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22 results for “Eddy covariance towers”
Eddy covariance 30-minute CO2 fluxes with accompanying biophysical variables from the GCE-LTER flux tower site from January 2014 to December 2017 for sensor Flux1
Eddy covariance (EC) CO2 fluxes from flux sensor set "Flux1" from January 2014 to December 2017 collected over a Spartina alterniflora marsh located on the western side of Sapelo Island bounded by the Duplin River and Barn Creek. EC fluxes were processed in EddyPro 7. Additional biophysical variables included are air temperature, relative humidity, vapor pressure deficit, and water table height from a nearby tidal creek and the marsh platform.
Eddy covariance 30-minute CO2 fluxes with accompanying biophysical variables from the GCE-LTER flux tower site from January 2014 to December 2022 for sensor Flux2
Eddy covariance (EC) CO2 fluxes from sensor set "Flux2" from January 2014 to December 2022 collected over a Spartina alterniflora marsh located on the western side of Sapelo Island bounded by the Duplin River and Barn Creek. EC fluxes were processed in EddyPro 7. Additional biophysical variables included are air temperature, relative humidity, vapor pressure deficit, and water table height from a nearby tidal creek and the marsh platform.
North Temperate Lakes LTER Processed eddy covariance time series fluxes from tower located on roof of the CFL building oriented toward Lake Mendota 2012 - current
We calculated eddy covariance based fluxes of CO2, H2O, heat, and momentum to study lake-atmosphere exchanges since 2012. These data were collected by Ankur Desai from 2012 to present using a CSAT-3 sonic anemometer and LI-7500 gas analyzer located on the roof of the CFL building. A footprint model (Kljun) was used to screen for lake only data.
Eddy covariance 30-minute CO2 fluxes with accompanying biophysical variables from the Grand Bay, Mississippi flux tower site from March 2018 to January 2019
Eddy covariance (EC) CO2 fluxes from March 2018 to January 2019 collected over a Juncus roemerianus marsh located in the Grand Bay National Estuarine Research Reserve (NERR) in Mississippi. EC fluxes were processed in EddyPro 7. Additional biophysical variables included are air temperature, relative humidity, vapor pressure deficit, soil temperature, and water table height within the marsh.
Eddy covariance 30-minute CO2 fluxes with accompanying biophysical variables from the GCE-LTER flux tower site from December 2018 to January 2020
Eddy covariance (EC) CO2 fluxes from December 2018 to January 2020 collected over a Spartina alterniflora marsh located on the western side of Sapelo Island bounded by the Duplin River and Barn Creek. EC fluxes were processed in EddyPro 7. Additional biophysical variables included are air temperature, relative humidity, vapor pressure deficit, soil temperature, and water table height from a nearby tidal creek.
Long-term Atmospheric, Soil and Water Sensor Data from the GCE-LTER Eddy Covariance Flux Tower on Sapelo Island, Georgia
Long-term measurements of various atmospheric, soil and water properties were made using electronic sensors attached to the GCE-LTER eddy covariance flux tower deployed in a Spartina alterniflora salt marsh on Sapelo Island, Georgia. Variables measured include air and water temperature, relative humidity, precipitation, wind speed and direction, soil temperature, water pressure and solar radiation components (i.e. incident and reflected photosynthetically available, total, long-wave and shortwave radiation). Measurements were logged at 5 minute intervals using multiple Campbell Scientific Instruments CR3000 data loggers, and then combined into a single monotonic time series data set. Quality control analyses were performed to remove values deemed invalid due to sensor failure or miscalibration and to assign Q/C qualifiers to values outside expected ranges or failing various sanity and quality checks of the data. Note that some measurements were spatially replicated with multiple sensors deployed in different micro-habitats (e.g. at the tower and in a nearby marsh platform or creek). Sensors were also added to the tower at various times after the initial installation, therefore some variables do not span the entire period of record. Measurements at this site are ongoing, and the data set will be updated annually to include additional observations.
Long-term Meteorological Data from the GCE-LTER Eddy Covariance Flux Tower on Sapelo Island, Georgia
Long-term measurements of key meteorological variables were made using electronic sensors attached to the GCE-LTER eddy covariance flux tower deployed in a Spartina alterniflora salt marsh on Sapelo Island, Georgia. Variables measured include air temperature, relative humidity, precipitation, wind speed, wind direction, photosynthetically-available and total solar radiation. Measurements were logged at 5 minute intervals using a Campbell Scientific Instruments CR3000 data logger then re-scaled to 15 minute and daily interval data sets. Quality control analyses were performed to remove values deemed invalid due to sensor failure or miscalibration, and to assign Q/C qualifiers to values outside expected ranges or failing various sanity and quality checks of the data. Measurements began in 2013; however, the total solar pyranometer was not installed until 2018 and minimum and maximum 5 minute air temperature were not added until 2019 so not all variables span the complete period of record. Measurements are continuing at this site and this data set will be updated annually to include additional observations.
GOES-R Land Surface Products at AmeriFlux and NEON Eddy Covariance Tower Locations
The terrestrial carbon cycle varies dynamically over short periods that can be difficult to observe. Geostationary (“weather”) satellites like the Geostationary Operational Environmental Satellite - R Series (GOES-R) deliver near-hemispheric imagery at a ten-minute cadence, and its Advanced Baseline Imager (ABI) measures visible and near-infrared spectral bands that can be used to estimate land surface properties and carbon dioxide flux. GOES-R data are designed for real-time dissemination and are difficult to link with eddy covariance time series of land-atmosphere carbon dioxide exchange. We compiled three-year time series of GOES-R land surface attributes including visible and near-infrared reflectances, land surface temperature, and downwelling shortwave radiation (DSR) at 318 ABI fixed grid pixels containing eddy covariance towers for years 2020-2022. We demonstrate how to best combine satellite and in-situ datasets, and show how ABI attributes useful for carbon cycle science vary across space and time. By connecting observation networks that infer rapid changes to the carbon cycle, we can gain a richer understanding of the processes that control it.
Inventory of Eddy Covariance Tower Data in AmeriFlux from Everglades Towers, Florida: 2004-ongoing
There are six eddy covariance towers that make continuous measurements of regional hydrology and carbon balance in the region. This long-term eddy covariance tower network includes 2008-ongoing data collection in a freshwater marl prairie (TS/Ph-1; US-Esm) and a freshwater marsh (SRS-2; US-Elm), 2016-ongoing data collection from a mangrove scrub (TS/Ph-7; US-TaS), 2004-ongoing data collection from a tall mangrove forest (SRS-6; US-Skr), 2020-ongoing data collection from a tower at the ecotone of marl prairie and mangrove scrub (SE1; US-EvM), and 2018-ongoing data collection from an aquatic Tower in Florida Bay (Bob Allen Key; US-FBE). Everglades ecosystems occur in predictable zonal patterns, and current Florida Coastal Everglades Long Term Ecological Research (FCE-LTER) sites are arranged to capture the variation in hydrology, community composition, and productivity. The hydrology and disturbance regime in the Everglades region developed a rich diversity of communities that have variable capacities to capture and sequester carbon. At each site, open-path infrared gas analyzers (IRGA, LI-7500 and Li-7700, Li-COR Inc., Lincoln, NE) are used to measure CO2 (mg mol-1), water vapor molar density (mg mol-1), and CH4. A paired sonic anemometer (CSAT3, Campbell Scientific Inc., Logan, UT) is employed to measure sonic temperature (Ts; K) and 3-dimensional wind speed (u, v and w, respectively; m s-1). Additional meteorological data is measured at the site to monitor conditions. This data package is an inventory of eddy covariance tower data and metadata available through the AmeriFlux repository.
AusEFlux: Empirical upscaling of OzFlux eddy covariance flux tower data over Australia
<p>AusEFlux (<strong>Aus</strong>tralian <strong>E</strong>mpirical <strong>Flux</strong>es) is a high resolution (500 metre) gridded estimate of Gross Primary Productivity (GPP), Ecosystem Respiration (ER), Net Ecosystem Exchange (NEE), and Evapotranspiration over the Australian continent for the period January 2003 to Present. These datasets provide a benchmark for assessment against Land Surface Model simulations, and a means for monitoring of Australia’s terrestrial carbon cycle at an unprecedented high-resolution.</p> <p><strong>Version 2.1 </strong>of AusEFlux has just been released (as of May 2025) and was created to <strong>operationalise</strong> the research datasets published in this <a href="https://doi.org/10.5194/bg-20-4109-2023">EGU Biogeosciences publication.</a> In order to operationalise these datasets, changes to the input datasets were required to align the data sources with datasets that are regularly and reliably updated, along with general improvements. The datasets provided on Zenodo have been reprojected to 5 km resolution to facilitate easier uploading and sharing, but<strong> full resolution datasets (both v1.1 and v2.1) can be accessed freely through <a href="https://thredds.nci.org.au/thredds/catalog/ub8/au/AusEFlux/catalog.html">NCI's THREDDS portal.</a></strong></p> <p><strong>Two Jupyter Notebooks</strong> have been created (one for GPP and one for NEE) that demonstrate the differences between the research datasets (v1.1) and the operational datasets (v2.1), including showing the differences in specifications and inputs. You can view/download these notebooks using the links below:</p> <p><a href="https://nbviewer.org/github/cbur24/AusEFlux/blob/master/notebooks/analysis/Compare_AusEFlux_versions_GPP.ipynb">GPP comparison between versions</a></p> <p><a href="https://nbviewer.org/github/cbur24/AusEFlux/blob/master/notebooks/analysis/Compare_AusEFlux_versions_NEE.ipynb">NEE comparisons between versions</a></p> <p>Each dataset contains three variables:</p> <ul> <li>"<flux>_median": represents the 'best-estimate' of a given flux, the units are gC/m<sup><sub>2</sub></sup>/mon<sup>-1</sup></li> <li>"<flux>_25th_percentile": represents the lower uncertainty bound, the units are gC/m<sup><sub>2</sub></sup>/mon<sup>-1</sup></li> <li>"<flux>_75th_percentile": represents the upper uncertainty bound, the units are gC/m<sup><sub>2</sub></sup>/mon<sup>-1</sup></li> </ul> <p><span><strong>Version Guide</strong>:</span></p> <p><em>v1.0:</em> DO NOT USE THIS VERSION. There was a mistake in the modelling of ecosystem respiration, so this version of the dataset should not be used. As of version 1.1, the error has been rectified.</p> <p><em>v1.1: </em>This version of the datasets are those used to inform the EGU Publication linked above. Its time range is 2003-July 2022, and its spatial resolution is 5 km on Zenodo, but the 1 km resolution datasets can be accessed through <a href="https://thredds.nci.org.au/thredds/catalog/ub8/au/AusEFlux/catalog.html">NCI's THREDDS portal</a>.</p> <p><em>v2.0: <strong>IMPORTANT NOTE:</strong> a bug in the modelling of vegetation height resulted in data artefacts in the NEE and ER fluxes over very tall mesic forests in this version. This resulted in unnaturally high ER and lower than expected NEE (less negative than would be expected). This issue has been rectified in version 2.1.</em> <strong>Version 2 datasets represent the operational version of the datasets</strong>, it includes several improvements over version 1.1. Its time-range is 2003-2024 (and will be updated annually), and its spatial resolution is 500m. A 5 km reprojected version of the dataset is included here on Zenodo, but the 500 metre datasets can be accessed through<a href="https://thredds.nci.org.au/thredds/catalog/ub8/au/AusEFlux/catalog.html"> NCI's THREDDS portal.</a></p> <p><strong>v2.1: </strong>This version is a patch to version 2.0 to remove a bug in the modelling of vegetation height. <strong>It is recommended to use this version </strong>over v2.0. 500 metre resolution datasets can be accessed through<a href="https://thredds.nci.org.au/thredds/catalog/ub8/au/AusEFlux/catalog.html"> NCI's THREDDS portal.</a></p>
CO2 Flux partioning in a Eddy Covariance tower of marsh ecosystem (Fuente Duque) in Doñana Biological Reserve
<p>This dataset consists of the estimated data of the CO2 flux partition: assimilation or gross primary production (GPP) and heterotrophic or ecosystem respiration (Reco), as well as the standard deviation of each estimate. These data have been estimated from the data provided by the ICTS of the Doñana Biological Reserve of the eddy covariance tower located in Fuente Duque, in the Hinojos marsh in the period between October 2020 and December 2022.</p>
Mass and energy fluxes from the US-Jo2 AmeriFlux eddy covariance tower in Tromble Weir experimental watershed at the Jornada Basin LTER site, 2010-ongoing
This data package contains metadata for, and links to, 30-minute mass and energy flux data collected at an eddy covariance tower in the Tromble Weir Watershed area of the Jornada Basin in southern New Mexico, USA. These data are used to quantify the water and energy balances in a small experimental watershed, including observational studies to calculate groundwater recharge as a water balance residual, to build relations between soil moisture state and ET flux, and to quantify land-atmosphere interactions and improve our understanding of the eddy covariance method. Additionally, they have been used in modeling studies as a validation of model performance. The .csv files included in this package list and describe the data entities and variables present in data files archived at the AmeriFlux data repository (site US-Jo2; http://ameriflux.lbl.gov/sites/siteinfo/US-Jo2). The data at AmeriFlux include the 30-minute mass and energy fluxes calculated from 20 Hz data collected at the Tromble Weir Watershed tower. Instrument descriptions and detailed procedures are found in the references listed in the Methods section of this EDI package. This is an ongoing dataset that will be updated annually.
An Excel spreadsheet including eddy covariance, meteorological, and tidal data measured at Yunxiao mangrove flux tower.
<p>An Excel spreadsheet including eddy covariance, meteorological, and tidal data at Yunxiao mangrove flux tower required to reproduce key findings in Figures 4-9 in the main text (each figure corresponds to a single sheet). Contact Xudong Zhu at Xiamen University (xdzhu@xmu.edu.cn) if you have any question.</p>
Data and code for: Combining eddy covariance towers, field measurements, and the MEMS 2 ecosystem model improves confidence in the climate impacts of bioenergy with carbon capture and storage
Open the record for dataset details and reuse information.
A dataset including 2-year eddy covariance and hyperspectral data at Yunxiao mangrove flux tower
<p>A dataset including 2-year eddy covariance and hyperspectral data at Yunxiao mangrove flux tower. The data is used for producing key findings in a manuscript under review.</p>
Eddy covariance SAFE Flux Tower
<p><strong>Description: </strong></p> <p>The eddy covariance technique was used to record continuous, non-invasive measurements of CO2, H2O and energy exchange between the ecosystem and the atmosphere. The measuring system consists of a semi-open path infrared gas analyser LI-7200 (LI-COR, USA), and a CSAT3 Sonic Anemometer (Campbell Scientific, USA) at a measuring height of 52 m over a canopy height of ~25 m. Data were recorded at a frequency of 20 Hz that was treated using the post-processing software EddyPro® (v.7.0.6; www.licor.com/eddypro) to compute fluxes for each 30-minute averaging period. To treat the raw fluxes, primary data processing steps were applied, including spike removal (Vickers, 1997 J Atmos Ocean Technol), coordinate rotation, block averaging detrending of CO2, H2O and sonic temperature, time lag compensation using covariance maximisation detection method, random uncertainty estimation (Finkelstein et al. 2001 Journal of Geophysical Research Atmospheres), computation of turbulent fluxes and mean fluxes, spectral corrections (Moncrieff et al. 1997 J Hydrol Amst) using correction of low-pass filtering effects, planar fit rotation (Wilczak et al. 2001 Boundary Layer Meteorol) and quality flagging policy (Göckede et al. 2006 Boundary Layer Meteorol). Eddy covariance meteorological data from above and below canopy is available at DOI 10.5281/zenodo.3888374. Cells with -9999 represent not enough data collected, which can be regarded as NA.<br> <br> This data has been collected over a heavily logged landscape between 2012 - 2018, please note 2016 was removed from this dataset. Before 2015, the landscape was ~10 years recovering from it's previous round of logging (four times logged). During 2015 the landscape was salvaged logged, removing 75% of tree stand basal area.<br> <br> The first data sheet, named "Raw_data" contains all raw fluxes that have been treated by EddyPro, which have not been filtered or quality controlled.<br> <br> The second sheet, named "Daily_fluxes" contains daily mean fluxes of net ecosystem CO2 exchange (NEE), ecosystem respirationn (Reco) and gross primary productivity and their associated standard errors. Net ecosystem CO2 exchange (NEE) was calculated by adding the estimated CO2 storage flux to the observed CO2 flux. Data was subjecto quality control including the removal of quality flags 4 and 5 (Göckede et al. 2006 Boundary Layer Meteorol) and the application of a mean u* threshold of >0.29 m s-1 to the dataset, as established using the package "REddyProc" (v.1.2; (Wultzer et al. 2019 Biogeosciences)) in based on the Moving Point Method (Reichstein et al. 2005, GCB). Data was subsequently gap filled and partitioned, as descripted within the variable methods of this sheet. This data was part of an analysis of carbon fluxes within three periods of data collection: in 2012 – 2013, which captured the four-times logged ecosystem ~10 years after its previous round of logging, in 2015 during a new round of active salvage logging, and in 2017 – 2018 when the ecosystem was recovery 2-3 years after the salvage logging. Days with large standard errors for Reco (> ± 5 µmol m−2 s−1) were deemed as bad quality and removed from the dataset and we used only days that had four or more observed half-hourly values of NEE. Of the final dataset , 29.5% of the half-hourly values are original observed fluxes, and 70.5% gap-filled. Of the 455 days remaining after all filtering processes were applied, 65 days were during the 10-years recovery phase (2012-2013), 100 during the active salvage logging (2015) and 290 during the 2-3 years recovery from active salvage logging phase (2017-2018).</p> <p><strong>Project: </strong>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/113"><strong>Changing carbon dioxide and water budgets from deforestation and habitat modification</strong></a></p> <p><strong>XML metadata: </strong>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=7307447">here</a></p> <p><strong>Files: </strong>This consists of 1 file: SAFE_EC_byYear.xlsx</p> <p><strong>SAFE_EC_byYear.xlsx</strong></p> <p>This file contains dataset metadata and 6 data tables:</p> <ol> <li> <p><strong>Raw_data_2012_2013</strong> (described in worksheet Raw_data_2012_2013)</p> <p>Description: EddyPro output of eddy covariance data collected at 52m at the top of the flux tower.</p> <p>Number of fields: 105</p> <p>Number of data rows: 24213</p> <p>Fields:</p> <ul> <li><strong>Location</strong>: SAFE flux tower location name, as in the SAFE Gazetteer (Field type: location)</li> <li><strong>date</strong>: Date of the end of the averaging period (Field type: date)</li> <li><strong>time</strong>: Time of the end of the averaging period (Field type: time)</li> <li><strong>DOY</strong>: decimal day of year (Field type: numeric)</li> <li><strong>daytime</strong>: Daytime or nightime, 1 = daytime, 0 = nighttime (Field type: numeric)</li> <li><strong>file_records</strong>: Number of valid records found in the raw file (or set of raw files) (Field type: numeric)</li> <li><strong>used_records</strong>: Number of valid records used for current the averaging period (Field type: numeric)</li> <li><strong>Tau</strong>: Corrected momentum flux (Field type: numeric)</li> <li><strong>qc_Tau</strong>: Quality flag for momentum flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_Tau</strong>: Random error for momentum flux, if selected (Field type: numeric)</li> <li><strong>H</strong>: Corrected sensible heat flux (Field type: numeric)</li> <li><strong>qc_H</strong>: Quality flag for sensible heat flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_H</strong>: Random error for momentum flux, if selected (Field type: numeric)</li> <li><strong>LE</strong>: Corrected latent heat flux (Field type: numeric)</li> <li><strong>qc_LE</strong>: Quality flag of latent heat flux based on Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_LE</strong>: Random error for latent heat flux, if selected (Field type: numeric)</li> <li><strong>co2_flux</strong>: CO2 flux (Field type: numeric)</li> <li><strong>qc_co2_flux</strong>: Quality flag for CO2 flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_co2_flux</strong>: Random error of CO2 flux (Field type: numeric)</li> <li><strong>h2o_flux</strong>: H2O flux (Field type: numeric)</li> <li><strong>qc_h2o_flux</strong>: Quality flag of H20 flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_h2o_flux</strong>: Random error of CO2 flux (Field type: numeric)</li> <li><strong>H_strg</strong>: Estimate of storage sensible heat flux (Field type: numeric)</li> <li><strong>LE_strg</strong>: Estimate of storage latent heat flux (Field type: numeric)</li> <li><strong>co2_strg</strong>: Estimate of storage CO2 flux (Field type: numeric)</li> <li><strong>h2o_strg</strong>: Estimate of storage H20 flux (Field type: numeric)</li> <li><strong>co2_v.adv</strong>: Estimate of vertical advection flux of CO2 (Field type: numeric)</li> <li><strong>h2o_v.adv</strong>: Estimate of vertical advection flux of H20 (Field type: numeric)</li> <li><strong>co2_molar_density</strong>: Measured or estimated molar density of gas (Field type: numeric)</li> <li><strong>co2_mole_fraction</strong>: Measured or estimated mole fraction of gas (Field type: numeric)</li> <li><strong>co2_mixing_ratio</strong>: Measured or estimated mixing ratio of gas (Field type: numeric)</li> <li><strong>co2_time_lag</strong>: Time lag used to synchronize gas time series (Field type: numeric)</li> <li><strong>co2_def_timelag</strong>: Flag: whether the reported time lag is the default (1) or calculated (0) (Field type: numeric)</li> <li><strong>h2o_molar_density</strong>: Measured or estimated molar density of gas (Field type: numeric)</li> <li><strong>h2o_mole_fraction</strong>: Measured or estimated mole fraction of gas (Field type: numeric)</li> <li><strong>h2o_mixing_ratio</strong>: Measured or estimated mixing ratio of gas (Field type: numeric)</li> <li><strong>h2o_time_lag</strong>: Time lag used to synchronize gas time series (Field type: numeric)</li> <li><strong>h2o_def_timelag</strong>: Flag: whether the reported time lag is the default (1) or calculated (0) (Field type: numeric)</li> <li><strong>sonic_temperature</strong>: Mean temperature of ambient air as measured by the anemometer (Field type: numeric)</li> <li><strong>air_temperature</strong>: Mean temperature of ambient air, either calculated from high frequency air temperature readings, or estimated from sonic temperature (Field type: numeric)</li> <li><strong>air_pressure</strong>: Mean pressure of ambient air, either calculated from high frequency air pressure readings, or estimated based on site altitude (barometric pressure) (Field type: numeric)</li> <li><strong>air_density</strong>: Density of ambient air (Field type: numeric)</li> <li><strong>air_heat_capacity</strong>: Specific heat at constant pressure of ambient air (Field type: numeric)</li> <li><strong>air_molar_volume</strong>: Molar volume of ambient air (Field type: numeric)</li> <li><strong>ET</strong>: Evapotranspiration flux (Field type: numeric)</li> <li><strong>water_vapor_density</strong>: Ambient mass density of water vapor (Field type: numeric)</li> <li><strong>e</strong>: Ambient water vapor partial pressure (Field type: numeric)</li> <li><strong>es</strong>: Ambient water vapor partial pressure at saturation (Field type: numeric)</li> <li><strong>specific_humidity</strong>: Ambient specific humidity on a mass basis (Field type: numeric)</li> <li><strong>RH</strong>: Ambient relative humidity (Field type: numeric)</li> <li><strong>VPD</strong>: Ambient water vapor pressure deficit (Field type: numeric)</li> <li><strong>Tdew</strong>: Ambient dew point temperature (Field type: numeric)</li> <li><strong>u_unrot</strong>: Wind component along the u anemometer axis (Field type: numeric)</li> <li><strong>v_unrot</strong>: Wind component along the v anemometer axis (Field type: numeric)</li> <li><strong>w_unrot</strong>: Wind component along the w anemometer axis (Field type: numeric)</li> <li><strong>u_rot</strong>: Rotated u wind component (mean wind speed) (Field type: numeric)</li> <li><strong>v_rot</strong>: Rotated v wind component (should be zero) (Field type: numeric)</li> <li><strong>w_rot</strong>: Rotated w wind component (should be zero) (Field type: numeric)</li> <li><strong>wind_speed</strong>: Mean wind speed (Field type: numeric)</li> <li><strong>max_wind_speed</strong>: Maximum instantaneous wind speed (Field type: numeric)</li> <li><strong>wind_dir</strong>: Direction from which the wind blows, with respect to Geographic or Magnetic north (Field type: numeric)</li> <li><strong>yaw</strong>: First rotation angle (Field type: numeric)</li> <li><strong>pitch</strong>: Second rotation angle (Field type: numeric)</li> <li><strong>u.</strong>: Friction velocity (Field type: numeric)</li> <li><strong>TKE</strong>: Turbulent kinetic energy (Field type: numeric)</li> <li><strong>L</strong>: Monin-Obukhov length (Field type: numeric)</li> <li><strong>X.z.d..L</strong>: Monin-Obukhov stability parameter - (z-d)/L (Field type: numeric)</li> <li><strong>bowen_ratio</strong>: Sensible heat flux to latent heat flux ratio (Field type: numeric)</li> <li><strong>T.</strong>: Scaling temperature (Field type: numeric)</li> <li><strong>model</strong>: Model for footprint estimation, 1- Kljun et al. (2004): A crosswind integrated parameterization of footprint estimations obtained with a 3D Lagrangian model by means of a scaling procedure.2 - Kormann and Meixner (2001): A crosswind integrated model based on the solution of the two dimensional advection-diffusion equation given by van Ulden (1978) and others for power-law profiles in wind velocity and eddy diffusivity, 3 - Hsieh et al. (2000): A crosswind integrated model based on the former model of Gash (1986) and on simulations with a Lagrangian stochastic model. (Field type: numeric)</li> <li><strong>x_peak</strong>: Along-wind distance providing <1% contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_offset</strong>: Along-wind distance providing the highest (peak) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_10.</strong>: Along-wind distance providing 10% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_30.</strong>: Along-wind distance providing 30% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_50.</strong>: Along-wind distance providing 50% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_70.</strong>: Along-wind distance providing 70% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_90.</strong>: Along-wind distance providing 90% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>un_Tau</strong>: Uncorrected momentum flux (Field type: numeric)</li> <li><strong>Tau_scf</strong>: Spectral correction factor for momentum flux (Field type: numeric)</li> <li><strong>un_H</strong>: Uncorrected sensible heat flux (Field type: numeric)</li> <li><strong>H_scf</strong>: Spectral correction factor for sensible heat flux (Field type: numeric)</li> <li><strong>un_LE</strong>: Uncorrected latent heat flux (Field type: numeric)</li> <li><strong>LE_scf</strong>: Spectral correction factor for latent heat flux (Field type: numeric)</li> <li><strong>un_co2_flux</strong>: Uncorrected gas flux (Field type: numeric)</li> <li><strong>co2_scf</strong>: Spectral correction factor for gas flux (Field type: numeric)</li> <li><strong>un_h2o_flux</strong>: Uncorrected gas flux (Field type: numeric)</li> <li><strong>h2o_scf</strong>: Spectral correction factor for gas flux (Field type: numeric)</li> <li><strong>spikes_hf</strong>: Hard flags for individual variables for spike test (Field type: numeric)</li> <li><strong>amplitude_resolution_hf</strong>: Hard flags for individual variables for amplitude resolution (Field type: numeric)</li> <li><strong>drop_out_hf</strong>: Hard flags for individual variables for drop-out test (Field type: numeric)</li> <li><strong>absolute_limits_hf</strong>: Hard flags for individual variables for absolute limits (Field type: numeric)</li> <li><strong>skewness_kurtosis_hf</strong>: Hard flags for individual variables for skewness and kurtosis (Field type: numeric)</li> <li><strong>skewness_kurtosis_sf</strong>: Soft flags for individual variables for skewness and kurtosis test (Field type: numeric)</li> <li><strong>discontinuities_hf</strong>: Hard flags for individual variables for discontinuities test (Field type: numeric)</li> <li><strong>discontinuities_sf</strong>: Soft flags for individual variables for discontinuities test (Field type: numeric)</li> <li><strong>timelag_hf</strong>: Hard flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>timelag_sf</strong>: Soft flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>attack_angle_hf</strong>: Hard flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>non_steady_wind_hf</strong>: Soft flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>u_spikes</strong>: Number of spikes detected and eliminated for rotated u wind component (Field type: numeric)</li> <li><strong>v_spikes</strong>: Number of spikes detected and eliminated forrotated v wind component (Field type: numeric)</li> <li><strong>w_spikes</strong>: Number of spikes detected and eliminated for rotated w wind component (Field type: numeric)</li> <li><strong>ts_spikes</strong>: Number of spikes detected and eliminated for ts variable (Field type: numeric)</li> <li><strong>co2_spikes</strong>: Number of spikes detected and eliminated for co2 variable (Field type: numeric)</li> <li><strong>h2o_spikes</strong>: Number of spikes detected and eliminated for h2o variable (Field type: numeric)</li> </ul> </li> <li> <p><strong>Raw_data_2014</strong> (described in worksheet Raw_data_2014)</p> <p>Description: EddyPro output of eddy covariance data collected at 52m at the top of the flux tower. There is a significant data gap, with some intermittent records available during the daytime, between 17/2/2014-17/06/2014 due to the problems in the power supply.</p> <p>Number of fields: 105</p> <p>Number of data rows: 17520</p> <p>Fields:</p> <ul> <li><strong>Location</strong>: SAFE flux tower location name, as in the SAFE Gazetteer (Field type: location)</li> <li><strong>date</strong>: Date of the end of the averaging period (Field type: date)</li> <li><strong>time</strong>: Time of the end of the averaging period (Field type: time)</li> <li><strong>DOY</strong>: decimal day of year (Field type: numeric)</li> <li><strong>daytime</strong>: Daytime or nightime, 1 = daytime, 0 = nighttime (Field type: numeric)</li> <li><strong>file_records</strong>: Number of valid records found in the raw file (or set of raw files) (Field type: numeric)</li> <li><strong>used_records</strong>: Number of valid records used for current the averaging period (Field type: numeric)</li> <li><strong>Tau</strong>: Corrected momentum flux (Field type: numeric)</li> <li><strong>qc_Tau</strong>: Quality flag for momentum flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_Tau</strong>: Random error for momentum flux, if selected (Field type: numeric)</li> <li><strong>H</strong>: Corrected sensible heat flux (Field type: numeric)</li> <li><strong>qc_H</strong>: Quality flag for sensible heat flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_H</strong>: Random error for momentum flux, if selected (Field type: numeric)</li> <li><strong>LE</strong>: Corrected latent heat flux (Field type: numeric)</li> <li><strong>qc_LE</strong>: Quality flag of latent heat flux based on Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_LE</strong>: Random error for latent heat flux, if selected (Field type: numeric)</li> <li><strong>co2_flux</strong>: CO2 flux (Field type: numeric)</li> <li><strong>qc_co2_flux</strong>: Quality flag for CO2 flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_co2_flux</strong>: Random error of CO2 flux (Field type: numeric)</li> <li><strong>h2o_flux</strong>: H2O flux (Field type: numeric)</li> <li><strong>qc_h2o_flux</strong>: Quality flag of H20 flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_h2o_flux</strong>: Random error of CO2 flux (Field type: numeric)</li> <li><strong>H_strg</strong>: Estimate of storage sensible heat flux (Field type: numeric)</li> <li><strong>LE_strg</strong>: Estimate of storage latent heat flux (Field type: numeric)</li> <li><strong>co2_strg</strong>: Estimate of storage CO2 flux (Field type: numeric)</li> <li><strong>h2o_strg</strong>: Estimate of storage H20 flux (Field type: numeric)</li> <li><strong>co2_v.adv</strong>: Estimate of vertical advection flux of CO2 (Field type: numeric)</li> <li><strong>h2o_v.adv</strong>: Estimate of vertical advection flux of H20 (Field type: numeric)</li> <li><strong>co2_molar_density</strong>: Measured or estimated molar density of gas (Field type: numeric)</li> <li><strong>co2_mole_fraction</strong>: Measured or estimated mole fraction of gas (Field type: numeric)</li> <li><strong>co2_mixing_ratio</strong>: Measured or estimated mixing ratio of gas (Field type: numeric)</li> <li><strong>co2_time_lag</strong>: Time lag used to synchronize gas time series (Field type: numeric)</li> <li><strong>co2_def_timelag</strong>: Flag: whether the reported time lag is the default (1) or calculated (0) (Field type: numeric)</li> <li><strong>h2o_molar_density</strong>: Measured or estimated molar density of gas (Field type: numeric)</li> <li><strong>h2o_mole_fraction</strong>: Measured or estimated mole fraction of gas (Field type: numeric)</li> <li><strong>h2o_mixing_ratio</strong>: Measured or estimated mixing ratio of gas (Field type: numeric)</li> <li><strong>h2o_time_lag</strong>: Time lag used to synchronize gas time series (Field type: numeric)</li> <li><strong>h2o_def_timelag</strong>: Flag: whether the reported time lag is the default (1) or calculated (0) (Field type: numeric)</li> <li><strong>sonic_temperature</strong>: Mean temperature of ambient air as measured by the anemometer (Field type: numeric)</li> <li><strong>air_temperature</strong>: Mean temperature of ambient air, either calculated from high frequency air temperature readings, or estimated from sonic temperature (Field type: numeric)</li> <li><strong>air_pressure</strong>: Mean pressure of ambient air, either calculated from high frequency air pressure readings, or estimated based on site altitude (barometric pressure) (Field type: numeric)</li> <li><strong>air_density</strong>: Density of ambient air (Field type: numeric)</li> <li><strong>air_heat_capacity</strong>: Specific heat at constant pressure of ambient air (Field type: numeric)</li> <li><strong>air_molar_volume</strong>: Molar volume of ambient air (Field type: numeric)</li> <li><strong>ET</strong>: Evapotranspiration flux (Field type: numeric)</li> <li><strong>water_vapor_density</strong>: Ambient mass density of water vapor (Field type: numeric)</li> <li><strong>e</strong>: Ambient water vapor partial pressure (Field type: numeric)</li> <li><strong>es</strong>: Ambient water vapor partial pressure at saturation (Field type: numeric)</li> <li><strong>specific_humidity</strong>: Ambient specific humidity on a mass basis (Field type: numeric)</li> <li><strong>RH</strong>: Ambient relative humidity (Field type: numeric)</li> <li><strong>VPD</strong>: Ambient water vapor pressure deficit (Field type: numeric)</li> <li><strong>Tdew</strong>: Ambient dew point temperature (Field type: numeric)</li> <li><strong>u_unrot</strong>: Wind component along the u anemometer axis (Field type: numeric)</li> <li><strong>v_unrot</strong>: Wind component along the v anemometer axis (Field type: numeric)</li> <li><strong>w_unrot</strong>: Wind component along the w anemometer axis (Field type: numeric)</li> <li><strong>u_rot</strong>: Rotated u wind component (mean wind speed) (Field type: numeric)</li> <li><strong>v_rot</strong>: Rotated v wind component (should be zero) (Field type: numeric)</li> <li><strong>w_rot</strong>: Rotated w wind component (should be zero) (Field type: numeric)</li> <li><strong>wind_speed</strong>: Mean wind speed (Field type: numeric)</li> <li><strong>max_wind_speed</strong>: Maximum instantaneous wind speed (Field type: numeric)</li> <li><strong>wind_dir</strong>: Direction from which the wind blows, with respect to Geographic or Magnetic north (Field type: numeric)</li> <li><strong>yaw</strong>: First rotation angle (Field type: numeric)</li> <li><strong>pitch</strong>: Second rotation angle (Field type: numeric)</li> <li><strong>u.</strong>: Friction velocity (Field type: numeric)</li> <li><strong>TKE</strong>: Turbulent kinetic energy (Field type: numeric)</li> <li><strong>L</strong>: Monin-Obukhov length (Field type: numeric)</li> <li><strong>X.z.d..L</strong>: Monin-Obukhov stability parameter - (z-d)/L (Field type: numeric)</li> <li><strong>bowen_ratio</strong>: Sensible heat flux to latent heat flux ratio (Field type: numeric)</li> <li><strong>T.</strong>: Scaling temperature (Field type: numeric)</li> <li><strong>model</strong>: Model for footprint estimation, 1- Kljun et al. (2004): A crosswind integrated parameterization of footprint estimations obtained with a 3D Lagrangian model by means of a scaling procedure.2 - Kormann and Meixner (2001): A crosswind integrated model based on the solution of the two dimensional advection-diffusion equation given by van Ulden (1978) and others for power-law profiles in wind velocity and eddy diffusivity, 3 - Hsieh et al. (2000): A crosswind integrated model based on the former model of Gash (1986) and on simulations with a Lagrangian stochastic model. (Field type: numeric)</li> <li><strong>x_peak</strong>: Along-wind distance providing <1% contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_offset</strong>: Along-wind distance providing the highest (peak) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_10.</strong>: Along-wind distance providing 10% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_30.</strong>: Along-wind distance providing 30% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_50.</strong>: Along-wind distance providing 50% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_70.</strong>: Along-wind distance providing 70% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_90.</strong>: Along-wind distance providing 90% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>un_Tau</strong>: Uncorrected momentum flux (Field type: numeric)</li> <li><strong>Tau_scf</strong>: Spectral correction factor for momentum flux (Field type: numeric)</li> <li><strong>un_H</strong>: Uncorrected sensible heat flux (Field type: numeric)</li> <li><strong>H_scf</strong>: Spectral correction factor for sensible heat flux (Field type: numeric)</li> <li><strong>un_LE</strong>: Uncorrected latent heat flux (Field type: numeric)</li> <li><strong>LE_scf</strong>: Spectral correction factor for latent heat flux (Field type: numeric)</li> <li><strong>un_co2_flux</strong>: Uncorrected gas flux (Field type: numeric)</li> <li><strong>co2_scf</strong>: Spectral correction factor for gas flux (Field type: numeric)</li> <li><strong>un_h2o_flux</strong>: Uncorrected gas flux (Field type: numeric)</li> <li><strong>h2o_scf</strong>: Spectral correction factor for gas flux (Field type: numeric)</li> <li><strong>spikes_hf</strong>: Hard flags for individual variables for spike test (Field type: numeric)</li> <li><strong>amplitude_resolution_hf</strong>: Hard flags for individual variables for amplitude resolution (Field type: numeric)</li> <li><strong>drop_out_hf</strong>: Hard flags for individual variables for drop-out test (Field type: numeric)</li> <li><strong>absolute_limits_hf</strong>: Hard flags for individual variables for absolute limits (Field type: numeric)</li> <li><strong>skewness_kurtosis_hf</strong>: Hard flags for individual variables for skewness and kurtosis (Field type: numeric)</li> <li><strong>skewness_kurtosis_sf</strong>: Soft flags for individual variables for skewness and kurtosis test (Field type: numeric)</li> <li><strong>discontinuities_hf</strong>: Hard flags for individual variables for discontinuities test (Field type: numeric)</li> <li><strong>discontinuities_sf</strong>: Soft flags for individual variables for discontinuities test (Field type: numeric)</li> <li><strong>timelag_hf</strong>: Hard flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>timelag_sf</strong>: Soft flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>attack_angle_hf</strong>: Hard flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>non_steady_wind_hf</strong>: Soft flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>u_spikes</strong>: Number of spikes detected and eliminated for rotated u wind component (Field type: numeric)</li> <li><strong>v_spikes</strong>: Number of spikes detected and eliminated forrotated v wind component (Field type: numeric)</li> <li><strong>w_spikes</strong>: Number of spikes detected and eliminated for rotated w wind component (Field type: numeric)</li> <li><strong>ts_spikes</strong>: Number of spikes detected and eliminated for ts variable (Field type: numeric)</li> <li><strong>co2_spikes</strong>: Number of spikes detected and eliminated for co2 variable (Field type: numeric)</li> <li><strong>h2o_spikes</strong>: Number of spikes detected and eliminated for h2o variable (Field type: numeric)</li> </ul> </li> <li> <p><strong>Raw_data_2015</strong> (described in worksheet Raw_data_2015)</p> <p>Description: EddyPro output of eddy covariance data collected at 52m at the top of the flux tower.</p> <p>Number of fields: 105</p> <p>Number of data rows: 17520</p> <p>Fields:</p> <ul> <li><strong>Location</strong>: SAFE flux tower location name, as in the SAFE Gazetteer (Field type: location)</li> <li><strong>date</strong>: Date of the end of the averaging period (Field type: date)</li> <li><strong>time</strong>: Time of the end of the averaging period (Field type: time)</li> <li><strong>DOY</strong>: decimal day of year (Field type: numeric)</li> <li><strong>daytime</strong>: Daytime or nightime, 1 = daytime, 0 = nighttime (Field type: numeric)</li> <li><strong>file_records</strong>: Number of valid records found in the raw file (or set of raw files) (Field type: numeric)</li> <li><strong>used_records</strong>: Number of valid records used for current the averaging period (Field type: numeric)</li> <li><strong>Tau</strong>: Corrected momentum flux (Field type: numeric)</li> <li><strong>qc_Tau</strong>: Quality flag for momentum flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_Tau</strong>: Random error for momentum flux, if selected (Field type: numeric)</li> <li><strong>H</strong>: Corrected sensible heat flux (Field type: numeric)</li> <li><strong>qc_H</strong>: Quality flag for sensible heat flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_H</strong>: Random error for momentum flux, if selected (Field type: numeric)</li> <li><strong>LE</strong>: Corrected latent heat flux (Field type: numeric)</li> <li><strong>qc_LE</strong>: Quality flag of latent heat flux based on Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_LE</strong>: Random error for latent heat flux, if selected (Field type: numeric)</li> <li><strong>co2_flux</strong>: CO2 flux (Field type: numeric)</li> <li><strong>qc_co2_flux</strong>: Quality flag for CO2 flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_co2_flux</strong>: Random error of CO2 flux (Field type: numeric)</li> <li><strong>h2o_flux</strong>: H2O flux (Field type: numeric)</li> <li><strong>qc_h2o_flux</strong>: Quality flag of H20 flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_h2o_flux</strong>: Random error of CO2 flux (Field type: numeric)</li> <li><strong>H_strg</strong>: Estimate of storage sensible heat flux (Field type: numeric)</li> <li><strong>LE_strg</strong>: Estimate of storage latent heat flux (Field type: numeric)</li> <li><strong>co2_strg</strong>: Estimate of storage CO2 flux (Field type: numeric)</li> <li><strong>h2o_strg</strong>: Estimate of storage H20 flux (Field type: numeric)</li> <li><strong>co2_v.adv</strong>: Estimate of vertical advection flux of CO2 (Field type: numeric)</li> <li><strong>h2o_v.adv</strong>: Estimate of vertical advection flux of H20 (Field type: numeric)</li> <li><strong>co2_molar_density</strong>: Measured or estimated molar density of gas (Field type: numeric)</li> <li><strong>co2_mole_fraction</strong>: Measured or estimated mole fraction of gas (Field type: numeric)</li> <li><strong>co2_mixing_ratio</strong>: Measured or estimated mixing ratio of gas (Field type: numeric)</li> <li><strong>co2_time_lag</strong>: Time lag used to synchronize gas time series (Field type: numeric)</li> <li><strong>co2_def_timelag</strong>: Flag: whether the reported time lag is the default (1) or calculated (0) (Field type: numeric)</li> <li><strong>h2o_molar_density</strong>: Measured or estimated molar density of gas (Field type: numeric)</li> <li><strong>h2o_mole_fraction</strong>: Measured or estimated mole fraction of gas (Field type: numeric)</li> <li><strong>h2o_mixing_ratio</strong>: Measured or estimated mixing ratio of gas (Field type: numeric)</li> <li><strong>h2o_time_lag</strong>: Time lag used to synchronize gas time series (Field type: numeric)</li> <li><strong>h2o_def_timelag</strong>: Flag: whether the reported time lag is the default (1) or calculated (0) (Field type: numeric)</li> <li><strong>sonic_temperature</strong>: Mean temperature of ambient air as measured by the anemometer (Field type: numeric)</li> <li><strong>air_temperature</strong>: Mean temperature of ambient air, either calculated from high frequency air temperature readings, or estimated from sonic temperature (Field type: numeric)</li> <li><strong>air_pressure</strong>: Mean pressure of ambient air, either calculated from high frequency air pressure readings, or estimated based on site altitude (barometric pressure) (Field type: numeric)</li> <li><strong>air_density</strong>: Density of ambient air (Field type: numeric)</li> <li><strong>air_heat_capacity</strong>: Specific heat at constant pressure of ambient air (Field type: numeric)</li> <li><strong>air_molar_volume</strong>: Molar volume of ambient air (Field type: numeric)</li> <li><strong>ET</strong>: Evapotranspiration flux (Field type: numeric)</li> <li><strong>water_vapor_density</strong>: Ambient mass density of water vapor (Field type: numeric)</li> <li><strong>e</strong>: Ambient water vapor partial pressure (Field type: numeric)</li> <li><strong>es</strong>: Ambient water vapor partial pressure at saturation (Field type: numeric)</li> <li><strong>specific_humidity</strong>: Ambient specific humidity on a mass basis (Field type: numeric)</li> <li><strong>RH</strong>: Ambient relative humidity (Field type: numeric)</li> <li><strong>VPD</strong>: Ambient water vapor pressure deficit (Field type: numeric)</li> <li><strong>Tdew</strong>: Ambient dew point temperature (Field type: numeric)</li> <li><strong>u_unrot</strong>: Wind component along the u anemometer axis (Field type: numeric)</li> <li><strong>v_unrot</strong>: Wind component along the v anemometer axis (Field type: numeric)</li> <li><strong>w_unrot</strong>: Wind component along the w anemometer axis (Field type: numeric)</li> <li><strong>u_rot</strong>: Rotated u wind component (mean wind speed) (Field type: numeric)</li> <li><strong>v_rot</strong>: Rotated v wind component (should be zero) (Field type: numeric)</li> <li><strong>w_rot</strong>: Rotated w wind component (should be zero) (Field type: numeric)</li> <li><strong>wind_speed</strong>: Mean wind speed (Field type: numeric)</li> <li><strong>max_wind_speed</strong>: Maximum instantaneous wind speed (Field type: numeric)</li> <li><strong>wind_dir</strong>: Direction from which the wind blows, with respect to Geographic or Magnetic north (Field type: numeric)</li> <li><strong>yaw</strong>: First rotation angle (Field type: numeric)</li> <li><strong>pitch</strong>: Second rotation angle (Field type: numeric)</li> <li><strong>u.</strong>: Friction velocity (Field type: numeric)</li> <li><strong>TKE</strong>: Turbulent kinetic energy (Field type: numeric)</li> <li><strong>L</strong>: Monin-Obukhov length (Field type: numeric)</li> <li><strong>X.z.d..L</strong>: Monin-Obukhov stability parameter - (z-d)/L (Field type: numeric)</li> <li><strong>bowen_ratio</strong>: Sensible heat flux to latent heat flux ratio (Field type: numeric)</li> <li><strong>T.</strong>: Scaling temperature (Field type: numeric)</li> <li><strong>model</strong>: Model for footprint estimation, 1- Kljun et al. (2004): A crosswind integrated parameterization of footprint estimations obtained with a 3D Lagrangian model by means of a scaling procedure.2 - Kormann and Meixner (2001): A crosswind integrated model based on the solution of the two dimensional advection-diffusion equation given by van Ulden (1978) and others for power-law profiles in wind velocity and eddy diffusivity, 3 - Hsieh et al. (2000): A crosswind integrated model based on the former model of Gash (1986) and on simulations with a Lagrangian stochastic model. (Field type: numeric)</li> <li><strong>x_peak</strong>: Along-wind distance providing <1% contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_offset</strong>: Along-wind distance providing the highest (peak) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_10.</strong>: Along-wind distance providing 10% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_30.</strong>: Along-wind distance providing 30% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_50.</strong>: Along-wind distance providing 50% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_70.</strong>: Along-wind distance providing 70% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_90.</strong>: Along-wind distance providing 90% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>un_Tau</strong>: Uncorrected momentum flux (Field type: numeric)</li> <li><strong>Tau_scf</strong>: Spectral correction factor for momentum flux (Field type: numeric)</li> <li><strong>un_H</strong>: Uncorrected sensible heat flux (Field type: numeric)</li> <li><strong>H_scf</strong>: Spectral correction factor for sensible heat flux (Field type: numeric)</li> <li><strong>un_LE</strong>: Uncorrected latent heat flux (Field type: numeric)</li> <li><strong>LE_scf</strong>: Spectral correction factor for latent heat flux (Field type: numeric)</li> <li><strong>un_co2_flux</strong>: Uncorrected gas flux (Field type: numeric)</li> <li><strong>co2_scf</strong>: Spectral correction factor for gas flux (Field type: numeric)</li> <li><strong>un_h2o_flux</strong>: Uncorrected gas flux (Field type: numeric)</li> <li><strong>h2o_scf</strong>: Spectral correction factor for gas flux (Field type: numeric)</li> <li><strong>spikes_hf</strong>: Hard flags for individual variables for spike test (Field type: numeric)</li> <li><strong>amplitude_resolution_hf</strong>: Hard flags for individual variables for amplitude resolution (Field type: numeric)</li> <li><strong>drop_out_hf</strong>: Hard flags for individual variables for drop-out test (Field type: numeric)</li> <li><strong>absolute_limits_hf</strong>: Hard flags for individual variables for absolute limits (Field type: numeric)</li> <li><strong>skewness_kurtosis_hf</strong>: Hard flags for individual variables for skewness and kurtosis (Field type: numeric)</li> <li><strong>skewness_kurtosis_sf</strong>: Soft flags for individual variables for skewness and kurtosis test (Field type: numeric)</li> <li><strong>discontinuities_hf</strong>: Hard flags for individual variables for discontinuities test (Field type: numeric)</li> <li><strong>discontinuities_sf</strong>: Soft flags for individual variables for discontinuities test (Field type: numeric)</li> <li><strong>timelag_hf</strong>: Hard flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>timelag_sf</strong>: Soft flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>attack_angle_hf</strong>: Hard flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>non_steady_wind_hf</strong>: Soft flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>u_spikes</strong>: Number of spikes detected and eliminated for rotated u wind component (Field type: numeric)</li> <li><strong>v_spikes</strong>: Number of spikes detected and eliminated forrotated v wind component (Field type: numeric)</li> <li><strong>w_spikes</strong>: Number of spikes detected and eliminated for rotated w wind component (Field type: numeric)</li> <li><strong>ts_spikes</strong>: Number of spikes detected and eliminated for ts variable (Field type: numeric)</li> <li><strong>co2_spikes</strong>: Number of spikes detected and eliminated for co2 variable (Field type: numeric)</li> <li><strong>h2o_spikes</strong>: Number of spikes detected and eliminated for h2o variable (Field type: numeric)</li> </ul> </li> <li> <p><strong>Raw_data_2017</strong> (described in worksheet Raw_data_2017)</p> <p>Description: EddyPro output of eddy covariance data collected at 52m at the top of the flux tower.</p> <p>Number of fields: 105</p> <p>Number of data rows: 18990</p> <p>Fields:</p> <ul> <li><strong>Location</strong>: SAFE flux tower location name, as in the SAFE Gazetteer (Field type: location)</li> <li><strong>date</strong>: Date of the end of the averaging period (Field type: date)</li> <li><strong>time</strong>: Time of the end of the averaging period (Field type: time)</li> <li><strong>DOY</strong>: decimal day of year (Field type: numeric)</li> <li><strong>daytime</strong>: Daytime or nightime, 1 = daytime, 0 = nighttime (Field type: numeric)</li> <li><strong>file_records</strong>: Number of valid records found in the raw file (or set of raw files) (Field type: numeric)</li> <li><strong>used_records</strong>: Number of valid records used for current the averaging period (Field type: numeric)</li> <li><strong>Tau</strong>: Corrected momentum flux (Field type: numeric)</li> <li><strong>qc_Tau</strong>: Quality flag for momentum flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_Tau</strong>: Random error for momentum flux, if selected (Field type: numeric)</li> <li><strong>H</strong>: Corrected sensible heat flux (Field type: numeric)</li> <li><strong>qc_H</strong>: Quality flag for sensible heat flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_H</strong>: Random error for momentum flux, if selected (Field type: numeric)</li> <li><strong>LE</strong>: Corrected latent heat flux (Field type: numeric)</li> <li><strong>qc_LE</strong>: Quality flag of latent heat flux based on Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_LE</strong>: Random error for latent heat flux, if selected (Field type: numeric)</li> <li><strong>co2_flux</strong>: CO2 flux (Field type: numeric)</li> <li><strong>qc_co2_flux</strong>: Quality flag for CO2 flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_co2_flux</strong>: Random error of CO2 flux (Field type: numeric)</li> <li><strong>h2o_flux</strong>: H2O flux (Field type: numeric)</li> <li><strong>qc_h2o_flux</strong>: Quality flag of H20 flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_h2o_flux</strong>: Random error of CO2 flux (Field type: numeric)</li> <li><strong>H_strg</strong>: Estimate of storage sensible heat flux (Field type: numeric)</li> <li><strong>LE_strg</strong>: Estimate of storage latent heat flux (Field type: numeric)</li> <li><strong>co2_strg</strong>: Estimate of storage CO2 flux (Field type: numeric)</li> <li><strong>h2o_strg</strong>: Estimate of storage H20 flux (Field type: numeric)</li> <li><strong>co2_v.adv</strong>: Estimate of vertical advection flux of CO2 (Field type: numeric)</li> <li><strong>h2o_v.adv</strong>: Estimate of vertical advection flux of H20 (Field type: numeric)</li> <li><strong>co2_molar_density</strong>: Measured or estimated molar density of gas (Field type: numeric)</li> <li><strong>co2_mole_fraction</strong>: Measured or estimated mole fraction of gas (Field type: numeric)</li> <li><strong>co2_mixing_ratio</strong>: Measured or estimated mixing ratio of gas (Field type: numeric)</li> <li><strong>co2_time_lag</strong>: Time lag used to synchronize gas time series (Field type: numeric)</li> <li><strong>co2_def_timelag</strong>: Flag: whether the reported time lag is the default (1) or calculated (0) (Field type: numeric)</li> <li><strong>h2o_molar_density</strong>: Measured or estimated molar density of gas (Field type: numeric)</li> <li><strong>h2o_mole_fraction</strong>: Measured or estimated mole fraction of gas (Field type: numeric)</li> <li><strong>h2o_mixing_ratio</strong>: Measured or estimated mixing ratio of gas (Field type: numeric)</li> <li><strong>h2o_time_lag</strong>: Time lag used to synchronize gas time series (Field type: numeric)</li> <li><strong>h2o_def_timelag</strong>: Flag: whether the reported time lag is the default (1) or calculated (0) (Field type: numeric)</li> <li><strong>sonic_temperature</strong>: Mean temperature of ambient air as measured by the anemometer (Field type: numeric)</li> <li><strong>air_temperature</strong>: Mean temperature of ambient air, either calculated from high frequency air temperature readings, or estimated from sonic temperature (Field type: numeric)</li> <li><strong>air_pressure</strong>: Mean pressure of ambient air, either calculated from high frequency air pressure readings, or estimated based on site altitude (barometric pressure) (Field type: numeric)</li> <li><strong>air_density</strong>: Density of ambient air (Field type: numeric)</li> <li><strong>air_heat_capacity</strong>: Specific heat at constant pressure of ambient air (Field type: numeric)</li> <li><strong>air_molar_volume</strong>: Molar volume of ambient air (Field type: numeric)</li> <li><strong>ET</strong>: Evapotranspiration flux (Field type: numeric)</li> <li><strong>water_vapor_density</strong>: Ambient mass density of water vapor (Field type: numeric)</li> <li><strong>e</strong>: Ambient water vapor partial pressure (Field type: numeric)</li> <li><strong>es</strong>: Ambient water vapor partial pressure at saturation (Field type: numeric)</li> <li><strong>specific_humidity</strong>: Ambient specific humidity on a mass basis (Field type: numeric)</li> <li><strong>RH</strong>: Ambient relative humidity (Field type: numeric)</li> <li><strong>VPD</strong>: Ambient water vapor pressure deficit (Field type: numeric)</li> <li><strong>Tdew</strong>: Ambient dew point temperature (Field type: numeric)</li> <li><strong>u_unrot</strong>: Wind component along the u anemometer axis (Field type: numeric)</li> <li><strong>v_unrot</strong>: Wind component along the v anemometer axis (Field type: numeric)</li> <li><strong>w_unrot</strong>: Wind component along the w anemometer axis (Field type: numeric)</li> <li><strong>u_rot</strong>: Rotated u wind component (mean wind speed) (Field type: numeric)</li> <li><strong>v_rot</strong>: Rotated v wind component (should be zero) (Field type: numeric)</li> <li><strong>w_rot</strong>: Rotated w wind component (should be zero) (Field type: numeric)</li> <li><strong>wind_speed</strong>: Mean wind speed (Field type: numeric)</li> <li><strong>max_wind_speed</strong>: Maximum instantaneous wind speed (Field type: numeric)</li> <li><strong>wind_dir</strong>: Direction from which the wind blows, with respect to Geographic or Magnetic north (Field type: numeric)</li> <li><strong>yaw</strong>: First rotation angle (Field type: numeric)</li> <li><strong>pitch</strong>: Second rotation angle (Field type: numeric)</li> <li><strong>u.</strong>: Friction velocity (Field type: numeric)</li> <li><strong>TKE</strong>: Turbulent kinetic energy (Field type: numeric)</li> <li><strong>L</strong>: Monin-Obukhov length (Field type: numeric)</li> <li><strong>X.z.d..L</strong>: Monin-Obukhov stability parameter - (z-d)/L (Field type: numeric)</li> <li><strong>bowen_ratio</strong>: Sensible heat flux to latent heat flux ratio (Field type: numeric)</li> <li><strong>T.</strong>: Scaling temperature (Field type: numeric)</li> <li><strong>model</strong>: Model for footprint estimation, 1- Kljun et al. (2004): A crosswind integrated parameterization of footprint estimations obtained with a 3D Lagrangian model by means of a scaling procedure.2 - Kormann and Meixner (2001): A crosswind integrated model based on the solution of the two dimensional advection-diffusion equation given by van Ulden (1978) and others for power-law profiles in wind velocity and eddy diffusivity, 3 - Hsieh et al. (2000): A crosswind integrated model based on the former model of Gash (1986) and on simulations with a Lagrangian stochastic model. (Field type: numeric)</li> <li><strong>x_peak</strong>: Along-wind distance providing <1% contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_offset</strong>: Along-wind distance providing the highest (peak) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_10.</strong>: Along-wind distance providing 10% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_30.</strong>: Along-wind distance providing 30% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_50.</strong>: Along-wind distance providing 50% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_70.</strong>: Along-wind distance providing 70% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_90.</strong>: Along-wind distance providing 90% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>un_Tau</strong>: Uncorrected momentum flux (Field type: numeric)</li> <li><strong>Tau_scf</strong>: Spectral correction factor for momentum flux (Field type: numeric)</li> <li><strong>un_H</strong>: Uncorrected sensible heat flux (Field type: numeric)</li> <li><strong>H_scf</strong>: Spectral correction factor for sensible heat flux (Field type: numeric)</li> <li><strong>un_LE</strong>: Uncorrected latent heat flux (Field type: numeric)</li> <li><strong>LE_scf</strong>: Spectral correction factor for latent heat flux (Field type: numeric)</li> <li><strong>un_co2_flux</strong>: Uncorrected gas flux (Field type: numeric)</li> <li><strong>co2_scf</strong>: Spectral correction factor for gas flux (Field type: numeric)</li> <li><strong>un_h2o_flux</strong>: Uncorrected gas flux (Field type: numeric)</li> <li><strong>h2o_scf</strong>: Spectral correction factor for gas flux (Field type: numeric)</li> <li><strong>spikes_hf</strong>: Hard flags for individual variables for spike test (Field type: numeric)</li> <li><strong>amplitude_resolution_hf</strong>: Hard flags for individual variables for amplitude resolution (Field type: numeric)</li> <li><strong>drop_out_hf</strong>: Hard flags for individual variables for drop-out test (Field type: numeric)</li> <li><strong>absolute_limits_hf</strong>: Hard flags for individual variables for absolute limits (Field type: numeric)</li> <li><strong>skewness_kurtosis_hf</strong>: Hard flags for individual variables for skewness and kurtosis (Field type: numeric)</li> <li><strong>skewness_kurtosis_sf</strong>: Soft flags for individual variables for skewness and kurtosis test (Field type: numeric)</li> <li><strong>discontinuities_hf</strong>: Hard flags for individual variables for discontinuities test (Field type: numeric)</li> <li><strong>discontinuities_sf</strong>: Soft flags for individual variables for discontinuities test (Field type: numeric)</li> <li><strong>timelag_hf</strong>: Hard flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>timelag_sf</strong>: Soft flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>attack_angle_hf</strong>: Hard flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>non_steady_wind_hf</strong>: Soft flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>u_spikes</strong>: Number of spikes detected and eliminated for rotated u wind component (Field type: numeric)</li> <li><strong>v_spikes</strong>: Number of spikes detected and eliminated forrotated v wind component (Field type: numeric)</li> <li><strong>w_spikes</strong>: Number of spikes detected and eliminated for rotated w wind component (Field type: numeric)</li> <li><strong>ts_spikes</strong>: Number of spikes detected and eliminated for ts variable (Field type: numeric)</li> <li><strong>co2_spikes</strong>: Number of spikes detected and eliminated for co2 variable (Field type: numeric)</li> <li><strong>h2o_spikes</strong>: Number of spikes detected and eliminated for h2o variable (Field type: numeric)</li> </ul> </li> <li> <p><strong>Raw_data_2018</strong> (described in worksheet Raw_data_2018)</p> <p>Description: EddyPro output of eddy covariance data collected at 52m at the top of the flux tower.</p> <p>Number of fields: 105</p> <p>Number of data rows: 12372</p> <p>Fields:</p> <ul> <li><strong>Location</strong>: SAFE flux tower location name, as in the SAFE Gazetteer (Field type: location)</li> <li><strong>date</strong>: Date of the end of the averaging period (Field type: date)</li> <li><strong>time</strong>: Time of the end of the averaging period (Field type: time)</li> <li><strong>DOY</strong>: decimal day of year (Field type: numeric)</li> <li><strong>daytime</strong>: Daytime or nightime, 1 = daytime, 0 = nighttime (Field type: numeric)</li> <li><strong>file_records</strong>: Number of valid records found in the raw file (or set of raw files) (Field type: numeric)</li> <li><strong>used_records</strong>: Number of valid records used for current the averaging period (Field type: numeric)</li> <li><strong>Tau</strong>: Corrected momentum flux (Field type: numeric)</li> <li><strong>qc_Tau</strong>: Quality flag for momentum flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_Tau</strong>: Random error for momentum flux, if selected (Field type: numeric)</li> <li><strong>H</strong>: Corrected sensible heat flux (Field type: numeric)</li> <li><strong>qc_H</strong>: Quality flag for sensible heat flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_H</strong>: Random error for momentum flux, if selected (Field type: numeric)</li> <li><strong>LE</strong>: Corrected latent heat flux (Field type: numeric)</li> <li><strong>qc_LE</strong>: Quality flag of latent heat flux based on Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_LE</strong>: Random error for latent heat flux, if selected (Field type: numeric)</li> <li><strong>co2_flux</strong>: CO2 flux (Field type: numeric)</li> <li><strong>qc_co2_flux</strong>: Quality flag for CO2 flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_co2_flux</strong>: Random error of CO2 flux (Field type: numeric)</li> <li><strong>h2o_flux</strong>: H2O flux (Field type: numeric)</li> <li><strong>qc_h2o_flux</strong>: Quality flag of H20 flux, Göckede et al., 2006: A system based on 5 quality grades. "0" is best, "5" is worst (Field type: numeric)</li> <li><strong>rand_err_h2o_flux</strong>: Random error of CO2 flux (Field type: numeric)</li> <li><strong>H_strg</strong>: Estimate of storage sensible heat flux (Field type: numeric)</li> <li><strong>LE_strg</strong>: Estimate of storage latent heat flux (Field type: numeric)</li> <li><strong>co2_strg</strong>: Estimate of storage CO2 flux (Field type: numeric)</li> <li><strong>h2o_strg</strong>: Estimate of storage H20 flux (Field type: numeric)</li> <li><strong>co2_v.adv</strong>: Estimate of vertical advection flux of CO2 (Field type: numeric)</li> <li><strong>h2o_v.adv</strong>: Estimate of vertical advection flux of H20 (Field type: numeric)</li> <li><strong>co2_molar_density</strong>: Measured or estimated molar density of gas (Field type: numeric)</li> <li><strong>co2_mole_fraction</strong>: Measured or estimated mole fraction of gas (Field type: numeric)</li> <li><strong>co2_mixing_ratio</strong>: Measured or estimated mixing ratio of gas (Field type: numeric)</li> <li><strong>co2_time_lag</strong>: Time lag used to synchronize gas time series (Field type: numeric)</li> <li><strong>co2_def_timelag</strong>: Flag: whether the reported time lag is the default (1) or calculated (0) (Field type: numeric)</li> <li><strong>h2o_molar_density</strong>: Measured or estimated molar density of gas (Field type: numeric)</li> <li><strong>h2o_mole_fraction</strong>: Measured or estimated mole fraction of gas (Field type: numeric)</li> <li><strong>h2o_mixing_ratio</strong>: Measured or estimated mixing ratio of gas (Field type: numeric)</li> <li><strong>h2o_time_lag</strong>: Time lag used to synchronize gas time series (Field type: numeric)</li> <li><strong>h2o_def_timelag</strong>: Flag: whether the reported time lag is the default (1) or calculated (0) (Field type: numeric)</li> <li><strong>sonic_temperature</strong>: Mean temperature of ambient air as measured by the anemometer (Field type: numeric)</li> <li><strong>air_temperature</strong>: Mean temperature of ambient air, either calculated from high frequency air temperature readings, or estimated from sonic temperature (Field type: numeric)</li> <li><strong>air_pressure</strong>: Mean pressure of ambient air, either calculated from high frequency air pressure readings, or estimated based on site altitude (barometric pressure) (Field type: numeric)</li> <li><strong>air_density</strong>: Density of ambient air (Field type: numeric)</li> <li><strong>air_heat_capacity</strong>: Specific heat at constant pressure of ambient air (Field type: numeric)</li> <li><strong>air_molar_volume</strong>: Molar volume of ambient air (Field type: numeric)</li> <li><strong>ET</strong>: Evapotranspiration flux (Field type: numeric)</li> <li><strong>water_vapor_density</strong>: Ambient mass density of water vapor (Field type: numeric)</li> <li><strong>e</strong>: Ambient water vapor partial pressure (Field type: numeric)</li> <li><strong>es</strong>: Ambient water vapor partial pressure at saturation (Field type: numeric)</li> <li><strong>specific_humidity</strong>: Ambient specific humidity on a mass basis (Field type: numeric)</li> <li><strong>RH</strong>: Ambient relative humidity (Field type: numeric)</li> <li><strong>VPD</strong>: Ambient water vapor pressure deficit (Field type: numeric)</li> <li><strong>Tdew</strong>: Ambient dew point temperature (Field type: numeric)</li> <li><strong>u_unrot</strong>: Wind component along the u anemometer axis (Field type: numeric)</li> <li><strong>v_unrot</strong>: Wind component along the v anemometer axis (Field type: numeric)</li> <li><strong>w_unrot</strong>: Wind component along the w anemometer axis (Field type: numeric)</li> <li><strong>u_rot</strong>: Rotated u wind component (mean wind speed) (Field type: numeric)</li> <li><strong>v_rot</strong>: Rotated v wind component (should be zero) (Field type: numeric)</li> <li><strong>w_rot</strong>: Rotated w wind component (should be zero) (Field type: numeric)</li> <li><strong>wind_speed</strong>: Mean wind speed (Field type: numeric)</li> <li><strong>max_wind_speed</strong>: Maximum instantaneous wind speed (Field type: numeric)</li> <li><strong>wind_dir</strong>: Direction from which the wind blows, with respect to Geographic or Magnetic north (Field type: numeric)</li> <li><strong>yaw</strong>: First rotation angle (Field type: numeric)</li> <li><strong>pitch</strong>: Second rotation angle (Field type: numeric)</li> <li><strong>u.</strong>: Friction velocity (Field type: numeric)</li> <li><strong>TKE</strong>: Turbulent kinetic energy (Field type: numeric)</li> <li><strong>L</strong>: Monin-Obukhov length (Field type: numeric)</li> <li><strong>X.z.d..L</strong>: Monin-Obukhov stability parameter - (z-d)/L (Field type: numeric)</li> <li><strong>bowen_ratio</strong>: Sensible heat flux to latent heat flux ratio (Field type: numeric)</li> <li><strong>T.</strong>: Scaling temperature (Field type: numeric)</li> <li><strong>model</strong>: Model for footprint estimation, 1- Kljun et al. (2004): A crosswind integrated parameterization of footprint estimations obtained with a 3D Lagrangian model by means of a scaling procedure.2 - Kormann and Meixner (2001): A crosswind integrated model based on the solution of the two dimensional advection-diffusion equation given by van Ulden (1978) and others for power-law profiles in wind velocity and eddy diffusivity, 3 - Hsieh et al. (2000): A crosswind integrated model based on the former model of Gash (1986) and on simulations with a Lagrangian stochastic model. (Field type: numeric)</li> <li><strong>x_peak</strong>: Along-wind distance providing <1% contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_offset</strong>: Along-wind distance providing the highest (peak) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_10.</strong>: Along-wind distance providing 10% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_30.</strong>: Along-wind distance providing 30% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_50.</strong>: Along-wind distance providing 50% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_70.</strong>: Along-wind distance providing 70% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>x_90.</strong>: Along-wind distance providing 90% (cumulative) contribution to turbulent fluxes (Field type: numeric)</li> <li><strong>un_Tau</strong>: Uncorrected momentum flux (Field type: numeric)</li> <li><strong>Tau_scf</strong>: Spectral correction factor for momentum flux (Field type: numeric)</li> <li><strong>un_H</strong>: Uncorrected sensible heat flux (Field type: numeric)</li> <li><strong>H_scf</strong>: Spectral correction factor for sensible heat flux (Field type: numeric)</li> <li><strong>un_LE</strong>: Uncorrected latent heat flux (Field type: numeric)</li> <li><strong>LE_scf</strong>: Spectral correction factor for latent heat flux (Field type: numeric)</li> <li><strong>un_co2_flux</strong>: Uncorrected gas flux (Field type: numeric)</li> <li><strong>co2_scf</strong>: Spectral correction factor for gas flux (Field type: numeric)</li> <li><strong>un_h2o_flux</strong>: Uncorrected gas flux (Field type: numeric)</li> <li><strong>h2o_scf</strong>: Spectral correction factor for gas flux (Field type: numeric)</li> <li><strong>spikes_hf</strong>: Hard flags for individual variables for spike test (Field type: numeric)</li> <li><strong>amplitude_resolution_hf</strong>: Hard flags for individual variables for amplitude resolution (Field type: numeric)</li> <li><strong>drop_out_hf</strong>: Hard flags for individual variables for drop-out test (Field type: numeric)</li> <li><strong>absolute_limits_hf</strong>: Hard flags for individual variables for absolute limits (Field type: numeric)</li> <li><strong>skewness_kurtosis_hf</strong>: Hard flags for individual variables for skewness and kurtosis (Field type: numeric)</li> <li><strong>skewness_kurtosis_sf</strong>: Soft flags for individual variables for skewness and kurtosis test (Field type: numeric)</li> <li><strong>discontinuities_hf</strong>: Hard flags for individual variables for discontinuities test (Field type: numeric)</li> <li><strong>discontinuities_sf</strong>: Soft flags for individual variables for discontinuities test (Field type: numeric)</li> <li><strong>timelag_hf</strong>: Hard flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>timelag_sf</strong>: Soft flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>attack_angle_hf</strong>: Hard flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>non_steady_wind_hf</strong>: Soft flags for gas concentration for time lag test (Field type: numeric)</li> <li><strong>u_spikes</strong>: Number of spikes detected and eliminated for rotated u wind component (Field type: numeric)</li> <li><strong>v_spikes</strong>: Number of spikes detected and eliminated forrotated v wind component (Field type: numeric)</li> <li><strong>w_spikes</strong>: Number of spikes detected and eliminated for rotated w wind component (Field type: numeric)</li> <li><strong>ts_spikes</strong>: Number of spikes detected and eliminated for ts variable (Field type: numeric)</li> <li><strong>co2_spikes</strong>: Number of spikes detected and eliminated for co2 variable (Field type: numeric)</li> <li><strong>h2o_spikes</strong>: Number of spikes detected and eliminated for h2o variable (Field type: numeric)</li> </ul> </li> <li> <p><strong>Daily_fluxes</strong> (described in worksheet Daily_fluxes)</p> <p>Description: Daily mean fluxes of net ecosystem CO2 exchange (NEE), ecosystem respirationn (Reco) and gross primary productivity and their associated standard errors that have been subject to quality control, filtering, gapfilling and partitioning.</p> <p>Number of fields: 12</p> <p>Number of data rows: 455</p> <p>Fields:</p> <ul> <li><strong>Location</strong>: SAFE flux tower location name, as in the SAFE Gazetteer (Field type: location)</li> <li><strong>Year</strong>: Year of data collection (Field type: numeric)</li> <li><strong>DOY</strong>: Julian day of year of data collection (Field type: numeric)</li> <li><strong>Date</strong>: Date of data collection (Field type: date)</li> <li><strong>obs_counts_daytime</strong>: Count of net eocsystem CO2 exchange (NEE) obervations for that 24 hour period (Field type: numeric)</li> <li><strong>obs_counts_24hr</strong>: Count of net eocsystem CO2 exchange (NEE) obervations for that day - during daytime only (06:30 - 18:30), this indicates how many values were gapfilled for that daytime period, as nightime values are gapfilled whereby NEE = Reco (Field type: numeric)</li> <li><strong>NEE</strong>: Net ecosystem CO2 exchange (NEE) (Field type: numeric)</li> <li><strong>Reco</strong>: Ecosystem respiration (Reco) (Field type: numeric)</li> <li><strong>GPP</strong>: Gross primary productivity (GPP) (Field type: numeric)</li> <li><strong>NEE_stderror</strong>: Standard error of net ecosystem CO2 exchange (NEE) (Field type: numeric)</li> <li><strong>Reco_stderror</strong>: Standard error of ecosystem respiration (Reco) (Field type: numeric)</li> <li><strong>GPP_stderror</strong>: Standard error of gross primary productivity (GPP) (Field type: numeric)</li> </ul> </li> </ol> <p><strong>Date range: </strong>2012-08-14 to 2018-11-30</p> <p><strong>Latitudinal extent: </strong>4.7173 to 4.7173</p> <p><strong>Longitudinal extent: </strong>117.6032 to 117.6032</p>
Evapotranspiration data from eddy-covariance flux-tower measurements and Landsat imagery in California’s Sierra Nevada from 1985 to 2019
Open the record for dataset details and reuse information.
An Excel spreadsheet including 7-year eddy covariance-based evapotranspiration and auxilary data at Yunxiao mangrove flux tower
<p>An Excel spreadsheet including 7-year eddy covariance-based evapotranspiration and auxilary data at Yunxiao mangrove flux tower required to reproduce key results in the main text of a manuscript (each figure corresponds to a single sheet). Contact Xudong Zhu at Xiamen University (xdzhu@xmu.edu.cn) if you have any question.</p>
Resampling code with sample data for: Eddy-covariance with slow-response greenhouse gas analyser on tall towers
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An Excel spreadsheet including eddy covariance and meteorological data measured at Nanji Island flux tower, Southern China.
<p>The data was measured using an open-path eddy covariance system in a subtropical island forest located in the Nanji Islands National Marine Protected Area in southern China. The results will support for a paper entitled "Carbon sink potential and its driving mechanisms in an island forest nature reserve in southern China". Contact Xianglan Li at Beijing Normal University (xlli@bnu.edu.cn) if you have any question.</p>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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