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Atmospheric Fields (atmospheric + field)

Distribution by Scientific Domains

Earth and Environmental Science	60%

Selected Abstracts

Statistical downscaling of daily precipitation from observed and modelled atmospheric fields

HYDROLOGICAL PROCESSES, Issue 8 2004
Stephen P. Charles
Abstract Statistical downscaling techniques have been developed to address the spatial scale disparity between the horizontal computational grids of general circulation models (GCMs), typically 300,500 km, and point-scale meteorological observations. This has been driven, predominantly, by the need to determine how enhanced greenhouse projections of future climate may impact at regional and local scales. As point-scale precipitation is a common input to hydrological models, there is a need for techniques that reproduce the characteristics of multi-site, daily gauge precipitation. This paper investigates the ability of the extended nonhomogeneous hidden Markov model (extended-NHMM) to reproduce observed interannual and interdecadal precipitation variability when driven by observed and modelled atmospheric fields. Previous studies have shown that the extended-NHMM can successfully reproduce the at-site and intersite statistics of daily gauge precipitation, such as the frequency characteristics of wet days, dry- and wet-spell length distributions, amount distributions, and intersite correlations in occurrence and amounts. Here, the extended-NHMM, as fitted to 1978,92 observed ,winter' (May,October) daily precipitation and atmospheric data for 30 rain gauge sites in southwest Western Australia, is driven by atmospheric predictor sets extracted from National Centers for Environmental Prediction,National Center for Atmospheric Research reanalysis data for 1958,98 and an atmospheric GCM hindcast run forced by observed 1955,91 sea-surface temperatures (SSTs). Downscaling from the reanalysis-derived predictors reproduces the 1958,98 interannual and interdecadal variability of winter precipitation. Downscaling from the SST-forced GCM hindcast only reproduces the precipitation probabilities of the recent 1978,91 period, with poor performance for earlier periods attributed to inadequacies in the forcing SST data. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Solar-induced and internal climate variability at decadal time scales

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 6 2005
Mihai Dima
Abstract Statistical analyses of long-term instrumental and proxy data emphasize a distinction between two quasi-decadal modes of climate variability. One mode is linked to atmosphere,ocean interactions (,the internal mode') and the other one is associated with the solar sunspots cycle (,the solar mode'). The distinct signatures of these two modes are also detected in a high-resolution sediment core located in the Cariaco basin. In the oceanic surface temperature the internal mode explains about three times more variance than the solar mode. In contrast, the solar mode dominates over the internal mode in the sea-level pressure and upper atmospheric fields. The heterogeneous methods and data sets used in this study underline the distinction between these decadal modes and enable estimation of their relative importance. The distinction between these modes is important for the understanding of climate variability, the recent global warming trend and the interpretation of high-resolution proxy data. Copyright © 2005 Royal Meteorological Society [source]

Small-scale precipitation variability in the Alps: Climatology in comparison with semi-idealized numerical simulations

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 636 2008
G. Zängl
Abstract This study examines small-scale precipitation patterns in a north-Alpine region, and their dependence on the freezing level and on the crest-level (700 hPa) wind direction and speed. On the one hand, measurements from a uniquely dense operational rain-gauge network are analyzed for a period of 15 years (1991--2005). Information on the ambient atmospheric fields was extracted from climate-mode MM5 simulations driven with ECMWF (re-analysis data. On the other hand, high-resolution semi-idealized MM5 simulations have been conducted, combining realistic topography with idealized atmospheric fields. The atmospheric flow parameters have been chosen to be representative of those used to classify the observational data, focusing on atmospheric conditions conducive to stratiform, orographically enhanced precipitation in the region under consideration. The results of the data analysis indicate a pronounced tendency for local precipitation maxima in the lee of individual mountain ridges, whereas the variability between stations in the centre of wider valleys and stations on the windward foot of individual ridges is comparatively small. This points towards a strong contribution of local precipitation enhancement due to the seeder--feeder mechanism, combined with downstream advection of the precipitating hydrometeors by the ambient winds. The data analysis also reveals that strong winds and high temperatures tend to shift the precipitation field towards the interior of the Alps, whereas low temperatures and weak winds favour precipitation maxima near the northern edge of the Alps. The semi-idealized simulations are consistent with these findings, but their quantitative agreement with the observed precipitation patterns depends on the ambient flow conditions. The closest agreement is found for atmospheric conditions conducive to strong orographic lifting, for which our present idealized flow fields were designed. Lower skill is obtained for conditions not dominated by orographic lifting, which implies that future work should include a generalization of the idealized flow fields. Nevertheless, precipitation patterns generated with semi-idealized simulations seem to be very promising to support the spatial interpolation of point measurements (such as are needed for precipitation climatologies), which currently is usually based on statistical methods rather than physically motivated structures. Copyright © 2008 Royal Meteorological Society [source]