Ali, M., Singh, N., Kumar, M., Zheng, Y., Bourassa, M., Kishtawal, C., et al. (2018). Dominant Modes of Upper Ocean Heat Content in the North Indian Ocean.
Climate, 6(3), 71.
Abstract: The thermal energy needed for the development of hurricanes and monsoons as well as any prolonged marine weather event comes from layers in the upper oceans, not just from the thin layer represented by sea surface temperature alone. Ocean layers have different modes of thermal energy variability because of the different time scales of ocean-atmosphere interaction. Although many previous studies have focused on the influence of upper ocean heat content (OHC) on tropical cyclones and monsoons, no study thus farparticularly in the North Indian Ocean (NIO)has specifically concluded the types of dominant modes in different layers of the ocean. In this study, we examined the dominant modes of variability of OHC of seven layers in the NIO during 1998-2014. We conclude that the thermal variability in the top 50 m of the ocean had statistically significant semiannual and annual modes of variability, while the deeper layers had the annual mode alone. Time series of OHC for the top four layers were analyzed separately for the NIO, Arabian Sea, and Bay of Bengal. For the surface to 50 m layer, the lowest and the highest values of OHC were present in January and May every year, respectively, which was mainly caused by the solar radiation cycle.
Ansong, J. K., Arbic, B. K., Simmons, H. L., Alford, M. H., Buijsman, M. C., Timko, P. G., et al. (2018). Geographical Distribution of Diurnal and Semidiurnal Parametric Subharmonic Instability in a Global Ocean Circulation Model.
J. Phys. Oceanogr., 48(6), 1409–1431.
Abstract: The evidence for, baroclinic energetics of, and geographic distribution of parametric subharmonic instability (PSI) arising from both diurnal and semidiurnal tides in a global ocean general circulation model is investigated using 1/12.5° and 1/25° simulations that are forced by both atmospheric analysis fields and the astronomical tidal potential. The paper examines whether PSI occurs in the model, and whether it accounts for a significant fraction of the tidal baroclinic energy loss. Using energy transfer calculations and bispectral analyses, evidence is found for PSI around the critical latitudes of the tides. The intensity of both diurnal and semidiurnal PSI in the simulations is greatest in the upper ocean, consistent with previous results from idealized simulations, and quickly drops off about 5° from the critical latitudes. The sign of energy transfer depends on location; the transfer is positive (from the tides to subharmonic waves) in some locations and negative in others. The net globally integrated energy transfer is positive in all simulations and is 0.5%�10% of the amount of energy required to close the baroclinic energy budget in the model. The net amount of energy transfer is about an order of magnitude larger in the 1/25° semidiurnal simulation than the 1/12.5° one, implying the dependence of the rate of energy transfer on model resolution.
Armstrong, E. M., Bourassa, M. A., Cram, T., Elya, J. L., Greguska, F. R., III, Huang, T., et al. (2018). An information technology foundation for fostering interdisciplinary oceanographic research and analysis. In
American Geophysical Union (Vol. Fall Meeting).
Abstract: Before complex analysis of oceanographic or any earth science data can occur, it must be placed in the proper domain of computing and software resources. In the past this was nearly always the scientist's personal computer or institutional computer servers. The problem with this approach is that it is necessary to bring the data products directly to these compute resources leading to large data transfers and storage requirements especially for high volume satellite or model datasets. In this presentation we will present a new technological solution under development and implementation at the NASA Jet Propulsion Laboratory for conducting oceanographic and related research based on satellite data and other sources. Fundamentally, our approach for satellite resources is to tile (partition) the data inputs into cloud-optimized and computation friendly databases that allow distributed computing resources to perform on demand and server-side computation and data analytics. This technology, known as NEXUS, has already been implemented in several existing NASA data portals to support oceanographic, sea-level, and gravity data time series analysis with capabilities to output time-average maps, correlation maps, Hovmöller plots, climatological averages and more. A further extension of this technology will integrate ocean in situ observations, event-based data discovery (e.g., natural disasters), data quality screening and additional capabilities. This particular activity is an open source project known as the Apache Science Data Analytics Platform (SDAP) (https://sdap.apache.org), and colloquially as OceanWorks, and is funded by the NASA AIST program. It harmonizes data, tools and computational resources for the researcher allowing them to focus on research results and hypothesis testing, and not be concerned with security, data preparation and management. We will present a few oceanographic and interdisciplinary use cases demonstrating the capabilities for characterizing regional sea-level rise, sea surface temperature anomalies, and ocean hurricane responses.
Bhardwaj, A., Misra, V., Mishra, A., Wootten, A., Boyles, R., Bowden, J. H., et al. (2018). Downscaling future climate change projections over Puerto Rico using a non-hydrostatic atmospheric model.
Climatic Change, 147(1-2), 133–147.
Bourassa, M. A., and P.J. Hughes. (2018). Surface Heat Fluxes and Wind Remote Sensing. In and J. Verron J. Tintoré A. Pascual E. P. Chassignet (Ed.), (pp. 245–270). Tallahassee, FL: GODAE OceanView.
Abstract: The exchange of heat and momentum through the air-sea surface are critical aspects of ocean forcing and ocean modeling. Over most of the global oceans, there are few in situ observations that can be used to estimate these fluxes. This chapter provides background on the calculation and application of air-sea fluxes, as well as the use of remote sensing to calculate these fluxes. Wind variability makes a large contribution to variability in surface fluxes, and the remote sensing of winds is relatively mature compared to the air sea differences in temperature and humidity, which are the other key variables. Therefore, the remote sensing of wind is presented in greater detail. These details enable the reader to understand how the improper use of satellite winds can result in regional and seasonal biases in fluxes, and how to calculate fluxes in a manner that removes these biases. Examples are given of high-resolution applications of fluxes, which are used to indicate the strengths and weakness of satellite-based calculations of ocean surface fluxes.
Buchanan, S., Misra, V., & Bhardwaj, A. (2018). https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.5450.
International Journal of Climatology, 38(6), 2651–2661.
Abstract: The integrated kinetic energy (IKE) of a tropical cyclone (TC), a volume integration of the surface winds around the centre of the TC, is computed from a comprehensive surface wind (National Aeronautics and Space Administration’s (NASA) cross‐calibrated multi‐platform [CCMP]) analysis available over the global oceans to verify against IKE from wind radii estimates of extended best‐track data maintained by NOAA for the North Atlantic TCs. It is shown that CCMP surface wind analysis severely underestimates IKE largely from not resolving hurricane force winds for majority of the Atlantic TCs, under sampling short‐lived and small‐sized TCs. The seasonal cycle of the North Atlantic TC IKE also verifies poorly in the CCMP analysis. In this article we introduce proxy IKE (PIKE) based on the kinetic energy of the winds at the radius of the last closed isobar (ROCI), which shows promise for a wide range of TC sizes including the smaller‐sized TCs unresolved in the CCMP data set.
Deng, J., Wu, Z., Zhang, M., Huang, N. E., Wang, S., & Qiao, F. (2018). Using Holo-Hilbert spectral analysis to quantify the modulation of Dansgaard-Oeschger events by obliquity.
Quaternary Science Reviews, 192, 282–299.
Abstract: Astronomical forcing (obliquity and precession) has been thought to modulate Dansgaard-Oeschger (DO) events, yet the detailed quantification of such modulations has not been examined. In this study, we apply the novel Holo-Hilbert Spectral Analysis (HHSA) to five polar ice core records, quantifying astronomical forcing's time-varying amplitude modulation of DO events and identifying the preferred obliquity phases for large amplitude modulations. The unique advantages of HHSA over the widely used windowed Fourier spectral analysis for quantifying astronomical forcing's nonlinear modulations of DO events is first demonstrated with a synthetic data that closely resembles DO events recorded in Greenland ice cores (NGRIP, GRIP, and GISP2 cores on GICC05 modelext timescale). The analysis of paleoclimatic proxies show that statistically significantly more frequent DO events, with larger amplitude modulation in the Greenland region, tend to occur in the decreasing phase of obliquity, especially from its mean value to its minimum value. In the eastern Antarctic, although statistically significantly more DO events tend to occur in the decreasing obliquity phase in general, the preferred phase of obliquity for large amplitude modulation on DO events is a segment of the increasing phase near the maximum obliquity, implying that the physical mechanisms of DO events may be different for the two polar regions. Additionally, by using cross-spectrum and magnitude-squared analyses, Greenland DO mode at a timescale of about 1400 years leads the Antarctic DO mode at the same timescale by about 1000 years. (C) 2018 Elsevier Ltd. All rights reserved.
Devanas, A., & Stefanova, L. (2018). Statistical Prediction Of Waterspout Probability For The Florida Keys.
Wea. Forecasting, 33, 389–410.
Abstract: A statistical model of waterspout probability was developed for wet-season (June–September) days over the Florida Keys. An analysis was performed on over 200 separate variables derived from Key West 1200 UTC daily wet-season soundings during the period 2006–14. These variables were separated into two subsets: days on which a waterspout was reported anywhere in the Florida Keys coastal waters and days on which no waterspouts were reported. Days on which waterspouts were reported were determined from the National Weather Service (NWS) Key West local storm reports. The sounding at Key West was used for this analysis since it was assumed to be representative of the atmospheric environment over the area evaluated in this study. The probability of a waterspout report day was modeled using multiple logistic regression with selected predictors obtained from the sounding variables. The final model containing eight separate variables was validated using repeated fivefold cross validation, and its performance was compared to that of an existing waterspout index used as a benchmark. The performance of the model was further validated in forecast mode using an independent verification wet-season dataset from 2015–16 that was not used to define or train the model. The eight-predictor model was found to produce a probability forecast with robust skill relative to climatology and superior to the benchmark waterspout index in both the cross validation and in the independent verification.
Glazer, R. H., & Misra, V. (2018). Ice versus liquid water saturation in simulations of the Indian summer monsoon.
Climate Dynamics, .
Groenen, D. (2018). The Effects of Climate Change on the Pests and Diseases of Coffee Crops in Mesoamerica.
Journal of Climatology & Weather Forecasting, 6(3).
Abstract: Coffee is an in-demand commodity that is being threatened by climate change. Increasing temperatures and rainfall variability are predicted in the region of Mexico and Central America (Mesoamerica). This region is plagued with pests and diseases that have already caused millions of dollars in damages and losses to the coffee industry.This paper examines three pests that negatively affect coffee plants: the coffee borer beetle, the black twig borer,and nematodes. In addition, this paper examines three diseases that can destroy coffee crops: bacterial blight,coffee berry disease, and coffee leaf rust. This paper will review the literature on how these pests and diseases are predicted to affect coffee crops under climate change models. In general, increased temperatures will increase the spread of pest and disease in coffee crops. Projected decreased rainfall in Honduras and Nicaragua may decrease the spread of pest and disease. However, these are complex issues which still require further study.