The data set contains nearly 15 years of eddy covariance data from an alpine steppe ecosystem on the central Tibetan Plateau. The data was processed following standardized quality control methods to allow for comparability between the different years of our record and with other data sets. To ensure meaningful estimates of ecosystem atmosphere exchange, careful application of the following correction procedures and analyses was necessary: (1) Due to the remote location, continuous maintenance of the eddy covariance (EC) system was not always possible, so that cleaning and calibration of the sensors was performed irregularly. Furthermore, the high proportion of bare soil and high wind speeds led to accumulation of dirt in the measurement path of the infrared gas analyzer (IRGA). The installation of the sensor in such a challenging environment resulted in a considerable drift in CO2 and H2O gas density measurements. If not accounted for, this concentration bias may distort the estimation of the carbon uptake. We applied a modified drift correction procedure following Fratini et al. (2014) which, instead of a linear interpolation between calibration dates, uses the CO2 concentration measurements from the Mt. Waliguan atmospheric observatory as reference time series. (2) We applied rigorous quality filtering of the calculated fluxes to retain only fluxes which represent actual physical processes. (3) During the long measurement period, there were several buildings constructed in the near vicinity of the EC system. We investigated the influence of these obstacles on the turbulent flow regime to identify fluxes with uncertain land cover contribution and exclude them from subsequent computations. (4) We calculated the de-facto standard correction for instrument surface heating during cold conditions (hereafter called sensor self heating correction) following Burba et al. (2008) and a revision of the original method following Frank and Massman (2020). (5) Subsequently, we applied the traditional and widely used gap filling procedure following Reichstein et al. (2005) to provide a more complete overview of the annual net ecosystem CO2 exchange. (6) We estimated the flux uncertainty by calculating the random flux error (RE) following Finkelstein and Sims (2001) and by using the standard deviation of the fluxes used for gap filling (NEE_fsd) as a measure for spatial and temporal variation. References: Burba, G. G., McDermitt, D. K., Grelle, A., Anderson, D., and XU, L. (2008). Addressing the influence of instrument surface heat exchange on the measurements of CO2 flux from open-path gas analyzers, Global Change Biology, 14, 1854-1876, https://doi.org/10.1111/j.1365-2486.2008.01606.x. Finkelstein, P. L. and Sims, P. F. (2001). Sampling error in eddy correlation flux measurements, J. Geophys. Res. Atmos., 106, 3503–3509, doi:10.1029/2000JD900731. Frank, J. M. and Massman, W. J.: A new perspective on the open-path infrared gas analyzer self-heating correction, Agricultural and Forest Meteorology, 290, 107986, doi:10.1016/j.agrformet.2020.107986, 2020. Fratini, G., McDermitt, D. K., and Papale, D. (2004). Eddy-covariance flux errors due to biases in gas concentration measurements: origins, quantification and correction, Biogeosciences, 11, 1037-1051, https://doi.org/10.5194/bg-11-1037-2014. Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grunwald, T., Havrankova, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-m., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and valentini, R. (20050. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm, Global Change Biology, 11, 1424-1439, https://doi.org/10.1111/j.1365-2486.2005.001002.x.

{"references": ["Ma, Y.M., Kang, S.C., Zhu, L.P., Xu, B.Q., Tian, L.D., & Yao, T.D. (2008). Tibetan Observation and Research Platform- Atmosphere-land interaction over a heterogeneous landscape, Bulletin of the American Meteorological Society. 89, 1487-1492. doi:10.1175/2008BAMS2545.1.", "Ma, Y.M., Ma, W.Q., Zhong, L., Hu, Z., Li, M., Zhu, Z., et al. (2017). Monitoring and Modeling the Tibetan Plateau's climate system and its impact on East Asia, Scientific Reports, 7, 44574, doi:10.1038/srep44574.", "Nieberding, F., Wille, C., Fratini, G., Asmussen, M. O., Wang, Y., Ma, Y., and Sachs, T.: A Long Term (2005\u20132019) Eddy Covariance Data Set of CO2 and H2O Fluxes from the Tibetan Alpine Steppe, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-63, in review, 2020."]}

The file "NAMORS_EC_2005-2019_v2.txt" contains the EddyPro full_output (https://www.licor.com/env/support/EddyPro/topics/output-files-full-output.html) and biomet data, quality flags for quality filtering, the CO2 fluxes corrected for sensor self heating effects and the REddyProc gap filling results (https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProcWebOutput). The file "NAMORS_EC_2005-2019_varnames_units_v2.txt" contains the variable descriptions and physical units for the above mentioned dataset. The uploaded files are tab-delimited .txt files with "-9999" representing missing data. A research paper with the detailed processing procedure was submitted to Earth System Science Data and is currently under review (https://essd.copernicus.org/preprints/essd-2020-63/).