Amplitude Of Seasonal Cycle Research Articles

Divergent roles of landscape and young streamflow fraction in stream water quality over seven catchments

Landscape patterns and water age are considered to play similar roles in influencing water quality, as human-caused landscape fragmentation usually leads to complex hydrological pathways and older water ages. The young streamflow fraction (Fyw), which can significantly alter water age, is believed to disproportionately impact water quality. Landscape and Fyw thus may play different roles in streamwater quality, but this assumption has not been examined. Here we examined the roles of Fyw (estimated by the amplitudes of seasonal cycles of oxygen isotope ratios in precipitation (Ap) and streamwater (As)) and landscape pattern (reflected by common landscape metrics) in streamwater quality over 7 forest-dominated catchments in eastern China. Landscape metrics, indicating land use arrangement, were closely related to multiple water quality parameters, suggesting a close association between stream water quality (sinks) and land use (sources). The Fyw had a positive relationship with ammonia nitrogen (R2 = 0.51, P = 0.044) and a negative relationship with nitrate nitrogen (R2 = 0.62, P = 0.022). The Fyw, determined by the heterogeneous-independent As/Ap, offers the possibility of modeling nitrogen compounds across multiple spatial scales. Importantly, the water quality parameters that significantly correlated with Fyw did not correlate with the landscape metrics. Differences in correlations of landscape and Fyw to water quality parameters imply that landscape and Fyw differed in their roles in water quality parameters, as well as the consideration for different water quality management strategies for different contaminants.

Sharp decline in surface water resources for agriculture and fisheries in the Lower Mekong Basin over 2000-2020

Water resources play a crucial role in the global water cycle and are affected by human activities and climate change. However, the impacts of hydropower infrastructures on the surface water extent and volume cycle are not well known. We used a multi-satellite approach to quantify the surface water storage variations over the 2000–2020 period and relate these variations to climate-induced and anthropogenic factors over the whole basin. Our results highlight that dam operations have strongly modified the water regime of the Mekong River, exhibiting a 55 % decrease in the seasonal cycle amplitude of inundation extent (from 3178 km2 to 1414 km2) and a 70 % decrease in surface water volume (from 1109 km3 to 327 km3) over 2000–2020. In the floodplains of the Lower Mekong Basin, where rice is cultivated, there has been a decline in water residence time by 30 to 50 days. The recent commissioning of big dams (2010 and 2014) has allowed us to choose 2015 as a turning point year. Results show a trend inversion in rice production, from a rise of 40 % between 2000 and 2014 to a decline of 10 % between 2015 and 2020, and a strong reduction in aquaculture growth, from +730 % between 2000 and 2014, to +53 % between 2015 and 2020. All these results show the negative impact of dams on the Mekong basin, causing a 70 % decline in surface water volumes, with major repercussions for agriculture and fisheries over the period 2000–2020. Therefore, new future projects such as the Funan Techo canal in Cambodia, scheduled to start construction at the end of 2024, will particularly affect 1300 km2 of floodplains in the lower Mekong basin, with a reduction in the amount of water received, and other areas will be subjected to flooding. The human, material and economic damage could be catastrophic.

Advection surface-flux balance controls the seasonal steric sea level amplitude

Along with the mean sea level rise due to climate change, the sea level exhibits natural variations at a large number of different time scales. One of the most important is the one linked with the seasonal cycle. In the Northern Hemisphere winter, the sea level is as much as 20 cm below its summer values in some locations. It is customary to associate these variations with the seasonal cycle of the sea surface net heat flux which drives an upper-ocean thermal expansion creating a positive steric sea level anomaly. Here, using a novel framework based on steric sea level variance budget applied to observations and to the Estimating the Circulation and Climate of the Ocean state estimate, we demonstrate that the steric sea level seasonal cycle amplitude results from a balance between the seasonal sea surface net heat flux and the oceanic advective processes. Moreover, for up to 50% of the ocean surface, surface heat fluxes act to damp the seasonal steric sea level cycle amplitude, which is instead forced by oceanic advection processes. We also show that eddies play an important role in damping the steric sea level seasonal cycle. Our study contributes to a better understanding of the steric sea level mechanisms which is crucial to ensure accurate and reliable climate projections.

Impacts of ENSO on Tropical Pacific Chlorophyll Biomass Under Historical and RCP8.5 Scenarios

AbstractThe present study aims to investigate the influences of El Niño and Southern Oscillation (ENSO) events on chlorophyll biomass in the tropical Pacific under historical and RCP8.5 scenarios with simulations from the Community Earth System Model Large Ensemble (CESM‐LE) project. Large variance in surface chlorophyll concentrations is identified across the Peruvian Upwelling (PU), Equatorial Upwelling (EU), and Western Pacific (WP) regions within the tropical Pacific. Results suggest that responses of surface chlorophyll to ENSO in these regions are governed by different mechanisms. The increasing chlorophyll during La Niña is a consequence of increasing nutrients, influenced by local upwelling systems in the PU and EU regions, while the supplementary nutrients in the WP region arise from the eastern Pacific through stronger surface westward currents. Under RCP8.5 scenario, stronger water warming in the eastern equatorial Pacific leads to a remarkable reduction in the amplitudes of seasonal cycles and interannual variations of chlorophyll in both PU and EU regions. This results in less responsiveness of the chlorophyll biomass to El Niño and moderate La Niña compared to the historical period. However, though warming induces a decrease in chlorophyll concentrations in the WP region, the interannual variations of chlorophyll have shown an improvement in correlation with ENSO events. Meanwhile, despite the small phytoplankton‐dominated community being observed under future scenario, species dominance is likely to shift back to diatoms once extreme La Niña occurs, which is unseen in all El Niño and moderate La Niña cases.

Satellite derived trends and variability of CO2 concentrations in the Middle East during 2014–2023

The Middle East has major sources of anthropogenic carbon dioxide (CO2) emissions, but a dearth of ground-based measurements precludes an investigation of its regional and temporal variability. This is achieved in this work with satellite-derived estimates from the Orbiting Carbon Observatory-2 (OCO-2) and OCO-3 missions from September 2014 to February 2023. The annual maximum and minimum column (XCO2) concentrations are generally reached in spring and autumn, respectively, with a typical seasonal cycle amplitude of 3–8 ± 0.5 ppmv in the Arabian Peninsula rising to 8–10 ± 1 ppmv in the mid-latitudes. A comparison of the seasonal-mean XCO2 values with the CO2 emissions estimated using the divergence method stresses the role played by the sources and transport of CO2 in the spatial distribution of XCO2, with anthropogenic emissions prevailing in arid and semi-arid regions that lack persistent vegetation. In the 8-year period 2015–2022, the XCO2 concentration in the United Arab Emirates (UAE) increased at a rate of about 2.50 ± 0.04 ppmv/year, with the trend empirical orthogonal function technique revealing a hotspot over northeastern UAE and southern Iran in the summer where anthropogenic emissions peak and accumulate aided by low-level wind convergence. A comparison of the satellite-derived CO2 concentration with that used to drive climate change models for different emission scenarios in the 8-year period revealed that the concentrations used in the latter is overestimated, with maximum differences exceeding 10 ppmv by 2022. This excess in the amount of CO2 can lead to an over-prediction of the projected increase in temperature in the region, an aspect that needs to be investigated further. This work stresses the need for a ground-based observational network of greenhouse gas concentrations in the Middle East to better understand its spatial and temporal variability and for the evaluation of remote sensing observations as well as climate models.

Drivers of Air‐Sea CO2 Flux in the Subantarctic Zone Revealed by Time Series Observations

AbstractThe subantarctic zone is an important region in the Southern Ocean with respect to its influence on air‐sea CO2 exchange and the global ocean carbon cycle. However, understanding of the magnitude and drivers of the flux are still being refined. Using observations from the Southern Ocean Time Series (SOTS) station (∼47°S, 142°E) and auxiliary data, we developed a multiple linear regression model to compute the sea surface partial pressure of CO2 (pCO2) over the past two decades. The mean amplitude of the pCO2 seasonal cycle between 2004 and 2021 was 44 μatm (range 30–54 μatm). Summer minima ranged from 310 to 370 μatm and winter maxima were near equilibrium with the atmosphere. The non‐thermal (i.e., biological processes and mixing) contribution to the seasonal variability in pCO2 was several times larger than the thermal contribution. The SOTS region acted as a net carbon sink at annual time scales, with mean magnitude of 6.0 mmol m−2 d−1. The positive phase of the Southern Annular Mode (SAM) increased ocean carbon uptake primarily through an increase in wind speed at zero time lag. Increased surface pCO2 was correlated with a positive SAM with a lag of 4 months, mainly due to reduced biological uptake and increased mixing. During the autotrophic season, pCO2 was predominantly impacted by primary productivity, whereas water mass movement, inferred by temperature and salinity anomalies, had a larger impact on the heterotrophic season. In general, mesoscale processes such as eddies and frontal movement impact the local biogeochemical features more than the SAM.

Seasonal and Diurnal Variations in XCO2 Characteristics in China as Observed by OCO‐2/3 Satellites: Effects of Land Cover and Local Meteorology

AbstractMonitoring the dynamics of atmospheric CO2 is crucial for enhancing comprehension of the carbon cycle. Using column‐averaged dry‐air mole fraction of CO2 (XCO2) data collected by the Orbiting Carbon Observatory (OCO)‐2 and OCO‐3 satellites during 2020–2021, this study explored seasonal and diurnal variations in XCO2 characteristics in typical land cover biomes in China, and investigated their relationships with meteorological drivers. Results showed that XCO2 products retrieved by OCO‐2 and OCO‐3 have good agreement with Total Carbon Column Observing Network measurements, with average deviations of 0.8 and 1.2 ppm, respectively. The satellite observations revealed XCO2 hotpots located mainly in central and eastern China, and areas of low XCO2 values in western China, with a seasonal curve that was highest (lowest) in spring (summer). The largest seasonal cycle amplitude (∼9 ppm) of XCO2 was observed in forest areas, highlighting its key role in carbon exchange. Additionally, XCO2 was found to have a near‐sinusoidal diurnal pattern, characterized by rapid decrease in the early morning as photosynthesis resumed after sunrise, as indicated by the sun‐induced chlorophyll fluorescence (SIF), a peak at around midday, and subsequent decrease as SIF increased after mid‐afternoon. Urban regions had the highest diurnal cycle amplitude (∼6 ppm) among biomes. Statistical analyses revealed seasonal shift and nonlinear variation in the relationships between XCO2 and meteorological variables, suggesting that CO2 uptake is influenced by favorable humidity conditions. These relationships also provide insight into the sensitivity and adaptability of XCO2 to meteorological factors in diverse ecosystems such as savanna and grassland.

Constraining the budget of atmospheric carbonyl sulfide using a 3-D chemical transport model

Abstract. Carbonyl sulfide (OCS) has emerged as a valuable proxy for photosynthetic uptake of carbon dioxide (CO2) and is known to be important in the formation of aerosols in the stratosphere. However, uncertainties in the global OCS budget remain large. This is mainly due to the following three flux terms: vegetation uptake, soil uptake and oceanic emissions. Bottom-up estimates do not yield a closed budget, which is thought to be due to tropical emissions of OCS that are not accounted for. Here we present a simulation of atmospheric OCS over the period 2004–2018 using the TOMCAT 3-D chemical transport model that is aimed at better constraining some terms in the OCS budget. Vegetative uptake of OCS is estimated by scaling gross primary productivity (GPP) output from the Joint UK Land Environment Simulator (JULES) using the leaf relative uptake (LRU) approach. The remaining surface budget terms are taken from available literature flux inventories and adequately scaled to bring the budget into balance. The model is compared with limb-sounding satellite observations made by the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS) and surface flask measurements from 14 National Oceanic and Atmospheric Administration – Earth System Research Laboratory (NOAA-ESRL) sites worldwide. We find that calculating vegetative uptake using the LRU underestimates the surface seasonal cycle amplitude (SCA) in the Northern Hemisphere (NH) mid-latitudes and high latitudes by approximately 37 ppt (35 %). The inclusion of a large tropical source is able to balance the global budget, but further improvement to the SCA and phasing would likely require a flux inversion scheme. Compared to co-located ACE-FTS OCS profiles between 5 and 30 km, TOMCAT remains within 25 ppt (approximately 5 % of mean tropospheric concentration) of the measurements throughout the majority of this region and lies within the standard deviation of these measurements. This provides confidence in the representation of atmospheric loss and surface fluxes of OCS in the model. Atmospheric sinks account for 154 Gg S of the annual budget, which is 10 %–50 % larger than previous studies. Comparing the surface monthly anomalies from the NOAA-ESRL flask data to the model simulations shows a root-mean-square error range of 3.3–25.8 ppt. We estimate the total biosphere uptake to be 951 Gg S, which is in the range of recent inversion studies (893–1053 Gg S), but our terrestrial vegetation flux accounts for 629 Gg S of the annual budget, which is lower than other recent studies (657–756 Gg S). However, to close the budget, we compensate for this with a large annual oceanic emission term of 689 Gg S focused over the tropics, which is much larger than bottom-up estimates (285 Gg S). Hence, we agree with recent findings that missing OCS sources likely originate from the tropical region. This work shows that satellite OCS profiles offer a good constraint on atmospheric sinks of OCS through the troposphere and stratosphere and are therefore useful for helping to improve surface budget terms. This work also shows that the LRU approach is an adequate representation of the OCS vegetative uptake, but this method could be improved by various means, such as using a higher-resolution GPP product or plant-functional-type-dependent LRU. Future work will utilise TOMCAT in a formal inversion scheme to better quantify the OCS budget.

Seasonal Variability of the Surface Ocean Carbon Cycle: A Synthesis

AbstractThe seasonal cycle is the dominant mode of variability in the air‐sea CO2 flux in most regions of the global ocean, yet discrepancies between different seasonality estimates are rather large. As part of the Regional Carbon Cycle Assessment and Processes Phase 2 project (RECCAP2), we synthesize surface ocean pCO2 and air‐sea CO2 flux seasonality from models and observation‐based estimates, focusing on both a present‐day climatology and decadal changes between the 1980s and 2010s. Four main findings emerge: First, global ocean biogeochemistry models (GOBMs) and observation‐based estimates (pCO2 products) of surface pCO2 seasonality disagree in amplitude and phase, primarily due to discrepancies in the seasonal variability in surface DIC. Second, the seasonal cycle in pCO2 has increased in amplitude over the last three decades in both pCO2 products and GOBMs. Third, decadal increases in pCO2 seasonal cycle amplitudes in subtropical biomes for both pCO2 products and GOBMs are driven by increasing DIC concentrations stemming from the uptake of anthropogenic CO2 (Cant). In subpolar and Southern Ocean biomes, however, the seasonality change for GOBMs is dominated by Cant invasion, whereas for pCO2 products an indeterminate combination of Cant invasion and climate change modulates the changes. Fourth, biome‐aggregated decadal changes in the amplitude of pCO2 seasonal variability are largely detectable against both mapping uncertainty (reducible) and natural variability uncertainty (irreducible), but not at the gridpoint scale over much of the northern subpolar oceans and over the Southern Ocean, underscoring the importance of sustained high‐quality seasonally resolved measurements over these regions.

Improved Constraints on the Recent Terrestrial Carbon Sink Over China by Assimilating OCO‐2 XCO2 Retrievals

AbstractThe magnitude and distribution of China's terrestrial carbon sink remain uncertain due to insufficient observational constraints; satellite column‐average dry‐air mole fraction carbon dioxide (XCO2) retrievals may fill some of this gap. Here, we estimate China's carbon sink using atmospheric inversions of the Orbiting Carbon Observatory 2 (OCO‐2) XCO2 retrievals within different platforms, including the Global Carbon Assimilation System (GCAS) v2, the Copernicus Atmosphere Monitoring Service, and the OCO‐2 Model Inter‐comparison Project (MIP). We find that they consistently place the largest net biome production (NBP) in the south on an annual basis compared to the northeast and other main agricultural areas during peak growing season, coinciding well with the distribution of forests and crops, respectively. Moreover, the mean seasonal cycle amplitude of NBP in OCO‐2 inversions is obviously larger than that of biosphere model simulations and slightly greater than surface CO2 inversions. More importantly, the mean seasonal cycle of the OCO‐2 inversions is well constrained in the temperate, tropical, and subtropical monsoon climate zones, with better inter‐model consistency at a sub‐regional scale compared to in situ inversions and biosphere model simulations. In addition, the OCO‐2 inversions estimate the mean annual NBP in China for 2015–2019 to be between 0.34 (GCASv2) and 0.47 ± 0.16 PgC/yr (median ± std; OCO‐2 v10 MIP), and indicate the impacts of climate extremes (e.g., the 2019 drought) on the interannual variations of NBP. Our results suggest that assimilating OCO‐2 XCO2 retrievals is crucial for improving our understanding of China's terrestrial carbon sink regime.

Decreasing seasonal cycle amplitude of methane in the northern high latitudes being driven by lower-latitude changes in emissions and transport

Abstract. Atmospheric methane (CH4) concentrations are rising, which are expected to lead to a corresponding increase in the global seasonal cycle amplitude (SCA) – the difference between its seasonal maximum and minimum values. The reaction between CH4 and its main sink, OH, is dependent on the amount of CH4 and OH in the atmosphere. The concentration of OH varies seasonally, and due to the increasing burden of CH4 in the atmosphere, it is expected that the SCA of CH4 will increase due to the increased removal of CH4 through a reaction with OH in the atmosphere. Spatially varying changes in the SCA could indicate long-term persistent variations in the seasonal sources and sinks, but such SCA changes have not been investigated. Here we use surface flask measurements and a 3D chemical transport model (TOMCAT) to diagnose changes in the SCA of atmospheric CH4 between 1995–2020 and attribute the changes regionally to contributions from different sectors. We find that the observed SCA decreased by 4 ppb (7.6 %) in the northern high latitudes (NHLs; 60–90∘ N), while the SCA increased globally by 2.5 ppb (6.5 %) during this time period. TOMCAT reproduces the change in the SCA at observation sites across the globe. Therefore, we use it to attribute regions which are contributing to the changes in the NHL SCA, which shows an unexpected change in the SCA that differs from the rest of the world. We find that well-mixed background CH4, likely from emissions originating in, and transported from, more southerly latitudes has the largest impact on the decreasing SCA in the NHLs (56.5 % of total contribution to NHLs). In addition to the background CH4, recent emissions from Canada, the Middle East, and Europe contribute 16.9 %, 12.1 %, and 8.4 %, respectively, to the total change in the SCA in the NHLs. The remaining contributions are due to changes in emissions and transport from other regions. The three largest regional contributions are driven by increases in summer emissions from the Boreal Plains in Canada, decreases in winter emissions across Europe, and a combination of increases in summer emissions and decreases in winter emissions over the Arabian Peninsula and Caspian Sea in the Middle East. These results highlight that changes in the observed seasonal cycle can be an indicator of changing emission regimes in local and non-local regions, particularly in the NHL, where the change is counterintuitive.

Variability of Atmospheric CO2 Over the Arctic Ocean: Insights From the O‐Buoy Chemical Observing Network

AbstractAs the Arctic climate rapidly warms, there is a critical need for understanding variability and change in the Arctic carbon cycle, but sparse spatial coverage of observations has hindered progress. This work analyzes measurements of atmospheric CO2 in the Arctic from long‐term on‐ice measurements (the O‐Buoy Network), as well as coastal observatories from 2009 to 2016. The on‐ice measurements showed smaller seasonal amplitudes than coastal observatories, in contrast to the general observation of poleward increases of seasonal cycle amplitude. Average on‐ice measurements were also lower than their coastal counterparts during winter and spring, contradicting the expectation that CO2 increases poleward in boreal winter. We compared the observations to CO2 simulated in an updated version of GEOS‐Chem 3‐D chemical transport model, which includes new tracers of airmass history and CO2 sources and sinks. The model reproduced the observed features of the seasonal cycle and showed that terrestrial biosphere fluxes and synoptic transport explain most CO2 variability (both synoptic and interannual) over the Arctic Ocean surface. The polar airmass partially isolates the Arctic Ocean surface air from terrestrial CO2 exchange, which explains the reduced seasonal cycle amplitude and winter maxima. All Arctic coastal sites had similar CO2 interannual variability, particularly in summer, which was largely reproduced by the model. The interannual variability observed over sea ice, however, was distinct from the coastal sites and not reproduced by the model. Air‐sea CO2 exchange in and around sea ice, which was once thought to be negligible, may be an important driver of interannual variability over the Arctic Ocean.

Isotopic approach to linking landscape and catchment storage across multiple spatial scales

Catchment heterogeneity leads to uncertainty about estimating timescales of storage and difficulty in extrapolating to larger scales. A heterogeneity-independent storage index (SI) was employed to build a connection with catchment characteristics, especially for landscapes, over six humid, forestry catchments. The SI is derived from the amplitudes of tracer cycles in precipitation and ephemeral/intermittent streamflow. The SI was significantly correlated with landscape metric (R2 = 0.81 and p = 0.014), specifically the fractal dimension index (FRAC) indicating the shape complexity of the landscape. Meanwhile, the topographic wetness index (TWI) (R2 = 0.77, p = 0.021) showed a close connection with the storage index as well. Close correlations suggested that the FRAC and TWI regulate the timescale of storage over the range of spatial scales, in particular the young water fraction in streams, because the SI is a heterogeneity-independent metric derived from seasonal tracer cycle amplitudes, which has a close relation to young water fraction. This also indicated the SI can be treated as an alternative travel-time metric and a reflection of the hydrological nature. Moreover, the findings implied the possibility of hydrological modeling over multiple spatial scales. The linkage between SI and landscape and topography provides insight into the mechanism of streamflow generation. Based on ephemeral streams, the crucial control of landscape and topography on the timescale of storage contributes to available water assessment and sustainable ecosystem management.

Evaluation of wetland CH4in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations

Abstract. Wetlands are the largest natural source of methane. The ability to model the emissions of methane from natural wetlands accurately is critical to our understanding of the global methane budget and how it may change under future climate scenarios. The simulation of wetland methane emissions involves a complicated system of meteorological drivers coupled to hydrological and biogeochemical processes. The Joint UK Land Environment Simulator (JULES) is a process-based land surface model that underpins the UK Earth System Model (UKESM) and is capable of generating estimates of wetland methane emissions. In this study, we use GOSAT satellite observations of atmospheric methane along with the TOMCAT global 3-D chemistry transport model to evaluate the performance of JULES in reproducing the seasonal cycle of methane over a wide range of tropical wetlands. By using an ensemble of JULES simulations with differing input data and process configurations, we investigate the relative importance of the meteorological driving data, the vegetation, the temperature dependency of wetland methane production and the wetland extent. We find that JULES typically performs well in replicating the observed methane seasonal cycle. We calculate correlation coefficients to the observed seasonal cycle of between 0.58 and 0.88 for most regions; however, the seasonal cycle amplitude is typically underestimated (by between 1.8 and 19.5 ppb). This level of performance is comparable to that typically provided by state-of-the-art data-driven wetland CH4 emission inventories. The meteorological driving data are found to be the most significant factor in determining the ensemble performance, with temperature dependency and vegetation having moderate effects. We find that neither wetland extent configuration outperforms the other, but this does lead to poor performance in some regions. We focus in detail on three African wetland regions (Sudd, Southern Africa and Congo) where we find the performance of JULES to be poor and explore the reasons for this in detail. We find that neither wetland extent configuration used is sufficient in representing the wetland distribution in these regions (underestimating the wetland seasonal cycle amplitude by 11.1, 19.5 and 10.1 ppb respectively, with correlation coefficients of 0.23, 0.01 and 0.31). We employ the Catchment-based Macro-scale Floodplain (CaMa-Flood) model to explicitly represent river and floodplain water dynamics and find that these JULES-CaMa-Flood simulations are capable of providing a wetland extent that is more consistent with observations in this regions, highlighting this as an important area for future model development.

How do Cl concentrations matter for the simulation of CH4 and δ13C(CH4) and estimation of the CH4 budget through atmospheric inversions?

Abstract. Atmospheric methane (CH4) concentrations have been rising since 2007 due to an imbalance between CH4 sources and sinks. The CH4 budget is generally estimated through top-down approaches using chemistry transport models (CTMs) and CH4 observations as constraints. The atmospheric isotopic CH4 composition, δ13C(CH4), can also provide additional constraints and helps to discriminate between emission categories. Nevertheless, to be able to use the information contained in these observations, the models must correctly account for processes influencing δ13C(CH4). The oxidation by chlorine (Cl) likely contributes less than 5 % to the total oxidation of atmospheric CH4. However, the large kinetic isotope effect of the Cl sink produces a large fractionation of 13C, compared with 12C in atmospheric CH4, and thus may strongly influence δ13C(CH4). When integrating the Cl sink in their setup to constrain the CH4 budget, which is not yet standard, atmospheric inversions prescribe different Cl fields, therefore leading to discrepancies between flux estimates. To quantify the influence of the Cl concentrations on CH4, δ13C(CH4), and CH4 budget estimates, we perform sensitivity simulations using four different Cl fields. We also test removing the tropospheric and the entire Cl sink. We find that the Cl fields tested here are responsible for between 0.3 % and 8.5 % of the total chemical CH4 sink in the troposphere and between 1.0 % and 1.6 % in the stratosphere. Prescribing these different Cl amounts in atmospheric inversions can lead to differences of up to 53.8 Tg CH4 yr−1 in global CH4 emissions and of up to 4.7 ‰ in the globally averaged isotopic signature of the CH4 source δ13C(CH4)source), although these differences are much smaller if only recent Cl fields are used. More specifically, each increase by 1000 molec.cm-3 in the mean tropospheric Cl concentration would result in an adjustment by +11.7 Tg CH4 yr−1, for global CH4 emissions, and −1.0 ‰, for the globally averaged δ13C(CH4)source. Our study also shows that the CH4 seasonal cycle amplitude is modified by less than 1 %–2 %, but the δ13C(CH4) seasonal cycle amplitude can be significantly modified by up to 10 %–20 %, depending on the latitude. In an atmospheric inversion performed with isotopic constraints, this influence can result in significant differences in the posterior source mixture. For example, the contribution from wetland emissions to the total emissions can be modified by about 0.8 % to adjust the globally averaged δ13C(CH4)source, corresponding to a 15 Tg CH4 yr−1 change. This adjustment is small compared to the current wetland source uncertainty, albeit far from negligible. Finally, tested Cl concentrations have a large influence on the simulated δ13C(CH4) vertical profiles above 30 km and a very small impact on the simulated CH4 vertical profiles. Overall, our model captures the observed CH4 and δ13C(CH4) vertical profiles well, especially in the troposphere, and it is difficult to prefer one Cl field over another based uniquely on the available observations of the vertical profiles.

Do Emergent Constraints on Carbon Cycle Feedbacks Hold in CMIP6?

AbstractEmergent constraints on carbon cycle feedbacks in response to warming and increasing atmospheric CO2 concentration have previously been identified in Earth system models participating in the Coupled Model Intercomparison Project (CMIP) Phase 5. Here, we examine whether two of these emergent constraints also hold for CMIP6. The spread of the sensitivity of tropical land carbon uptake to tropical warming in an idealized simulation with a 1% per year increase of atmospheric CO2 shows only a slight decrease in CMIP6 (−52 ± 35 GtC/K) compared to CMIP5 (−49 ± 40 GtC/K). For both model generations, the observed interannual variability in the growth rate of atmospheric CO2 yields a consistent emergent constraint on the sensitivity of tropical land carbon uptake with a constrained range of −37 ± 14 GtC/K for the combined ensemble (i.e., a reduction of ∼30% in the best estimate and 60% in the uncertainty range relative to the multimodel mean of the combined ensemble). A further emergent constraint is based on a relationship between CO2 fertilization and the historical increase in the CO2 seasonal cycle amplitude in high latitudes. However, this emergent constraint is not evident in CMIP6. This is in part because the historical increase in the amplitude of the CO2 seasonal cycle is more accurately simulated in CMIP6, such that the models are all now close to the observational constraint.

Regional Features of the Arctic Sea Ice Area Changes in 2000–2019 versus 1979–1999 Periods

One of the most striking manifestations of ongoing climate change is a rapid shrinking of the Arctic sea ice area (SIA). An important feature of the observed SIA loss is a nonlinear rate of a decline with an accelerated decrease in the 2000–2019 period relative to a more gradual decline in 1979–1999. In this study, we perform a quantitative assessment and comparison of the spatial-temporal SIA changes during these two periods. It was found that winter Arctic SIA loss is primarily associated with changes in the Barents Sea, where the SIA decline in 2000–2019 has accelerated more than three-fold in comparison with 1979–1999. In summer and autumn, rates of SIA decline in 2000–2019 increased most strongly in the Kara, Beaufort Seas, the Northwestern Passage, and inner Arctic Ocean. The amplitude of the SIA seasonal cycle has also increased in 2000–2019 in comparison with the earlier period, with the largest changes in the inner Arctic Ocean, the Kara, Laptev, East Siberian and Beaufort Seas in summer and in the Barents Sea in winter. The results may reflect a transition to a new dynamic state in the recent two decades with the triggering of positive feedbacks in the Arctic climate system.

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.

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.