3 resultados para U.S. Community College Model

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


Relevância:

100.00% 100.00%

Publicador:

Resumo:

This work investigates the eproducibility of precipitation simulated with an atmospheric general circulation model (AGCM) forced by subtropical South Atlantic sea surface temperature (SST) anomalies. This represents an important test of the model prior to investigating the impact of SSTs on regional climate. A five-member ensemble run was performed using the National Center for Atmospheric Research (NCAR) Community Climate Model, version 3 (CCM3). The CCM3 was forced by observed monthly SST over the South Atlantic from 20 to 60 S. The SST dataset used is from the Hadley Centre covering the period of September 1949-October 2001; this covers more than 50 yr of simulation. A statistical technique is used to determine the reproducibility in the CCM3 runs and to assess potential predictability in precipitation. Empirical orthogonal function analysis is used to reconstruct the ensemble using the most reproducible forced modes in order to separate the atmospheric response to local SST forcing from its internal variability. Results for reproducibility show a seasonal dependence, with higher values during austral autumn and spring. The spatial distribution of reproducibility shows that the tropical atmosphere is dominated by the underlying SSTs while variations in the subtropical-extratropical regions are primarily driven by internal variability. As such, changes in the South Atlantic convergence zone (SACZ) region are mainly dominated by internal atmospheric variability while the ITCZ has greater external dependence, making it more predictable. The reproducibility distribution reveals increased values after the reconstruction of the ensemble.

Relevância:

100.00% 100.00%

Publicador:

Resumo:

We report on charmonium measurements [J/psi (1S), psi' (2S), and chi(c) (1P)] in p + p collisions at root s = 200 GeV. We find that the fraction of J/psi coming from the feed-down decay of psi' and chi(c) in the midrapidity region (vertical bar y vertical bar < 0: 35) is 9.6 +/- 2.4% and 32 +/- 9%, respectively. We also present the p(T) and rapidity dependencies of the J/psi yield measured via dielectron decay at midrapidity (vertical bar y vertical bar < 0.35) and via dimuon decay at forward rapidity (1.2 < vertical bar y vertical bar < 2.2). The statistical precision greatly exceeds that reported in our previous publication [Phys. Rev. Lett. 98, 232002 (2007)]. The new results are compared with other experiments and discussed in the context of current charmonium production models.

Relevância:

100.00% 100.00%

Publicador:

Resumo:

This study aims to compare and validate two soil-vegetation-atmosphere-transfer (SVAT) schemes: TERRA-ML and the Community Land Model (CLM). Both SVAT schemes are run in standalone mode (decoupled from an atmospheric model) and forced with meteorological in-situ measurements obtained at several tropical African sites. Model performance is quantified by comparing simulated sensible and latent heat fluxes with eddy-covariance measurements. Our analysis indicates that the Community Land Model corresponds more closely to the micrometeorological observations, reflecting the advantages of the higher model complexity and physical realism. Deficiencies in TERRA-ML are addressed and its performance is improved: (1) adjusting input data (root depth) to region-specific values (tropical evergreen forest) resolves dry-season underestimation of evapotranspiration; (2) adjusting the leaf area index and albedo (depending on hard-coded model constants) resolves overestimations of both latent and sensible heat fluxes; and (3) an unrealistic flux partitioning caused by overestimated superficial water contents is reduced by adjusting the hydraulic conductivity parameterization. CLM is by default more versatile in its global application on different vegetation types and climates. On the other hand, with its lower degree of complexity, TERRA-ML is much less computationally demanding, which leads to faster calculation times in a coupled climate simulation.