Jackson, L. C., Dubois, C., Forget, G., Haines, K., Harrison, M., Iovino, D., et al. (2019). The Mean State and Variability of the North Atlantic Circulation: A Perspective From Ocean Reanalyses. J. Geophys. Res. Oceans , 124 (12), 8969–9003.
Abstract: The transfer of Indian Ocean thermocline and intermediate waters into the South Atlantic via the Agulhas leakage is generally believed to be primarily accomplished through mesoscale eddy processes, essentially anticyclones known as Agulhas Rings. Here we take advantage of a recent eddy tracking algorithm and Argo float profiles to study the evolution and the thermohaline structure of one of these eddies over the course of 1.5 years (May 2013–November 2014). We found that during this period the ring evolved according to two different phases: During the first one, taking place in winter, the mixing layer in the eddy deepened significantly. During the second phase, the eddy subsided below the upper warmer layer of the South Atlantic subtropical gyre while propagating west. The separation of this eddy from the sea surface could explain the decrease in its surface signature in satellite altimetry maps, suggesting that such changes are not due to eddy dissipation processes. It is a very large eddy (7.1×1013 m3 in volume), extending, after subduction, from a depth of 200–1,200 m and characterized by two mode water cores. The two mode water cores represent the largest eddy heat and salt anomalies when compared with the surrounding. In terms of its impact over 1 year, the north‐westward propagation of this long‐lived anticyclone induces a transport of 2.2 Sv of water, 0.008 PW of heat, and 2.2×105 kg s−1 of salt. These results confirm that Agulhas Rings play a very important role in the Indo‐Atlantic interocean exchange of heat and salt.
Nelson, A. D., Arbic, B. K., Zaron, E. D., Savage, A. C., Richman, J. G., Buijsman, M. C., et al. (2019). Toward Realistic Nonstationarity of Semidiurnal Baroclinic Tides in a Hydrodynamic Model. J. Geophys. Res. Oceans , 124 (9), 6632–6641.
Abstract: Semidiurnal baroclinic tide sea surface height (SSH) variance and semidiurnal nonstationary variance fraction (SNVF) are compared between a hydrodynamic model and altimetry for the low- to middle-latitude global ocean. Tidal frequencies are aliased by similar to 10-day altimeter sampling, which makes it impossible to unambiguously identify nonstationary tidal signals from the observations. In order to better understand altimeter sampling artifacts, the model was analyzed using its native hourly outputs and by subsampling it in the same manner as altimeters. Different estimates of the semidiurnal nonstationary and total SSH variance are obtained with the model depending on whether they are identified in the frequency domain or wave number domain and depending on the temporal sampling of the model output. Five sources of ambiguity in the interpretation of the altimetry are identified and briefly discussed. When the model and altimetry are analyzed in the same manner, they display qualitatively similar spatial patterns of semidiurnal baroclinic tides. The SNVF typically correlates above 80% at all latitudes between the different analysis methods and above 60% between the model and altimetry. The choice of analysis methodology was found to have a profound effect on estimates of the semidiurnal baroclinic SSH variance with the wave number domain methodology underestimating the semidiurnal nonstationary and total SSH variances by 68% and 66%, respectively. These results produce a SNVF estimate from altimetry that is biased low by a factor of 0.92. This bias is primarily a consequence of the ambiguity in the separation of tidal and mesoscale signals in the wave number domain.
Misra, V., & Bhardwaj, A. (2020). The impact of varying seasonal lengths of the rainy seasons of India on its teleconnections with tropical sea surface temperatures. Atmos Sci Lett , 21 (3), 9658–9689.
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 seasons 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.
Rahaman, H., Srinivasu, U., Panickal, S., Durgadoo, J. V., Griffies, S. M., Ravichandran, M., et al. (2020). An assessment of the Indian Ocean mean state and seasonal cycle in a suite of interannual CORE-II simulations. Ocean Modelling , 145 .
Mende, M., & Misra, V. (2020). Time to Flatten the Curves on COVID-19 and Climate Change. Marketing Can Help. Journal of Public Policy & Marketing , .
Abstract: The health, economic, and social impact of the COVID-19 pandemic is unprecedented in our lifetime, and no individual in this globalized, interconnected world is immune from its effects. This pandemic is a fundamental challenge for consumers, companies, and governments. Against this background, our commentary underscores linkages between public health, environment, and economy and explores how lessons from COVID-19 can help prevent other large-scale disasters.1 We focus on global climate change (GCC), because rising temperatures increase the likelihood of future pandemics.2 Accordingly, experts consider GCC “the largest public health threat of the century” (Wyns 2020). Although societal crises are underresearched in marketing, we propose that marketers should add their expertise to help avoid future crises. Notably, the Journal of Public Policy & Marketing (JPP&M) is uniquely positioned as a premier outlet for corresponding research at the intersection of marketing and policy.
Zou, S., Lozier, M. S., & Xu, X. (2020). Latitudinal Structure of the Meridional Overturning Circulation Variability on Interannual to Decadal Time Scales in the North Atlantic Ocean. J. Climate , 33 (9), 3845–3862.
Abstract: The latitudinal structure of the Atlantic meridional overturning circulation (AMOC) variability in the North Atlantic is investigated using numerical results from three ocean circulation simulations over the past four to five decades. We show that AMOC variability south of the Labrador Sea (53°N) to 25°N can be decomposed into a latitudinally coherent component and a gyre-opposing component. The latitudinally coherent component contains both decadal and interannual variabilities. The coherent decadal AMOC variability originates in the subpolar region and is reflected by the zonal density gradient in that basin. It is further shown to be linked to persistent North Atlantic Oscillation (NAO) conditions in all three models. The interannual AMOC variability contained in the latitudinally coherent component is shown to be driven by westerlies in the transition region between the subpolar and the subtropical gyre (40°–50°N), through significant responses in Ekman transport. Finally, the gyre-opposing component principally varies on interannual time scales and responds to local wind variability related to the annual NAO. The contribution of these components to the total AMOC variability is latitude-dependent: 1) in the subpolar region, all models show that the latitudinally coherent component dominates AMOC variability on interannual to decadal time scales, with little contribution from the gyre-opposing component, and 2) in the subtropical region, the gyre-opposing component explains a majority of the interannual AMOC variability in two models, while in the other model, the contributions from the coherent and the gyre-opposing components are comparable. These results provide a quantitative decomposition of AMOC variability across latitudes and shed light on the linkage between different AMOC variability components and atmospheric forcing mechanisms.
Vinayachandran, P. N., Davidson, F., & Chassignet, E. P. (2020). Towards joint assessments, modern capabilities and new links for ocean prediction systems. Bull. Amer. Meteor. Soc. , 101 (4).
Abstract: Approximately 260 individuals from forecasting centers, research laboratories, academia, and industry representing 40 countries met to discuss recent developments in operational oceanography and brainstorm about the future directions of ocean prediction services.
Liu, Q., Tan, Z. - M., Sun, J., Hou, Y., Fu, C., & Wu, Z. (2020). Changing rapid weather variability increases influenza epidemic risk in a warming climate. Environmental Research Letters , 15 (4).
Abstract: The continuing change of the Earth's climate is believed to affect the influenza viral activity and transmission in the coming decades. However, a consensus of the severity of the risk of influenza epidemic in a warming climate has not been reached. It was previously reported that the warmer winter can reduce influenza epidemic-caused mortality, but this relation cannot explain the deadly influenza epidemic in many countries over northern mid-latitudes in the winter of 2017-2018, one of the warmest winters in recent decades. Here we reveal that the widely spread 2017-2018 influenza epidemic can be attributed to the abnormally strong rapid weather variability. We demonstrate, from historical data, that the large rapid weather variability in autumn can precondition the deadly influenza epidemic in the subsequent months in highly populated northern mid-latitudes; and the influenza epidemic season of 2017-2018 was a typical case. We further show that climate model projections reach a consensus that the rapid weather variability in autumn will continue to strengthen in some regions of northern mid-latitudes in a warming climate, implying that the risk of influenza epidemic may increase 20% to 50% in some highly populated regions in later 21st century.
Bruno-Piverger, R. E. (2019). Applying Neural Networks to Simulate Visual Inspection of Observational Weather Data. Florida State University College of Arts and Sciences, Master's Thesis , .
Wang, S., Kranz, S. A., Kelly, T. B., Song, H., Stukel, M. R., & Cassar, N. (2020). Lagrangian Studies of Net Community Production: The Effect of Diel and Multiday Nonsteady State Factors and Vertical Fluxes on O2 /Ar in a Dynamic Upwelling Region. J. Geophys. Res. Biogeosci. , 125 (6), e2019JG005569.
Abstract: The ratio of dissolved oxygen to argon in seawater is frequently employed to estimate rates of net community production (NCP) in the oceanic mixed layer. The in situ O2/Ar‐based method accounts for many physical factors that influence oxygen concentrations, permitting isolation of the biological oxygen signal produced by the balance of photosynthesis and respiration. However, this technique traditionally relies upon several assumptions when calculating the mixed‐layer O2/Ar budget, most notably the absence of vertical fluxes of O2/Ar and the principle that the air‐sea gas exchange of biological oxygen closely approximates net productivity rates. Employing a Lagrangian study design and leveraging data outputs from a regional physical oceanographic model, we conducted in situ measurements of O2/Ar in the California Current Ecosystem in spring 2016 and summer 2017 to evaluate these assumptions within a �worst‐case� field environment. Quantifying vertical fluxes, incorporating nonsteady state changes in O2/Ar, and comparing NCP estimates evaluated over several day versus longer timescales, we find differences in NCP metrics calculated over different time intervals to be considerable, also observing significant potential effects from vertical fluxes, particularly advection. Additionally, we observe strong diel variability in O2/Ar and NCP rates at multiple stations. Our results reemphasize the importance of accounting for vertical fluxes when interpreting O2/Ar‐derived NCP data and the potentially large effect of nonsteady state conditions on NCP evaluated over shorter timescales. In addition, diel cycles in surface O2/Ar can also bias interpretation of NCP data based on local productivity and the time of day when measurements were made.
