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SST Data (sst + data)

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]

The Gulf Stream and Atlantic sea-surface temperatures in AD1790,1825

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 12 2010
G. van der Schrier
Abstract We present gridded sea-surface temperatures (SSTs) for the Atlantic basin (45°S,60°N) as averages over the period AD1790,1825, based on early-instrumental SST data. The original measurements were compiled by Major James Rennell and made by numerous British naval vessels on behalf of the British Admiralty. We describe the digitization of this dataset and the reconstruction of spatially coherent, averaged conditions for the boreal cold (November-March) and warm (May,September) season using a reduced space optimal interpolation (RSOI) technique, in which the data is projected on a limited number of empirical orthogonal functions. This approach is validated on modern data that are sampled in a similar way as the early-instrumental data. The reconstruction for the November,March period shows a large area with anomalously high temperatures from the point where the Gulf Stream separates from the coast until ca. 20°W. A tongue of anomalous cool water is found at the eastern side of the North Atlantic basin, along the coast of Europe and northern Africa. In the northeastern South Atlantic, anomalously high temperatures are found, while temperatures in the southwestern South Atlantic are anomalously cool. For the March,September season, anomalous temperatures in the South Atlantic are similar, but stronger, compared with those in the boreal cold season. Over the North Atlantic, there is not much similarity between the current SST reconstructions and those published in the late 1950s. Copyright © 2009 Royal Meteorological Society [source]

Interpreting variability in global SST data using independent component analysis and principal component analysis

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 3 2010
Seth Westra
Abstract Component extraction techniques are used widely in the analysis and interpretation of high-dimensional climate datasets such as global sea surface temperatures (SSTs). Principal component analysis (PCA), a frequently used component extraction technique, provides an orthogonal representation of the multivariate dataset and maximizes the variance explained by successive components. A disadvantage of PCA, however, is that the interpretability of the second and higher components may be limited. For this reason, a Varimax rotation is often applied to the PCA solution to enhance the interpretability of the components by maximizing a simple structure. An alternative rotational approach is known as independent component analysis (ICA), which finds a set of underlying ,source signals' which drive the multivariate ,mixed' dataset. Here we compare the capacity of PCA, the Varimax rotation and ICA in explaining climate variability present in globally distributed SST anomaly (SSTA) data. We find that phenomena which are global in extent, such as the global warming trend and the El Niño-Southern Oscillation (ENSO), are well represented using PCA. In contrast, the Varimax rotation provides distinct advantages in interpreting more localized phenomena such as variability in the tropical Atlantic. Finally, our analysis suggests that the interpretability of independent components (ICs) appears to be low. This does not diminish the statistical advantages of deriving components that are mutually independent, with potential applications ranging from synthetically generating multivariate datasets, developing statistical forecasts, and reconstructing spatial datasets from patchy observations at multiple point locations. Copyright © 2009 Royal Meteorological Society [source]

Multidecadal climate variability of global lands and oceans

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 7 2006
Gregory J. McCabe
Abstract Principal components analysis (PCA) and singular value decomposition (SVD) are used to identify the primary modes of decadal and multidecadal variability in annual global Palmer Drought Severity Index (PDSI) values and sea-surface temperatures (SSTs). The PDSI and SST data for 1925,2003 were detrended and smoothed (with a 10-year moving average) to isolate the decadal and multidecadal variability. The first two principal components (PCs) of the PDSI PCA explained almost 38% of the decadal and multidecadal variance in the detrended and smoothed global annual PDSI data. The first two PCs of detrended and smoothed global annual SSTs explained nearly 56% of the decadal variability in global SSTs. The PDSI PCs and the SST PCs are directly correlated in a pairwise fashion. The first PDSI and SST PCs reflect variability of the detrended and smoothed annual Pacific Decadal Oscillation (PDO), as well as detrended and smoothed annual Indian Ocean SSTs. The second set of PCs is strongly associated with the Atlantic Multidecadal Oscillation (AMO). The SVD analysis of the cross-covariance of the PDSI and SST data confirmed the close link between the PDSI and SST modes of decadal and multidecadal variation and provided a verification of the PCA results. These findings indicate that the major modes of multidecadal variations in SSTs and land-surface climate conditions are highly interrelated through a small number of spatially complex but slowly varying teleconnections. Therefore, these relations may be adaptable to providing improved baseline conditions for seasonal climate forecasting. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Decadal and longer term changes in El Niño,southern oscillation characteristics

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 4 2004
I. I. Mokhov
Abstract The time variations of El Niño,southern oscillation (ENSO) amplitude A, period P, and their relationship were studied using observed Niño-3 sea-surface temperature (SST) (GISST 2.2, GISST 2.3) and the southern oscillation index (SOI). Different tendencies in the A,P relationship were found in the decadal and longer term variations. On the decadal time scale, the SOI shows a statistically significant positive correlation between ENSO period and amplitude. This result was confirmed by analysing the observed Niño-3 SST data as well. A negative relationship between longer variations in A and P was then found for certain subintervals of the observed SST time series available, e.g. for 1921,80 and 1903,94, and the dataset representing the latter period is the GISST 2.2 dataset. These longer variations can be interdecadal, and/or secular trends in the A (positive) and P (negative). In contrast, the SOI showed no trends in P and A; consequently, there were no significant P,A correlations found in the SOI data on these time scales. The ECHAM4/OPYC3 model was then tested in order to determine whether it could reproduce the tendencies found in the observed data. The ECHAM4/OPYC3 SST showed a negative A,P relationship in the simulation with increasing greenhouse-gas concentration. This tendency did not manifest itself in the control run. The model SOI agrees with observation results, showing a positive correlation between ENSO period and amplitude on decadal time scales. Copyright © 2004 Royal Meteorological Society [source]

Statistical prediction of global sea-surface temperature anomalies

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 14 2003
A. W. Colman
Abstract Sea-surface temperature (SST) is one of the principal factors that influence seasonal climate variability, and most seasonal prediction schemes make use of information regarding SST anomalies. In particular, dynamical atmospheric prediction models require global gridded SST data prescribed through the target season. The simplest way of providing those data is to persist the SST anomalies observed at the start of the forecast at each grid point, with some damping, and this strategy has proved to be quite effective in practice. In this paper we present a statistical scheme that aims to improve that basic strategy by combining three individual methods together: simple persistence, canonical correlation analysis (CCA), and nearest-neighbour regression. Several weighting schemes were tested: the best of these is one that uses equal weight in all areas except the east tropical Pacific, where CCA is preferred. The overall performance of the combined scheme is better than the individual schemes. The results show improvements in tropical ocean regions for lead times beyond 1 or 2 months, but the skill of simple persistence is difficult to beat in the extratropics at all lead times. Aspects such as averaging periods and grid size were also investigated: results showed little sensitivity to these factors. The combined statistical SST prediction scheme can also be used to improve statistical regional rainfall forecasts that use SST anomaly patterns as predictors. Copyright © Crown Copyright 2003. Published by John Wiley & Sons, Ltd. [source]

TEMPERATURE THRESHOLD AS A BIOGEOGRAPHIC BARRIER IN NORTHERN INDIAN OCEAN MACROALGAE,

JOURNAL OF PHYCOLOGY, Issue 4 2006
Tom Schils
The most eastern point of the Arabian Peninsula, Ras Al Hadd, marks the boundary between the Arabian Sea and the Gulf of Oman. This geographic landmark coincides with an abrupt floristic turnover, probably one of the sharpest biotic transitions known in marine biogeography. The floras of different Arabian localities across this floristic break were compared using macrophyte distribution data throughout the Indian Ocean and seasonal sea-surface temperature (SST) data. The localities from the Arabian Gulf and Gulf of Oman differ significantly from those of the Arabian Sea based on their species richness, species composition, average distribution range per species, general temperature affinity of the composing species, and seasonal temperature data of the coastal waters. Pooling the temperature data into two groups (SST3avg, average SST of the three warmest seasons; SSTmin, minimum of the seasonal SSTs) revealed a temperature limit at 28°C using both the temperature affinity data of the floras and the seasonal temperatures recorded for the specific Arabian localities, which significantly separates the Arabian Sea from localities of both Gulfs. Finally, SST data of the Indian Ocean were analyzed using this upper temperature threshold of macrophytes at 28°C and the lower temperature limit of corals at 25°C, revealing general macrophyte diversity patterns. [source]

Variability in temperature and geometry of the Norwegian Current over the past 600,yr; stable isotope and grain size evidence from the Norwegian margin

JOURNAL OF QUATERNARY SCIENCE, Issue 7 2003
Ida Malene Berstad
Abstract Core P1-003MC was retrieved from 851,m water depth on the southern Norwegian continental margin, close to the boundary between the Norwegian Current (NC) and the underlying cold Norwegian Sea Deep Water. The core chronology was established by using 210Pb measurements and 14C dates, suggesting a sampling resolution of between 2 and 9,yr. Sea-surface temperature (SST) variations in the NC are reconstructed from stable oxygen isotope measurements in two planktonic Foraminifera species, Neogloboquadrina pachyderma (d.) and Globigerina bulloides. The high temporal resolution of the SST proxy records allows direct comparison with instrumental ocean temperature measurements from Ocean Weather Ship (OWS) Mike in the Norwegian Sea and an air temperature record from the coastal island Ona, western Norway. The comparison of the instrumental and the proxy SST data suggests that N. pachyderma (d.) calcify during summer, whereas G. bulloides calcify during spring. The ,18O records of both species suggest that the past 70,yr have been the warmest throughout the past 600,yr. The spring and summer proxy temperature data suggest differences in the duration of the cold period of the Little Ice Age. The spring temperature was 1,3°C colder throughout most of the period between ca. AD 1400 and 1700, and the summer temperature was 1,2°C colder throughout most of the period between ca. AD 1400 and 1920. Fluctuations in the depth of the lower boundary of the NC have been investigated by examining grain size data and benthic foraminiferal assemblages. The data show that the transition depth of the lower boundary of the NC was deeper between ca. AD 1400 and 1650 than after ca. AD 1750 until present. Copyright © 2003 John Wiley & Sons, Ltd. [source]

Basic aspects of geopotential field approximation from satellite-to-satellite tracking data

MATHEMATICAL METHODS IN THE APPLIED SCIENCES, Issue 11 2001
W. Freeden
Abstract The satellite-to-satellite tracking (SST) problems are characterized from mathematical point of view. Uniqueness results are formulated. Moreover, the basic relations are developed between (scalar) approximation of the earth's gravitational potential by ,scalar basis systems' and (vectorial) approximation of the gravitational field by ,vectorial basis systems'. Finally, the mathematical justification is given for approximating the external geopotential field by finite linear combinations of certain gradient fields (for example, gradient fields of multi-poles) consistent to a given set of SST data. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Influence of assimilated SST on regional atmospheric simulation: A case of a cold-air outbreak over the Japan Sea

ATMOSPHERIC SCIENCE LETTERS, Issue 1 2008
Masaru Yamamoto
Abstract Sea surface temperature (SST) assimilated using an ocean circulation model is used for the atmospheric simulation of a cold-air outbreak over the Japan Sea. The upward surface-turbulent heat fluxes are significantly influenced by the high-resolution SST structure resulting from mesoscale oceanic eddies. A strong deceleration of the outbreak due to local convective activity arises in a coastal area when using the assimilated SST data, in good agreement with observations; however, this feature is not observed when using the interpolated SST. In general, the use of assimilated temperature does improve regional atmospheric simulations. Copyright © 2008 Royal Meteorological Society [source]