A31N-03: Lower-Tropospheric CO2 from Near-Infrared ACOS-GOSAT Observations

We present two new products from near-infrared GOSAT observations: lower tropospheric (LMT, from 0-2.5 km) and upper tropospheric/stratospheric (U, above 2.5 km) carbon dioxide partial columns. We compare these new products to aircraft profiles and remote surface flask measurements and find that the seasonal and year-to-year variations in the new partial columns significantly improve over the ACOS-GOSAT initial guess/a priori, with distinct patterns in the LMT and U seasonal cycles which match validation data. For land monthly averages, we find errors of 1.9, 0.7, and 0.8 ppm for retrieved GOSAT LMT, U, and XCO2; for ocean monthly averages, we find errors of 0.7, 0.5, and 0.5 ppm for retrieved GOSAT LMT, U, and XCO2. In the southern hemisphere biomass burning season, the new partial columns show similar patterns to MODIS fire maps and MOPITT multispectral CO for both vertical levels, despite a flat ACOS-GOSAT prior, and CO/CO2 emission factor consistent with published values. The difference of LMT and U, useful for evaluation of model transport error, has also been validated with monthly average error of 0.8 (1.4) ppm for ocean (land). The new LMT partial column is more locally influenced than the U partial column, meaning that local fluxes can now be separated from CO2 transported from far away

The effect of relative humidity on eddy covariance latent heat flux measurements and its implication for partitioning into transpiration and evaporation

While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or 'evapotranspiration’, ET), the measurement is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (>70%), due to low-pass filtering with some EC systems. Yet, this underestimation for different types of EC systems (e.g. open-path or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of latent heat fluxes (LE, or ET) from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that the LE underestimation is most apparent during hours when RH is higher than 70%, predominantly observed at sites using closed-path EC systems, but the extent of the LE underestimation is highly site-specific. We then propose a machine learning based method to correct for this underestimation, and compare it to two energy balance closure based LE correction approaches (Bowen ratio correction, BRC, and attributing all errors to LE). Our correction increases LE by 189% for closed-path sites at high RH (>90%), while BRC increases LE by around 30% for all RH conditions. Additionally, we assess the influence of these corrections on ET-based transpiration (T) estimates using two different ET partitioning methods. Results show opposite responses (increasing vs. slightly decreasing T-to-ET ratios, T/ET) between the two methods when comparing T based on corrected and uncorrected LE. Overall, our results demonstrate the existence of a high RH bias in water fluxes in the FLUXNET2015 dataset and suggest that this bias is a pronounced source of uncertainty in ET measurements to be considered when estimating ecosystem T/ET and WUE.Peer reviewe

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.Peer reviewe

Carbon, water, and heat flux responses to experimental burning and drought in a tallgrass prairie

Drought and fire are common disturbances to grassland ecosystems. We report two years of eddy covariance ecosystem–atmosphere fluxes and biometric variables measured in nearby burned and unburned pastures in the US Southern Great Plains. Over the course of the experiment, annual precipitation (∼600 mm yr−1) was lower than the long term mean (∼860 mm yr−1). Soil moisture decreased from productive conditions in March 2005 dry, unproductive conditions during the growing season starting in March 2006. Just prior to the burn in early March 2005, burned and unburned pastures contained 520 ± 60 and 360 ± 40 g C m−2 of total above ground biomass (AGB) and litter, respectively. The fire removed approximately 200 g C m−2 of litter and biomass. In the 2005 growing season following the burn, maximum green AGB was 450 ± 60 and 270 ± 40 g C m−2, with corresponding cumulative annual net ecosystem carbon exchange (NEE) of −330 and −150 g C m−2 for the burned and unburned pastures, respectively. In contrast to NEE, cumulative mean sensible heat and water fluxes were approximately equal in both pastures during the growing season, suggesting either an increase in water use efficiency or a decrease in evaporation in the burned relative to the unburned pasture. In the 2006 growing season, dry conditions decreased carbon uptake and latent heat, and increased sensible heat fluxes. Peak AGB was reduced to 210 ± 30 g C m−2 and 140 ± 30 g C m−2 in the burned and unburned pastures, respectively, while NEE was near zero. These results suggest that the lack of precipitation was responsible for most of the interannual variation in carbon exchange for these un-irrigated prairie pastures

Regional CO\u3csub\u3e2\u3c/sub\u3e and latent heat surface fluxes in the Southern Great Plains: Measurements, modeling, and scaling

[1] Characterizing net ecosystem exchanges (NEE) of CO2 and sensible and latent heat fluxes in heterogeneous landscapes is difficult, yet critical given expected changes in climate and land use. We report here a measurement and modeling study designed to improve our understanding of surface to atmosphere gas exchanges under very heterogeneous land cover in the mostly agricultural U.S. Southern Great Plains (SGP). We combined three years of site-level, eddy covariance measurements in several of the dominant land cover types with regional-scale climate data from the distributed Mesonet stations and Next Generation Weather Radar precipitation measurements to calibrate a land surface model of trace gas and energy exchanges (isotope-enabled land surface model (ISOLSM)). Yearly variations in vegetation cover distributions were estimated from Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index and compared to regional and subregional vegetation cover type estimates from the U.S. Department of Agriculture census. We first applied ISOLSM at a 250 m spatial scale to account for vegetation cover type and leaf area variations that occur on hundred meter scales. Because of computational constraints, we developed a subsampling scheme within 10 km ‘‘macrocells’’ to perform these high-resolution simulations. We estimate that the Atmospheric Radiation Measurement Climate Research Facility SGP region net CO2 exchange with the local atmosphere was –240, –340, and –270 gC m–2 yr–1 (positive toward the atmosphere) in 2003, 2004, and 2005, respectively, with large seasonal variations. We also performed simulations using two scaling approaches at resolutions of 10, 30, 60, and 90 km. The scaling approach applied in current land surface models led to regional NEE biases of up to 50 and 20% in weekly and annual estimates, respectively. An important factor in causing these biases was the complex leaf area index (LAI) distribution within cover types. Biases in predicted weekly average regional latent heat fluxes were smaller than for NEE, but larger than for either ecosystem respiration or assimilation alone. However, spatial and diurnal variations of hundreds of W m–2 in latent heat fluxes were common. We conclude that, in this heterogeneous system, characterizing vegetation cover type and LAI at the scale of spatial variation are necessary for accurate estimates of bottom-up, regional NEE and surface energy fluxes

Vulnerability of crops and native grasses to summer drying in the U.S. Southern Great Plains

The Southern Great Plains are characterized by a fine-scale mixture of different land-cover types, predominantly winter-wheat and grazed pasture, with relatively small areas of other crops, native prairie, and switchgrass. Recent droughts and predictions of increased drought in the Southern Great Plains, especially during the summer months, raise concern for these ecosystems. We measured ecosystem carbon and water fluxes with eddy-covariance systems over cultivated cropland for 10 years, and over lightly grazed prairie and new switchgrass fields for 2 years each. Growing-season precipitation showed the strongest control over net carbon uptake for all ecosystems, but with a variable effect: grasses (prairie and switchgrass) needed at least 350 mm of precipitation during the growing season to become net carbon sinks, while crops needed only 100 mm. In summer, high temperatures enhanced evaporation and led to higher likelihood of dry soil conditions. Therefore, summer-growing native prairie species and switchgrass experienced more seasonal droughts than spring-growing crops. For wheat, the net reduction in carbon uptake resulted mostly from a decrease in gross primary production rather than an increase in respiration. Flux measurements suggested that management practices for crops were effective in suppressing evapotranspiration and decomposition (by harvesting and removing secondary growth), and in increasing carbon uptake (by fertilizing and conserving summer soil water). In light of future projections for wetter springs and drier and warmer summers in the Southern Great Plains, our study indicates an increased vulnerability in native ecosystems and summer crops over time