358 resultados para satellite nests

em Publishing Network for Geoscientific


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CFC-11 (CCl3F), CFC-12 (CCl2F2), HF, and SF6 products from limb-viewing satellite instruments are provided in the form of monthly zonal mean time series obtained from HALOE, MIPAS, ACE-FTS, and HIRDLS within the time period 1991-2010. The data products are made available as part of the Stratosphere-troposphere Processes And their Role in Climate (SPARC) Data Initiative. The trace gas time series extend from the mid-troposphere to as high as the mesosphere. The zonal monthly mean time series are calculated on the SPARC Data Initiative climatology grid using 5° latitude bins and 28 pressure levels. The zonal monthly mean volume mixing ratio (VMR) and the standard deviation along with the number of averaged data values are given for each month, latitude bin, and pressure level. Furthermore, the mean, minimum, and maximum local solar time, the average latitude, and the average day of the month within each bin for one selected pressure level are provided. The time series of all variables are saved in a consistent netcdf format.

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Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography-the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99-110, 2012, doi:10.1016/j.jog.2011.07.0069; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie, 2012, http://nbn-resolving.de/nbn:de:hbz:5n-29199). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the geodetically derived mean dynamic topography with the full error structure in a 3D stationary inverse ocean model improves modeled oceanographic features over previous estimates.

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EOT11a is a global (E)mpirical (O)cean (T)ide model derived in 2011 by residual analysis of multi-mission satellite (a)ltimeter data. EOT11a includes amplitudes and phases of the main astronomical tides M2, S2, N2, K2, 2N2, O1, K1, P2, and Q1, the non-linear constituent M4, the long period tides Mm and Mf, and the radiational tide S1. Ocean tides as well as loading tides are provided. EOT11a was computed by means of residual tidal analysis of multi-mission altimeter data from TOPEX/Poseidon, ERS-2, ENVISAT, and Jason-1/2, as far as acquired between September 1992 and April 2010. The resolution of 7.5'x7.5' is identical with FES2004 which was used as reference model for the residual tide analysis. The development of EOT11a was funded by the Deutsche Forschungsgemeinschaft (DFG) under grant BO1228/6-2.