS data record has an appropriate length of 7.5 years since late 2009, but with a coarse resolution of 25km only. In contrast, a spatially-enhanced SMAP product is available at a higher resolution of 9 km, but for a shorter time period (since March 2015 only). Being the fundamental observable from passive microwave sensors, reliable brightness temperatures (Tbs) are a mandatory precondition for satellite-based soil moisture products. We therefore develop, evaluate and apply a copula-based data fusion approach for combining SMAP Enhanced (SMAP_E) and SMOS brightness Temperature (Tb) data. The approach exploits both linear and non-linear dependencies between the two satellite-based Tb products and allows one to generate conditional SMAP_E-like random samples during the pre-SMAP period. Our resulting global Copula-combined SMOS-SMAP_E (CoSMOP) Tbs are statistically consistent with SMAP_E brightness temperatures, have a spatial resolution of 9km and cover the period from 2010 to 2018. A comparison with Service Soil Climate Analysis Network (SCAN)-sites over the Contiguous United States (CONUS) domain shows that the approach successfully reduces the average RMSE of the original SMOS data by 15%. At certain locations, improvements of 40% and more can be observed. Moreover, the median NSE can be enhanced from zero to almost 0.5. Hence, CoSMOP, which will be made freely available to the public, provides a first step towards a global, long-term, high-resolution and multi-sensor brightness temperature product, and thereby, also soil moisture

Linking satellite derived LAI patterns with subsoil heterogeneity using large-scale ground-based electromagnetic induction measurements

Patterns in crop development and yield are often directly related to lateral and vertical changes in soil texture causing changes in available water and resource supply for plant growth, especially under dry conditions. Relict geomorphologic features, such as old river channels covered by shallow sediments can challenge assumptions of uniformity in precision agriculture, subsurface hydrology, and crop modeling. Hence a better detection of these subsurface structures is of great interest. In this study, the origins of narrow and undulating leaf area index (LAI) patterns showing better crop performance in large scale multi-temporal satellite imagery were for the first time interpreted by proximal soil sensor data. A multi-receiver electromagnetic induction (EMI) sensor measuring soil apparent electrical conductivity (ECa) for six depths of exploration (DOE) ranging from 0–0.25 to 0–1.9 m was used as reconnaissance soil survey tool in combination with selected electrical resistivity tomography (ERT) transects, and ground truth texture data to investigate lateral and vertical changes of soil properties at ten arable fields. The moderate to excellent spatial consistency (R2 0.19–0.82) of ECa patterns and LAI crop marks that indicate a higher water storage capacity as well as the increased correlations between large-offset ECa data and the subsoil clay content and soil profile depth, implies that along this buried paleo-river structure the subsoil is mainly responsible for better crop development in drought periods. Furthermore, observed stagnant water in the subsoil indicates that this paleo-river structure still plays an important role in subsurface hydrology. These insights should be considered and implemented in local hydrological as well as crop models