Parameter estimation of GOES precipitation index at different calibration timescales

We examined two techniques that adjust the parameters of the GOES Precipitation Index (GPI) by combining the polar microwave and the geosynchronous infrared observations at three frequencies: daily, pentad, and monthly. The first technique is the adjusted GPI (AGPI), and the second is the universally adjusted GPI (UAGPI). The study shows that rainfall estimates can be improved by frequent calibrations providing there is sufficient superior (microwave) rainfall sampling within the calibration time and space domain. For this work, daily and pentad calibrations produce monthly rainfall estimates almost as good as monthly calibration. The daily calibration produced better daily rainfall estimates than pentad and monthly calibration, but it generates similar pentad rainfall estimates to these of the pentad calibration. The monthly calibrated scheme is not suitable for the daily and pentad rainfall estimates. Under the current twice-per-day sampling rate of polar-orbiting microwave observations, the pentad calibration scheme is suggested for the monthly, pentad, and daily rainfall. The potentials of applying the UAGPI and the AGPI techniques for daily rainfall estimation are also investigated. Copyright 2000 by the American Geophysical Union

Antiproton-Proton Channels in J/psi Decays

The recent measurements by the BES Collaboration of J/psi decays into a photon and a proton-antiproton pair indicate a strong enhancement at the proton-antiproton threshold not observed in the decays into a neutral pion and a proton-antiproton pair. Is this enhancement due to a proton-antiproton quasi-bound state or a baryonium? A natural explanation follows from a traditional model of proton-antiproton interactions based on G-parity transformation. The observed proton-antiproton structure is due to a strong attraction in the 1S0 state, and possibly to a near-threshold quasi-bound state in the 11S0 wave.Comment: 6 pages, 5 figures. The antiproton-proton pair being in isospin one in the J/Psi decay into neutral pion-antiproton-proton, the antiproton-proton 1P1 and 3S1 waves have been replaced by the 31P1 and 33S1 ones and Figs. 1 and 2 have been replaced accordingly. Conclusions are unchanged. Most of the content of the paper is published in Phys. Rev. C72, 011001 (2005

A chaotic approach to rainfall disaggregation

The importance of high-resolution rainfall data to understanding the intricacies of the dynamics of hydrological processes and describing them in a sophisticated and accurate way has been increasingly realized. The last decade has witnessed a number of studies and numerous approaches to the possibility of transformation of rainfall data from one scale to another, nearly unanimously pointing to such a possibility. However, an important limitation of such approaches is that they treat the rainfall process as a realization of a stochastic process, and therefore there seems to be a lack of connection between the structure of the models and the underlying physics of the rainfall process. The present study introduces a new framework based on the notion of deterministic chaos to investigate the behavior of the dynamics of rainfall transformation between different temporal scales aimed toward establishing this connection. Rainfall data of successively doubled resolutions (i.e., 6, 12, 24, 48, 96, and 192 hours) observed at Leaf River basin, in the state of Mississippi, United States of America, are studied. The correlation dimension method is employed to investigate the presence of chaos in the rainfall transformation. The finite and low correlation dimensions obtained for the distributions of weights between rainfall data of different scales indicate the existence of chaos in the rainfall transformation, suggesting the applicability of a chaotic model. The formulation of a simple chaotic disaggregation model and its application to the Leaf River rainfall data provides encouraging results with practical potential. The disaggregation model results themselves indicate the presence of chaos in the dynamics of rainfall transformation, providing support for the results obtained using the correlation dimension method

Self-organizing linear output map (SOLO): An artificial neural network suitable for hydrologic modeling and analysis

Artificial neural networks (ANNs) can be useful in the prediction of hydrologic variables, such as streamflow, particularly when the underlying processes have complex nonlinear interrelationships. However, conventional ANN structures suffer from network training issues that significantly limit their widespread application. This paper presents a multivariate ANN procedure entitled self-organizing linear output map (SOLO), whose structure has been designed for rapid, precise, and inexpensive estimation of network structure/parameters and system outputs. More important, SOLO provides features that facilitate insight into the underlying processes, thereby extending its usefulness beyond forecast applications as a tool for scientific investigations. These characteristics are demonstrated using a classic rainfall-runoff forecasting problem. Various aspects of model performance are evaluated in comparison with other commonly used modeling approaches, including multilayer feedforward ANNs, linear time series modeling, and conceptual rainfall-runoff modeling

Possible Σ(12−)\Sigma({1\over2}^-) under the Σ∗(1385)\Sigma^*(1385) peak in KΣ∗K\Sigma^* photoproduction

The LEPS collaboration has recently reported a measurement of the reaction $\gamma n\to K^+\Sigma^{*-}(1385)$ with linearly polarized photon beam at resonance region. The observed beam asymmetry is sizably negative at $E_\gamma=1.8-2.4 \mathrm{GeV}$, in contrast to the presented theoretical prediction. In this paper, we calculate this process in the framework of the effective Lagrangian approach. By including a newly proposed $\Sigma(J^P={1\over2}^-)$ state with mass around 1380~MeV, the experimental data for both $\gamma n$ and $\gamma p$ experiments can be well reproduced. It is found that the $\Sigma({1\over2}^-)$ and/or the contact term may play important role and deserve further investigation.Comment: modified version to be published at Phys. Rev.