Shropshire, T., Morey, S. L., Chassignet, E. P., Bozec, A., Coles, V. J., Landry, M. R., et al. (2019). Quantifying spatiotemporal variability in zooplankton dynamics in the Gulf of Mexico with a physical-biogeochemical model.
Abstract: Zooplankton play an important role in global biogeochemistry and their secondary production supports valuable fisheries of the world's oceans. Currently, zooplankton abundances cannot be estimated using remote sensing techniques. Hence, coupled physical-biogeochemical models (PBMs) provide an important tool for studying zooplankton on regional and global scales. However, evaluating the accuracy of zooplankton abundance estimates from PBMs has been a major challenge as a result of sparse observations. In this study, we configure a PBM for the Gulf of Mexico (GoM) from 1993�2012 and validate the model against an extensive combination of in situ biomass and rate measurements including total mesozooplankton biomass, size-fractionated mesozooplankton biomass and grazing rates, microzooplankton specific grazing rates, surface chlorophyll, deep chlorophyll maximum depth, phytoplankton specific growth rates, and net primary production. Spatial variability in mesozooplankton biomass climatology observed in a multi-decadal database for the northern GoM is well resolved by the model with a statistically significant (p < 0.01) correlation of 0.90. Mesozooplankton secondary production for the region averaged 66 + 8 mt C yr−1 equivalent to approximately 10 % of NPP and ranged from 51 to 82 mt C yr−1. In terms of diet, model results from the shelf regions suggest that herbivory is the dominant feeding mode for small mesozooplankton (< 1-mm) whereas larger mesozooplankton are primarily carnivorous. However, in open-ocean, oligotrophic regions, both groups of mesozooplankton have proportionally greater reliance on heterotrophic protists as a food source. This highlights the important role of microbial and protistan food webs in sustaining mesozooplankton biomass in the GoM which serves as the primary food source for early life stages of many commercially-important fish species, including tuna.
Sun, J., & Wu, Z. (2019). Isolating spatiotemporally local mixed Rossby-gravity waves using multi-dimensional ensemble empirical mode decomposition.
Clim Dyn, (3-4), 1383–1405.
Abstract: Tropical waves have relatively large amplitudes in and near convective systems, attenuating as they propagate away from the area where they are generated due to the dissipative nature of the atmosphere. Traditionally, nonlocal analysis methods, such as those based on the Fourier transform, are applied to identify tropical waves. However, these methods have the potential to lead to the misidentification of local wavenumbers and spatial locations of local wave activities. To address this problem, we propose a new method for analyzing tropical waves, with particular focus placed on equatorial mixed Rossby-gravity (MRG) waves. The new tropical wave analysis method is based on the multi-dimensional ensemble empirical mode decomposition and a novel spectral representation based on spatiotemporally local wavenumber, frequency, and amplitude of waves. We first apply this new method to synthetic data to demonstrate the advantages of the method in revealing characteristics of MRG waves. We further apply the method to reanalysis data (1) to identify and isolate the spatiotemporally heterogeneous MRG waves event by event, and (2) to quantify the spatial inhomogeneity of these waves in a wavenumber-frequency-energy diagram. In this way, we reveal the climatology of spatiotemporal inhomogeneity of MRG waves and summarize it in wavenumber-frequency domain: The Indian Ocean is dominated by MRG waves in the period range of 8–12 days; the western Pacific Ocean consists of almost equal energy distribution of MRG waves in the period ranges of 3–6 and 8–12 days, respectively; and the eastern tropical Pacific Ocean and the tropical Atlantic Ocean are dominated by MRG waves in the period range of 3–6 days. The zonal wavenumbers mostly fall within the band of 4–15, with Indian Ocean has larger portion of higher wavenumber (smaller wavelength components) MRG waves.
Vinayachandran, P. N., Davidson, F., & Chassignet, E. P. (2019). Towards joint assessments, modern capabilities and new links for ocean prediction systems.
Bulletin of the American Meteorological Society, .
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