Sensitivity of Pan-Arctic Terrestrial Net Primary Productivity Simulations to Daily Surface Meterology From NCEP-NCAR and ERA-40 Reanalyses

We applied a terrestrial net primary production (NPP) model driven by satellite remote sensing observations of vegetation properties and daily surface meteorology from the 45-year ECMWF Re-Analysis (ERA-40) and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP-NCAR) reanalysis (NNR) to assess NPP spatial and temporal variability for the pan-Arctic basin and Alaska from 1982 to 2000. Sensitivity analysis of the production efficiency model (PEM) to uncertainties in surface meteorological inputs indicate that ERA-40 solar radiation and NNR solar radiation and surface temperatures are the primary sources of PEM-based NPP uncertainty for the region. Considerable positive bias in solar radiation inputs relative to surface observation networks resulted in overprediction of annual NPP by approximately 35.2 and 61.6% using ERA-40 and NNR inputs, respectively. Despite these uncertainties, both reanalysis products captured the major annual anomalies and trends in surface meteorology for the domain. The two reanalysis products also produced similar NPP spatial patterns for 74.7% of the domain, and similar annual anomalies and temporal trends, though there were significant regional differences particularly for Eurasia. A simple correction method based on a sensitivity experiment between reanalysis and surface station meteorological measurements produced generally consistent NPP results that were considerably smaller than PEM simulations derived from uncorrected reanalysis drivers. The results of this study identify major sources of uncertainty in reanalysis-based surface meteorology, and associated impacts on regional NPP simulations of the northern high latitudes

Satellite-based model detection of recent climate-driven changes in northern high-latitude vegetation productivity

We applied a satellite remote sensing based production efficiency model (PEM) using an integrated AVHRR and MODIS FPAR/LAI time series with a regionally corrected NCEP/NCAR reanalysis daily surface meteorology and NASA/GEWEX Surface Radiation Budget shortwave solar radiation inputs to assess annual terrestrial net primary productivity (NPP) for the pan-Arctic basin and Alaska from 1983 to 2005. Our results show that low temperature constraints on Boreal-Arctic NPP are decreasing by 0.43% per year (P \u3c 0.001), whereas a positive trend in vegetation moisture constraints of 0.49% per year (P = 0.04) are offsetting the potential benefits of longer growing seasons and contributing to recent disturbances in NPP. The PEM simulations of NPP seasonality, annual anomalies and trends are similar to stand inventory network measurements of boreal aspen stem growth (r = 0.56; P = 0.007) and atmospheric CO2 measurement based estimates of the timing of growing season onset (r = 0.78; P \u3c 0.001). Our results indicate that summer drought led to marked NPP decreases in much of the boreal forest region after the late-1990s. However, seasonal low temperatures are still a dominant limitation on regional NPP. Despite recent drought events, mean annual NPP for the pan-Arctic region showed a positive growth trend of 0.34% per year (20.27 TgC/a; P = 0.002) from 1983 to 2005. Drought induced NPP decreases may become more frequent and widespread as regional ecosystems adjust to a warmer, drier atmosphere, though the occurrence and severity of drought events will depend on future patterns of plant-available moisture

Pulse‐labeling studies of carbon cycling in Arctic tundra ecosystems: The contribution of photosynthates to methane emission

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94952/1/gbc790.pd

A multi-scale comparison of modeled and observed seasonal methane emissions in northern wetlands

Wetlands are the largest global natural methane (CH4) source, and emissions between 50 and 70° N latitude contribute 10–30% to this source. Predictive capability of land models for northern wetland CH4 emissions is still low due to limited site measurements, strong spatial and temporal variability in emissions, and complex hydrological and biogeochemical dynamics. To explore this issue, we compare wetland CH4 emission predictions from the Community Land Model 4.5 (CLM4.5-BGC) with siteto regional-scale observations. A comparison of the CH4 fluxes with eddy flux data highlighted needed changes to the model’s estimate of aerenchyma area, which we implemented and tested. The model modification substantially reduced biases in CH4 emissions when compared with CarbonTracker CH4 predictions. CLM4.5 CH4 emission predictions agree well with growing season (May–September) CarbonTracker Alaskan regional-level CH4 predictions and sitelevel observations. However, CLM4.5 underestimated CH4 emissions in the cold season (October–April). The monthly atmospheric CH4 mole fraction enhancements due to wetland emissions are also assessed using the Weather Research and Forecasting-Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model coupled with daily emissions from CLM4.5 and compared with aircraft CH4 mole fraction measurements from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) campaign. Both the tower and aircraft analyses confirm the underestimate of cold-season CH4 emissions by CLM4.5. The greatest uncertainties in predicting the seasonal CH4 cycle are from the wetland extent, coldseason CH4 production and CH4 transport processes. We recommend more cold-season experimental studies in highlatitude systems, which could improve the understanding and parameterization of ecosystem structure and function during this period. Predicted CH4 emissions remain uncertain, but we show here that benchmarking against observations across spatial scales can inform model structural and parameter improvements

Cold season emissions dominate the Arctic tundra methane budget

Arctic terrestrial ecosystems are major global sources of methane (CH4); hence, it is important to understand the seasonal and climatic controls on CH4 emissions from these systems. Here, we report year-round CH4 emissions from Alaskan Arctic tundra eddy flux sites and regional fluxes derived from aircraft data. We find that emissions during the cold season (September to May) account for >= 50% of the annual CH4 flux, with the highest emissions from noninundated upland tundra. A major fraction of cold season emissions occur during the "zero curtain" period, when subsurface soil temperatures are poised near 0 degrees C. The zero curtain may persist longer than the growing season, and CH4 emissions are enhanced when the duration is extended by a deep thawed layer as can occur with thick snow cover. Regional scale fluxes of CH4 derived from aircraft data demonstrate the large spatial extent of late season CH4 emissions. Scaled to the circumpolar Arctic, cold season fluxes from tundra total 12 +/- 5 (95% confidence interval) Tg CH4 y(-1), similar to 25% of global emissions from extratropical wetlands, or similar to 6% of total global wetland methane emissions. The dominance of late-season emissions, sensitivity to soil environmental conditions, and importance of dry tundra are not currently simulated in most global climate models. Because Arctic warming disproportionally impacts the cold season, our results suggest that higher cold-season CH4 emissions will result from observed and predicted increases in snow thickness, active layer depth, and soil temperature, representing important positive feedbacks on climate warming.Peer reviewe

Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties

The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990-2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km(2)) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE -46 and -29 g C m(-2) yr(-1), respectively) compared to tundra (average annual NEE +10 and -2 g C m(-2) yr(-1)). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990-2015, although uncertainty remains high

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions

Wetland methane (CH4) emissions (FCH4) are important in global carbon budgets and climate change assessments. Currently, FCH4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent FCH4 temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that FCH4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between FCH4 and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between FCH4 and temperature, suggesting larger FCH4 sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments. Wetland methane emissions contribute to global warming, and are oversimplified in climate models. Here the authors use eddy covariance measurements from 48 global sites to demonstrate seasonal hysteresis in methane-temperature relationships and suggest the importance of microbial processes.Peer reviewe

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible

The uncertain climate footprint of wetlands under human pressure

Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems,making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse– response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange