Seasonal Amplitude Research Articles

Seasonal variation in temperature sensitivity of bacterial growth in a temperate soil and lake.

Faster bacterial biomass turnover is expected in water compared to soil, which would result in more rapid community adaption to changing environmental conditions, including temperature. Bacterial community adaptation for growth is therefore predicted to have larger seasonal amplitudes in lakes than in soil. To test this prediction, we compared the seasonal variation in temperature adaptation of bacterial community growth in a soil and lake in Southern Sweden (Tin situ 0–20°C, mean 10°C) during 1.5 years, based on monthly samplings including two winters and summers. An indicator of community adaptation, minimum temperature for growth (Tmin), was calculated from bacterial growth measurements (Leu incorporation) using the Ratkowsky model. The seasonal variation in Tmin (sinusoidal function, R2 = 0.71) was most pronounced for the lake bacterial community, with an amplitude for Tmin of 3.0°C (−4.5 to −10.5°C) compared to 0.6°C (−7 to −8°C) for the soil. Thus, Tmin in water increased by 0.32°C/degree change of Tin situ. Similar differences were also found when comparing four lakes and soils in the winter and summer (amplitudes 2.9°C and 0.9°C for lakes and soils, respectively). Thus, seasonal variation in temperature adaptation has to be taken into account in lakes, while for soils a constant Tmin can be used.

Observation-based Sea surface temperature trends in Atlantic large marine ecosystems

Variations in Sea Surface Temperature (SST) are an important driver of marine species abundance in Large Marine Ecosystems (LMEs). Studies concerned with climate change induced SST trends within these LMEs have so far been relying on satellite data and reanalysis products, with the disadvantages of only having short time-periods available and having to rely on the ability of the models to correctly simulate SST-dynamics, respectively. Here, we provide for the first time a long-term trend analysis of SST for 17 LMEs of the Atlantic Ocean over two different time-periods (1957–2020 and 1980–2020) based on in-situ data gathered from three data collections. We sort our results according to warming categories that were established in an earlier study, i.e., “cooling” (below 0 °C/dec), “slow” (0–0.07 °C/dec), “moderate” (0.07–0.14 °C/dec), “fast” (0.14–0.21 °C/dec) and “superfast” (above 0.21 °C/dec). Our results show a persistent “slow” to “superfast” warming in all considered LMEs. However, the sparse data coverage induces large uncertainties, so that many LMEs cannot uniquely be assigned to one warming category only. We detect no systematic changes in the seasonal SST amplitude of the considered LMEs. We find that the LMEs of the North Atlantic warm faster than those of the South Atlantic and that this difference is increasing with time. Out of the North Atlantic LMEs, the Norwegian Sea, North Sea, Celtic-Biscay Shelf, Gulf of Mexico and the Northeast U.S. Continental Shelf belong exclusively to the superfast warming category for the period 1980–2020.

Characterization of the Land Deformation Induced by Groundwater Withdrawal and Aquifer Parameters Using InSAR Observations in the Xingtai Plain, China

Long-term overexploitation of groundwater has led to significant land subsidence and ground fissures in the Xingtai plain. These geo-hazards have threatened the safety of buildings and infrastructures. It is extremely important to investigate the coupling relationship between land deformation and hydraulic head change for controlling land subsidence and mitigating ground fissures. In this study, we obtained the spatial and temporal evolution of land deformation in the Xingtai plain by using Envisat/ASAR data during 2009~2010 and Sentinel-1A data during 2015~2021. Combining InSAR results, head observations and geological data, we investigated the response of land deformation to head change and estimate the aquifer parameters. First, joint analysis of displacement time series and head changes infers that land subsidence was mainly caused by the inelastic compaction in aquitards. Compared with the subsidence patterns during 2009~2010, both the rate and spatial extent of land subsidence increased obviously during 2015~2021. Second, seasonal fluctuations in hydraulic head resulted in significant seasonal deformation with an amplitude of 10~30 mm and peak time of January~March, of which the spatial–temporal distribution was consistent with that of the rapid subsidence. Third, obvious differences in the deformation rate and seasonal amplitude were observed across the Longyao ground fissures and other three potential fissures during 2015~2021, suggesting that the activity of ground fissures increased compared with that during 2009~2010. Finally, using InSAR results and head observations, we estimated the elastic and inelastic skeletal storativity, with values ranging from 0.9 × 10−3 to 12.4 × 10−3 and 6.2 × 10−3 to 88.0 × 10−3, respectively. The comparison between elastic and inelastic skeletal storativity suggests that ~84.5% of total subsidence was irreversible and permanent.

Seasonality of Hashimoto Thyroiditis: Infodemiology Study of Google Trends Data

Background Hashimoto thyroiditis (HT) is an autoimmune thyroid disease and the leading cause of hypothyroidism in areas with sufficient iodine intake. The quality-of-life impact and financial burden of hypothyroidism and HT highlight the need for additional research investigating the disease etiology with the aim of revealing potential modifiable risk factors. Objective Implementation of measures against such risk factors, once identified, has the potential to lessen the financial burden while also improving the quality of life of many individuals. Therefore, we aimed to examine the potential seasonality of HT in Europe using the Google Trends data to explore whether there is a seasonal characteristic of Google searches regarding HT, examine the potential impact of the countries’ geographic location on the potential seasonality, and identify potential modifiable risk factors for HT, thereby inspiring future research on the topic. Methods Monthly Google Trends data on the search topic “Hashimoto thyroiditis” were retrieved in a 17-year time frame from January 2004 to December 2020 for 36 European countries. A cosinor model analysis was conducted to evaluate potential seasonality. Simple linear regression was used to estimate the potential effect of latitude and longitude on seasonal amplitude and phase of the model outputs. Results Of 36 included European countries, significant seasonality was observed in 30 (83%) countries. Most phase peaks occurred in spring (14/30, 46.7%) and winter (8/30, 26.7%). A statistically significant effect was observed regarding the effect of geographical latitude on cosinor model amplitude (y = –3.23 + 0.13 x; R2=0.29; P=.002). Seasonal increases in HT search volume may therefore be a consequence of an increased incidence or higher disease activity. It is particularly interesting that in most countries, a seasonal peak occurred in spring and winter months; when viewed in the context of the statistically significant impact of geographical latitude on seasonality amplitude, this may indicate the potential role of vitamin D levels in the seasonality of HT. Conclusions Significant seasonality of HT Google Trends search volume was observed in our study, with seasonal peaks in most countries occurring in spring and winter and with a significant impact of latitude on seasonality amplitude. Further studies on the topic of seasonality in HT and factors impacting it are required.

Water-temperature controlled deformation patterns in Heifangtai loess terraces revealed by wavelet analysis of InSAR time series and hydrological parameters

Loess deposits are widely distributed in western and central China. Because loess is wet-collapsible, loess mass is prone to failure after water infiltration. Heifangtai, composed of two adjacent typical loess platforms located in the Loess Plateau beside the Yellow River, has experienced hundreds of landslides in the past few decades. Here, we derived surficial time-series deformation, velocity, and amplitude of seasonality from the Sentinel-1 SAR images acquired from October 2014 to March 2021 in the Heifangtai region and studied their relation with precipitation, temperature, and irrigation applying wavelet analysis. The decomposed velocities show that not only a large amount of along-slope deformation occurred surrounding the terrace but also a significant subsidence in the residential area in the middle of the platform was observed. The high-seasonality areas are distributed along the Yellow River and on the terrace consistent with other water sources, e.g., springs and irrigation, revealing a promotion of a periodic water-involved process on deformation in loess. Through the wavelet analysis, we found that the temperature is almost in phase with the uplift velocity when the temperature is below the freezing point. The precipitation precedes the surface displacement of ∼1 to 2 months for water penetration. The comparison between irrigation volumes and averaged displacements suggests that irrigation also plays a role in promoting subsidence from March to October but uplift in winter due to frost heave. We highlight that the retrogressions of the terraces in this region may be accelerated by both natural and anthropogenic factors. Careful monitoring and water management are highly recommended for the safety of local residences and infrastructures.

Remote‐Sensing Derived Trends in Gross Primary Production Explain Increases in the CO2 Seasonal Cycle Amplitude

AbstractAn increase in the seasonal cycle amplitude (SCA) of atmospheric CO2 since the 1960s has been observed in the Northern Hemisphere (NH). However, the underlying dominant drivers are still debated. The peak season CO2 uptake by vegetation is critical in shaping the CO2 seasonality. Using satellite‐upscaled gross primary production (GPP) from FLUXCOM and near‐infrared reflectance of vegetation (NIRV), we demonstrate that peak GPP has increased across the NH over the last two decades. We relate this productivity increase to changes in the CO2 SCA using an atmospheric transport model. The increased photosynthesis has strongly contributed to CO2 SCA trends, but with substantial latitudinal and longitudinal variations. Despite a general increase in the CO2 SCA, there are distinct regional differences. These differences are mainly controlled by regional biosphere carbon fluxes, with the remainder explained by non‐biome factors, including large‐scale atmospheric transport, changes in fossil fuel combustion, biomass burning and oceanic fluxes. Using the global flask and in situ CO2 measurement sites, we find that SCA trends at high latitude are mainly driven by increasingly productive natural ecosystems, whereas mid latitude sites around the Midwest United States are mainly impacted by intensified agriculture and atmospheric transport. Averaging across the 15 long‐term surface sites, forests contribute 26% (7%) to the SCA trends, while crops contribute 17% (24%) and the combined shrubland, grassland and wetland regions contribute 23% (37%) for simulations driven by FLUXCOM (NIRv) ecosystem fluxes. Our findings demonstrate that satellite inferred trends of ecosystem fluxes can capture the observed CO2 SCA trend.

Increases in the temperature seasonal cycle indicate long-term drying trends in Amazonia

Earth System Models project a wide range of rainfall changes in the Amazon rainforest, and hence changes in soil moisture and evapotranspiration. Hydrological changes are heterogeneous, meaning local measurements are too sparse to constrain projections of large-scale hydrological change. Here we show that changes in the amplitude of the temperature seasonal cycle are strongly correlated with annual mean evaporative fraction (surface latent heat flux as a fraction of surface net radiation) changes, across reanalyses and Earth System Model projections. We find an increase in annual temperature amplitude of 1 °C is associated with a reduction in evaporative fraction of up to 0.04. The observed temperature seasonal cycle amplitude increase (0.4 °C) over the last three decades implies Amazon drying, determined in the absence of soil or energy flux measurements, matches Earth System Model simulations of the recent past. Additionally, Earth System Models predict further temperature seasonal cycle amplitude increases, suggesting drying will continue with future climate change.

Global and regional carbon budget for 2015–2020 inferred from OCO-2 based on an ensemble Kalman filter coupled with GEOS-Chem

Abstract. Understanding carbon sources and sinks across the Earth's surface is fundamental in climate science and policy; thus, these topics have been extensively studied but have yet to be fully resolved and are associated with massive debate regarding the sign and magnitude of the carbon budget from global to regional scales. Developing new models and estimates based on state-of-the-art algorithms and data constraints can provide valuable knowledge and contribute to a final ensemble model in which various optimal carbon budget estimates are integrated, such as the annual global carbon budget paper. Here, we develop a new atmospheric inversion system based on the 4D local ensemble transform Kalman filter (4D-LETKF) coupled with the GEOS-Chem global transport model to infer surface-to-atmosphere net carbon fluxes from Orbiting Carbon Observatory-2 (OCO-2) V10r XCO2 retrievals. The 4D-LETKF algorithm is adapted to an OCO-2-based global carbon inversion system for the first time in this work. On average, the mean annual terrestrial and oceanic fluxes between 2015 and 2020 are estimated as − 2.02 and − 2.34 GtC yr−1, respectively, compensating for 21 % and 24 %, respectively, of global fossil carbon dioxide (CO2) emissions (9.80 GtC yr−1). Our inversion results agree with the CO2 atmospheric growth rates reported by the National Oceanic and Atmospheric Administration (NOAA) and reduce the modeled CO2 concentration biases relative to the prior fluxes against surface and aircraft measurements. Our inversion-based carbon fluxes are broadly consistent with those provided by other global atmospheric inversion models, although discrepancies still occur in the land–ocean flux partitioning schemes and seasonal flux amplitudes over boreal and tropical regions, possibly due to the sparse observational constraints of the OCO-2 satellite and the divergent prior fluxes used in different inversion models. Four sensitivity experiments are performed herein to vary the prior fluxes and uncertainties in our inversion system, suggesting that regions that lack OCO-2 coverage are sensitive to the priors, especially over the tropics and high latitudes. In the further development of our inversion system, we will optimize the data-assimilation configuration to fully utilize current observations and increase the spatial and seasonal representativeness of the prior fluxes over regions that lack observations.

Elevation change of the Antarctic Ice Sheet: 1985 to 2020

Abstract. The largest uncertainty in future projections of sea level change comes from the uncertain response of the Antarctic Ice Sheet to the warming oceans and atmosphere. The ice sheet gains roughly 2000 km3 of ice from precipitation each year and loses a similar amount through solid ice discharge into the surrounding oceans. Numerous studies have shown that the ice sheet is currently out of long-term equilibrium, losing mass at an accelerated rate and increasing sea level rise. Projections of sea level change rely on accurate estimates of the contribution of land ice to the contemporary sea level budget. The longest observational record available to study the mass balance of the Earth's ice sheets comes from satellite altimeters. This record, however, consists of multiple satellite missions with different life spans and inconsistent measurement types (radar and laser) of varying quality. To fully utilize these data, measurements from different missions must be cross-calibrated and integrated into a consistent record of change. Here, we present a novel approach for generating such a record that implies improved topography removal, cross-calibration, and normalization of seasonal amplitudes from different mission. We describe in detail the advanced geophysical corrections applied and the processes needed to derive elevation change estimates. We processed the full archive record of satellite altimetry data, providing a seamless record of elevation change for the Antarctic Ice Sheet that spans the period 1985 to 2020. The data are produced and distributed as part of the NASA MEaSUREs ITS_LIVE (Making Earth System Data Records for Use in Research Environments Inter-mission Time Series of Land Ice Velocity and Elevation) project (Nilsson et al., 2021, DOI: https://doi.org/10.5067/L3LSVDZS15ZV​​​​​​​).

Increased Water Content in the Active Layer Revealed by Regional‐Scale InSAR and Independent Component Analysis on the Central Qinghai‐Tibet Plateau

AbstractIsolating seasonal deformation from Interferometric Synthetic Aperture Radar (InSAR) time‐series is critical to quantitative understanding the freeze‐thaw processes in permafrost regions. Physics‐ or statistics‐based approaches have been developed to extract seasonal deformation, yet both constraining their evolution in time domain, and thus impeded the quantification of their amplitude variability especially over large scales. By applying Independent Component Analysis (ICA) on Sentinel‐1 InSAR measurements during 2015–2019 on the central Qinghai‐Tibet Plateau, we reveal that the averaged seasonal deformation is increasing with a linear trend of around 0.17 cm/year. The growing seasonal amplitude is attributed to an 8 cm increase of the Equivalent Water Thickness in the active layer. The results demonstrate the capability of ICA‐based decomposition on isolating freeze‐thaw‐related deformation from other components. The large‐scale spatial distribution of varied seasonal deformation can provide new insight into quantifying the water mass balance in vast permafrost regions.

Stability analysis of Shiwei-Labudalin Highway in Inner Mongolia, Northeastern China using Sentinel-1 InSAR

Permafrost in Northeastern China has significantly degraded due to global warming, deforestation and urbanization in the last few decades. The frost heave and thaw subsidence induced by freeze-thaw cycles of deep seasonal frozen ground have caused serious damage to infrastructures. The Shiwei-Labudalin (Shi-La) Highway is an important infrastructure connecting Shiwei town and Labudalin town of Argun city, Inner Mongolia, which passes through the areas covered by deep seasonal frozen ground or isolated patchy permafrost. In this paper, we mapped the long-term linear displacement trend and amplitude of seasonal displacement of the Shi-La Highway and its nearby areas, with an ascending Sentinel-1 dataset acquired from September 2016 to April 2020. Seasonal displacement amplitudes of 5–20 mm are widely detected in low-lying areas (e.g., the basin of the Gen and Derbugan rivers). The time lags between frozen ground displacement and temperature variations generally range from 10 to 80 days while larger values of 100–120 days caused by soil moisture or land cover difference are also observed. Linear creep displacement rates greater than −20 mm/yr are detected on mountainous slopes and sections of the Shi-La Highway in the line-of-sight (LOS) direction. Our results provide a method for evaluating highway stability in cold regions, which is helpful to highway route selection and design in Northeastern China.

Titan's haze at opposite seasons from HST-STIS spectroscopy

We present an analysis of three new image cubes of Titan by the Space Telescope Imaging Spectrograph taken in 2017, 2018, and 2019, half a Titan year after previously analyzed image cubes. Both data sets probe periods when Titan's seasonal north-south-asymmetry switched. The new observations show that the new reversal came exactly half a Titan year after the previous opposite reversal. On the other hand, the phase lag of the reversals with respect to Titan's equinoxes was different indicating that the seasonal variation is close to harmonic and does not follow variations due to Saturn's orbital eccentricity. The reversal had two components, a major one at altitudes below 80 km reversing two years after a minor one above 150 km. The observations further revealed small temporary deviations of <10% of the seasonal amplitude. The new observations provide an improved seasonal model of Titan that gives accurate constraints for future global circulation models.

Biophysical impacts of northern vegetation changes on seasonal warming patterns

The seasonal greening of Northern Hemisphere (NH) ecosystems, due to extended growing periods and enhanced photosynthetic activity, could modify near-surface warming by perturbing land-atmosphere energy exchanges, yet this biophysical control on warming seasonality is underexplored. By performing experiments with a coupled land-atmosphere model, here we show that summer greening effectively dampens NH warming by −0.15 ± 0.03 °C for 1982–2014 due to enhanced evapotranspiration. However, greening generates weak temperature changes in spring (+0.02 ± 0.06 °C) and autumn (−0.05 ± 0.05 °C), because the evaporative cooling is counterbalanced by radiative warming from albedo and water vapor feedbacks. The dwindling evaporative cooling towards cool seasons is also supported by state-of-the-art Earth system models. Moreover, greening-triggered energy imbalance is propagated forward by atmospheric circulation to subsequent seasons and causes sizable time-lagged climate effects. Overall, greening makes winter warmer and summer cooler, attenuating the seasonal amplitude of NH temperature. These findings demonstrate complex tradeoffs and linkages of vegetation-climate feedbacks among seasons.

Characteristics of Freeze–Thaw Cycles in an Endorheic Basin on the Qinghai-Tibet Plateau Based on SBAS-InSAR Technology

The freeze–thaw (F-T) cycle of the active layer (AL) causes the “frost heave and thaw settlement” deformation of the terrain surface. Accurately identifying its amplitude and time characteristics is important for climate, hydrology, and ecology research in permafrost regions. We used Sentinel-1 SAR data and small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) technology to obtain the characteristics of F-T cycles in the Zonag Lake-Yanhu Lake permafrost-affected endorheic basin on the Qinghai-Tibet Plateau from 2017 to 2019. The results show that the seasonal deformation amplitude (SDA) in the study area mainly ranges from 0 to 60 mm, with an average value of 19 mm. The date of maximum frost heave (MFH) occurred between November 27th and March 21st of the following year, averaged in date of the year (DOY) 37. The maximum thaw settlement (MTS) occurred between July 25th and September 21st, averaged in DOY 225. The thawing duration is the thawing process lasting about 193 days. The spatial distribution differences in SDA, the date of MFH, and the date of MTS are relatively significant, but there is no apparent spatial difference in thawing duration. Although the SDA in the study area is mainly affected by the thermal state of permafrost, it still has the most apparent relationship with vegetation cover, the soil water content in AL, and active layer thickness. SDA has an apparent negative and positive correlation with the date of MFH and the date of MTS. In addition, due to the influence of soil texture and seasonal rivers, the seasonal deformation characteristics of the alluvial-diluvial area are different from those of the surrounding areas. This study provides a method for analyzing the F-T cycle of the AL using multi-temporal InSAR technology.

Impact of Changing Winds on the Mauna Loa CO2 Seasonal Cycle in Relation to the Pacific Decadal Oscillation.

Long‐term measurements at the Mauna Loa Observatory (MLO) show that the CO2 seasonal cycle amplitude (SCA) increased from 1959 to 2019 at an overall rate of 0.22 ± 0.034 ppm decade−1 while also varying on interannual to decadal time scales. These SCA changes are a signature of changes in land ecological CO2 fluxes as well as shifting winds. Simulations with the TM3 tracer transport model and CO2 fluxes from the Jena CarboScope CO2 Inversion suggest that shifting winds alone have contributed to a decrease in SCA of −0.10 ± 0.022 ppm decade−1 from 1959 to 2019, partly offsetting the observed long‐term SCA increase associated with enhanced ecosystem net primary production. According to these simulations and MIROC‐ACTM simulations, the shorter‐term variability of MLO SCA is nearly equally driven by varying ecological CO2 fluxes (49%) and varying winds (51%). We also show that the MLO SCA is strongly correlated with the Pacific Decadal Oscillation (PDO) due to varying winds, as well as with a closely related wind index (U‐PDO). Since 1980, 44% of the wind‐driven SCA decrease has been tied to a secular trend in the U‐PDO, which is associated with a progressive weakening of westerly winds at 700 mbar over the central Pacific from 20°N to 40°N. Similar impacts of varying winds on the SCA are seen in simulations at other low‐latitude Pacific stations, illustrating the difficulty of constraining trend and variability of land CO2 fluxes using observations from low latitudes due to the complexity of circulation changes.

Anthropogenic Carbon Increase has Caused Critical Shifts in Aragonite Saturation Across a Sensitive Coastal System

AbstractEstuarine systems host a rich diversity of marine life that is vulnerable to changes in ocean chemistry due to addition of anthropogenic carbon. However, the detection and impact of secular carbon trends in these systems is complicated by heightened natural variability as compared to open‐ocean regimes. We investigate biogeochemical changes between the pre‐industrial (PI) and modern periods using a high‐resolution, three‐dimensional, biophysical model of the Salish Sea, a representative Northeast Pacific coastal system. While the seasonal amplitude of the air‐sea difference in pCO2 has increased on average since pre‐industrial times, the net CO2 source has changed little. Our simulations show that inorganic carbon has increased throughout the model domain by 29–39 mmol m−3 (28–38 µmol kg−1) from the pre‐industrial to present. While this increase is modest in a global context, the region's naturally high inorganic carbon content and the low buffering capacity of the local carbonate system amplify the resultant effects. Notably, this increased carbon drives the estuary toward system‐wide undersaturation of aragonite, negatively impacting shell‐forming organisms. Undersaturation events were rare during the pre‐industrial experiment, with 10%–25% of the domain undersaturated by volume throughout the year, while under present‐day conditions, the majority (55%–75%) of the system experiences corrosive, undersaturated conditions year‐round. These results are extended using recent global coastal observations to show that estuaries throughout the Pacific Rim have already undergone a similar saturation state regime shift.

Response of dryland vegetation under extreme wet events with satellite measures of greenness and fluorescence

Extreme wet events in central Australia triggered large vegetation responses that contributed greatly to large global land carbon sink anomalies. There remain significant uncertainties on the extent to which these events over dryland vegetation can be monitored and assessed with satellite data. In this study, we investigated the vegetation responses of the major Australian semiarid biomes to two extreme wet events utilizing multi-satellite observations of (1) solar-induced chlorophyll fluorescence (SIF), as a proxy for photosynthetic activity and (2) the enhanced vegetation index (EVI), as a measure of canopy chlorophyll or greenness. We related these satellite observations with gross primary productivity (GPP) estimated from eddy covariance tower sites, as a performance benchmark.The C3-dominated Mulga woodland was the most responsive biome to both wet pulses and exhibited the highest sensitivity to soil moisture. The C4-dominated Hummock grassland was more responsive to the 2011 “big wet” event, relative to the later 2016–2017 wet pulse. EVI swiftly responded to the extreme wet events and showed markedly amplified seasonal amplitude, however, there was a time lag as compared with SIF during the post-wet period, presumably due to the relatively slower chlorophyll degradation in contrast with declines in photosynthetic activity. Despite a robust linear SIF-GPP relationship (r2 ranging from 0.59 to 0.85), the spatially coarse SIF derived from the Global Ozone Monitoring Experiment-2 (GOME-2) yielded high retrieval noise over the xeric biomes, hindering its capacity to capture thoroughly the dryland vegetation dynamics in central Australia. Our study highlights that synchronous satellite observations of greenness and fluorescence can potentially offer an improved understanding of dryland vegetation dynamics and can advance our ability to detect ecosystem alterations under future changing climates.

Mixed Layer Depth Promotes Trophic Amplification on a Seasonal Scale

AbstractThe Humboldt Upwelling System is of global interest due to its importance to fisheries, though the origin of its high productivity remains elusive. In regional physical‐biogeochemical model simulations, the seasonal amplitude of mesozooplankton net production exceeds that of phytoplankton, indicating “seasonal trophic amplification.” An analytical approach identifies amplification to be driven by a seasonally varying trophic transfer efficiency due to mixed layer variations. The latter alters the vertical distribution of phytoplankton and thus the zooplankton and phytoplankton encounters, with lower encounters occurring in a deeper mixed layer where phytoplankton are diluted. In global model simulations, mixed layer depth appears to affect trophic transfer similarly in other productive regions. Our results highlight the importance of mixed layer depth for trophodynamics on a seasonal scale with potential significant implications, given mixed layer depth changes projected under climate change.

Drivers for seasonal variability in sea level around the China seas

Globally variable ocean and atmospheric dynamics lead to spatially complex seasonal cycles in sea level. The China Seas, that is the Bohai, Yellow, East China and the South China seas, is a region with strong seasonal amplitudes, and straddles the transition between tropical and temperature zones, monsoonal and westerlies, shelf and deep ocean zones. Here we investigate the drivers for seasonal variability in sea level from tide gauge records, satellite altimetry along with output from the NEMO (Nucleus for European Modeling of the Ocean) model including sea surface height and ocean bottom pressure along with meteorological data in the China Seas. The seasonal cycle accounts for 37% - 94% of monthly sea level variability in 81 tide gauge records, ranging from 18 to 59 cm. We divided the seasonal cycles into four types: 1) an asymmetric sinusoid; 2) a clearly defined peak on a flat background; 3) a relatively flat signal; 4) a symmetric co-sinusoid. Type 1 is found in northern China and Taiwan, Korea, Japan and The Philippines where Inverse Barometer (IB) effects dominates seasonality along with a steric contribution. The seasonal monsoon associated with barotropic response and freshwater exchange play important roles in type 2, (eastern and southern Chinese coasts), type 3 (East Malaysia) and type 4 (Vietnam and Gulf of Thailand). IB corrected seasonal cycle amplitudes are larger in continental shelf areas than the deep ocean, with a maximum in the Gulf of Thailand, and NEMO underestimates the seasonal amplitude along the coast by nearly 50%.

Quantifying the Role of Seasonality in the Marine Carbon Cycle Feedback: An ESM2M Case Study

AbstractObservations and climate models indicate that changes in the seasonal amplitude of sea surface carbon dioxide partial pressure (A‐pCO2) are underway and driven primarily by anthropogenic carbon (Cant) accumulation in the ocean. This occurs because pCO2 is more responsive to seasonal changes in physics (including warming) and biology in an ocean that contains more Cant. A‐pCO2 changes have the potential to alter annual ocean carbon uptake and contribute to the overall marine carbon cycle feedback. Using the GFDL ESM2M Large Ensemble and a novel analysis framework, we quantify the influence of Cant accumulation on pCO2 seasonal cycles and sea‐air CO2 fluxes. Specifically, we reconstruct alternative evolutions of the contemporary ocean state in which the sensitivity of pCO2 to seasonal thermal and biophysical variation is fixed at preindustrial levels, however the background, mean‐state pCO2 fully responds to anthropogenic forcing. We find near‐global A‐pCO2 increases of &gt;100% by 2100, under RCP8.5 forcing, with rising Cant accounting for ∼100% of thermal and ∼50% of nonthermal pCO2 component amplitude changes. The other ∼50% of nonthermal pCO2 component changes are attributed to modeled changes in ocean physics and biology caused by climate change. Cant‐induced A‐pCO2 changes cause an 8.1 ± 0.4% (ensemble mean ± 1σ) increase in ocean carbon uptake by 2100. This is because greater wintertime wind speeds enhance the impact of wintertime pCO2 changes, which work to increase the ocean carbon sink. Thus, the seasonal ocean carbon cycle feedback works in opposition to the larger, mean‐state feedback that reduces ocean carbon uptake by ∼60%.