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At least 415 records · Page 23

Partitioning Net Ecosystem Exchange (NEE) of CO 2 Using Solar-Induced Chlorophyll Fluorescence (SIF)

Accurate partitioning of net ecosystem exchange (NEE) of CO 2 to gross primary production (GPP) and ecosystem respiration (R eco ) is crucial for understanding carbon cycle dynamics under changing climate. However, it remains as a long-standing problem in global ecology due to lack of independent constraining information for the two offsetting component fluxes. solar-induced chlorophyll fluorescence (SIF), a mechanistic proxy for photosynthesis, holds great promise to improve NEE partitioning by constraining GPP. We developed a parsimonious SIF-based approach for NEE partitioning and examined its performance using synthetic simulations and field measurements. This approach outperforms conventional approaches in reproducing simulated GPP and R eco , especially under high vapor pressure deficit. For field measurements, it results in lower daytime GPP and R eco than conventional approaches. Furthermore, this study made the first attempt to demonstrate SIF's potential for improving NEE partitioning accuracy and sets the stage for future efforts to examine its robustness and scalability under real-world environmental conditions.

54 ENVIRONMENTAL SCIENCES↗

Superthermal Electron Deposition on the Mars Nightside During ICMEs

Superthermal electron precipitation is one of the main sources supporting the Mars nightside ionosphere. It is expected that solar wind electron fluxes are to increase significantly during interplanetary coronal mass ejections (ICMEs) and therefore an enhanced nightside ionospheric density. This study is to quantify the variation of the precipitating and deposited electron fluxes during five extreme ICMEs encountered by Mars Global Surveyor (MGS). We find that energy fluxes correlate better with the upstream dynamic pressure proxy than number fluxes and electron fluxes increase more at high energies, which means that electrons tend to have a lower peak production altitude during storm times. The precipitating and net/deposited fluxes are increased up to an order of magnitude from low to high dynamic pressures. The estimated total electron content (TEC) is a few times of 10 14 m -2 for quiet times and on the order of 1015 m -2 for storm times, with an enhancement up to an order of magnitude locally near strong crustal fields. Crustal magnetic fields have an effect on the deposited fluxes with more prominent magnetic reflection over strong magnetic fields during quiet periods, which is significantly reduced during storm times. Lastly, we estimate a global energy input from downward fluxes of 1.1 × 10 8 and 5.5 × 10 8 W and the globally deposited energy from net fluxes of 2.0 × 10 7 and 1.6 × 10 8 W for quiet and storm time periods, a factor of 5 and 8 enhancement globally, respectively, but up to an order of magnitude locally near strong crustal fields.

79 ASTRONOMY AND ASTROPHYSICS↗

An Observational Comparison of Level of Neutral Buoyancy and Level of Maximum Detrainment in Tropical Deep Convective Clouds

Tropical deep convective clouds are important drivers of large-scale atmospheric circulation representing the main vertical transport pathway through the depth of the troposphere for heat, momentum, water, and chemical species. The strength and depth of this transport are impacted by the convective updraft size and intensity that are driven by buoyancy, dynamical forcing, and mixing of environmental air, i.e., entrainment. In this paper, we identify tropical deep convective systems with well-defined forward anvils using Atmospheric Radiation Measurement (ARM) ground-based profiling radars, at three ARM fixed-sites in the Tropical Western Pacific (TWP; i.e., Manus, Nauru, Darwin) and three ARM Mobile Facility deployments in Niamey, Niger; Gan Island, Maldives; and Manacapuru, Brazil. We use the difference between the level of neutral buoyancy (LNB) and the level of maximum detrainment (LMD) as a proxy for the effective bulk convective entrainment (εproxy). The LNB, the theoretical height that a parcel raised above the level of free convection would reach with no mixing, is calculated based on pre-convection radiosonde measurements using parcel theory. The LMD is the height of the maximum reflectivity observed in forward anvil clouds by profiling radars. Deep convective systems over the TWP show higher LNBs that extend to 16.3 km on average and larger εproxy (median LNB minus LMD up to 6.5 km) compared to their continental counterparts in the Amazon and West Africa. Oceanic conditions show larger convective available potential energy (CAPE) coupled with higher moisture at low levels which favors larger εproxy. In contrast, continental cases initiate and develop under high convective inhibition, steeper environmental lapse rate, and high wind shear conditions, which show smaller offset between LNB and LMD. Deep convective cases that promote significant cold pools at the surface experience less εproxy. Using a Random Forest regression algorithm, CAPE is associated with the highest feature importance score for predicting convective εproxy, followed by low-level relative humidity. For continental cases, the low-level wind shear also indicates higher importance.

54 ENVIRONMENTAL SCIENCES↗

Assessing the Representation of Synoptic Variability Associated With California Extreme Precipitation in CMIP6 Models

Abstract Days of extreme precipitation over California are evaluated in Coupled Model Intercomparison Project Phase 6 (CMIP6) models and the ERA‐Interim reanalysis. In the current climate, the model spread in composited precipitation on extreme precipitation days is closely related to the magnitude of composited integrated vapor transport (IVT) across models, a proxy for the intensity of atmospheric rivers. Most models underestimate the magnitude of IVT associated with extreme precipitation, according to ERA‐Interim. This is due mostly to the contribution of moisture, which almost all models overestimate, while the contribution of lower‐tropospheric wind speed is generally closer to the reanalyses. Moreover, most models underestimate the variance in the latitude of maxima of numerous variables among days of extreme California precipitation. That is, in the general circulation models there is a lack of diversity in the latitude of the disturbances bringing winter precipitation to California. In the future climate, most models project a decrease in the frequency of southward‐displaced disturbances among California extreme precipitation days. Hence, the greatest increases in extreme precipitation are over northern California. However, the historical underestimate of the latitudinal variance of disturbances calls into question the reliability of these projections. This bias should be especially considered for dynamical downscaling efforts over the region.

Norris, Jesse↗

Analysis of Oil and Gas Ethane and Methane Emissions in the Southcentral and Eastern United States Using Four Seasons of Continuous Aircraft Ethane Measurements

In the last decade, much work has been done to better understand methane (CH 4 ) emissions from the oil and gas (O&G) industry in the United States. Ethane (C 2 H 6 ), a gas that is co-emitted with thermogenic sources of CH 4 , is emitted in the US predominantly by the O&G sector. Here, in this study, we perform an inverse analysis on 200 h of atmospheric boundary layer C 2 H 6 measurements to estimate C 2 H 6 emissions from the US O&G sector. Measurements were collected from 2017 to 2019 as part of the Atmospheric Carbon and Transport (ACT) America aircraft campaign and encompass much of the central and eastern United States. We find that for the fall, winter, and spring campaigns, C 2 H 6 data consistently exceeds values that would be expected based on EPA O&G leak rate estimates by more than 50%. C 2 H 6 observations from the summer 2019 data set show significantly lower C 2 H 6 enhancements in the southcentral region that cannot be reconciled with data from the other three seasons, either due to complex meteorological conditions or a temporal shift in the emissions. Combining the fall, winter, and spring C 2 H 6 posterior emissions estimate to an inventory of O&G CH 4 emissions, we estimate that O&G CH 4 emissions are larger than EPA inventory values by 48%–76%. Uncertainties in the gas composition data limit the accuracy of using C 2 H 6 as a proxy for O&G CH 4 emissions. These limits could be resolved retroactively by increasing the availability of industry-collected gas composition data.

54 ENVIRONMENTAL SCIENCES↗

Slope-Aspect Induced Climate Differences Influence How Water Is Exchanged Between the Land and Atmosphere

Cross-slope climate differences in the midlatitudes are ecologically important, and impact vegetation-mediated water balance between the earth surface and the atmosphere. We made high-resolution in situ observations of air temperature, relative humidity, soil moisture, insolation, and sap velocity observations on 14 Pacific madrone trees (Arbutus menziesii) spanning adjacent north and south slopes at the University of California's Angelo Coast Range Reserve. To understand the cross-slope response of sap velocity, a proxy for transpiration, to microclimate, we modeled the sap velocity on each slope using a transpiration model driven by ambient environment and parameterized with a Markov Chain Monte Carlo parameter estimation process. The results show that trees on opposing slopes do not follow a shared pattern of physiological response to transpiration drivers. This means that the observed sap velocity differences are not due entirely to observed microclimate differences, but also due to population-level physiological differences, which indicates acclimation to inhabited microclimate. While our present data set and analytical tools do not identify mechanisms of acclimation, we speculate that differing proportions of sun-adapted and shade-adapted leaves, differences in stomatal regulation, and cross-slope root zone moisture differences could explain some of the observed and modeled differences.

54 ENVIRONMENTAL SCIENCES↗

The Relation of Environmental Conditions With Charge Structure in Central Argentina Thunderstorms

In this study we explored the environmental conditions hypothesized to induce a dominant charge structure in thunderstorms in the province of Cordoba, Argentina, during the RELAMPAGO-CACTI (Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations-Clouds, Aerosols, Complex Terrain Interactions) field campaigns. Hypothesized environmental conditions are thought to be related to small warm cloud residence time and warm rain growth suppression, which lead to high cloud liquid water contents in the mixed-phase zone, contributing to positive charging of graupel and anomalous charge structure storms. Data from radiosondes, a cloud condensation nuclei (CCN) ground-based instrument and reanalysis were used to characterize the proximity inflow air of storms with anomalous and normal charge structures. Consistent with the initial hypothesis, anomalous storms had small warm cloud depth caused by dry low-level humidity and low 0°C height. Anomalous storms were associated with lower CCN concentrations than normal storms, an opposite result to the initial expectation. High CAPE is not an important condition for the development of anomalous storms in Argentina, as no clear pattern could be found among the different parameters calculated for updraft proxy that would be consistent with the initial hypothesis.

54 ENVIRONMENTAL SCIENCES↗

Quantifying Northern High Latitude Gross Primary Productivity (GPP) Using Carbonyl Sulfide (OCS)

The northern high latitude (NHL, 40°N to 90°N) is where the second peak region of gross primary productivity (GPP) other than the tropics. The summer NHL GPP is about 80% of the tropical peak, but both regions are still highly uncertain. Carbonyl sulfide (OCS) provides an important proxy for photosynthetic carbon uptake. Here we optimize the OCS plant uptake fluxes across the NHL by fitting atmospheric concentration simulation with the GEOS-CHEM global transport model to the aircraft profiles acquired over Alaska during NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (2012–2015). We use the empirical biome-specific linear relationship between OCS plant uptake flux and GPP to derive the six plant uptake OCS fluxes from different GPP data. Such GPP-based fluxes are used to drive the concentration simulations. We evaluate the simulations against the independent observations at two ground sites of Alaska. The optimized OCS fluxes suggest the NHL plant uptake OCS flux of -247 Gg S year -1 , about 25% stronger than the ensemble mean of the six GPP-based OCS fluxes. GPP-based OCS fluxes systematically underestimate the peak growing season across the NHL, while a subset of models predict early start of season in Alaska, consistent with previous studies of net ecosystem exchange. The OCS optimized GPP of 34 PgC yr -1 for NHL is also about 25% more than the ensembles mean from six GPP data. Further work is needed to fully understand the environmental and biotic drivers and quantify their rate of photosynthetic carbon uptake in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Isolating Detrital and Diagenetic Signals in Magnetic Susceptibility Records From Methane‐Bearing Marine Sediments

Abstract Volume‐dependent magnetic susceptibility (κ) is commonly used for paleoenvironmental reconstructions in both terrestrial and marine sedimentary environments where it reflects a mixed signal between primary deposition and secondary diagenesis. In the marine environment, κ is strongly influenced by the abundance of ferrimagnetic minerals regulated by sediment transport processes. Post‐depositional alteration by H 2 S, however, can dissolve titanomagnetite, releasing reactive Fe that promotes pyritization and subsequently decreases κ. Here, we provide a new approach for isolating the detrital signal in κ and identifying intervals of diagenetic alteration of κ driven by organoclastic sulfate reduction (OSR) and the anaerobic oxidation of methane (AOM) in methane‐bearing marine sediments offshore India. Using the correlation of a heavy mineral proxy from X‐ray fluorescence data (Zr/Rb) and κ in unaltered sediments, we predict the primary detrital κ signal and identify intervals of decreased κ, which correspond to increased total sulfur content. Our approach is a rapid, high‐resolution method that can identify overprinted κ resulting from pyritization of titanomagnetite due to H 2 S production in marine sediments. In addition, total organic carbon, total sulfur, and authigenic carbonate δ 13 C measurements indicate that both OSR and AOM can drive the observed κ loss, but AOM drives the greatest decreases in κ. Overall, our approach can enhance paleoenvironmental reconstructions and provide insight into paleo‐positions of the sulfate‐methane transition zone, past enhancements of OSR or paleo‐methane seepage, and the role of detrital iron oxide minerals on the marine sediment sulfur sink, with consequences influencing the development of chemosynthetic biological communities at methane seeps.

58 GEOSCIENCES↗

Development of Heterogeneous Ice Nucleation Rate Coefficient Parameterizations From Ambient Measurements

Ice nucleating particles (INPs) are a rare subset of particles that can have an outsized impact relative to their prevalence. To simulate INP variability, models require parameterizations for the most important sources of INPs. Most parameterizations in the literature were developed from laboratory experiments that used proxies for ambient particles. Whether these laboratory models effectively represent ambient aerosol is still not well understood and parameterizations developed from field measurements may be more atmospherically relevant. Expanding on previous work in which we used an ice chamber and a single-particle mass spectrometer (SPMS) to characterize INP composition, we calculate heterogeneous ice nucleation rate coefficients for ambient particles. We find good agreement between our dust and previous measurements of airborne dust. We also use a Monte Carlo approach to assess the relative contribution of each measurement to the uncertainty and find that the biggest source is the sampling efficiency of the SPMS.

54 ENVIRONMENTAL SCIENCES↗

Increasing Functional Diversity in a Global Land Surface Model Illustrates Uncertainties Related to Parameter Simplification

Abstract Simulations of the land surface carbon cycle typically compress functional diversity into a small set of plant functional types (PFT), with parameters defined by the average value of measurements of functional traits. In most earth system models, all wild plant life is represented by between five and 14 PFTs and a typical grid cell (≈100 × 100 km) may contain a single PFT. Model logic applied to this coarse representation of ecological functional diversity provides a reasonable proxy for the carbon cycle, but does not capture the non‐linear influence of functional traits on productivity. Here we show through simulations using the Energy Exascale Land Surface Model in 15 diverse terrestrial landscapes, that better accounting for functional diversity markedly alters predicted total carbon uptake. The shift in carbon uptake is as great as 30% and 10% in boreal and tropical regions, respectively, when compared to a single PFT parameterized with the trait means. The traits that best predict gross primary production vary based on vegetation phenology, which broadly determines where traits fall within the global distribution. Carbon uptake is more closely associated with specific leaf area for evergreen PFTs and the leaf carbon to nitrogen ratio in deciduous PFTs.

58 GEOSCIENCES↗

Model Evaluation and Intercomparison of Marine Warm Low Cloud Fractions With Neural Network Ensembles

Abstract Low cloud fractions (LCFs) and meteorological factors (MFs) over an oceanic region containing multiple cloud regimes are examined for three data sets: one Energy Exascale Earth System Model (E3SM) simulation with the default 72‐layer vertical grid (E3SM72), another one with 8‐times vertical resolution via the Framework for Improvement by Vertical Enhancement (E3SM 8), and one with MFs from ERA5 reanalysis and LCFs from the CERES SSF product (ERA5‐SSF). Neural networks (NNs) are trained to capture the relationship between MFs and LCF and to select the best‐performing MF subsets for predicting LCF. NN ensembles are used to (a) confirm the performance of selected MF subsets, (b) to serve as proxy models for each data set to predict LCFs for MFs from all data sets, and (c) to classify MFs into those in shared and uniquely occupied MF subspaces. Overall, E3SM72 and E3SM 8 have large fractions of MFs in shared MF subspace, but less so near the Californian and Peruvian stratocumulus decks. E3SM 8 and ERA5 have small fractions of MFs in shared MF subspace but greater than E3SM72 and ERA5, especially in the Southeast Pacific. The differences in LCFs between three pairs of data sets are decomposed into those associated with the differences in the LCF‐MF relationship and those involving different MFs. Given the same MFs, LCFs produced by E3SM 8 are greater than those produced by E3SM72 but are still different from those in ERA5‐SSF. In general, the shift in MFs dominates the difference in the LCFs.

54 ENVIRONMENTAL SCIENCES↗

Achievements and Prospects of Global Broadband Seismographic Networks After 30 Years of Continuous Geophysical Observations

Global seismographic networks (GSNs) emerged during the late nineteenth and early twentieth centuries, facilitated by seminal international developments in theory, technology, instrumentation, and data exchange. The mid- to late-twentieth century saw the creation of the World-Wide Standardized Seismographic Network (1961) and International Deployment of Accelerometers (1976), which advanced global geographic coverage as seismometer bandwidth increased greatly allowing for the recording of the Earth's principal seismic spectrum. The modern era of global observations and rapid data access began during the 1980s, and notably included the inception of the GEOSCOPE initiative (1982) and GSN (1988). Through continual improvements, GEOSCOPE and the GSN have realized near-real time recording of ground motion with state-of-art data quality, dynamic range, and timing precision to encompass 180 seismic stations, many in very remote locations. Data from GSNs are increasingly integrated with other geophysical data (e.g., space geodesy, infrasound and Interferometric Synthetic Aperture Radar). Globally distributed seismic data are critical to resolving crust, mantle, and core structure; illuminating features of the plate tectonic and mantle convection system; rapid characterization of earthquakes; identification of potential tsunamis; global nuclear test verification; and provide sensitive proxies for environmental changes. As the global geosciences community continues to advance our understanding of Earth structure and processes controlling elastic wave propagation, GSN infrastructure offers a springboard to realize increasingly multi-instrument geophysical observatories. Here, we review the historical, scientific, and monitoring heritage of GSNs, summarize key discoveries, and discuss future associated opportunities for Earth Science.

58 GEOSCIENCES↗

Earlier Ecological Drought Detection by Involving the Interaction of Phenology and Eco-Physiological Function

Meteorological drought indices like the Standardized Precipitation Evaporation Index (SPEI) are frequently used to diagnose “ecological drought,” despite the fact that they were not explicitly designed for this purpose. More recently developed indices like the Evaporative Stress Index (ESI), which is based on the degree of coupling between actual to potential evapotranspiration, may better capture dynamic plant response to moisture limitations. However, the skill of these indices at describing plant water stress is rarely evaluated at sub-seasonal timescales over which drought evolves. Moreover, it remains unclear how variability in phenological timing impacts and complicates early drought detection. Here, we compared the ability of ESI and SPEI to reflect the dynamics of ecological drought in forests and grasslands, based on anomalies of Gross Primary Productivity (GPP), surface conductance (G s , a proxy for stomatal conductance), soil moisture, and vapor pressure deficit. ESI performed better than SPEI in capturing the dynamics of GPP and G s , but still missed early ecological drought signals due to biases linked to earlier onset of spring leaf development. Thus, we developed a modified variant of the ESI (ESI LAI ) that accounts for the complicating effects of phenological shifts in leaf area index (LAI). The ESI LAI detected drought onset up to 7–10 weeks earlier than SPEI and ESI. Additionally, drought onset dates determined from ESI LAI are close to (±2 weeks) the dates determined from LAI-corrected anomalies of G s , and GPP, as well as the onset dates of soil water deficit and atmospheric aridity.

54 ENVIRONMENTAL SCIENCES↗

Uncertainty in Reconstructing Paleo‐Elevation of the Antarctic Ice Sheet From Temperature‐Sensitive Ice Core Records

Paleotemperature reconstructions from ice cores are mixed signals of changes in climate and ice‐surface elevation. A common, temperature‐based paleoaltimetry method suggests these signals can be disentangled by comparing two proxy locations with similar climates. The difference between the records is assumed to be due to elevation, which is estimated by scaling the temperature difference by a lapse rate. We investigate the uncertainty associated with this approach using a case study of the Antarctic Ice Sheet during the Last Glacial Maximum. From an ensemble of climate simulations, we extract modeled temperatures at locations of real ice cores. We find uncertainty on the order of hundreds of meters that results from spatial heterogeneity in non‐adiabatic temperature change, which itself stems in part from elevation‐induced atmospheric circulation change. Our findings suggest that caution is needed when interpreting temperature‐based paleoaltimetry results for ice sheets.

58 GEOSCIENCES↗

Using Multiscale Ethane/Methane Observations to Attribute Coal Mine Vent Emissions in the San Juan Basin From 2013 to 2021

Abstract Source attribution of natural gas emissions from fossil fuels in New Mexico's San Juan Basin (SJB) is challenging due to source heterogeneity and emissions transience. We demonstrate that ethane (C 2 H 6 ) to methane (CH 4 ) mixing ratios can identify and separate sources over different scales using various measurement techniques. We report simultaneous CH 4 and C 2 H 6 observations near a coal mine vent and oil and gas (O&G) emission sources using ground‐based in situ measurements in 2020/2021. During these campaigns, we observed a stable coal vent C 2 H 6 :CH 4 ratio of 1.28% ± 0.11%, discernibly different than nearby O&G source ratios ranging from 0.9% to 16.8%. We analyze airborne observations of the SJB taken in 2014/2015 that exhibit similar coal vent ratios and further show the region's heterogeneity. We identify episodic O&G sources, including a gas plant source detected in 2014/2015 that is absent in our 2020/2021 data. We examine total column observations of C 2 H 6 and CH 4 made in 2013 with a solar spectrometer and find a C 2 H 6 :CH 4 ratio of 1.3% ± 0.4% for the coal vent. The stable and unique coal vent ratio relative to other O&G sources in the region is used to demonstrate that consistent attribution is possible using various measurement methods at multiple scales across many years. Finally, we demonstrate that using C 2 H 6 as a proxy for fossil CH 4 inversions can inform detailed basin‐scale inversions, provided we understand source specific changes in the C 2 H 6 :CH 4 ratio like we report in the SJB.

54 ENVIRONMENTAL SCIENCES↗

Microtopography Matters: Belowground CH 4 Cycling Regulated by Differing Microbial Processes in Peatland Hummocks and Lawns

Water table depth and vegetation are key controls of methane (CH 4 ) emissions from peatlands. Microtopography integrates these factors into features called microforms. Microforms often differ in CH 4 emissions, but microform-dependent patterns of belowground CH 4 cycling remain less clearly resolved. Here, to investigate the impact of microtopography on belowground CH 4 cycling, we characterized depth profiles of the community composition and activity of CH 4 -cycling microbes using 16S rRNA amplicon sequencing, incubations, and measurements of porewater CH 4 concentration and isotopic composition from hummocks and lawns at Sallie's Fen in NH, USA. Geochemical proxies of methanogenesis and methanotrophy indicated that microforms differ in dominant microbial CH 4 cycling processes. Hummocks, where water table depth is lower, had higher porewater redox potential (Eh) and higher porewater δ 13 C-CH 4 values in the upper 30 cm than lawns, where water table depth is closer to the peat surface. Porewater δ 13 C-CH 4 and δD-CH 3 D values were highest at the surface of hummocks where the ratio of methanotrophs to methanogens was also greatest. These results suggest that belowground CH 4 cycling in hummocks is more strongly regulated by methanotrophy, while in lawns methanogenesis is more dominant. We also investigated controls of porewater CH 4 chemistry. The ratio of the relative abundance of methanotrophs to methanogens was the strongest predictor of porewater CH 4 concentration and δ 13 C-CH 4 , while vegetation composition had minimal influence. As microbial community composition was strongly influenced by redox conditions but not vegetation, we conclude that water table depth is a stronger control of belowground CH 4 cycling across microforms than vegetation.

59 BASIC BIOLOGICAL SCIENCES↗

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH 4 Sites Using Wavelet Analyses

Process-based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments.

58 GEOSCIENCES↗