73,209 research outputs found
MPI-ESM1.2-LR P2k+ with a deep version of JSBACH (MPI-ESM P2k+d)
No full text<p>This dataset corresponds to the following publication:</p><p>García-Pereira, F. et al. (2023): "First comprehensive assessment of industrial era land heat uptake from multiple sources". Submittted to Earth System Dynamics.</p><p>The dataset includes surface air temperature at 2 m (SAT) and subsurface temperature (soilTs) yearly information for a Past2k (0-1850) simulation extended to the historical period (1850-2014) and SSP585 climate change scenario (2015-2100, P2k+) conducted with a modified version of the CMIP6 low-resolution Earth System Model of the Max Planck Institute for Meteorology, the MPI-ESM1.2-LR (Mauritsen et al., 2019). MPI-ESM1.2 comprises the ocean model MPIOM1.6 and the atmosphere model ECHAM6.3 (Stevens et al., 2013). The latter is directly coupled to the Land Surface Model JSBACH3.2 (Reick et al., 2021) through the surface exchange of mass, momentum, and heat. The low-resolution configuration (MPI-ESM1.2-LR) has an atmospheric horizontal resolution truncated to T63, corresponding approximately to a 200-km grid cell size. This resolution is shared by the LSM. The standard shallow 5-layer vertical discretization of JSBACH3.2 (bottom boundary ca. 10 m) is modified to a much deeper 12-layer configuration (bottom boundary ca. 1400 m), following González-Rouco et al. (2021).</p><p>Additionally to the SAT and soilTs data, the land mask, and the global gridded maps of soil volumetric heat capacity (soilhcap) and diffusivity (soilhdiff) used by JSBACH are included.</p><p> </p><p>REFERENCES</p><p>González-Rouco, J. F., Steinert, N. J., García-Bustamante, E., Hagemann, S., de Vrese, P., Jungclaus, J. H., Lorenz, S. J., Melo-Aguilar, C., García-Pereira, F., and Navarro, J.: Increasing the Depth of a Land Surface Model. Part I: Impacts on the Subsurface Thermal Regime and Energy Storage, Journal of Hydrometeorology, 22, 3211 – 3230, https://doi.org/10.1175/JHM-D-21-0024.1, 2021.</p><p>Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R., Brovkin, V., Claussen, M., Crueger, T., Esch, M., Fast, I., Fiedler, S., Fläschner, D., Gayler, V., Giorgetta, M., Goll, D. S., Haak, H., Hagemann, S., Hedemann, C., Hohenegger, C., Ilyina, T., Jahns, T., Jimenéz-de-la Cuesta, D., Jungclaus, J., Kleinen, T., Kloster, S., Kracher, D., Kinne, S., Kleberg, D., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Möbis, B., Müller, W. A., Nabel, J. E. M. S., Nam, C. C. W., Notz, D., Nyawira, S.-S., Paulsen, H., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J., Popp, M., Raddatz, T. J., Rast, S., Redler, R., Reick, C. H., Rohrschneider, T., Schemann, V., Schmidt, H., Schnur, R., Schulzweida, U., Six, K. D., Stein, L., Stemmler, I., Stevens, B., von Storch, J.-S., Tian, F., Voigt, A., Vrese, P., Wieners, K.-H., Wilkenskjeld, S., Winkler, A., and Roeckner, E.: Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and Its Response to Increasing CO2, Journal of Advances in Modeling Earth Systems, 11, 998–1038, https://doi.org/10.1029/2018MS001400, 2019.</p><p>Reick, C. H., Gayler, V., Goll, D., Hagemann, S., Heidkamp, M., Nabel, J. E. M. S., Raddatz, T., Roeckner, E., Schnur, R., and Wilkenskjeld, S.: JSBACH 3 - The land component of the MPI Earth System Model: documentation of version 3.2, Hamburg: MPI für Meteorologie, https://doi.org/10.17617/2.3279802, 2021.</p><p>Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric component of the MPI-M Earth System Model: ECHAM6, Journal of Advances in Modeling Earth Systems, 5, 146–172, https://doi.org/10.1002/jame.20015, 2013.</p><p> </p><p>For any questions regarding the dataset, please free feel to contact Félix García-Pereira ([email protected])</p><p>Acknowledgement</p><p>We thank the Deutsches Klimarechenzentrum (DKRZ) for the resources granted by its Scientific Steering Committee (WLA) to run MPI-ESM1.2-LR P2k+ deep simulation under project ID bm1026 (PI: Johann Jungclaus).</p>
Ontogeny of upper beakin Octopus vulgaris Cuvier, 1797
No full textWe describe for the first time the formation of upper beak in Octopus vulgaris from embryonic stage XIV (Naef, 1928) up to paralarval stage, focusing on the main regions used for age estimation and assessing the presence of any pre-hatching increments in the beak microstructur
Evidence for the decay B0→J/ψω and measurement of the relative branching fractions of meson decays to J/ψη and J/ψη′
No full textFirst evidence of the B 0 → J / ψ ω decay is found and the B s 0 → J / ψ η and B s 0 → J / ψ η ′ decays are studied using a dataset corresponding to an integrated luminosity of 1.0 fb -1 collected by the LHCb experiment in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV. The branching fractions of these decays are measured relative to that of the B 0 → J / ψ ρ 0 decay:frac(B (B 0 → J / ψ ω), B (B 0 → J / ψ ρ 0)) = 0.89 ± 0.19 (stat) - 0.13 + 0.07 (syst),frac(B (B s 0 → J / ψ η), B (B 0 → J / ψ ρ 0)) = 14.0 ± 1.2 (stat) - 1.5 + 1.1 (syst) - 1.0 + 1.1 (frac(f d, f s)),frac(B (B s 0 → J / ψ η ′), B (B 0 → J / ψ ρ 0)) = 12.7 ± 1.1 (stat) - 1.3 + 0.5 (syst) - 0.9 + 1.0 (frac(f d, f s)), where the last uncertainty is due to the knowledge of f d / f s, the ratio of b-quark hadronization factors that accounts for the different production rate of B 0 and B s 0 mesons. The ratio of the branching fractions of B s 0 → J / ψ η ′ and B s 0 → J / ψ η decays is measured to befrac(B (B s 0 → J / ψ η ′), B (B s 0 → J / ψ η)) = 0.90 ± 0.09 (stat) - 0.02 + 0.06 (syst)
Letter from Carl Hayden to M. J. Riordan
No full textLetter from Carl Hayden to M. J. Riordan expressing his support for Coconino County in turning over the Bright Angel Trail to the federal government
Letter from M. J. Riordan, Arizona Lumber and Timber Company, to Carl Hayden
No full textLetter from M. J. Riordan to Carl Hayden expressing his opposition to the federal government's takeover of Bright Angel Trail
Post-Columbian environmental history of Lago Petén Itzá, Guatemala. Revista Mexicana de Ciencias Geológicas
No full textABSTRACT Two ~40-cm-long sediment cores, Revista Mexicana de Ciencias Geológicas, v. 27, núm. 3, 2010, p. 490-507 Pérez, L., Bugja, R., Massaferro, J., Steeb, P., van Geldern, R., Frenzel,. P, Brenner, M., Scharf, B., Schwalb, A., 2010, Post-Columbian environmental history of Lago Petén Itzá, Guatemala: Revista Mexicana de Ciencias Geológicas, v. 27, núm. 3, p. 490-507. Post-Columbian environmental history of Lago Petén Itzá, Guatemala 491 RESUMEN Dos núcleos de sedimentos PI-SC-1-10m y PI-SC-2-40m de 40 cm de largo fueron extraídos bajo un tirante de agua de 10 y 40 m en el Lago Petén Itzá, Departamento de Petén, en el norte de Guatemala. Los núcleos abarcan los pasados ~525 años de acumulación de sedimentos en el lago. Este estudio explora los cambios en los niveles del lago y cambios en el estado trófico que el Lag
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Lee Govatos as a guest at mar-a Lago,Palm Brach residence of Marjorie Merriweather Post/Donald J. Trump
No full textLee Govatos as a guest at mar-a Lago,Palm Brach residence of Marjorie Merriweather Post/Donald J. Trum
Compact and Tractable Automaton-based Representations for Time Granularities
No full textMost approaches to time granularity proposed in the literature are based on algebraic and logical formalisms [J. Euzenat, A.
Montanari, Time granularity, in: M. Fisher, D. Gabbay, L. Vila (Eds.), Handbook of Temporal Reasoning in Artificial Intelligence,
Elsevier, 2005, pp. 59–118]. Here we follow an alternative automaton-based approach, originally outlined in [U. Dal Lago,
A. Montanari, Calendars, time granularities, and automata, in: Proceedings of the 7th International Symposium on Spatial and
Temporal Databases, SSTD, in: LNCS, vol. 2121, Springer, 2001, pp. 279–298], which makes it possible to deal with infinite time
granularities in an effective and efficient way. Such an approach provides a neat solution to fundamental algorithmic problems, such as the granularity equivalence and granule conversion problems, which have been often neglected in the literature. In this paper, we focus our attention on two basic optimization problems for the automaton-based representation of time granularities, namely, the problem of computing the smallest representation of a time granularity and that of computing the most tractable representation of it, that is, the one on which crucial algorithms, such as granule conversion algorithms, run fastest
Measurement of the time-dependent CP asymmetry in B0 -> J/ψ KS0 decays
No full textThis Letter reports a measurement of the CP violation observables SJ/ψK0S and CJ/ψK0S in the decay channel B0→J/ψK0S performed with 1.0 fb−1 of pp collisions at s√=7 TeV collected by the LHCb experiment. The fit to the data yields SJ/ψK0S=0.73±0.07(stat)±0.04(syst) and CJ/ψK0S=0.03±0.09(stat)±0.01(syst). Both values are consistent with the current world averages and within
expectations from the Standard Model
Compact and Tractable Automaton−based Representations for Time Granularities
No full textAbstractMost approaches to time granularity proposed in the literature are based on algebraic and logical formalisms [J. Euzenat, A. Montanari, Time granularity, in: M. Fisher, D. Gabbay, L. Vila (Eds.), Handbook of Temporal Reasoning in Artificial Intelligence, Elsevier, 2005, pp. 59–118]. Here we follow an alternative automaton-based approach, originally outlined in [U. Dal Lago, A. Montanari, Calendars, time granularities, and automata, in: Proceedings of the 7th International Symposium on Spatial and Temporal Databases, SSTD, in: LNCS, vol. 2121, Springer, 2001, pp. 279–298], which makes it possible to deal with infinite time granularities in an effective and efficient way. Such an approach provides a neat solution to fundamental algorithmic problems, such as the granularity equivalence and granule conversion problems, which have been often neglected in the literature. In this paper, we focus our attention on two basic optimization problems for the automaton-based representation of time granularities, namely, the problem of computing the smallest representation of a time granularity and that of computing the most tractable representation of it, that is, the one on which crucial algorithms, such as granule conversion algorithms, run fastest
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