Global Change Abstracts The Swiss Contribution - SCNAT

More documents

Recommendations

Info

152 Global Change Abstracts – The Swiss Contribution | Coupled Systems and Cycles the interannual variability of the BSWB data set in the investigated regions, but the different models sometimes display considerable discrepancies in the seasonal evolution of TWS. In particular, we find that all models suffer from a considerable underestimation of interannual TWS variability. The deviations of the individual models from the BSWB data set can be linked to biases in the hydrological fluxes (i.e., precipitation, runoff, evapotranspiration). The simulated future changes for the Intergovernmental Panel on Climate Change (IPCC) A2 scenario suggest an enhancement of the seasonal cycle of TWS, with drier soils in summer. Mainly in the Central European domain, several models show a reduction of the year-to-year variability of summer TWS variations, indicating an exhaustion of the models’ soil water reservoirs by the end of summer under future climatic conditions. Journal of Geophysical Research Atmospheres, 2007, V112, ND22, NOV 30 ARTN: D22109. 08.1-299 Evaluation of AMIP II global climate model simulations of the land surface water budget and its components over the GEWEX-CEOP regions Irannejad P, Henderson Sellers A Iran, Australia, Switzerland Meteorology & Atmospheric Sciences , Modelling , Hydrology The land surface water balance components simulated by 20 atmospheric global circulation models (AGCMs) participating in phase II of the Atmospheric Model Intercomparison Project (AMIP II) are analyzed globally and over seven Global Energy and Water Cycle Experiment Coordinated Enhanced Observing Period basins. In contrast to the conclusions from analysis of AMIP I, the results presented here suggest that the group average of available AGCMs does not outperform all individual AGCMs in simulating the surface water balance components. Analysis shows that the available reanalysis products are not appropriate for evaluation of AGCMs’ simulated land surface water components. The worst simulation of the surface water budget is in the Murray-Darling, the most arid basin, where all the reanalyses and seven of the AGCMs produce a negative surface water budget, with evaporation alone exceeding precipitation and soil moisture decreasing over the whole AMIP II period in this basin. The spatiotemporal correlation coefficients between observed and AGCM- simulated runoff are smaller than those for precipitation. In almost all basins (except for the two most arid basins), the spatiotemporal variations of the AGCMs’ simulated evaporation are more coherent and agree better with observations, compared to those of simulated precipitation. This suggests that differences among the AGCMs’ surface water budget predictions are not solely due to model- generated precipitation differences. Specifically, it is shown that different land surface parameterization schemes partition precipitation between evaporation and runoff differently and that this, in addition to the predicted differences in atmospheric forcings, is responsible for different predictions of basin-scale water budgets. The authors conclude that the selection of a land surface scheme for an atmospheric model has significant impacts on the predicted continental and basin-scale surface hydrology. Journal of Hydrometeorology, 2007, V8, N3, JUN, pp 304-326. 08.1-300 Comprehensive comparison of gap-filling techniques for eddy covariance net carbon fluxes Moffat A M, Papale D, Reichstein M, Hollinger D Y, Richardson A D, Barr A G, Beckstein C, Braswell B H, Churkina G, Desai A R, Falge E, Gove J H, Heimann M, Hui D, Jarvis A J, Kattge J, Noormets Asko, Stauch V J Germany, Italy, USA, Canada, England, Switzerland Modelling , Forestry , Plant Sciences , Agriculture, Soil Sciences We review 15 techniques for estimating missing values of net ecosystem CO 2 exchange (NEE) in eddy covariance time series and evaluate their performance for different artificial gap scenarios based on a set of 10 benchmark datasets from six forested sites in Europe. The goal of gap filling is the reproduction of the NEE time series and hence this present work focuses on estimating missing NEE values, not on editing or the removal of suspect values in these time series due to systematic errors in the measurements (e.g., nighttime flux, advection). The gap filling was examined by generating 50 secondary datasets with artificial gaps (ranging in length from single half- hours to 12 consecutive days) for each benchmark dataset and evaluating the performance with a variety of statistical metrics. The performance of the gap filling varied among sites and depended on the level of aggregation (native half-hourly time step versus daily), long gaps were more difficult to fill than short gaps, and differences among the techniques were more pronounced during the day than at night. The non-linear regression techniques (NLRs), the look-up table (LUT), marginal distribution sampling (MDS), and the semiparametric model (SPM) generally showed good overall performance. The
Global Change Abstracts – The Swiss Contribution | Coupled Systems and Cycles artificial neural network based techniques (ANNs) were generally, if only slightly, superior to the other techniques. The simple interpolation technique of mean diurnal variation (MDV) showed a moderate but consistent performance. Several sophisticated techniques, the dual unscented Kalman filter (UKF), the multiple imputation method (MIM), the terrestrial biosphere model (BETHY), but also one of the ANNs and one of the NLRs showed high biases which resulted in a low reliability of the annual sums, indicating that additional development might be needed. An uncertainty analysis comparing the estimated random error in the 10 benchmark datasets with the artificial gap residuals suggested that the techniques are already at or very close to the noise limit of the measurements. Based on the techniques and site data examined here, the effect of gap filling on the annual sums of NEE is modest, with most techniques falling within a range of +/- 25 g C m(-2) year(-1.) Agricultural and Forest Meteorology, 2007, V147, N3-4, DEC 10, pp 209-232. 08.1-301 Impact of circulation on export production, dissolved organic matter, and dissolved oxygen in the ocean: Results from Phase II of the Ocean Carbon-cycle Model Intercomparison Project (OCMIP-2) Najjar R G, Jin X, Louanchi F, Aumont O, Caldeira K, Doney S C, Dutay J C, Follows M, Gruber N, Joos F, Lindsay K, Maier Reimer E, Matear R J, Matsumoto K, Monfray P, Mouchet A, Orr J C, Plattner G K, Sarmiento J L, Schlitzer R, Slater R D, Weirig M F, Yamanaka Y, Yool A USA, France, Switzerland, Algeria, Germany, Australia, Belgium, Japan, England Modelling , Oceanography , Geochemistry & Geophysics Results are presented of export production, dissolved organic matter (DOM) and dissolved oxygen simulated by 12 global ocean models participating in the second phase of the Ocean Carbon-cycle Model Intercomparison Project. A common, simple biogeochemical model is utilized in different coarse-resolution ocean circulation models. The model mean (+/- 1 sigma) downward flux of organic matter across 75 m depth is 17 +/- 6 Pg C yr(-1). Model means of globally averaged particle export, the fraction of total export in dissolved form, surface semilabile dissolved organic carbon (DOC), and seasonal net outgassing (SNO) of oxygen are in good agreement with observation- based estimates, but particle export and surface DOC are 153 too high in the tropics. There is a high sensitivity of the results to circulation, as evidenced by (1) the correlation of surface DOC and export with circulation metrics, including chlorofluorocarbon inventory and deep-ocean radiocarbon, (2) very large intermodel differences in Southern Ocean export, and (3) greater export production, fraction of export as DOM, and SNO in models with explicit mixed layer physics. However, deep-ocean oxygen, which varies widely among the models, is poorly correlated with other model indices. Crossmodel means of several biogeochemical metrics show better agreement with observation-based estimates when restricted to those models that best simulate deep-ocean radiocarbon. Overall, the results emphasize the importance of physical processes in marine biogeochemical modeling and suggest that the development of circulation models can be accelerated by evaluating them with marine biogeochemical metrics. Global Biogeochemical Cycles, 2007, V21, N3, AUG 8 ARTN: GB3007. 08.1-302 Experimental assessment of N 2O background fluxes in grassland systems Neftel A, Flechard C, Ammann C, Conen F, Emmenegger L, Zeyer K Switzerland Agriculture, Soil Sciences , Meteorology & Atmospheric Sciences In the absence of, or between, fertilization events in agricultural systems, soils are generally assumed to emit N 2O at a small rate, often described as the ‘background’ flux. In contrast, net uptake of N 2O by soil has been observed in many field studies, but has not gained much attention. Observations of net uptake of N 2O form a large fraction (about half) of all individual flux measurements in a long- term time series at our temperate fertilized grassland site. Individual uptake fluxes from chamber measurements are often not statistically significant but mean values integrated over longer time periods from days to weeks do show a clear uptake. An analysis of semi- continuous chamber flux data in conjunction with continuous measurements of the N 2O concentration in the soil profile and eddy covariance measurements suggests that gross production and gross consumption of N 2O are of the same order, and as consequence only a minor fraction of N 2O molecules produced in the soil reaches the atmosphere. Tellus Series B Chemical and Physical Meteorology, 2007, V59, N3, JUL, pp 470-482.
Page 1 and 2:
Global Change Abstracts The Swiss C
Page 3 and 4:
Global Change Abstracts - The Swiss
Page 5 and 6:
Page 7 and 8:
Page 9 and 10:
Page 11 and 12:
Page 13 and 14:
Page 15 and 16:
Page 17 and 18:
Page 19 and 20:
Page 21 and 22:
Page 23 and 24:
Page 25 and 26:
Page 27 and 28:
Page 29 and 30:
Page 31 and 32:
Page 33 and 34:
Page 35 and 36:
Page 37 and 38:
Page 39 and 40:
Page 41 and 42:
Page 43 and 44:
Page 45 and 46:
Page 47 and 48:
Page 49 and 50:
Page 51 and 52:
Page 53 and 54:
Page 55 and 56:
Page 57 and 58:
Page 59 and 60:
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102: Global Change Abstracts - The Swiss
Page 151: Global Change Abstracts - The Swiss
Page 203 and 204:
Page 205 and 206:
Page 207 and 208:
Page 209 and 210:
Page 211 and 212:
Page 213 and 214:
Page 215 and 216:
Page 217 and 218:
Page 219 and 220:
Page 221 and 222:
Page 223 and 224:
Page 225 and 226:
Page 227 and 228:
Page 229 and 230:
Page 231 and 232:
Page 233 and 234:
show all

Global Change Abstracts The Swiss Contribution - SCNAT

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?