Quantifying horizontal length scales for surface wind variability in the tropical Pacific based on reanalyses
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Quantifying horizontal length scales for surface wind variability in the tropical Pacific based on reanalyses Caihong Wen1,2 · Arun Kumar1 · Yan Xue1 Received: 12 March 2019 / Accepted: 21 June 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The characteristic spatial sampling length scales (for example, in the longitudinal direction) to adequately resolve the variability associated with a quantity to be observed, depends on the typical length scales of its variability. For example, if temporal variations in the longitudinal direction are correlated over thousands of Kilometers then an observing network with a similar spatial density may be enough to sample the variability with adequate fidelity. Given the importance of surface wind stress in the equatorial tropical Pacific in determining sub-surface oceanic variability, particularly in relation to the evolution of El Niño—Southern Oscillation (ENSO), in this analysis the horizontal length scales of surface wind stress variability based on two reanalysis products—the Climate Forecast System Reanalysis and the ERA-Interim—are documented. The analysis is of relevance to the future evolution of the Tropical Pacific Observing System. As the current design of the Tropical Atmosphere Ocean [that has a wider (narrower) separation in the longitudinal (latitudinal) direction] was originally envisioned following estimates of the length scales of wind variability based on the observational record from tropical Pacific Islands (Harrison and Luther in J Clim 3:251–271, 1990), we find a similar characteristics for length scales for the surface wind variability based on reanalyses datasets. Further, the inferences based on two reanalysis products have a large degree of similarity, and thereby, give us some confidence in the reanalysis products for the purposes of analyzing the length scales of surface wind stress variability, and further, providing some basic information about the requirements for a sustained observing system in the tropical Pacific to monitor and to predict ENSO.
1 Introduction In the equatorial tropical Pacific, El Niño-Southern Oscillation (ENSO) is the largest mode of coupled variability with global influence on atmospheric and terrestrial climate. Skillful forecasts of ENSO using statistical and dynamical models are now routinely made and are the underpinnings for global operational seasonal prediction infrastructure. In recent decades, with advances in data assimilation techniques and coupled models, ENSO forecasts have come to rely progressively more on dynamical seasonal prediction systems and their skill is comparable, if not better, than statistical methods (Barnston et al. 2012). Within the operational infrastructure coordinated by the World
* Caihong Wen [email protected] 1
NOAA/NWS/NCEP/Climate Prediction Center, 5830 University Research Court, College Park, MD 20740, USA
Innovim, Greenbelt, MD, USA
2
Meteorological Organization (WMO), 11 of 13 operational centers for seasonal predictions now use coupled
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