No abstract

During the second year of the NASA Cold Land Processes Experiment (CLPX), an eddy covariance (EC) system was deployed at the Local Scale Observation Site (LSOS) from mid-February to June 2003. The EC system was located beneath a uniform pine canopy, where the trees are regularly spaced and are of similar age and height. In an effort to evaluate the turbulent flux calculations of an energy balance snowmelt model (SNOBAL), modeled and EC-measured sensible and latent heat fluxes between the snow cover and the atmosphere during this period are presented and compared. Turbulent fluxes comprise a large component of the snow cover energy balance in the premelt and ripening period (March-early May) and therefore control the internal energy content of the snow cover as melt accelerates in late spring. Simulated snow cover depth closely matched measured values (RMS difference 8.3 cm; Nash-Sutcliff model efficiency 0.90), whereas simulated snow cover mass closely matched the few measured values taken during the season. Over the 927-h comparison period using the default model configuration, simulated sensible heat H was within 1 W m Ϫ2 , latent heat L E within 4 W m Ϫ2 , and cumulative sublimation within 3 mm of that measured by the EC system. Differences between EC-measured and simulated fluxes occurred primarily at night. The reduction of the surface layer specification in the model from 25 to 10 cm reduced flux differences between EC-measured and modeled fluxes to 0 W m Ϫ2 for H, 2 W m Ϫ2 for L E, and 1 mm for sublimation. When only daytime fluxes were compared, differences were further reduced to 1 W m Ϫ2 for L E and Ͻ1 mm for sublimation. This experiment shows that in addition to traditional mass balance methods, ECmeasured fluxes can be used to diagnose the performance of a snow cover energy balance model. It also demonstrates the use of eddy covariance methods for measuring heat and mass fluxes from snow covers at a low-wind, below-canopy site.

Abstract:Sublimation is a critical component of the snow cover mass balance. Although sublimation can be directly measured using eddy covariance (EC), such measurements are relatively uncommon in complex mountainous environments. The EC measurements of surface snowpack sublimation from three consecutive winter seasons (2004, 2005 and 2006) at a wind-exposed and wind-sheltered site were analysed to characterise sublimation in mountainous terrain. During the 2006 snow season, snow surface and near-surface air temperature, humidity and wind were also measured, permitting the calculation of sublimation rates and a comparison with EC measurements. This comparison showed that measured and simulated sublimation was very similar at the exposed site but less so at the sheltered site. Wind speeds at the exposed site were nearly four times than that at the sheltered site, and the exposed site yielded measured sublimation that was two times the magnitude of that at the sheltered site. The time variation of measured sublimation showed diurnal increases in the early afternoon and increased rates overall as the snow season progressed. Measured mean daily sublimation rates were 0.39 and 0.15 mm day À1 at the exposed and sheltered sites, respectively. At the exposed site, measured sublimation accounted for 16% and 41% of the maximum snow accumulation in 2006 and 2005, respectively. At the sheltered site, measured seasonal sublimation was approximately 4% in 2004 and 2006 and 8% in 2005 of the maximum snow water equivalent. Simulated sublimation was only available for 2006 and suggested smaller but comparable percentages to the sublimation estimated from observations. At the exposed site, a total of 42 mm sublimated for the snow season, which constituted 12% of the maximum accumulation. At the sheltered site, 17 mm (2.2% of maximum accumulation) was sublimated over the snow season.

[1] Snow-covered complex terrain is an extremely important runoff-generating landscape in high-altitude and high-latitude environments, yet it is often considered nonviable for eddy covariance measurements of turbulent fluxes. Turbulent flux data are useful for evaluating the coupled snow cover mass and energy balance that control snow ablation and melt. In particular, detailed, multiseason analyses of eddy covariance data postprocessing requirements and resulting data quality for hydrological analyses in open and sheltered mountain sites have not been conducted. These analyses are needed since these landscapes typify those that generate snowmelt runoff in the mountain west of North America. Eddy covariance measurements taken from exposed hilltop and sheltered subcanopy snow research sites during three snow seasons underwent rigorous postprocessing and data quality assessments. Procedures included data filtering, air density corrections, sensor heating, axis rotation, and exclusion of nonstationary data. Data quality analysis showed that 77% of the sensible heat flux data and 95% of the latent heat flux data were of high quality. There was little interannual variability over three seasons in quality or improvements due to postprocessing results. A comparison of summary data based on a 30-min averaging period to postprocessed high-resolution flux data found that the postprocessed sensible heat fluxes were up to 14% less than the summary fluxes for the snow season. The results indicated that application of unattended eddy covariance techniques at these sites was viable, but the full suite of corrections and postprocessing are advisable to obtain flux observations of sufficient reliability for snow hydrology calculations.

Abstract. Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

[1] A modeling data set (meteorological forcing data, geographic information system data, and validation data) is presented for water years 1984 through 2008 for a snow-dominated mountain catchment. The forcing data include hourly precipitation, wind speed and direction, air and soil temperature, relative humidity, dew point temperature, and incoming solar and thermal radiation from two sites. Validation data include stream discharge, snow water equivalent, snow depth, soil moisture, and groundwater elevation. These data will improve the development, testing, and application of the next generation of hydrologic models. Marks, M. Seyfried, A. Winstral, M. Kumar, and G. Flerchinger (2011), A long-term data set for hydrologic modeling in a snow-dominated mountain catchment, Water Resour. Res., 47, W07702,

No abstract

Previous reviews have quantified factors affecting greenhouse gas (GHG) emissions from Asian rice ( L.) systems, but not from rice systems typical for the United States, which often vary considerably particularly in practices (i.e., water and carbon management) that affect emissions. Using meta-analytic and regression approaches, existing data from the United States were examined to quantify GHG emissions and major practices affecting emissions. Due to different production practices, major rice production regions were defined as the mid-South (Arkansas, Texas, Louisiana, Mississippi, and Missouri) and California, with emissions being evaluated separately. Average growing season CH emissions for the mid-South and California were 194 (95% confidence interval [CI] = 129-260) and 218 kg CH ha season (95% CI = 153-284), respectively. Growing season NO emissions were similar between regions (0.14 kg NO ha season). Ratoon cropping (allowing an additional harvestable crop to grow from stubble after the initial harvest), common along the Gulf Coast of the mid-South, had average CH emissions of 540 kg CH ha season (95% CI = 465-614). Water and residue management practices such as alternate wetting and drying, and stand establishment method (water vs. dry seeding), and the amount of residue from the previous crop had the largest effect on growing season CH emissions. However, soil texture, sulfate additions, and cultivar selection also affected growing season CH emissions. This analysis can be used for the development of tools to estimate and mitigate GHG emissions from US rice systems and other similarly mechanized systems in temperate regions.