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Fowler D.,UK Center for Ecology and Hydrology | Coyle M.,UK Center for Ecology and Hydrology | Skiba U.,UK Center for Ecology and Hydrology | Sutton M.A.,UK Center for Ecology and Hydrology | And 14 more authors.
Philosophical Transactions of the Royal Society B: Biological Sciences | Year: 2013

Global nitrogen fixation contributes 413 Tg of reactive nitrogen (Nr) to terrestrial and marine ecosystems annually of which anthropogenic activities are responsible for half, 210 Tg N. The majority of the transformations of anthropogenic Nr are on land (240 Tg N yr-1) within soils and vegetation where reduced Nr contributes most of the input through the use of fertilizer nitrogen in agriculture. Leakages from the use of fertilizer Nr contribute to nitrate (NO3-) in drainage waters from agricultural land and emissions of trace Nr compounds to the atmosphere. Emissions, mainly of ammonia (NH3) from land together with combustion related emissions of nitrogen oxides (NOx), contribute 100 Tg N yr-1 to the atmosphere, which are transported between countries and processed within the atmosphere, generating secondary pollutants, including ozone and other photochemical oxidants and aerosols, especially ammonium nitrate (NH4NO3) and ammonium sulfate (NH4)2SO4. Leaching and riverine transport of NO3 contribute 40-70 Tg N yr-1 to coastal waters and the open ocean, which together with the 30 Tg input to oceans from atmospheric deposition combine with marine biological nitrogen fixation (140 TgN yr-1) to double the ocean processing of Nr. Some of the marine Nr is buried in sediments, the remainder being denitrified back to the atmosphere as N2 or N2O. The marine processing is of a similar magnitude to that in terrestrial soils and vegetation, but has a larger fraction of natural origin. The lifetime ofNr in the atmosphere, with the exception ofN2O, is only a fewweeks,while in terrestrial ecosystems, with the exception of peatlands (where it can be 102-103 years), the lifetime is a few decades. In the ocean, the lifetime of Nr is less well known but seems to be longer than in terrestrial ecosystems and may represent an important long-term source of N2O that will respond very slowly to control measures on the sources of Nr from which it is produced. © 2013 The Author(s) Published by the Royal Society. All rights reserved.

Schneising O.,University of Bremen | Bergamaschi P.,European Commission - Joint Research Center Ispra | Bovensmann H.,University of Bremen | Buchwitz M.,University of Bremen | And 15 more authors.
Atmospheric Chemistry and Physics | Year: 2012

SCIAMACHY onboard ENVISAT (launched in 2002) enables the retrieval of global long-term column-averaged dry air mole fractions of the two most important anthropogenic greenhouse gases carbon dioxide and methane (denoted XCO2 and XCH4). In order to assess the quality of the greenhouse gas data obtained with the recently introduced v2 of the scientific retrieval algorithm WFM-DOAS, we present validations with ground-based Fourier Transform Spectrometer (FTS) measurements and comparisons with model results at eight Total Carbon Column Observing Network (TCCON) sites providing realistic error estimates of the satellite data. Such validation is a prerequisite to assess the suitability of data sets for their use in inverse modelling. It is shown that there are generally no significant differences between the carbon dioxide annual increases of SCIAMACHY and the assimilation system CarbonTracker (2.00 ± 0.16 ppm yr-1 compared to 1.94 ± 0.03 ppm yr-1 on global average). The XCO2 seasonal cycle amplitudes derived from SCIAMACHY are typically larger than those from TCCON which are in turn larger than those from CarbonTracker. The absolute values of the northern hemispheric TCCON seasonal cycle amplitudes are closer to SCIAMACHY than to CarbonTracker and the corresponding differences are not significant when compared with SCIAMACHY, whereas they can be significant for a subset of the analysed TCCON sites when compared with CarbonTracker. At Darwin we find discrepancies of the seasonal cycle derived from SCIAMACHY compared to the other data sets which can probably be ascribed to occurrences of undetected thin clouds. Based on the comparison with the reference data, we conclude that the carbon dioxide data set can be characterised by a regional relative precision (mean standard deviation of the differences) of about 2.2 ppm and a relative accuracy (standard deviation of the mean differences) of 1.1-1.2 ppm for monthly average composites within a radius of 500 km. For methane, prior to November 2005, the regional relative precision amounts to 12 ppb and the relative accuracy is about 3 ppb for monthly composite averages within the same radius. The loss of some spectral detector pixels results in a degradation of performance thereafter in the spectral range currently used for the methane column retrieval. This leads to larger scatter and lower XCH4 values are retrieved in the tropics for the subsequent time period degrading the relative accuracy. As a result, the overall relative precision is estimated to be 17 ppb and the relative accuracy is in the range of about 10-20 ppb for monthly averages within a radius of 500 km. The derived estimates show that the SCIAMACHY XCH4 data set before November 2005 is suitable for regional source/sink determination and regional-scale flux uncertainty reduction via inverse modelling worldwide. In addition, the XCO2 monthly data potentially provide valuable information in continental regions, where there is sparse sampling by surface flask measurements. © 2012 Author(s).

Jardine K.J.,University of Arizona | Monson R.K.,University of Arizona | Abrell L.,University of Arizona | Saleska S.R.,University of Arizona | And 11 more authors.
Global Change Biology | Year: 2012

Isoprene is emitted from many terrestrial plants at high rates, accounting for an estimated 1/3 of annual global volatile organic compound emissions from all anthropogenic and biogenic sources combined. Through rapid photooxidation reactions in the atmosphere, isoprene is converted to a variety of oxidized hydrocarbons, providing higher order reactants for the production of organic nitrates and tropospheric ozone, reducing the availability of oxidants for the breakdown of radiatively active trace gases such as methane, and potentially producing hygroscopic particles that act as effective cloud condensation nuclei. However, the functional basis for plant production of isoprene remains elusive. It has been hypothesized that in the cell isoprene mitigates oxidative damage during the stress-induced accumulation of reactive oxygen species (ROS), but the products of isoprene-ROS reactions in plants have not been detected. Using pyruvate-2- 13C leaf and branch feeding and individual branch and whole mesocosm flux studies, we present evidence that isoprene (i) is oxidized to methyl vinyl ketone and methacrolein (i ox) in leaves and that i ox/i emission ratios increase with temperature, possibly due to an increase in ROS production under high temperature and light stress. In a primary rainforest in Amazonia, we inferred significant in plant isoprene oxidation (despite the strong masking effect of simultaneous atmospheric oxidation), from its influence on the vertical distribution of i ox uptake fluxes, which were shifted to low isoprene emitting regions of the canopy. These observations suggest that carbon investment in isoprene production is larger than that inferred from emissions alone and that models of tropospheric chemistry and biota-chemistry-climate interactions should incorporate isoprene oxidation within both the biosphere and the atmosphere with potential implications for better understanding both the oxidizing power of the troposphere and forest response to climate change. © 2012 Blackwell Publishing Ltd.

Berg P.,Institute for Meteorology and Climate Research IMK TRO | Berg P.,Rossby Center | Wagner S.,Institute for Meteorology and Climate Research IMK IFU | Kunstmann H.,Institute for Meteorology and Climate Research IMK IFU | Schadler G.,Institute for Meteorology and Climate Research IMK TRO
Climate Dynamics | Year: 2013

A five-member ensemble of regional climate model (RCM) simulations for Europe, with a high resolution nest over Germany, is analysed in a two-part paper: Part I (the current paper) presents the performance of the models for the control period, and Part II presents results for near future climate changes. Two different RCMs, CLM and WRF, were used to dynamically downscale simulations with the ECHAM5 and CCCma3 global climate models (GCMs), as well as the ERA40-reanalysis for validation purposes. Three realisations of ECHAM5 and one with CCCma3 were downscaled with CLM, and additionally one realisation of ECHAM5 with WRF. An approach of double nesting was used, first to an approximately 50 km resolution for entire Europe and then to a domain of approximately 7 km covering Germany and its near surroundings. Comparisons of the fine nest simulations are made to earlier high resolution simulations for the region with the RCM REMO for two ECHAM5 realisations. Biases from the GCMs are generally carried over to the RCMs, which can then reduce or worsen the biases. The bias of the coarse nest is carried over to the fine nest but does not change in amplitude, i. e. the fine nest does not add additional mean bias to the simulations. The spatial pattern of the wet bias over central Europe is similar for all CLM simulations, and leads to a stronger bias in the fine nest simulations compared to that of WRF and REMO. The wet bias in the CLM model is found to be due to a too frequent drizzle, but for higher intensities the distributions are well simulated with both CLM and WRF at the 50 and 7 km resolutions. Also the spatial distributions are close to high resolution gridded observations. The REMO model has low biases in the domain averages over Germany and no drizzle problem, but has a shift in the mean precipitation patterns and a strong overestimation of higher intensities. The GCMs perform well in simulating the intensity distribution of precipitation at their own resolution, but the RCMs add value to the distributions when compared to observations at the fine nest resolution. © 2012 Springer-Verlag.

Wagner S.,Institute for Meteorology and Climate Research IMK IFU | Berg P.,Institute for Meteorology and Climate Research IMK TRO | Berg P.,Rossby Center | Schadler G.,Institute for Meteorology and Climate Research IMK TRO | Kunstmann H.,Institute for Meteorology and Climate Research IMK IFU
Climate Dynamics | Year: 2013

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971-2000) and future A1B scenario (2021-2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0. 8 and 1. 3 K with an average of 1. 1 K. For mean annual precipitation the climate change signal varies in the range of -2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly. © 2012 The Author(s).

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