Surface-Layer Similarity Functions for Dissipation Rate and Structure Parameters of Temperature and Humidity Based on Eleven Field Experiments

In the literature, no consensus can be found on the exact form of the universal funtions of Monin-Obukhov similarity theory (MOST) for the structure parameters of temperature, CT 2, and humidity, Cq 2, and the dissipation rate of turbulent kinetic energy, ε. By combining 11 datasets and applying data treatment with spectral data filtering and error-weighted curve-fitting we first derived robust MOST functions of CT 2,Cq 2 and ε that cover a large stability range for both unstable and stable conditions. Second, as all data weregathered with the same instrumentation and were processed in the same way—in contrast to earlier studies—we were able to investigate the similarity of MOST functions across different datasets by defining MOST functions for all datasets individually. For CT 2 and ε we found no substantial differences in MOST functions for datasets over different surface types or moisture regimes. MOST functions of Cq 2 differ from that of CT 2, but we could not relate these differences to turbulence parameters often associated with non-local effects.Furthermore, we showed that limited stability ranges and a limited number of data points are plausible reasons for variations of MOST functions in the literature. Last, we investigated the sensitivity of fluxes to the uncertainty of MOST functions.We provide an overview of the uncertainty range for MOST functions of CT 2,Cq 2 and ε, and suggest their use in determining the uncertainty in surface fluxes.<br/

Towards standardized processing of eddy covariance flux measurements of carbonyl sulfide

Carbonyl sulfide (COS) flux measurements with the eddy covariance (EC) technique are becoming popular for estimating gross primary productivity. To compare COS flux measurements across sites, we need standardized protocols for data processing. In this study, we analyze how various data processing steps affect the calculated COS flux and how they differ from carbon dioxide (CO2) flux processing steps, and we provide a method for gap-filling COS fluxes. Different methods for determining the time lag between COS mixing ratio and the vertical wind velocity (w) resulted in a maximum of 15.9 % difference in the median COS flux over the whole measurement period. Due to limited COS measurement precision, small COS fluxes (below approximately 3 pmol m(-2) s(-1)) could not be detected when the time lag was determined from maximizing the covariance between COS and w. The difference between two high-frequency spectral corrections was 2.7 % in COS flux calculations, whereas omitting the high-frequency spectral correction resulted in a 14.2 % lower median flux, and different detrending methods caused a spread of 6.2 %. Relative total uncertainty was more than 5 times higher for low COS fluxes (lower than +/- 3 pmol m(-2) s(-1)) than for low CO2 fluxes (lower than +/- 1.5 mu mol m(-2) s(-1)), indicating a low signal-to-noise ratio of COS fluxes. Due to similarities in ecosystem COS and CO2 exchange, we recommend applying storage change flux correction and friction velocity filtering as usual in EC flux processing, but due to the low signal-to-noise ratio of COS fluxes, we recommend using CO2 data for time lag and high-frequency corrections of COS fluxes due to the higher signal-to-noise ratio of CO2 measurements.Peer reviewe

Intercomparison of methods to estimate gross primary production based on CO2 and COS flux measurements

Separating the components of ecosystem-scale carbon exchange is crucial in order to develop better models and future predictions of the terrestrial carbon cycle. However, there are several uncertainties and unknowns related to current photosynthesis estimates. In this study, we evaluate four different methods for estimating photosynthesis at a boreal forest at the ecosystem scale, of which two are based on carbon dioxide (CO2) flux measurements and two on carbonyl sulfide (COS) flux measurements. The CO2-based methods use traditional flux partitioning and artificial neural networks to separate the net CO2 flux into respiration and photosynthesis. The COS-based methods make use of a unique 5-year COS flux data set and involve two different approaches to determine the leaf-scale relative uptake ratio of COS and CO2 (LRU), of which one (LRUCAP) was developed in this study. LRUCAP was based on a previously tested stomatal optimization theory (CAP), while LRUPAR was based on an empirical relation to measured radiation. For the measurement period 2013-2017, the artificial neural network method gave a GPP estimate very close to that of traditional flux partitioning at all timescales. On average, the COS-based methods gave higher GPP estimates than the CO2-based estimates on daily (23 % and 7 % higher, using LRUPAR and LRUCAP, respectively) and monthly scales (20 % and 3 % higher), as well as a higher cumulative sum over 3 months in all years (on average 25 % and 3 % higher). LRUCAP was higher than LRU estimated from chamber measurements at high radiation, leading to underestimation of midday GPP relative to other GPP methods. In general, however, use of LRUCAP gave closer agreement with CO2-based estimates of GPP than use of LRUPAR. When extended to other sites, LRUCAP may be more robust than LRUPAR because it is based on a physiological model whose parameters can be estimated from simple measurements or obtained from the literature. In contrast, the empirical radiation relation in LRUPAR may be more site-specific. However, this requires further testing at other measurement sites.Peer reviewe

Inverse modelling of carbonyl sulfide: implementation, evaluation and implications for the global budget

Carbonyl sulfide (COS) has the potential to be used as a climate diagnostic due to its close coupling to the biospheric uptake of CO2 and its role in the formation of stratospheric aerosol. The current understanding of the COS budget, however, lacks COS sources, which have previously been allocated to the tropical ocean. This paper presents a first attempt at global inverse modelling of COS within the 4-dimensional variational data-assimilation system of the TM5 chemistry transport model (TM5-4DVAR) and a comparison of the results with various COS observations. We focus on the global COS budget, including COS production from its precursors carbon disulfide (CS2) and dimethyl sulfide (DMS). To this end, we implemented COS uptake by soil and vegetation from an updated biosphere model (Simple Biosphere Model-SiB4). In the calculation of these fluxes, a fixed atmospheric mole fraction of 500 pmol mol-1 was assumed. We also used new inventories for anthropogenic and biomass burning emissions. The model framework is capable of closing the COS budget by optimizing for missing emissions using NOAA observations in the period 2000-2012. The addition of 432 Gg a-1 (as S equivalents) of COS is required to obtain a good fit with NOAA observations. This missing source shows few year-to-year variations but considerable seasonal variations. We found that the missing sources are likely located in the tropical regions, and an overestimated biospheric sink in the tropics cannot be ruled out due to missing observations in the tropical continental boundary layer. Moreover, high latitudes in the Northern Hemisphere require extra COS uptake or reduced emissions. HIPPO (HIAPER Pole-to-Pole Observations) aircraft observations, NOAA airborne profiles from an ongoing monitoring programme and several satellite data sources are used to evaluate the optimized model results. This evaluation indicates that COS mole fractions in the free troposphere remain underestimated after optimization. Assimilation of HIPPO observations slightly improves this model bias, which implies that additional observations are urgently required to constrain sources and sinks of COS. We finally find that the biosphere flux dependency on the surface COS mole fraction (which was not accounted for in this study) may substantially lower the fluxes of the SiB4 biosphere model over strong-uptake regions. Using COS mole fractions from our inversion, the prior biosphere flux reduces from 1053 to 851 Gg a-1, which is closer to 738 Gg a-1 as was found by Berry et al. (2013). In planned further studies we will implement this biosphere dependency and additionally assimilate satellite data with the aim of better separating the role of the oceans and the biosphere in the global COS budget..</p

Long-term fluxes of carbonyl sulfide and their seasonality and interannual variability in a boreal forest

The seasonality and interannual variability of terrestrial carbonyl sulfide (COS) fluxes are poorly constrained. We present the first easy-to-use parameterization for the net COS forest sink based on the longest existing eddy covariance record from a boreal pine forest, covering 32 months over 5 years. Fluxes from hourly to yearly scales are reported, with the aim of revealing controlling factors and the level of interannual variability. The parameterization is based on the photosynthetically active radiation, vapor pressure deficit, air temperature, and leaf area index. Wavelet analysis of the ecosystem fluxes confirmed earlier findings from branch-level fluxes at the same site and revealed a 3 h lag between COS uptake and air temperature maxima at the daily scale, whereas no lag between radiation and COS flux was found. The spring recovery of the flux after the winter dormancy period was mostly governed by air temperature, and the onset of the uptake varied by 2 weeks. For the first time, we report a significant reduction in ecosystem-scale COS uptake under a large water vapor pressure deficit in summer. The maximum monthly and weekly median COS uptake varied by 26% and 20% between years, respectively. The timing of the latter varied by 6 weeks. The fraction of the nocturnal uptake remained below 21% of the total COS uptake. We observed the growing season (April-August) average net flux of COS totaling -58 :0 gS ha(-1) with 37% interannual variability. The long-term flux observations were scaled up to evergreen needleleaf forests (ENFs) in the whole boreal region using the Simple Biosphere Model Version 4 (SiB4). The observations were closely simulated using SiB4 meteorological drivers and phenology. The total COS uptake by boreal ENFs was in line with a missing COS sink at high latitudes pointed out in earlier studies.Peer reviewe

Combined assimilation of NOAA surface and MIPAS satellite observations to constrain the global budget of carbonyl sulfide

Carbonyl sulfide (COS), a trace gas in our atmosphere that leads to the formation of aerosols in the stratosphere, is taken up by terrestrial ecosystems. Quantifying the biosphere uptake of (COS) could provide a useful quantity to estimate Gross Primary Productivity. Some COS sources and sinks still contain large uncertainties, and several top down estimates of the COS budget point to an underestimation of sources especially in the tropics. We extended the inverse model TM5-4DVAR to assimilate MIPAS satellite data, in addition to NOAA surface data as used in a previous study. To resolve possible discrepancies among the two observational datasets, a bias correction scheme was implemented. A set of inversions is presented that explores the influence of the different measurement instruments and the settings of the prior fluxes. To evaluate the performance of the inverse system, the HIAPER Pole-to-Pole Observations (HIPPO) aircraft observations and NOAA airborne profiles are used. All inversions reduce the (COS) biosphere uptake from a prior value of 1053 GgS a-1 to much smaller values, depending on the inversion settings. These large adjustments of the biosphere uptake often turn parts of the Amazonia into a (COS) source. Only inversions that exclusively use MIPAS observations, or strongly reduce the prior errors on the biosphere flux maintain the Amazonia as a COS sink. Assimilating both NOAA surface data and MIPAS data requires a small bias correction for MIPAS data, mostly at higher latitudes, to correct for inconsistencies in the observational data and/or transport model errors. Analysis of the error reduction and posterior correlation between land and ocean fluxes indicates that co-assimilation of NOAA surface observations and MIPAS data better constrains the (COS) budget than assimilation of one individual dataset alone. Our inversions with bias corrections reduce the global biosphere uptake to respectively 570 and 687 GgS a-1, depending on the prior biosphere error. Over the Amazonia, these inversions reduce the biosphere uptake from roughly 300 to 100 GgS a-1, indicating a strongly overestimated prior uptake over the Amazonia. Although a recent study also reported reduced (COS) uptake over the Amazonia, we emphasise that a careful construction of prior fluxes and their associated errors remains important. For instance, an inversion that gives large freedom to adjust the anthropogenic and ocean fluxes of CS2, an important (COS) precursor, also closes the budget satisfactorily with much smaller adjustments to the biosphere. Thus, a better characterisation of biosphere and ocean fluxes by observations is urgently needed, especially over the data-poor tropics