Air- Sea Interactions And Ocean Dynamics In The Southwest Tropical Indian Ocean

The Southwest Tropical Indian Ocean (SWTIO) features a unique, seasonal upward lift of the thermocline, which is known as the Seychelles-Chagos Thermocline Ridge (SCTR; 55°E-65°E, 5°S-12°S). It is known that a high correlation exists between the depth of the thermocline and sea surface temperature (SST; a key ingredient for tropical cyclogenesis). With a particular focus on 2012/2013, this study reveals the dynamic properties of the SCTR that play an important role in the modulation of tropical cyclones in the SWTIO. Phenomena including Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO) are also well correlated to cyclogenesis through changes in the thermocline of the SCTR. More tropical cyclones form over the SWTIO when the thermocline is deeper, which has a positive relation to the arrival of downwelling Rossby waves originating in the southeast tropical Indian Ocean due to the anomalous effects of IOD. In addition to influencing cyclogeneis over the SCTR region, remote processes such as IOD and ENSO are also the primary drivers of the SCTR interannual variability with respect to both ocean temperature and salinity. Thus, this study also explores how temperature and salinity with depth, as well as at the surface, in the SCTR change with the climatic events in a given year. Although ENSO is known to have a stronger impact on SST south of the SCTR (10°S-15°S), this study reveals the stronger impact of ENSO on sea surface salinity (SSS) in the SCTR

NASA CYGNSS Mission Applications Workshop

NASA's Cyclone Global Navigation Satellite System, (CYGNSS), mission is a constellation of eight microsatellites that will measure surface winds in and near the inner cores of hurricanes, including regions beneath the eyewall and intense inner rainbands that could not previously be measured from space. The CYGNSS-measured wind fields, when combined with precipitation fields (e.g., produced by the Global Precipitation Measurement [GPM] core satellite and its constellation of precipitation imagers), will provide coupled observations of moist atmospheric thermodynamics and ocean surface response, enabling new insights into hurricane inner core dynamics and energetics. The outcomes of this workshop, which are detailed in this report, comprise two primary elements: (1) A report of workshop proceedings, and; (2) Detailed Applications Traceability Matrices with requirements and operational considerations to serve broadly for development of value-added tools, applications, and products

Potential Effect of Bio-Surfactants on Sea Spray Generation in Tropical Cyclone Conditions

Despite significant improvement in computational and observational capabilities, predicting intensity and intensification of major tropical cyclones remains a challenge. In 2017 Hurricane Maria intensified to a Category 5 storm within 24 h, devastating Puerto Rico. In 2019 Hurricane Dorian, predicted to remain tropical storm, unexpectedly intensified into a Category 5 storm and destroyed the Bahamas. The official forecast and computer models were unable to predict rapid intensification of these storms. One possible reason for this is that key physics, including microscale processes at the air-sea interface, are poorly understood and parameterized in existing forecast models. Here we show that surfactants significantly affect the generation of sea spray, which provides some of the fuel for tropical cyclones and their intensification, but also provides some of the drag that limits intensity and intensification. Using a numerical model verified with a laboratory experiment, which predicts spray radii distribution starting from a 100 μm radius, we show that surfactants increase spray generation by 20–34%. We anticipate that bio-surfactants affect heat, energy, and momentum exchange through altered size distribution and concentration of sea spray, with consequences for tropical cyclone intensification or decline, particularly in areas of algal blooms and near coral reefs, as well as in areas affected by oil spills and dispersants

Downscaling GLDAS Soil Moisture Data in East Asia through Fusion of Multi-Sensors by Optimizing Modified Regression Trees

Soilmoisture is a key part of Earth's climate systems, including agricultural and hydrological cycles. Soil moisture data from satellite and numerical models is typically provided at a global scale with coarse spatial resolution, which is not enough for local and regional applications. In this study, a soil moisture downscaling model was developed using satellite-derived variables targeting Global Land Data Assimilation System (GLDAS) soil moisture as a reference dataset in East Asia based on the optimization of a modified regression tree. A total of six variables, Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced SCATterometer (ASCAT) soil moisture products, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and MODerate resolution Imaging Spectroradiometer (MODIS) products, including Land Surface Temperature, Normalized Difference Vegetation Index, and land cover, were used as input variables. The optimization was conducted through a pruning approach for operational use, and finally 59 rules were extracted based on root mean square errors (RMSEs) and correlation coefficients (r). The developed downscaling model showed a good modeling performance (r = 0.79, RMSE = 0.056 m(3)center dot m(3), and slope = 0.74). The 1 km downscaled soil moisture showed similar time series patterns with both GLDAS and ground soil moisture and good correlation with ground soil moisture (average r = 0.47, average RMSD = 0.038 m(3)center dot m(3)) at 14 ground stations. The spatial distribution of 1 km downscaled soil moisture reflected seasonal and regional characteristics well, although the model did not result in good performance over a few areas such as Southern China due to very high cloud cover rates. The results of this study are expected to be helpful in operational use to monitor soil moisture throughout East Asia since the downscaling model produces daily high resolution (1 km) real time soil moisture with a low computational demand. This study yielded a promising result to operationally produce daily high resolution soil moisture data from multiple satellite sources, although there are yet several limitations. In future research, more variables including Global Precipitation Measurement (GPM) precipitation, Soil Moisture Active Passive (SMAP) soil moisture, and other vegetation indices will be integrated to improve the performance of the proposed soil moisture downscaling model.ope

Quasi-biweekly mode of the Asian summer monsoon revealed in Bay of Bengal surface observations

Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 125(12),(2020): e2020JC016271, https://doi.org/10.1029/2020JC016271.Asian summer monsoon has a planetary‐scale, westward propagating “quasi‐biweekly” mode of variability with a 10–25 day period. Six years of moored observations at 18°N, 89.5°E in the north Bay of Bengal (BoB) reveal distinct quasi‐biweekly variability in sea surface salinity (SSS) during summer and autumn, with peak‐to‐peak amplitude of 3–8 psu. This large‐amplitude SSS variability is not due to variations of surface freshwater flux or river runoff. We show from the moored data, satellite SSS, and reanalyses that surface winds associated with the quasi‐biweekly monsoon mode and embedded weather‐scale systems, drive SSS and coastal sea level variability in 2015 summer monsoon. When winds are calm, geostrophic currents associated with mesoscale ocean eddies transport Ganga‐Brahmaputra‐Meghna river water southward to the mooring, salinity falls, and the ocean mixed layer shallows to 1–10 m. During active (cloudy, windy) spells of quasi‐biweekly monsoon mode, directly wind‐forced surface currents carry river water away to the east and north, leading to increased salinity at the moorings, and rise of sea level by 0.1–0.5 m along the eastern and northern boundary of the bay. During July–August 2015, a shallow pool of low‐salinity river water lies in the northeastern bay. The amplitude of a 20‐day oscillation of sea surface temperature (SST) is two times larger within the fresh pool than in the saltier ocean to the west, although surface heat flux is nearly identical in the two regions. This is direct evidence that spatial‐temporal variations of BoB salinity influences sub‐seasonal SST variations, and possibly SST‐mediated monsoon air‐sea interaction.The authors thank the Ministry of Earth Sciences (MoES) institutes NIOT and INCOIS, and the Upper Ocean Processes (UOP) group at WHOI for design, integration, and deployment of moorings in the BoB. The WHOI mooring was deployed from the ORV Sagar Nidhi and recovered from the ORV Sagar Kanya—we thank the officers, crew and science teams on the cruises for their support. Sengupta, Ravichandran and Sukhatme acknowledge MoES and the National Monsoon Mission, Indian Institute of Tropical Meteorology (IITM), Pune, for support; Lucas and Farrar acknowledge the US Office of Naval Research for support of ASIRI through grants N00014‐13‐1‐0489, N0001413‐100453, N0001417‐12880. We thank S. Shivaprasad, Dipanjan Chaudhuri and Jared Buckley for discussion on ocean currents and Ekman flow, and Fabien Durand for discussion on sea level. JSL would like to thank the Divecha Center for Climate Change, IISc., for support. DS acknowledges support from the Department of Science and Technology (DST), New Delhi, under the Indo‐Spanish Programme.2021-05-1

Remote Sensing of Tropical Cyclones: Applications from Microwave Radiometry and Global Navigation Satellite System Reflectometry

Tropical cyclones (TCs) are important to observe, especially over the course of their lifetimes, most of which is spent over the ocean. Very few in situ observations are available. Remote sensing has afforded researchers and forecasters the ability to observe and understand TCs better. Every remote sensing platform used to observe TCs has benefits and disadvantages. Some remote sensing instruments are more sensitive to clouds, precipitation, and other atmospheric constituents. Some remote sensing instruments are insensitive to the atmosphere, which allows for unobstructed observations of the ocean surface. Observations of the ocean surface, either of surface roughness or emission can be used to estimate ocean surface wind speed. Estimates of surface wind speed can help determine the intensity, structure, and destructive potential of TCs. While there are many methods by which TCs are observed, this thesis focuses on two main types of remote sensing techniques: passive microwave radiometry and Global Navigation Satellite System reflectometry (GNSS-R). First, we develop and apply a rain rate and ocean surface wind speed retrieval algorithm for the Hurricane Imaging Radiometer (HIRAD). HIRAD, an airborne passive microwave radiometer, operates at C-band frequencies, and is sensitive to rain absorption and emission, as well as ocean surface emission. Motivated by the unique observing geometry and high gradient rain scenes that HIRAD typically observes, a more robust rain rate and wind speed retrieval algorithm is developed. HIRAD’s observing geometry must be accounted for in the forward model and retrieval algorithm, if high rain gradients are to be estimated from HIRAD’s observations, with the ultimate goal of improving surface wind speed estimation. Lastly, TC science data products are developed for the Cyclone Global Navigation Satellite System (CYGNSS). The CYGNSS constellation employs GNSS-R techniques to estimate ocean surface wind speed in all precipitating conditions. From inputs of CYGNSS level-2 wind speed observations and the storm center location, a variety of products are created: integrated kinetic energy, wind radii, radius of maximum wind speed, and maximum wind speed. These products provide wind structure and intensity information—valuable for situational awareness and science applications.PHDAtmospheric, Oceanic & Space ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137109/1/marygm_1.pd

Ocean observations in support of studies and forecasts of tropical and extratropical cyclones

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Domingues, R., Kuwano-Yoshida, A., Chardon-Maldonado, P., Todd, R. E., Halliwell, G., Kim, H., Lin, I., Sato, K., Narazaki, T., Shay, L. K., Miles, T., Glenn, S., Zhang, J. A., Jayne, S. R., Centurioni, L., Le Henaff, M., Foltz, G. R., Bringas, F., Ali, M. M., DiMarco, S. F., Hosoda, S., Fukuoka, T., LaCour, B., Mehra, A., Sanabia, E. R., Gyakum, J. R., Dong, J., Knaff, J. A., & Goni, G. Ocean observations in support of studies and forecasts of tropical and extratropical cyclones. Frontiers in Marine Science, 6, (2019): 446, doi:10.3389/fmars.2019.00446.Over the past decade, measurements from the climate-oriented ocean observing system have been key to advancing the understanding of extreme weather events that originate and intensify over the ocean, such as tropical cyclones (TCs) and extratropical bomb cyclones (ECs). In order to foster further advancements to predict and better understand these extreme weather events, a need for a dedicated observing system component specifically to support studies and forecasts of TCs and ECs has been identified, but such a system has not yet been implemented. New technologies, pilot networks, targeted deployments of instruments, and state-of-the art coupled numerical models have enabled advances in research and forecast capabilities and illustrate a potential framework for future development. Here, applications and key results made possible by the different ocean observing efforts in support of studies and forecasts of TCs and ECs, as well as recent advances in observing technologies and strategies are reviewed. Then a vision and specific recommendations for the next decade are discussed.This study was supported by the National Oceanic and Atmospheric Administration and JSPS KAKENHI (Grant Numbers: JP17K19093, JP16K12591, and JP16H01846)

Satellite remote sensing of surface winds, waves, and currents: Where are we now?

This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields