Air-Sea Heat Flux Variability in the Southeast Indian Ocean and Its Relation With Ningaloo Niño

Previous studies suggest that both air-sea heat flux anomalies and heat advection caused by an anomalous Leeuwin Current play an important role in modulating the sea surface temperature (SST) variability associated with the Ningaloo Niño. However, the estimates of surface heat fluxes vary substantially with the datasets, and the uncertainties largely depend on the time scale and locations. This study investigates air-sea flux variability associated with the Ningaloo Niño using multiple datasets of surface fluxes. The climatological net surface heat flux off the west coast of Australia from six major air-sea flux products shows large uncertainties, which exceeds 80 W m-2, especially in the austral summer when the Ningaloo Niño develops. These uncertainties stem mainly from those in shortwave radiation and latent heat flux. The use of different bulk flux algorithms and uncertainties of bulk atmospheric variables (wind speed and air specific humidity) are mostly responsible for the difference in latent heat flux climatology between the datasets. The composite evolution of air-sea heat fluxes over the life cycle of Ningaloo Niño indicates that the anomalous latent heat flux is dominant for the net surface heat flux variations, and that the uncertainties in latent heat flux anomaly largely depend on the phase of the Ningaloo Niño. During the recovery period of Ningaloo Niño, large negative latent heat flux anomalies (cooling the ocean) are evident in all datasets and thus significantly contribute to the SST cooling. Because the recovery of winds occurs earlier than SST, high SST and strong winds favor large evaporative cooling during the recovery phase. In contrast, the role of latent heat flux during the developing phase is not clear, because the sign of the anomalies depends on the datasets in this period. The use of high-resolution SST data, which can adequately represent SST variations produced by the anomalous Leeuwin Current, could largely reduce the errors in latent heat flux anomalies during the onset and peak phases

Upper Ocean Response to the Atmospheric Cold Pools Associated With the Madden-Julian Oscillation

Atmospheric cold pools are frequently observed during the Madden‐Julian Oscillation events and play an important role in the development and organization of large‐scale convection. They are generally associated with heavy precipitation and strong winds, inducing large air‐sea fluxes and significant sea surface temperature (SST) fluctuations. This study provides a first detailed investigation of the upper ocean response to the strong cold pools associated with the Madden‐Julian Oscillation, based on the analysis of in situ data collected during the Dynamics of the Madden‐Julian Oscillation (DYNAMO) field campaign and one‐dimensional ocean model simulations validated by the data. During strong cold pools, SST drops rapidly due to the atmospheric cooling in a shoaled mixed layer caused by the enhanced near‐surface salinity stratification generated by heavy precipitation. Significant contribution also comes from the component of surface heat flux produced by the cold rain temperature. After the period of heavy rain, while net surface cooling remains, SST gradually recovers due to the enhanced entrainment of warmer waters below the mixed layer

Climate Process Team: improvement of ocean component of NOAA Climate Forecast System relevant to Madden-Julian Oscillation simulations

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Shinoda, T., Pei, S., Wang, W., Fu, J. X., Lien, R.-C., Seo, H., & Soloviev, A. Climate Process Team: improvement of ocean component of NOAA Climate Forecast System relevant to Madden-Julian Oscillation simulations. Journal of Advances in Modeling Earth Systems, 13(12), (2021): e2021MS002658, https://doi.org/10.1029/2021MS002658.Given the increasing attention in forecasting weather and climate on the subseasonal time scale in recent years, National Oceanic and Atmospheric Administration (NOAA) announced to support Climate Process Teams (CPTs) which aim to improve the Madden-Julian Oscillation (MJO) prediction by NOAA’s global forecasting models. Our team supported by this CPT program focuses primarily on the improvement of upper ocean mixing parameterization and air-sea fluxes in the NOAA Climate Forecast System (CFS). Major improvement includes the increase of the vertical resolution in the upper ocean and the implementation of General Ocean Turbulence Model (GOTM) in CFS. In addition to existing mixing schemes in GOTM, a newly developed scheme based on observations in the tropical ocean, with further modifications, has been included. A better performance of ocean component is demonstrated through one-dimensional ocean model and ocean general circulation model simulations validated by the comparison with in-situ observations. These include a large sea surface temperature (SST) diurnal cycle during the MJO suppressed phase, intraseasonal SST variations associated with the MJO, ocean response to atmospheric cold pools, and deep cycle turbulence. Impact of the high-vertical resolution of ocean component on CFS simulation of MJO-associated ocean temperature variations is evident. Also, the magnitude of SST changes caused by high-resolution ocean component is sufficient to influence the skill of MJO prediction by CFS.This research was supported by NOAA Grant NA15OAR431074. Computing resources were provided partly by the HPC systems at the Texas A&M University (College Station and Corpus Christi) and the Climate Simulation Laboratory at NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. TS and SP are supported by DOD Grant W911NF-20-1-0309. TS is also supported by NSF Grant OCE-1658218 and NOAA Grant NA17OAR4310256

Novel Iron Chelators, Super-Polyphenols, Show Antimicrobial Effects against Cariogenic Streptococcus mutans

Dental caries are an oral infectious disease that can affect human health both orally and systemically. It remains an urgent issue to establish a novel antibacterial method to prevent oral infection for a healthy life expectancy. The aim of this study was to evaluate the inhibitory effects of novel iron chelators, super-polyphenols (SPs), on the cariogenic bacterium Streptococcus mutans, in vitro. SPs were developed to reduce the side effects of iron chelation therapy and were either water-soluble or insoluble depending on their isoforms. We found that SP6 and SP10 inhibited bacterial growth equivalent to povidone-iodine, and viability tests indicated that their effects were bacteriostatic. These results suggest that SP6 and SP10 have the potential to control oral bacterial infections such as Streptococcus mutans

Effects of the diurnal cycle in solar radiation on the tropical Indian Ocean mixed layer variability during wintertime Madden-Julian Oscillations

The effects of solar radiation diurnal cycle on intraseasonal mixed layer variability in the tropical Indian Ocean during boreal wintertime Madden-Julian Oscillation (MJO) events are examined using the HYbrid Coordinate Ocean Model. Two parallel experiments, the main run and the experimental run, are performed for the period of 2005–2011 with daily atmospheric forcing except that an idealized hourly shortwave radiation diurnal cycle is included in the main run. The results show that the diurnal cycle of solar radiation generally warms the Indian Ocean sea surface temperature (SST) north of 10 °S, particularly during the calm phase of the MJO when sea surface wind is weak, mixed layer is thin, and the SST diurnal cycle amplitude (dSST) is large. The diurnal cycle enhances the MJO-forced intraseasonal SST variability by about 20% in key regions like the Seychelles-Chagos Thermocline Ridge (SCTR; 55° –70° E, 12° –4 °S) and the central equatorial Indian Ocean (CEIO; 65° –95° E, 3° S–3° N) primarily through nonlinear rectification. The model also well reproduced the upper-ocean variations monitored by the CINDY/DYNAMO field campaign between September-November 2011. During this period, dSST reaches 0.7° C in the CEIO region, and intraseasonal SST variability is significantly amplified. In the SCTR region where mean easterly winds are strong during this period, diurnal SST variation and its impact on intraseasonal ocean variability are much weaker. In both regions, the diurnal cycle also has a large impact on the upward surface turbulent heat flux Q[Subscript T] and induces diurnal variation of Q[subscript T] with a peak-to-peak difference of O(10 W m⁻ ²).Keywords: Sea surface temperature, CINDY/DYNAMO, Madden-Julian Oscillation, Diurnal cycl

A road map to IndOOS-2 better observations of the rapidly warming Indian Ocean

Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 101(11), (2020): E1891-E1913, https://doi.org/10.1175/BAMS-D-19-0209.1The Indian Ocean Observing System (IndOOS), established in 2006, is a multinational network of sustained oceanic measurements that underpin understanding and forecasting of weather and climate for the Indian Ocean region and beyond. Almost one-third of humanity lives around the Indian Ocean, many in countries dependent on fisheries and rain-fed agriculture that are vulnerable to climate variability and extremes. The Indian Ocean alone has absorbed a quarter of the global oceanic heat uptake over the last two decades and the fate of this heat and its impact on future change is unknown. Climate models project accelerating sea level rise, more frequent extremes in monsoon rainfall, and decreasing oceanic productivity. In view of these new scientific challenges, a 3-yr international review of the IndOOS by more than 60 scientific experts now highlights the need for an enhanced observing network that can better meet societal challenges, and provide more reliable forecasts. Here we present core findings from this review, including the need for 1) chemical, biological, and ecosystem measurements alongside physical parameters; 2) expansion into the western tropics to improve understanding of the monsoon circulation; 3) better-resolved upper ocean processes to improve understanding of air–sea coupling and yield better subseasonal to seasonal predictions; and 4) expansion into key coastal regions and the deep ocean to better constrain the basinwide energy budget. These goals will require new agreements and partnerships with and among Indian Ocean rim countries, creating opportunities for them to enhance their monitoring and forecasting capacity as part of IndOOS-2.We thank the World Climate Research Programme (WCRP) and its core project on Climate and Ocean: Variability, Predictability and Change (CLIVAR), the Indian Ocean Global Ocean Observing System (IOGOOS), the Intergovernmental Oceanographic Commission of UNESCO (IOC-UNESCO), the Integrated Marine Biosphere Research (IMBeR) project, the U.S. National Oceanic and Atmospheric Administration (NOAA), and the International Union of Geodesy and Geophysics (IUGG) for providing the financial support to bring international scientists together to conduct this review. We thank the members of the independent review board that provided detailed feedbacks on the review report that is summarized in this article: P. E. Dexter, M. Krug, J. McCreary, R. Matear, C. Moloney, and S. Wijffels. PMEL Contribution 5041. C. Ummenhofer acknowledges support from The Andrew W. Mellon Foundation Award for Innovative Research.2021-05-0

A Study of CINDY/DYNAMO MJO Suppressed Phase

The diurnal variability and the environmental conditions that support the moisture resurgence of MJO events observed during the Cooperative Indian Ocean Experiment on Intraseasonal Variability (CINDY)/DYNAMO campaign in October–December 2011 are investigated using in situ observations and the cloud-resolving fully air–ocean–wave Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS). Spectral density and wavelet analysis of the total precipitable water (TPW) constructed from the DYNAMO soundings and TRMM satellite precipitation reveal a deep layer of vapor resurgence during the observed Wheeler and Hendon real-time multivariate MJO index phases 5–8 (MJO suppressed phase), which include diurnal, quasi-2-, quasi-3–4-, quasi-6–8-, and quasi-16-day oscillations. A similar oscillatory pattern is found in the DYNAMO moorings sea surface temperature analysis, suggesting a tightly coupled atmosphere and ocean system during these periods. COAMPS hindcast focused on the 12–16 November 2011 event suggests that both the diurnal sea surface temperature (SST) pumping and horizontal and vertical moisture transport associated with the westward propagating mixed Rossby–Gravity (MRG) waves play an essential role in the moisture resurgence during this period. Idealized COAMPS simulations of MRG waves are used to estimate the MRG and diurnal SST contributions to the overall moisture increase. These idealized MRG sensitivity experiments showed the TPW increase varies from 9% to 13% with the largest changes occurring in the simulations that included a diurnal SST variation of 2.5°C as observed.Keywords: Madden-Julian oscillation, Coupled models, Oscillations, performance, Model evaluation, Diurnal effects, Atmosphere-ocean interactio

A sustained ocean observing system in the Indian Ocean for climate related scientific knowledge and societal needs

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hermes, J. C., Masumoto, Y., Beal, L. M., Roxy, M. K., Vialard, J., Andres, M., Annamalai, H., Behera, S., D'Adamo, N., Doi, T., Peng, M., Han, W., Hardman-Mountford, N., Hendon, H., Hood, R., Kido, S., Lee, C., Lees, T., Lengaigne, M., Li, J., Lumpkin, R., Navaneeth, K. N., Milligan, B., McPhaden, M. J., Ravichandran, M., Shinoda, T., Singh, A., Sloyan, B., Strutton, P. G., Subramanian, A. C., Thurston, S., Tozuka, T., Ummenhofer, C. C., Unnikrishnan, A. S., Venkatesan, R., Wang, D., Wiggert, J., Yu, L., & Yu, W. (2019). A sustained ocean observing system in the Indian Ocean for climate related scientific knowledge and societal needs. Frontiers in Marine Science, 6, (2019): 355, doi: 10.3389/fmars.2019.00355.The Indian Ocean is warming faster than any of the global oceans and its climate is uniquely driven by the presence of a landmass at low latitudes, which causes monsoonal winds and reversing currents. The food, water, and energy security in the Indian Ocean rim countries and islands are intrinsically tied to its climate, with marine environmental goods and services, as well as trade within the basin, underpinning their economies. Hence, there are a range of societal needs for Indian Ocean observation arising from the influence of regional phenomena and climate change on, for instance, marine ecosystems, monsoon rains, and sea-level. The Indian Ocean Observing System (IndOOS), is a sustained observing system that monitors basin-scale ocean-atmosphere conditions, while providing flexibility in terms of emerging technologies and scientificand societal needs, and a framework for more regional and coastal monitoring. This paper reviews the societal and scientific motivations, current status, and future directions of IndOOS, while also discussing the need for enhanced coastal, shelf, and regional observations. The challenges of sustainability and implementation are also addressed, including capacity building, best practices, and integration of resources. The utility of IndOOS ultimately depends on the identification of, and engagement with, end-users and decision-makers and on the practical accessibility and transparency of data for a range of products and for decision-making processes. Therefore we highlight current progress, issues and challenges related to end user engagement with IndOOS, as well as the needs of the data assimilation and modeling communities. Knowledge of the status of the Indian Ocean climate and ecosystems and predictability of its future, depends on a wide range of socio-economic and environmental data, a significant part of which is provided by IndOOS.This work was supported by the PMEL contribution no. 4934