Molecular Line Parameters for the “MASTER” (Millimeter Wave Acquisitions for Stratosphere/Troposphere Exchange Research) Database

In order to investigate the upper troposphere/lower stratosphere (UTLS) region of the earth's atmosphere, ESA/ESTEC (European space agency) is considering the opportunity to develop the spaceborne limb sounding millimeter sensor “MASTER” (millimeter wave acquisitions for stratosphere/troposphere exchange research). This instrument is part of the “atmospheric composition explorer for chemistry and climate interactions” (ACECHEM) project. In addition, ESA/ESTEC is developing the “MARSCHALS” (millimeter-wave airborne receiver for spectroscopic characterization of atmospheric limb sounding) airborne instrument which will demonstrate the feasibility of MASTER. The present paper describes the line-by-line database which was generated in order to meet at best the needs of the MASTER (or MARSCHALS) instrument. The linelist involves line positions, line intensities, line broadening and line shift parameters in the 294–305, 316–325, 342–348, 497–506 and 624–626 GHz spectral microwindows. This database was first generated for the target molecules for MASTER (H₂O, O₃, N₂O, CO, O₂, HNO₃, HCl, ClO, CH₃Cl, BrO). In addition, ten additional molecules (SO₂, NO₂, OCS, H₂CO, HOCl, HCN, H₂O₂, COF₂, HO₂ and HOBr) had also to be considered in the database as “possible interfering species” for the retrieval of the target molecules of MASTER. The line parameters were derived, depending on their estimated accuracy, (i) from a combination of spectral parameters included in the JPL and HITRAN catalogs (ii) from data taken into the literature or (iii) using data obtained through experimental measurements (and/or) calculations performed during the present study.     

Predictions of the maximum amplitude for solar cycle 23 and its subsequent behavior using nonlinear methods

Two nonlinear methods are employed for the prediction of the maximum amplitude for solar cycle 23 and its declining behavior. First, a new heuristic method based on the second derivative of the (conveniently smoothed) sunspot data is proposed. The curvature of the smoothed sunspot data at cycle minimum appears to correlate (R 0.92) with the cycle's later-occurring maximum amplitude. Secondly, in order to predict the near-maximum and declining activity of solar cycle 23, a neural network analysis of the annual mean sunspot time series is also performed. The results of the present study are then compared with some other recent predictions.     

Secular Behavior of Solar Magnetic Activity: Nonstationary Time-Series Analysis of the Sunspot Record

The sunspot record of solar magnetic activity is studied as a nonstationary time series by means of a previously developed algorithm for treating perturbed dynamical systems. This approach incorporates secular changes into the modeling process through an external driving parameter, whose temporal behavior is shown to correspond in this case to the long-term trend of the sunspot record. Our method is able to reduce by approximately 13% the prediction error of this series when compared to the standard stationary approach. Such a reduction is remarkable in view of the benchmark status of the sunspot record in the statistical literature and, moreover, the fact that this gain is obtained over the performance of an already very competitive modeling technique based on ensembles of artificial neural networks.