Characterizing Ecosystem-Atmosphere Interactions from Short to Interannual Time Scales

Characterizing ecosystem-atmosphere interactions in terms of carbon and water exchange on different time scales is considered a major challenge in terrestrial biogeochemical cycle research. The respective time series are now partly comprising an observation 5 period of one decade. In this study, we explored whether the observation period is already sufficient to detect cross relationships of the variables beyond the annual cycle as they are expected from comparable studies in climatology. We explored the potential of Singular System Analysis (SSA) to extract arbitrary kinds of oscillatory patterns. The method is completely data adaptive and performs an 10 effective signal to noise separation. We found that most observations (NEE, GP P , Reco, V P D, LE, H, u, P ) were influenced significantly by low frequency components (interannual variability). Furthermore we extracted a set of nonlinear relationships and found clear annual hysteresis effects except for the NEE-Rg relationship which turned out to be the sole linear relationship 15 in the observation space. SSA provides a new tool to investigate these phenomena explicitly on different time scales. Furthermore, we showed that SSA has great potential for eddy covariance data processing since it can be applied as novel gap fillingapproach relying on the temporal time series structure only.JRC.H.2-Climate chang

Diagnosing modeling errors of global terrestrial water storage interannual variability

Terrestrial water storage (TWS) is an integrative hydrological state that is key for our understanding of the global water cycle. The TWS observation from the GRACE missions has, therefore, been instrumental in the calibration and validation of hydrological models and understanding the variations in the hydrological storage. The models, however, still show significant uncertainties in reproducing observed TWS variations, especially for the interannual variability (IAV) at the global scale. Here, we diagnose the regions dominating the variance in globally integrated TWS IAV and the sources of the errors in two data-driven hydrological models that were calibrated against global TWS, snow water equivalent, evapotranspiration, and runoff data. We used (1) a parsimonious process-based hydrological model, the Strategies to INtegrate Data and BiogeochemicAl moDels (SINDBAD) framework and (2) a machine learning, physically based hybrid hydrological model (H2M) that combines a dynamic neural network with a water balance concept. While both models agree with the Gravity Recovery and Climate Experiment (GRACE) that global TWS IAV is largely driven by the semi-arid regions of southern Africa, the Indian subcontinent and northern Australia, and the humid regions of northern South America and the Mekong River basin, the models still show errors such as the overestimation of the observed magnitude of TWS IAV at the global scale. Our analysis identifies modeling error hotspots of the global TWS IAV, mostly in the tropical regions including the Amazon, sub-Saharan regions, and Southeast Asia, indicating that the regions that dominate global TWS IAV are not necessarily the same as those that dominate the error in global TWS IAV. Excluding those error hotspot regions in the global integration yields large improvements in the simulated global TWS IAV, which implies that model improvements can focus on improving processes in these hotspot regions. Further analysis indicates that error hotspot regions are associated with lateral flow dynamics, including both sub-pixel moisture convergence and across-pixel lateral river flow, or with interactions between surface processes and groundwater. The association of model deficiencies with land processes that delay the TWS variation could, in part, explain why the models cannot represent the observed lagged response of TWS IAV to precipitation IAV in hotspot regions that manifest as errors in global TWS IAV. Our approach presents a general avenue to better diagnose model simulation errors for global data streams to guide efficient and focused model development for regions and processes that matter the most.</p

Characterizing ecosystem-atmosphere interactions from short to interannual time scales

International audienceCharacterizing ecosystem-atmosphere interactions in terms of carbon and water exchange on different time scales is considered a major challenge in terrestrial biogeochemical cycle research. The respective time series currently comprise an observation period of up to one decade. In this study, we explored whether the observation period is already sufficient to detect cross-relationships between the variables beyond the annual cycle, as they are expected from comparable studies in climatology. We investigated the potential of Singular System Analysis (SSA) to extract arbitrary kinds of oscillatory patterns. The method is completely data adaptive and performs an effective signal to noise separation. We found that most observations (Net Ecosystem Exchange, NEE, Gross Primary Productivity, GPP, Ecosystem Respiration, Reco, Vapor Pressure Deficit, VPD, Latent Heat, LE, Sensible Heat, H, Wind Speed, u, and Precipitation, P) were influenced significantly by low-frequency components (interannual variability). Furthermore, we extracted a set of nontrivial relationships and found clear seasonal hysteresis effects except for the interrelation of NEE with Global Radiation (Rg). SSA provides a new tool for the investigation of these phenomena explicitly on different time scales. Furthermore, we showed that SSA has great potential for eddy covariance data processing, since it can be applied as a novel gap filling approach relying on the temporal correlation structure of the time series structure only

Total Photoabsorption Cross Sections of A=6 Nuclei with Complete Final State Interaction

The total photoabsorption cross sections of 6He and 6Li are calculated microscopically with full inclusion of the six-nucleon final state interaction using semirealistic nucleon-nucleon potentials. The Lorentz Integral Transform (LIT) method and the effective interaction approach for the hyperspherical formalism are employed. While 6Li has a single broad giant resonance peak, there are two well separated peaks for 6He corresponding to the breakup of the neutron halo and the alpha core, respectively. The comparison with the few available experimental data is discussed.Comment: LaTeX, 8 pages, 3 ps figure

Fields of definition for division algebras

Abstract Let A be a finite-dimensional division algebra containing a base field k in its center F. A is defined over a subfield F 0 if there exists an F 0 -algebra A 0 such that A = A 0 F 0 F. The following are shown. (i) In many cases A can be defined over a rational extension of k. (ii) If A has odd degree n &gt; 5, then A is defined over a field F 0 of transcendence degree 6 1 2 (n − 1)(n − 2) over k. (iii) If A is a Z/m × Z/2-crossed product for some m &gt; 2 (and in particular, if A is any algebra of degree 4) then A is Brauer equivalent to a tensor product of two symbol algebras. Consequently, M m (A) can be defined over a field F 0 such that trdeg k (F 0 ) 6 4. (iv) If A has degree 4 then the trace form of A can be defined over a field F 0 of transcendence degree 6 4. (In (i), (iii) and (iv) it is assumed that the center of A contains certain roots of unity.

Comparison of 3D transitional CFD simulations for rotating wind turbine wings with measurements:Paper

Since the investigation of van Ingen et al., attempts were undertaken to search for laminar parts within the boundary layer of wind turbines operating in the lower atmosphere with much higher turbulence levels than seen in wind tunnels or at higher altitudes where airplanes usually fly. Based on the results of the DAN-Aero experiment and the Aerodynamic Glove project, a special work package Boundary Layer Transition was embedded in IAEwind Task 29 MexNext 3rd phase (MN3). Here, we report on the results of the application of various CFD tools to predict transition on the MEXICO blade. In addition, recent results from a comparison of thermographic pictures (aimed at detecting transition) with 3D transitional CFD are included as well. The MEXICO (2006) and NEW MEXICO (2014) wind tunnel experiments on a turbine equipped with three 2.5 m blades have been described extensively in the literature. In addition, during MN3, high-frequency Kulite data from experiments were used to detect traces of transitional effects. Complementary, the following set of codes were applied to cases 1.1 and 1.2 (axial inflow with 10 m/s and 15 m/s respectively) – elsA, CFX, OpenFOAM (with 2 different turbulence/transitional models), Ellipsys, (with 2 different turbulence models and eN transition prediction tool), FLOWer and TAU – to search for detection of laminar parts by means of simulation. Obviously, the flow around a rotating blade is much more complicated than around a simple 2D section. Therefore, results for even integrated quantities like thrust and torque are varying strongly. Nevertheless, visible differences between fully turbulent and transitional set-ups are present. We discuss our findings, especially with respect to turbulence and transition models used

Occupation probability of harmonic-oscillator quanta for microscopic cluster-model wave functions

We present a new and simple method of calculating the occupation probability of the number of total harmonic-oscillator quanta for a microscopic cluster-model wave function. Examples of applications are given to the recent calculations including $\alpha+n+n$-model for $^6$He, $\alpha+t+n+n$-model for $^9$Li, and $\alpha+\alpha+n$-model for $^9$Be as well as the classical calculations of $\alpha+p+n$-model for $^6$Li and $\alpha+\alpha+\alpha$-model for $^{12}$C. The analysis is found to be useful for quantifying the amount of excitations across the major shell as well as the degree of clustering. The origin of the antistretching effect is discussed.Comment: 9 page