Comparison of continuous in situ CO2 observations at Jungfraujoch using two different measurement techniques

Since 2004, atmospheric carbon dioxide (CO2) is being measured at the High Altitude Research Station Jungfraujoch by the division of Climate and Environmental Physics at the University of Bern (KUP) using a nondispersive infrared gas analyzer (NDIR) in combination with a paramagnetic O2 analyzer. In January 2010, CO2 measurements based on cavity ring-down spectroscopy (CRDS) as part of the Swiss National Air Pollution Monitoring Network were added by the Swiss Federal Laboratories for Materials Science and Technology (Empa). To ensure a smooth transition – a prerequisite when merging two data sets, e.g., for trend determinations – the two measurement systems run in parallel for several years. Such a long-term intercomparison also allows the identification of potential offsets between the two data sets and the collection of information about the compatibility of the two systems on different time scales. A good agreement of the seasonality, short-term variations and, to a lesser extent mainly due to the short common period, trend calculations is observed. However, the comparison reveals some issues related to the stability of the calibration gases of the KUP system and their assigned CO2 mole fraction. It is possible to adapt an improved calibration strategy based on standard gas determinations, which leads to better agreement between the two data sets. By excluding periods with technical problems and bad calibration gas cylinders, the average hourly difference (CRDS – NDIR) of the two systems is −0.03 ppm ± 0.25 ppm. Although the difference of the two data sets is in line with the compatibility goal of ±0.1 ppm of the World Meteorological Organization (WMO), the standard deviation is still too high. A significant part of this uncertainty originates from the necessity to switch the KUP system frequently (every 12 min) for 6 min from ambient air to a working gas in order to correct short-term variations of the O2 measurement system. Allowing additional time for signal stabilization after switching the sample, an effective data coverage of only one-sixth for the KUP system is achieved while the Empa system has a nearly complete data coverage. Additionally, different internal volumes and flow rates may affect observed differences

Inferring Rn-222 soil fluxes from ambient Rn-222 activity and eddy covariance measurements of CO2

We present a new methodology, which we call Single Pair of Observations Technique with Eddy Covariance (SPOT-EC), to estimate regional-scale surface fluxes of 222Rn from tower-based observations of 222Rn activity concentration, CO2 mole fractions and direct CO2 flux measurements from eddy covariance. For specific events, the regional (222Rn) surface flux is calculated from short-term changes in ambient (222Rn) activity concentration scaled by the ratio of the mean CO2 surface flux for the specific event to the change in its observed mole fraction. The resulting 222Rn surface emissions are integrated in time (between the moment of observation and the last prior background levels) and space (i.e. over the footprint of the observations). The measurement uncertainty obtained is about ±15 % for diurnal events and about ±10 % for longer-term (e.g. seasonal or annual) means. The method does not provide continuous observations, but reliable daily averages can be obtained. We applied our method to in situ observations from two sites in the Netherlands: Cabauw station (CBW) and Lutjewad station (LUT). For LUT, which is an intensive agricultural site, we estimated a mean 222Rn surface flux of (0.29 ± 0.02) atoms cm−2 s−1 with values  > 0.5 atoms cm−2 s−1 to the south and south-east. For CBW we estimated a mean 222Rn surface flux of (0.63 ± 0.04) atoms cm−2 s−1. The highest values were observed to the south-west, where the soil type is mainly river clay. For both stations good agreement was found between our results and those from measurements with soil chambers and two recently published 222Rn soil flux maps for Europe. At both sites, large spatial and temporal variability of 222Rn surface fluxes were observed which would be impractical to measure with a soil chamber. SPOT-EC, therefore, offers an important new tool for estimating regional-scale 222Rn surface fluxes. Practical applications furthermore include calibration of process-based 222Rn soil flux models, validation of atmospheric transport models and performing regional-scale inversions, e.g. of greenhouse gases via the SPOT 222Rn-tracer method

Changes in surface hydrology, soil moisture and gross primary production in the Amazon during the 2015/2016 El Niño

The 2015/2016 El Niño event caused severe changes in precipitation across the tropics. This impacted surface hydrology, such as river run-off and soil moisture availability, thereby triggering reductions in gross primary production (GPP). Many biosphere models lack the detailed hydrological component required to accurately quantify anomalies in surface hydrology and GPP during droughts in tropical regions. Here, we take the novel approach of coupling the biosphere model SiBCASA with the advanced hydrological model PCR-GLOBWB to attempt such a quantification across the Amazon basin during the drought in 2015/2016. We calculate 30-40% reduced river discharge in the Amazon starting in October 2015, lagging behind the precipitation anomaly by approximately one month and in good agreement with river gauge observations. Soil moisture shows distinctly asymmetrical spatial anomalies with large reductions across the north-eastern part of the basin, which persisted into the following dry season. This added to drought stress in vegetation, already present owing to vapour pressure deficits at the leaf, resulting in a loss of GPP of 0.95 (0.69 to 1.20) PgC between October 2015 and March 2016 compared with the 2007-2014 average. Only 11% (10-12%) of the reduction in GPP was found in the (wetter) north-western part of the basin, whereas the north-eastern and southern regions were affected more strongly, with 56% (54-56%) and 33% (31-33%) of the total, respectively. Uncertainty on this anomaly mostly reflects the unknown rooting depths of vegetation.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.</p

Estimating Asian terrestrial carbon fluxes from CONTRAIL aircraft and surface CO2 observations for the period 2006 to 2010

Current estimates of the terrestrial carbon fluxes in Asia show large uncertainties particularly in the boreal and mid-latitudes and in China. In this paper, we present an updated carbon flux estimate for Asia ("Asia" refers to lands as far west as the Urals and is divided into boreal Eurasia, temperate Eurasia and tropical Asia based on TransCom regions) by introducing aircraft CO2 measurements from the CONTRAIL (Comprehensive Observation Network for Trace gases by Airline) program into an inversion modeling system based on the CarbonTracker framework. We estimated the averaged annual total Asian terrestrial land CO2 sink was about -1.56 Pg C yr-1 over the period 2006–2010, which offsets about one-third of the fossil fuel emission from Asia (+4.15 Pg C yr-1). The uncertainty of the terrestrial uptake estimate was derived from a set of sensitivity tests and ranged from -1.07 to -1.80 Pg C yr-1, comparable to the formal Gaussian error of ±1.18 Pg C yr-1 (1-sigma). The largest sink was found in forests, predominantly in coniferous forests (-0.64 ± 0.70 Pg C yr-1) and mixed forests (-0.14 ± 0.27 Pg C yr-1); and the second and third large carbon sinks were found in grass/shrub lands and croplands, accounting for -0.44 ± 0.48 Pg C yr-1 and -0.20 ± 0.48 Pg C yr-1, respectively. The carbon fluxes per ecosystem type have large a priori Gaussian uncertainties, and the reduction of uncertainty based on assimilation of sparse observations over Asia is modest (8.7–25.5%) for most individual ecosystems. The ecosystem flux adjustments follow the detailed a priori spatial patterns by design, which further increases the reliance on the a priori biosphere exchange model. The peak-to-peak amplitude of inter-annual variability (IAV) was 0.57 Pg C yr-1 ranging from -1.71 Pg C yr-1 to -2.28 Pg C yr-1. The IAV analysis reveals that the Asian CO2 sink was sensitive to climate variations, with the lowest uptake in 2010 concurrent with a summer flood and autumn drought and the largest CO2 sink in 2009 owing to favorable temperature and plentiful precipitation conditions. We also found the inclusion of the CONTRAIL data in the inversion modeling system reduced the uncertainty by 11% over the whole Asian region, with a large reduction in the southeast of boreal Eurasia, southeast of temperate Eurasia and most tropical Asian areas