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Baigorria, G. A., Jones, J. W., & O'Brien, J. J. (2007). Understanding rainfall spatial variability in southeast USA at different timescales. Int. J. Climatol., 27(6), 749–760.
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Schoof, J. T., & Pryor, S. C. (2006). An evaluation of two GCMs: simulation of North American teleconnection indices and synoptic phenomena. Int. J. Climatol., 26(2), 267–282.
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Smith, S. R., Briggs, K., Bourassa, M. A., Elya, J., & Paver, C. R. (2018). Shipboard automated meteorological and oceanographic system data archive: 2005-2017. Geosci Data J, 5(2), 73–86.
Abstract: Since 2005, the Shipboard Automated Meteorological and Oceanographic System (SAMOS) initiative has been collecting, quality-evaluating, distributing, and archiving underway navigational, meteorological, and oceanographic observations from research vessels. Herein we describe the procedures for acquiring ship and instrumental metadata and the one-minute interval observations from 44 research vessels that have contributed to the SAMOS initiative from 2005 to 2017. The overall data processing workflow and quality control procedures are documented along with data file formats and version control procedures. The SAMOS data are disseminated to the user community via web, FTP, and Thematic Real-time Environmental Distributed Data Services from both the Marine Data Center at the Florida State University and the National Centers for Environmental Information, which serves as the long-term archive for the SAMOS initiative. They have been used to address topics ranging from air-sea interaction studies, the calibration, evaluation, and development of satellite observational products, the evaluation of numerical atmospheric and ocean models, and the development of new tools and techniques for geospatial data analysis in the informatics community. Maps provide users the geospatial coverage within the SAMOS dataset, with a focus on the Essential Climate/Ocean Variables, and recommendations are made regarding which versions of the dataset should be accessed by different user communities.
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Jardak, M., Navon, I. M., & Zupanski, M. (2009). Comparison of sequential data assimilation methods for the Kuramoto-Sivashinsky equation. Int. J. Numer. Meth. Fluids, .
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Yu, B., Seed, A., Pu, L., & Malone, T. (2019). Integration of weather radar data into a raster GIS framework for improved flood estimation. Atmos. Sci. Lett., 6(1).
Abstract: We present in this paper the interannual variability of seasonal temperature and rainfall in the Indian meteorological subdivisions (IMS) for boreal winter and summer seasons that take in to account the varying length of the seasons.Our study reveals that accounting for the variations in the length of the sea-sons produces stronger teleconnections between the seasonal anomalies of surface temperature and rainfall over India with corresponding sea surface temperature anomalies of the tropical Oceans (especially over the northern Indian and the equatorial Pacific Oceans) compared to the same teleconnections from fixed length seasons over the IMS. It should be noted that the IMS show significant spatial heterogeneity in these teleconnections
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Krishnamurthy, V., & Misra, V. (2010). Observed ENSO teleconnections with the South American monsoon system. Atmos. Sci. Lett., .
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Luecke, C. A., Arbic, B. K., Bassette, S. L., Richman, J. G., Shriver, J. F., Alford, M. H., et al. (2017). The Global Mesoscale Eddy Available Potential Energy Field in Models and Observations. J. Geophys. Res. Oceans, 122(11), 9126–9143.
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Luecke, C. A., Arbic, B. K., Bassette, S. L., Richman, J. G., Shriver, J. F., Alford, M. H., et al. (2017). The Global Mesoscale Eddy Available Potential Energy Field in Models and Observations: GLOBAL LOW-FREQUENCY EDDY APE. J. Geophys. Res. Oceans, 122(11), 9126–9143.
Abstract: Global maps of the mesoscale eddy available potential energy (EAPE) field at a depth of 500 m are created using potential density anomalies in a high‐resolution 1/12.5° global ocean model. Maps made from both a free‐running simulation and a data‐assimilative reanalysis of the HYbrid Coordinate Ocean Model (HYCOM) are compared with maps made by other researchers from density anomalies in Argo profiles. The HYCOM and Argo maps display similar features, especially in the dominance of western boundary currents. The reanalysis maps match the Argo maps more closely, demonstrating the added value of data assimilation. Global averages of the simulation, reanalysis, and Argo EAPE all agree to within about 10%. The model and Argo EAPE fields are compared to EAPE computed from temperature anomalies in a data set of “moored historical observations” (MHO) in conjunction with buoyancy frequencies computed from a global climatology. The MHO data set allows for an estimate of the EAPE in high‐frequency motions that is aliased into the Argo EAPE values. At MHO locations, 15–32% of the EAPE in the Argo estimates is due to aliased motions having periods of 10 days or less. Spatial averages of EAPE in HYCOM, Argo, and MHO data agree to within 50% at MHO locations, with both model estimates lying within error bars observations. Analysis of the EAPE field in an idealized model, in conjunction with published theory, suggests that much of the scatter seen in comparisons of different EAPE estimates is to be expected given the chaotic, unpredictable nature of mesoscale eddies.
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Savage, A. C., Arbic, B. K., Alford, M. H., Ansong, J. K., Farrar, J. T., Menemenlis, D., et al. (2017). Spectral decomposition of internal gravity wave sea surface height in global models. J. Geophys. Res. Oceans, 122(10), 7803–7821.
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Savage, A. C., Arbic, B. K., Alford, M. H., Ansong, J. K., Farrar, J. T., Menemenlis, D., et al. (2017). Spectral decomposition of internal gravity wave sea surface height in global models: INTERNAL GRAVITY WAVE SEA SURFACE HEIGHT. J. Geophys. Res. Oceans, 122(10), 7803–7821.
Abstract: Two global ocean models ranging in horizontal resolution from 1/128 to 1/488 are used to study the space and time scales of sea surface height (SSH) signals associated with internal gravity waves (IGWs). Frequency-horizontal wavenumber SSH spectral densities are computed over seven regions of the world ocean from two simulations of the HYbrid Coordinate Ocean Model (HYCOM) and three simulations of the Massachusetts Institute of Technology general circulation model (MITgcm). High wavenumber, high-frequency SSH variance follows the predicted IGW linear dispersion curves. The realism of high-frequency motions (>0:87 cpd) in the models is tested through comparison of the frequency spectral density of dynamic height variance computed from the highest-resolution runs of each model (1/258 HYCOM and 1/488 MITgcm) with dynamic height variance frequency spectral density computed from nine in situ profiling instruments. These high-frequency motions are of particular interest because of their contributions to the small-scale SSH variability that will be observed on a global scale in the upcoming Surface Water and Ocean Topography (SWOT) satellite altimetry mission. The variance at supertidal frequencies can be comparable to the tidal and low-frequency variance for high wavenumbers (length scales smaller than 50 km), especially in the higher-resolution simulations. In the highest-resolution simulations, the high-frequency variance can be greater than the low-frequency variance at these scales.
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