Seasonal Amplitude Research Articles

Monitoring Plant Diversity to Support Agri-Environmental Schemes: Evaluating Statistical Models Informed by Satellite and Local Factors in Southern European Mountain Pastoral Systems

The spatial monitoring of plant diversity in the endangered species-rich grasslands of European mountain pastoral systems is an important step for fairer and more efficient Agri-Environmental policy schemes supporting conservation. This study assessed the underlying support for a spatially explicit monitoring of plant species richness at parcel level (policy making scale) in Southern European mountain grasslands, with statistical models informed by Sentinel-2 satellite and environmental factors. Twenty-four grassland parcels were surveyed for species richness in the Peneda-Gerês National Park, northern Portugal. Using a multi-model inference approach, three competing hypotheses guided by the species-scaling theoretical framework were established: species–area (P1), species–energy (P2) and species–spectral heterogeneity (P3), each representing a candidate spatial pathway to predict species richness. To evaluate the statistical support of each spatial pathway, generalized linear models were fitted and model selection based on Akaike information criterion (AIC) was conducted. Later, the performance of the most supported spatial pathway(s) was assessed using a leave-one-out cross validation. A model guided by the species–energy hypothesis (P2) was the most parsimonious spatial pathway to monitor plant species richness in mountain grassland parcels (P2, AICc = 137.6, ∆AIC = 0.0, wi = 0.97). Species–area and species–spectral heterogeneity pathways (P1 and P3) were less statistically supported (ΔAICc values in the range 5.7–10.0). The underlying support of the species–energy spatial pathway was based on Sentinel-2 satellite data, namely on the near-infrared (NIR) green ratio in the spring season (NIR/Greenspring) and on its ratio of change between spring and summer (NIR/Greenchange). Both predictor variables related negatively to species richness. Grassland parcels with lower values of near-infrared (NIR) green ratio and lower seasonal amplitude presented higher species richness records. The leave-one-out cross validation indicated a moderate performance of the species–energy spatial pathway in predicting species richness in the grassland parcels covered by the dataset (R2 = 0.44, RMSE = 4.3 species, MAE = 3.5 species). Overall, a species–energy framework based on Sentinel 2 data resulted in a promising spatial pathway for the monitoring of species richness in mountain grassland parcels and for informing decision making on Agri-Environmental policy schemes. The near-infrared (NIR) green ratio and its change in time seems a relevant variable to deliver predictions for plant species richness and further research should be conducted on that.

Evaluation of carbonyl sulfide biosphere exchange in the Simple Biosphere Model (SiB4)

Abstract. The uptake of carbonyl sulfide (COS) by terrestrial plants is linked to photosynthetic uptake of CO2 as these gases partly share the same uptake pathway. Applying COS as a photosynthesis tracer in models requires an accurate representation of biosphere COS fluxes, but these models have not been extensively evaluated against field observations of COS fluxes. In this paper, the COS flux as simulated by the Simple Biosphere Model, version 4 (SiB4), is updated with the latest mechanistic insights and evaluated with site observations from different biomes: one evergreen needleleaf forest, two deciduous broadleaf forests, three grasslands, and two crop fields spread over Europe and North America. We improved SiB4 in several ways to improve its representation of COS. To account for the effect of atmospheric COS mole fractions on COS biosphere uptake, we replaced the fixed atmospheric COS mole fraction boundary condition originally used in SiB4 with spatially and temporally varying COS mole fraction fields. Seasonal amplitudes of COS mole fractions are ∼50–200 ppt at the investigated sites with a minimum mole fraction in the late growing season. Incorporating seasonal variability into the model reduces COS uptake rates in the late growing season, allowing better agreement with observations. We also replaced the empirical soil COS uptake model in SiB4 with a mechanistic model that represents both uptake and production of COS in soils, which improves the match with observations over agricultural fields and fertilized grassland soils. The improved version of SiB4 was capable of simulating the diurnal and seasonal variation in COS fluxes in the boreal, temperate, and Mediterranean region. Nonetheless, the daytime vegetation COS flux is underestimated on average by 8±27 %, albeit with large variability across sites. On a global scale, our model modifications decreased the modeled COS terrestrial biosphere sink from 922 Gg S yr−1 in the original SiB4 to 753 Gg S yr−1 in the updated version. The largest decrease in fluxes was driven by lower atmospheric COS mole fractions over regions with high productivity, which highlights the importance of accounting for variations in atmospheric COS mole fractions. The change to a different soil model, on the other hand, had a relatively small effect on the global biosphere COS sink. The secondary role of the modeled soil component in the global COS budget supports the use of COS as a global photosynthesis tracer. A more accurate representation of COS uptake in SiB4 should allow for improved application of atmospheric COS as a tracer of local- to global-scale terrestrial photosynthesis.

Seasonal variation in serum metabolites of northern European dogs.

BackgroundMetabolic profiling identifies seasonal variance of serum metabolites in humans. Despite the presence of seasonal disease patterns, no studies have assessed whether serum metabolites vary seasonally in dogs.HypothesisThere is seasonal variation in the serum metabolite profiles of healthy dogs.AnimalsEighteen healthy, client‐owned dogs.MethodsA prospective cohort study. Serum metabolomic profiles were assessed monthly in 18 healthy dogs over a 12‐month period. Metabolic profiling was conducted using a canine‐specific proton nuclear magnetic resonance spectroscopy platform, and the effects of seasonality were studied for 98 metabolites using a cosinor model. Seasonal component was calculated, which describes the seasonal variation of each metabolite.ResultsWe found no evidence of seasonal variation in 93 of 98 metabolites. Six metabolites had statistically significant seasonal variance, including cholesterol (mean 249 mg/dL [6.47 mmol/L] with a seasonal component amplitude of 9 mg/dL [0.23 mmol/L]; 95% confidence interval [CI] 6‐13 mg/dL [0.14‐0.33 mmol/L], P < .008), with a peak concentration of 264 mg/dL (6.83 mmol/L) in June and trough concentration of 236 mg/dL (6.12 mmol/L) in December. In contrast, there was a significantly lower concentration of lactate (mean 20 mg/dL [2.27 mmol/L] with a seasonal component amplitude of 4 mg/dL [0.42 mmol/L]; 95% CI 2‐6 mg/dL [0.22‐0.62 mmol/L], P < .001) during the summer months compared to the winter months, with a peak concentration of 26 mg/dL (2.9 mmol/L) in February and trough concentration of 14 mg/dL (1.57 mmol/L) in July.Conclusions and Clinical ImportanceWe found no clear evidence that seasonal reference ranges need to be established for serum metabolites of dogs.

Updated total ozone climate normals over the territory of Ukraine

The study presents the results of analysis of spatiotemporal distribution of updated total ozone climate normals for the period of 1991–2020. It analyzes the changes since the last total ozone climate normals estimate conducted for the period of 1981–2010. The daily data retrieved using TOMS and OMI satellite instruments over the territory of Ukraine allowed calculation of multiyear average values, climate normals for each day of the year, amplitudes, phases and determination coefficients for total ozone seasonal variations. Use of the NCEP/NCAR reanalysis data allowed establishment of the relation between total ozone and meridional wind changes in the lower stratosphere. The research shows the existence of the regions with higher/lower total ozone content that are not in line with the characteristics of latitudinal distribution. They are formed due to more frequent recurrence of air advection with ozone content that is not typical for the Ukrainian territory, mostly from January to March. The study describes a typical temporal distribution of the total ozone climate normals varying from 285 to 375 Dobson units (D.u.) and analyzes the statistic patterns of deviations distribution and recurrence of extremely high/low total ozone content. The paper emphasizes a small variation of total ozone over the territory of Ukraine. The authors also researched the features of spatial distribution of seasonal variation amplitudes varying within the range of 42–46 D.u. and the specifics of maximum values periods observed from 19 to 30 of March, depending on a region. It was established that, since the previous update of the climate normals, the total ozone decreased for all months with its maximum decrease of about 8 D.u. in winter. However, no increase of recurrence of ultraviolet radiation high levels was observed. Total ozone changes are mainly associated with shifts of meridional wind values to negative ones. This process indicates the increase of recurrence of air advection from the north. The paper also emphasizes the complexness of total ozone changes during the period of research and the lack of consistency of such changes with the circulation factor of summer months.

Assessment of Vegetation Phenological Extractions Derived From Three Satellite-Derived Vegetation Indices Based on Different Extraction Algorithms Over the Tibetan Plateau

Remote sensing phenology retrieval can remedy the deficiencies in field investigations and has the advantage of catching the continuous characteristics of phenology on a large scale. However, there are some discrepancies in the results of remote sensing phenological metrics derived from different vegetation indices based on different extraction algorithms, and there are few studies that evaluate the impact of different vegetation indices on phenological metrics extraction. In this study, three satellite-derived vegetation indices (enhanced vegetation index, EVI; normalized difference vegetation index, NDVI; and normalized difference phenology index, NDPI; calculated using surface reflectance data from MOD09A1) and two algorithms were used to detect the start and end of growing season (SOS and EOS, respectively) in the Tibetan Plateau (TP). Then, the retrieved SOS and EOS were evaluated from different aspects. Results showed that the missing rates of both SOS and EOS based on the Seasonal Trend Decomposition by LOESS (STL) trendline crossing method were higher than those based on the seasonal amplitude method (SA), and the missing rate varied using different vegetation indices among different vegetation types. Also, the temporal and spatial stabilities of phenological metrics based on SA using EVI or NDPI were more stable than those from others. The accuracy assessment based on ground observations showed that phenological metrics based on SA had better agreements with ground observations than those based on STL, and EVI or NDVI may be more appropriate for monitoring SOS than NDPI in the TP, while EOS from NDPI had better agreements with ground-observed EOS. Besides, the phenological metrics over the complex terrain also presented worse performances than those over the flat terrain. Our findings suggest that previous results of inter-annual variability of phenology from a single data or method should be treated with caution.

Diurnal and seasonal dynamics of the electrical conductivity of water of the northeastern part of the Great Vasyugan Mire (Western Siberia)

In this study, we determined the diurnal and seasonal dynamics of the electrical conductivity of waters of the northeastern part of the Great Vasyugan Mire in Western Siberia. Our studies showed that the electrical conductivity of the waters for the period of April to September 2016 was characterised by a value of 35 μS/cm, and the seasonal amplitude was 25 μS/cm. In seasonal dynamics, there are three maximums of electrical conductivity in waters. The first maximum was formed in April (48 μS/cm) and is associated with snowmelt water supply. The second one was observed in May after the complete thawing of the peat deposit (39 μS/cm), and the third was observed at the end of July as a result of biochemical processes in the peat deposit (43 μS/cm). Our studies have shown the electrical conductivity hysteresis during time intervals from 3–5 to 6–10 days electrical conductivity remains constant despite the change in hydrometeorological conditions (water table level, temperature).

Coral perspective on temperature seasonality and interannual variability in the northern South China Sea during the Roman Warm Period

Few reconstructions of sea-surface temperature (SST) have focused on seasonal and interannual variability, two major components of the global climate system, due to the limited temporal resolution of proxies. This study presents a combined 228-year-long, monthly resolved strontium to calcium ratios (Sr/Ca) record covering the period of 2070–1740 a BP (years before 1950 CE (Common Era)) extracted from three U-series-based sub-fossil Porites corals located on the Xisha Islands, northern South China Sea (SCS). The composite time series allowed for accurate assessment of the natural range of SST variations during snapshots of the Roman Warm Period (RWP). Reconstructed SST revealed that the RWP was characterized by cooler conditions compared with the 20th century, consistent with climatic variations in the western Pacific and East Asia. The amplitude of SST seasonality was within the modern range, except for a lower value at 1980–1928 a BP. Interannual variability associated with El Niño–Southern Oscillation (ENSO) activity was enhanced by 39% relative to 1980–2014 CE. The results of the sliding window demonstrate that ENSO variability persistently strengthened during 2070–2010 a BP, followed by an overall fluctuating attenuation during 1980–1928 a BP. Then, the trends of rising first before descending twice during 1852–1800 a BP appeared. Furthermore, ENSO activity played a leading role in steering short-term changes in SST seasonality in the northern SCS, manifested as stronger ENSO activity with more frequent El Niño events and decreased SST seasonality. Considering that the frequency of extreme ENSO events may strengthen in the future under global warming, the climate in the northern SCS might become more variable and complex.

Assessment of the ParFlow–CLM CONUS 1.0 integrated hydrologic model: evaluation of hyper-resolution water balance components across the contiguous United States

Abstract. Recent advancements in computational efficiency and Earth system modeling have awarded hydrologists with increasingly high-resolution models of terrestrial hydrology, which are paramount to understanding and predicting complex fluxes of moisture and energy. Continental-scale hydrologic simulations are, in particular, of interest to the hydrologic community for numerous societal, scientific, and operational benefits. The coupled hydrology–land surface model ParFlow–CLM configured over the continental United States (PFCONUS) has been employed in previous literature to study scale-dependent connections between water table depth, topography, recharge, and evapotranspiration, as well as to explore impacts of anthropogenic aquifer depletion to the water and energy balance. These studies have allowed for an unprecedented process-based understanding of the continental water cycle at high resolution. Here, we provide the most comprehensive evaluation of PFCONUS version 1.0 (PFCONUSv1) performance to date by comparing numerous modeled water balance components with thousands of in situ observations and several remote sensing products and using a range of statistical performance metrics for evaluation. PFCONUSv1 comparisons with these datasets are a promising indicator of model fidelity and ability to reproduce the continental-scale water balance at high resolution. Areas for improvement are identified, such as a positive streamflow bias at gauges in the eastern Great Plains, a shallow water table bias over many areas of the model domain, and low bias in seasonal total water storage amplitude, especially for the Ohio, Missouri, and Arkansas River basins. We discuss several potential sources for model bias and suggest that minimizing error in topographic processing and meteorological forcing would considerably improve model performance. Results here provide a benchmark and guidance for further PFCONUS model development, and they highlight the importance of concurrently evaluating all hydrologic components and fluxes to provide a multivariate, holistic validation of the complete modeled water balance.

Pronghorn (Antilocapra americana) enamel phosphate δ18O values reflect climate seasonality: Implications for paleoclimate reconstruction.

Stable oxygen isotope (δ18O) compositions from vertebrate tooth enamel are widely used as biogeochemical proxies for paleoclimate. However, the utility of enamel oxygen isotope values for environmental reconstruction varies among species. Herein, we evaluate the use of stable oxygen isotope compositions from pronghorn (Antilocapra americana Gray, 1866) enamel for reconstructing paleoclimate seasonality, an elusive but important parameter for understanding past ecosystems. We serially sampled the lower third molars of recent adult pronghorn from Wyoming for δ18O in phosphate (δ18OPO4) and compared patterns to interpolated and measured yearly variation in environmental waters as well as from sagebrush leaves, lakes, and rivers (δ18Ow). As expected, the oxygen isotope compositions of phosphate from pronghorn enamel are enriched in 18O relative to environmental waters. For a more direct comparison, we converted δ18Ow values into expected δ18OPO4* values (δ18OW‐PO4*). Pronghorn δ18OPO4 values from tooth enamel record nearly the full amplitude of seasonal variation from Wyoming δ18OW‐PO4* values. Furthermore, pronghorn enamel δ18OPO4 values are more similar to modeled δ18OW‐PO4* values from plant leaf waters than meteoric waters, suggesting that they obtain much of their water from evaporated plant waters. Collectively, our findings establish that seasonality in source water is reliably reflected in pronghorn enamel, providing the basis for exploring changes in the amplitude of seasonality of ancient climates. As a preliminary test, we sampled historical pronghorn specimens (1720 ± 100 AD), which show a mean decrease (a shift to lower values) of 1–2‰ in δ18OPO4 compared to the modern specimens. They also exhibit an increase in the δ18O amplitude, representing an increase in seasonality. We suggest that the cooler mean annual and summer temperatures typical of the 18th century, as well as enhanced periods of drought, drove differences among the modern and historical pronghorn, further establishing pronghorn enamel as excellent sources of paleoclimate proxy data.

Spatial distributions of &amp;lt;i&amp;gt;X&amp;lt;/i&amp;gt;&amp;lt;sub&amp;gt;CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;&amp;lt;/sub&amp;gt; seasonal cycle amplitude and phase over northern high-latitude regions

Abstract. Satellite-based observations of atmospheric carbon dioxide (CO2) provide measurements in remote regions, such as the biologically sensitive but undersampled northern high latitudes, and are progressing toward true global data coverage. Recent improvements in satellite retrievals of total column-averaged dry air mole fractions of CO2 (XCO2) from the NASA Orbiting Carbon Observatory 2 (OCO-2) have allowed for unprecedented data coverage of northern high-latitude regions, while maintaining acceptable accuracy and consistency relative to ground-based observations, and finally providing sufficient data in spring and autumn for analysis of satellite-observed XCO2 seasonal cycles across a majority of terrestrial northern high-latitude regions. Here, we present an analysis of XCO2 seasonal cycles calculated from OCO-2 data for temperate, boreal, and tundra regions, subdivided into 5∘ latitude by 20∘ longitude zones. We quantify the seasonal cycle amplitudes (SCAs) and the annual half drawdown day (HDD). OCO-2 SCAs are in good agreement with ground-based observations at five high-latitude sites, and OCO-2 SCAs show very close agreement with SCAs calculated for model estimates of XCO2 from the Copernicus Atmosphere Monitoring Services (CAMS) global inversion-optimized greenhouse gas flux model v19r1 and the CarbonTracker2019 model (CT2019B). Model estimates of XCO2 from the GEOS-Chem CO2 simulation version 12.7.2 with underlying biospheric fluxes from CarbonTracker2019 (GC-CT2019) yield SCAs of larger magnitude and spread over a larger range than those from CAMS, CT2019B, or OCO-2; however, GC-CT2019 SCAs still exhibit a very similar spatial distribution across northern high-latitude regions to that from CAMS, CT2019B, and OCO-2. Zones in the Asian boreal forest were found to have exceptionally large SCA and early HDD, and both OCO-2 data and model estimates yield a distinct longitudinal gradient of increasing SCA from west to east across the Eurasian continent. In northern high-latitude regions, spanning latitudes from 47 to 72∘ N, longitudinal gradients in both SCA and HDD are at least as pronounced as latitudinal gradients, suggesting a role for global atmospheric transport patterns in defining spatial distributions of XCO2 seasonality across these regions. GEOS-Chem surface contact tracers show that the largest XCO2 SCAs occur in areas with the greatest contact with land surfaces, integrated over 15–30 d. The correlation of XCO2 SCA with these land surface contact tracers is stronger than the correlation of XCO2 SCA with the SCA of CO2 fluxes or the total annual CO2 flux within each 5∘ latitude by 20∘ longitude zone. This indicates that accumulation of terrestrial CO2 flux during atmospheric transport is a major driver of regional variations in XCO2 SCA.

Machine‐Learning Characterization of Tectonic, Hydrological and Anthropogenic Sources of Active Ground Deformation in California

AbstractTectonic, hydrological and industrial processes coexist in the dynamic natural environments. However, our knowledge of ground deformation associated with tectonic, hydrological and anthropogenic processes and their interactions remains limited. California represents a natural laboratory that hosts the San Andreas fault system, Central Valley and other aquifer systems, and extensive human extraction of natural resources. The attendant multi‐scale ground deformation that has been mapped using Copernicus Sentinel‐1 Synthetic Aperture Radar (SAR)‐satellite constellation from four ascending and five descending tracks during 2015–2019. We consider the secular horizontal surface velocities and strain rates, constrained from GNSS measurements and tectonic models, as proxies for tectonic processes, and seasonal displacement amplitudes from interferometric SAR (InSAR) time series as proxies for hydrological processes. We synergize 23 types of multidisciplinary datasets, including ground deformation, sedimentary basins, precipitation, soil moisture, topography, and hydrocarbon production fields, using a machine learning algorithm–random forest, and we succeed in predicting 86%–95% of the representative data sets. High strain rates along the SAF system mainly occur in areas with a low‐to‐moderate vegetation fraction (∼0.3), suggesting a correlation of rough/high‐relief coastal range morphology and topography with the active faulting, seasonal and orographic rainfall, and vegetation growth. Linear discontinuities in the long‐term, seasonal amplitude and phase of the surface displacement fields coincide with some fault strands, the boundary zone between the sediment‐fill Central Valley and bedrock‐dominated Sierra Nevada, and the margins of the inelastically deforming aquifer in the San Joaquin Valley, suggesting groundwater flow interruptions, contrasting elastic properties, and heterogeneous hydrological units.

Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century

This study evaluates the performance of 13 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for simulating the temperature over Thailand during 2000–2014, for land-only, sea-only, and both land and sea. Both observation and reanalysis datasets are employed to compare with the GCMs, evaluated by five performance metrics including mean annual temperature, mean bias errors, mean seasonal cycle amplitude, correlation coefficient, and root mean square error. GCMs are ranked by relative error of all performance metrics. Results show that the temperatures from most GCM simulations are below the mean reference data (i.e., average of ground-based and reanalysis datasets), with north to south gradient in the range from 19 °C to 33 °C. In addition, all the GCM biases range from -0.07 °C to 2.78 °C and show severity of the temperature changes in spatial pattern ranging from -5 °C to 15 °C. The correlations of most GCMs range from 0.70 to 0.95, while the magnitudes of error are less than 2 °C. Study cases point out that the 13-MODEL ENSEMBLE, CESM2, and CNRM-CM6-1 perform better than the other models in simulating the temperature over Thailand for land-only and sea-only, and both land and sea cases, respectively, while MIROC6 performs the worst for all study cases in this study area. From the designed methodology, CNRM-CM6-1 has the best performance and is the most appropriate choice to simulate the temperature for the overall Thailand area.

Resonances and Lander Modes Observed by InSight on Mars (1–9 Hz)

ABSTRACT The National Aeronautics and Space Administration’s (NASAs) Interior exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) lander successfully touched down on Mars in November 2018, and, for the first time, a seismometer was deployed on the surface of the planet. The seismic recordings reveal diurnal and seasonal changes of the broadband noise level that are consistent with variations of the local atmospheric conditions. The seismic data include a variety of spectral peaks, which are interpreted as wind-excited, mechanical resonances of the lander, resonances of the subsurface, or artifacts produced in the measurement system. Understanding the origin of these signals is critical for the detection and characterization of marsquakes as well as for studies investigating the ambient noise. We identify the major spectral peaks up to 9 Hz, corresponding to the frequency range the most relevant to observed marsquakes. We track the variations in frequency, amplitude, and polarization of these peaks over the duration of the mission so far. The majority of these peaks can readily be classified as measurement artifacts or lander resonances (lander modes), of which the latter have a temperature-dependent peak frequency and a wind-sensitive amplitude. Of particular interest is a prominent resonance at 2.4 Hz, which is used to discriminate between seismic events and local noise and is possibly produced by a subsurface structure. In contrast to the lander modes, the 2.4 Hz resonance has distinctly different features: (1) a broad and stable spectral shape, slightly shifted on each component; (2) predominantly vertical energy; (3) temperature-independent peak frequency; (4) comparatively weak amplification by local winds, though there is a slow change in the diurnal and seasonal amplitude; and (5) excitation during all seismic events that excite this frequency band. Based on these observations, we suggest that the 2.4 Hz resonance is the only mode below 9 Hz that could be related to a local ground structure.

The Impact of a Hydroelectric Power Plant on a Regional Climate in Portugal

This paper summarizes the results from microclimatic monitoring of the impacts related to the construction and exploration phase of a hydroelectric powerplant in the upper Douro River (Portugal). Reference climatic elements for both periods were obtained and the impacts of the reservoir water mass on the region’s microclimate were evaluated. For this purpose, Sen’s slope estimate non-parametric test was used to detect the meteorological variables’ trends over 10 years, considering the division into the construction (2011–2015) and exploration (2016–2020) phases. A network of meteorological stations located close to the dam, in addition to a control station relatively distant from the dam, was used to collect the meteorological data. The control station is still integrated into the same regional climatic context but not exposed to the direct influence of the resulting reservoirs. As a result, temporal differences were determined for temperature and relative humidity. The results show a statistically significant increase in the minimum relative humidity, accompanied by a statistically significant decrease in the daily and seasonal temperature amplitudes between the construction and the exploration phase periods. These outcomes thereby suggest that large reservoirs affect the local climate and may create new microclimates, in the surrounding area, with both positive and negative potential effects.

The CO2 record at the Amazon Tall Tower Observatory: A new opportunity to study processes on seasonal and inter-annual scales.

High-quality atmospheric CO2 measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2 . In this study, we present the first 6years (2014-2019) of continuous, high-precision measurements of atmospheric CO2 at the Amazon Tall Tower Observatory (ATTO, 2.1°S, 58.9°W). After subtracting the simulated background concentrations from our observational record, we define a CO2 regional signal ( ) that has a marked seasonal cycle with an amplitude of about 4ppm. At both seasonal and inter-annual scales, we find differences in phase between and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of . In addition, we present how the 2015-2016 El Niño-induced drought was captured by our atmospheric record as a positive 2σ anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales.

Changes of Atmospheric CO2 in the Tibetan Plateau From 1994 to 2019

AbstractThe importance of carbon neutrality and green development rose sharply in the post‐pandemic era in China. This study investigated the long‐term variability of atmospheric carbon dioxide (CO2) in China using CO2 records from Mount Waliguan (WLG), the only global station of World Meteorological Organization/Global Atmosphere Watch in Eurasia, covering a 26‐year period (1994–2019). Overall, the atmospheric CO2 mole fraction increased continuously and steadily with a growth rate of 2.15 ± 0.01 ppm yr−1 over 1994–2019 at WLG. The average CO2 mole fraction was only 359.9 ± 0.04 ppm in 1994, but reached a historic level of 414.9 ± 0.04 ppm by 2019. The mean growth rates in city sectors (data from the city regions) were slightly higher than that in the Tibetan Plateau. The seasonal amplitude of atmospheric CO2 at WLG was lower than those at adjacent regional stations, such as Lin'an, and Shangdianzi, but larger those at global stations Mauna Loa and Minamitorishima. Potential strong source regions moved from urban areas to the southwest region away from WLG, suggesting the potential emergence of Northern India as a strong CO2 source region. The area of potential CO2 sources at WLG prominently expanded with time, reflecting the effect of more intensifying anthropogenic emissions in recent decades. Although numerous measures for carbon emission reduction have already been implemented, it is clear that much work, e.g., carbon emission estimation, sources/sinks tracing, cleaner energy technologies, remains to be done in order to achieve carbon emission peak and carbon neutrality set by the Chinese government.

Climate response to drastically modified PDO, PNA and NAM in the superinterglacial MIS 31

The Pacific Decadal Oscillation (PDO), the Pacific‐North American Pattern (PNA) and the Northern Annular Mode (NAM) influence the Northern Hemisphere climate over all sorts of time scales, from days to decades. This study evaluates these climate modes under drastically modified conditions. It is found that in Marine Isotope Stage 31 (MIS 31), an interglacial with enhanced seasonal amplitude, the PDO, PNA and NAM are completely different in their temporal and spatial patterns with respect to current conditions. Moreover, the MIS 31 boundary conditions induce an amplification of the interannual variability, but a suppression of the decadal peak. It is found that changes in the air–sea interaction in the NH, in particular due to a weaker Aleutian low, are responsible for the absence of the decadal periodicity. However, no large changes are verified in terms of explained variance of those modes with respect to CTR. However, the amplitude of response related to the PDO, NAM and PNA is weaker in the MIS 31 experiment, very likely due to a reduced meridional thermal gradient. The results presented here are useful for palaeoreconstruction interpretation because proxies may reproduce dominant characteristics of temperature and precipitation related to the persistence of those modes of variability. Thus, their ability to reproduce long‐term environmental conditions in some situations can be related to a preferential phase of the PDO, PNA and NAM.

Seasonal trends in the Southeast Florida current and shelf CO2 fluxes

An anthropogenically driven increase in atmospheric CO2 concentrations is known to drive an increase in the globally integrated ocean carbon sink. However, there is significant regional and seasonal variability, and significant changes in seasonal cycle amplitudes have been predicted. Three decades of sea surface observations collected from the southeast Florida Current and shelf waters reveal behavior over seasonal and interannual timescales for a region important to global carbon storage and transport. The strong temperature dependence of fCO2 in the region dominates the seasonal cycle of air-sea flux, although biophysical processes are also important. The possibility of wet and dry seasonal asymmetric trends through time were evaluated, but no statistically significant trends were found. The results indicate that uptake in the region has not changed over the last three decades after accounting for sampling bias and demonstrate the importance of robust seasonally unbiased data sets in conducting climate studies. Even in this highly sampled region, data distribution biases were found, mainly in the early 1990s. Seasonally biased data are thus not only a problem for polar regions but can also affect flux calculations in sub-tropical regions. Although not statistically significant to date, different responses in different seasons with time may lead to seasonal amplification and a decoupling of the annual mean and the seasonal means in the future.

Crustal vertical deformation of Amazon Basin derived from GPS and GRACE/GFO data over past two decades

In this study, the Gravity Recovery and Climate Experiment (GRACE) satellite observations, combining 71 continuous Global Positioning System (CGPS) data, are used to detect surface vertical loading deformation of the Amazon Basin during 2002–2020. The results show that the maximal annual amplitude of the surface mass changes derived by GRACE is more than 80 cm in terms of the equivalent water height (EWH) in the Amazon Basin. Most part of Amazon experiences mass gain, especially the Amazon River, while there is little mass loss in the northern and eastern parts. Through the Pearson correlation analysis, the monthly de-trended time series of GPS-observed vertical deformation and GRACE-derived mass loading are in good agreement with an average correlation coefficient of about 0.75 throughout the Amazon region. The common seasonal signals of GPS vertical displacements and GRACE/GFO loading deformations are extracted using the stack averaging. The two kinds of common seasonal signals show a good consistency, and together indicate approximate 20 mm peak-to-peak seasonal amplitude. Strong annual variations are identified both in the monthly GPS and GRACE/GFO data by the wavelet analysis. However, the time-frequency spectrum of GPS has more signal details and more significant semi-annual variations than that of GRACE/GFO. These results may contribute to the understanding of secular crustal vertical deformation in the Amazon Basin.

Geocenter Variations Assessment using Frequency Analysis and Allan Variance Method

The objective of this work is to characterize the signals and noises of Geocenter variations time series obtained from different space geodesy techniques as Global Positioning System (GPS), Doppler Orbitography and Radiopositioning Integrated on Satellite (DORIS), and Satellite Laser Ranging (SLR). The proposed methodology is based on the estimation of periodic signals by performing frequency analysis using FAMOUS software (Frequency Analysis Mapping On Unusual Sampling) and evaluation of level and type of noises by Allan variance technique and Three Corned Hat (TCH) method. The available data concern 13 years (from 1993 to 2006) of weekly series of Geocenter residuals components and scale factor variations, according to ITRF2000. The results estimated are more accurate according to GPS and SLR of about 2-8 mm than DORIS of about 8-42 mm, for Geocenter. Better RMS of scale factor was obtained of about 0.1ppb (0.6mm) for GPS technique than SLR and DORIS with 0.6 and 0.9 ppb (3.6 and 5.4mm), respectively. The estimated seasonal signals amplitudes are in the range of few milimeters per technique with centimetre level for Z Geocenter component of DORIS. The Geocenter motion derived from SLR technique is more accurate and close to the geodynamic models. The noise analysis shows a dominant white noise in the SLR and DORIS Geocenter solutions at a level of 0.6-1 mm and 10-40 mm, respectively. However, the GPS solution is characterized by a flicker noise at millimetre level, relating to mismodeling systematic errors.