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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.|
Banks, R. (2006). Variability of Indian Ocean Surface Fluxes Using a New Objective Method. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: A new objective technique is used to analyze monthly mean gridded fields of air and sea temperature, scalar and vector wind, specific humidity, sensible and latent heat flux, and wind stress over the Indian Ocean. A variational method produces a 1°x1° gridded product of surface turbulent fluxes and the variables needed to calculate these fluxes. The surface turbulent fluxes are forced to be physically consistent with the other variables. The variational method incorporates a state of the art flux model, which should reduce regional biases in heat and moisture fluxes. The time period is January 1982 to December 2003. The wind vectors are validated through comparison to monthly scatterometer winds. Empirical orthogonal function (EOF) analyses of the annual cycle emphasize significant modes of variability in the Indian Ocean. The dominant monsoon reversal and its connection with the southeast trades are linked in eigenmodes one and two of the surface fluxes. The third eigenmode of latent and sensible heat flux reveal a structure similar to the Indian Ocean Dipole (IOD) mode. The variability in surface fluxes associated with the monsoons and IOD are discussed. September-October-November composites of the surface fluxes during the 1997 positive IOD event and the 1983 negative IOD event are examined. The composites illustrate characteristics of fluxes during different IOD phases.
Keywords: Indian Ocean Dipole Mode, Indian Ocean, Objective Method, Surface Turbulent Fluxes, Monsoon, Gridded Product
|Banks, R. F. (2004). Spatial and temporal variability of precipitation runs across the Southeast U.S. Tallahassee, FL: Florida State University.|
|Banks, R. F., Bourassa, M. A., Hughes, P., O'Brien, J. J., & Smith, S. R. (2006). Variability of surface turbulent fluxes over the Indian Ocean. In 14th Conference on Interactions of the Sea and Atmosphere (cdrom).|
|Banks, R. F., O'Brien, J. J., & Smith, S. R. (2005). Spatial and temporal variability of precipitation runs in the Southeast U.S. and their potential impact on agriculture. In 15th AMS Conference on Applied Climatology, AMS, Savannah, GA, USA.|
|Bartels, W. - L., Furman, C. A., Diehl, D. C., Royce, F. S., Dourte, D. R., Ortiz, B. V., et al. (2013). Warming up to climate change: a participatory approach to engaging with agricultural stakeholders in the Southeast US. Reg Environ Change, 13(S1), 45–55.|
Bashmachnikov, I. L., Fedorov, A. M., Vesman, A. V., Belonenko, T. V., & Dukhovskoy, D. S. (2019). Thermohaline convection in the subpolar seas of the North Atlantic from satellite and in situ observations. Part 2: indices of intensity of deep convection.16(1), 191–201.
Abstract: Variation in locations of the maximum development of deep convection in the subpolar seas, taking into account their small dimensions, represent difficulty in identifying its interannual variability from usually sparse in situ data. In this work, the interannual variability of the maximum convection depth, is obtained using one of the most complete datasets ARMOR, which combines in situ and satellite data. The convection depths, derived from ARMOR, are used for testing the efficiency of two indices of convection intensity: (1) sea-level anomalies from satellite altimetry and (2) the integral water density in the areas of the most frequent development of deep convection. The first index, capturing some details, shows low correlations with the interannual variability of the deep convection intensity. The second index shows high correlation with the deep convection intensity in the Greenland, Irminger and Labrador seas. Asynchronous variations in the deep convection intensity in the Labrador-Irminger seas and in the Greenland Sea are obtained. In the Labrador and in the Irminger seas, the quasi-seven-year variations in the convection intensity are identified.
Keywords: deep convection, assimilation of satellite data, altimetry, water density, the Greenland Sea, the Labrador Sea, the Irminger Sea
|Bastola, S. (2014). Uncertainty in Climate Change Studies. In S. Shrestha, M. S. Babel, & V. P. Pandey (Eds.), Climate Change and Water Resources (pp. 81–108). CRC Press.|
|Bastola, S. (2013). Hydrologic impacts of future climate change on Southeast US watersheds. Reg Environ Change, 13(S1), 131–139.|
|Bastola, S., & Misra, V. (2015). Seasonal hydrological and nutrient loading forecasts for watersheds over the Southeastern United States. Environmental Modelling & Software, 73, 90–102.|