This paper overviews the short‐term (biophysical) and long‐term (out to around 100 year timescales; biogeochemical and biogeographical) influences of the land surface on weather and climate. From our review of the literature, the evidence is convincing that terrestrial ecosystem dynamics on these timescales significantly influence atmospheric processes. In studies of past and possible future climate change, terrestrial ecosystem dynamics are as important as changes in atmospheric dynamics and composition, ocean circulation, ice sheet extent, and orbit perturbations.

Abstract. Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthropogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU281). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990–2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.3662371 (Petrescu et al., 2020).

The Global Soil Wetness Project (GSWP) is an ongoing land surface modeling activity of the International Satellite Land-Surface Climatology Project (ISLSCP), a part of the Global Energy and Water Cycle Experiment. The pilot phase of GSWP deals with the production of a two-year global dataset of soil moisture, temperature, runoff, and surface fluxes by integrating uncoupled land surface schemes (LSSs) using externally specified surface forcings from observations and standardized soil and vegetation distributions. Approximately one dozen participating LSS groups in five nations have taken the common ISLSCP forcing data to drive their state-of-the-art models over the 1987-88 period to generate global datasets. Many of the LSS groups have performed specific sensitivity studies, which are intended to evaluate the impact of uncertainties in model parameters and forcing fields on simulation of the surface water and energy balances. A validation effort exists to compare the global products to other forms of estimation and measurement, either directly (by comparison to field studies or soil moisture measuring networks) or indirectly (e.g., use of modeled runoff to drive river routing schemes for comparison to streamflow data). The soil wetness data produced are also being tested within general circulation models to evaluate their quality and their impact on seasonal to interannual climate simulations. An Inter-Comparison Center has also been established for evaluating and comparing data from the different LSSs. Comparison among the model results is used to assess the uncertainty in estimates of surface components of the moisture and energy balances at large scales and as a quality check on the model products themselves.

Globally, peat lands are considered to be a sink of CO 2 , but a source when drained. Additionally, wet peat lands are thought to emit considerable amounts of CH 4 and N 2 O. Hitherto, reliable and integrated estimates of emissions and emission factors for this type of land cover have been lacking and the effects of wetland restoration on methane emissions have been poorly quantified. In this paper we estimate the full greenhouse gas (GHG) balance of a restored natural peat land by determining the fluxes of CO 2 , CH 4 and N 2 O through atmosphere and water, while accounting for the different Global Warming Potentials (GWP's). The site is an abandoned agricultural peat meadow, which has been converted into a wetland nature reserve ten years ago, after which the water level was raised. GHG fluxes were measured continuously with an eddy covariance system (CO 2) and flux chamber measurements (CH 4 and N 2 O). Meteorological and hydrological measurements were collected as well. With growing seasons of respectively 192, 168 and 129 days, the annual net ecosystem exchange of CO 2 (NEE) was −446+±83 g C m −2 yr −1 for 2004, −311±58 g C m −2 yr −1 for 2005 and −232±57 g m −2 yr −1 for 2006. Ecosystem respiration (R eco) was estimated as 869±668 g C m −2 yr −1 for 2004, 866±666 g C m −2 yr −1 for 2005 and 924±711 g C m −2 yr −1 for 2006. CH 4 emissions from the saturated land and water surfaces were high compared to the relatively dry land. Annual weighted CH 4 emissions were 31.27±20.40 g C m −2 yr −1 for 2005 and 32.27±21.08 g C m −2 yr −1 for 2006. N 2 O fluxes were too low to be of significance. The water balance of the area was dominated by precipitation and evapotranspiration and therefore fluxes of carbon and CH 4 through seepage, infiltration and drainage were relatively small (17.25 g C m −2 yr −1). The carbon-balance consisted for the largest part of CO 2 uptake , CO 2 respiration and CH 4 emission from water saturated Correspondence to: D. M. D. Hendriks (dimmie.hendriks@falw.vu.nl) land and water. CO 2 emission has decreased significantly as result of the raised water table, while CH 4 fluxes have increased. In GWP's the area was a small net GHG sink given as CO 2-equiv. of −86 g m −2 yr −1 (over a 100-year period).

Abstract. A DLT-100 Fast Methane Analyser (FMA) from Los Gatos Research (LGR) Ltd. is assessed for its applicability in a closed path eddy covariance field set-up. The FMA uses off-axis integrated cavity output spectroscopy (ICOS) combined with a highly specific narrow band laser for the detection of CH4 and strongly reflective mirrors to obtain a laser path length of 2×10³ to 20×10³ m. Statistical testing, a calibration experiment and comparison with high tower data showed high precision and very good stability of the instrument. The measurement cell response time was tested to be 0.10 s. In the field set-up, the FMA is attached to a scroll pump and combined with a Gill Windmaster Pro 3 axis Ultrasonic Anemometer and a Licor 7500 open path infrared gas analyzer. The power-spectra and co-spectra of the instrument are satisfactory for 10 Hz sampling rates. The correspondence with CH4 flux chamber measurements is good and the observed CH4 emissions are comparable with (eddy covariance) CH4 measurements in other peat areas. CH4 emissions are rather variable over time and show a diurnal pattern. The average CH4 emission is 50±12.5 nmol m−2 s−1, while the typical maximum CH4 emission is 120±30 nmol m−2 s−1 (during daytime) and the typical minimum flux is –20±2.5 nmol m−2 s−1 (uptake, during night time). Additionally, the set-up was tested for three measurement techniques with slower measurement rates, which could be used in the future to make the scroll pump superfluous and save energy. Both disjunct eddy covariance as well as slow 1 Hz eddy covariance showed results very similar to normal 10 Hz eddy covariance. Relaxed eddy accumulation (REA) only matched with normal 10 Hz eddy covariance over an averaging period of at least several weeks.