Miller Arthur J.

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Miller
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Arthur J.
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0000-0003-3459-2676

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The role of air-sea interactions in atmospheric rivers: Case studies using the SKRIPS regional coupled model

2021-02-12 , Sun, Rui , Subramanian, Aneesh C. , Cornuelle, Bruce D. , Mazloff, Matthew R. , Miller, Arthur J. , Ralph, F. Martin

Atmospheric rivers (ARs) play a key role in California's water supply and are responsible for most of the extreme precipitation and major flooding along the west coast of North America. Given the high societal impact, it is critical to improve our understanding and prediction of ARs. This study uses a regional coupled ocean–atmosphere modeling system to make hindcasts of ARs up to 14 days. Two groups of coupled runs are highlighted in the comparison: (1) ARs occurring during times with strong sea surface temperature (SST) cooling and (2) ARs occurring during times with weak SST cooling. During the events with strong SST cooling, the coupled model simulates strong upward air–sea heat fluxes associated with ARs; on the other hand, when the SST cooling is weak, the coupled model simulates downward air–sea heat fluxes in the AR region. Validation data shows that the coupled model skillfully reproduces the evolving SST, as well as the surface turbulent heat transfers between the ocean and atmosphere. The roles of air–sea interactions in AR events are investigated by comparing coupled model hindcasts to hindcasts made using persistent SST. To evaluate the influence of the ocean on ARs we analyze two representative variables of AR intensity, the vertically integrated water vapor (IWV) and integrated vapor transport (IVT). During strong SST cooling AR events the simulated IWV is improved by about 12% in the coupled run at lead times greater than one week. For IVT, which is about twice more variable, the improvement in the coupled run is about 5%.

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Coupled impacts of the diurnal cycle of sea surface temperature on the Madden–Julian oscillation

2014-11-15 , Seo, Hyodae , Subramanian, Aneesh C. , Miller, Arthur J. , Cavanaugh, Nicholas R.

This study quantifies, from a systematic set of regional ocean–atmosphere coupled model simulations employing various coupling intervals, the effect of subdaily sea surface temperature (SST) variability on the onset and intensity of Madden–Julian oscillation (MJO) convection in the Indian Ocean. The primary effect of diurnal SST variation (dSST) is to raise time-mean SST and latent heat flux (LH) prior to deep convection. Diurnal SST variation also strengthens the diurnal moistening of the troposphere by collocating the diurnal peak in LH with those of SST. Both effects enhance the convection such that the total precipitation amount scales quasi-linearly with preconvection dSST and time-mean SST. A column-integrated moist static energy (MSE) budget analysis confirms the critical role of diurnal SST variability in the buildup of column MSE and the strength of MJO convection via stronger time-mean LH and diurnal moistening. Two complementary atmosphere-only simulations further elucidate the role of SST conditions in the predictive skill of MJO. The atmospheric model forced with the persistent initial SST, lacking enhanced preconvection warming and moistening, produces a weaker and delayed convection than the diurnally coupled run. The atmospheric model with prescribed daily-mean SST from the coupled run, while eliminating the delayed peak, continues to exhibit weaker convection due to the lack of strong moistening on a diurnal basis. The fact that time-evolving SST with a diurnal cycle strongly influences the onset and intensity of MJO convection is consistent with previous studies that identified an improved representation of diurnal SST as a potential source of MJO predictability.

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Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments

2020-02-20 , Jacox, Michael , Alexander, Michael A. , Siedlecki, Samantha A. , Chen, Ke , Kwon, Young-Oh , Brodie, Stephanie , Ortiz, Ivonne , Tommasi, Desiree , Widlansky, Matthew J. , Barrie, Daniel , Capotondi, Antonietta , Cheng, Wei , Di Lorenzo, Emanuele , Edwards, Christopher , Fiechter, Jerome , Fratantoni, Paula S. , Hazen, Elliott L. , Hermann, Albert J. , Kumar, Arun , Miller, Arthur J. , Pirhalla, Douglas , Pozo Buil, Mercedes , Ray, Sulagna , Sheridan, Scott , Subramanian, Aneesh C. , Thompson, Philip , Thorne, Lesley , Annamalai, Hariharasubramanian , Aydin, Kerim , Bograd, Steven , Griffis, Roger B. , Kearney, Kelly , Kim, Hyemi , Mariotti, Annarita , Merrifield, Mark , Rykaczewski, Ryan R.

Marine ecosystem forecasting is an area of active research and rapid development. Promise has been shown for skillful prediction of physical, biogeochemical, and ecological variables on a range of timescales, suggesting potential for forecasts to aid in the management of living marine resources and coastal communities. However, the mechanisms underlying forecast skill in marine ecosystems are often poorly understood, and many forecasts, especially for biological variables, rely on empirical statistical relationships developed from historical observations. Here, we review statistical and dynamical marine ecosystem forecasting methods and highlight examples of their application along U.S. coastlines for seasonal-to-interannual (1–24 month) prediction of properties ranging from coastal sea level to marine top predator distributions. We then describe known mechanisms governing marine ecosystem predictability and how they have been used in forecasts to date. These mechanisms include physical atmospheric and oceanic processes, biogeochemical and ecological responses to physical forcing, and intrinsic characteristics of species themselves. In reviewing the state of the knowledge on forecasting techniques and mechanisms underlying marine ecosystem predictability, we aim to facilitate forecast development and uptake by (i) identifying methods and processes that can be exploited for development of skillful regional forecasts, (ii) informing priorities for forecast development and verification, and (iii) improving understanding of conditional forecast skill (i.e., a priori knowledge of whether a forecast is likely to be skillful). While we focus primarily on coastal marine ecosystems surrounding North America (and the U.S. in particular), we detail forecast methods, physical and biological mechanisms, and priority developments that are globally relevant.

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Observational needs supporting marine ecosystems modeling and forecasting: from the global ocean to regional and coastal systems

2019-10-15 , Capotondi, Antonietta , Jacox, Michael , Bowler, Chris , Kavanaugh, Maria T. , Lehodey, Patrick , Barrie, Daniel , Brodie, Stephanie , Chaffron, Samuel , Cheng, Wei , Dias, Daniela F. , Eveillard, Damien , Guidi, Lionel , Iudicone, Daniele , Lovenduski, Nicole S. , Nye, Janet A. , Ortiz, Ivonne , Pirhalla, Douglas , Pozo Buil, Mercedes , Saba, Vincent S. , Sheridan, Scott , Siedlecki, Samantha A. , Subramanian, Aneesh C. , de Vargas, Colomban , Di Lorenzo, Emanuele , Doney, Scott C. , Hermann, Albert J. , Joyce, Terrence M. , Merrifield, Mark , Miller, Arthur J. , Not, Fabrice , Pesant, Stephane

Many coastal areas host rich marine ecosystems and are also centers of economic activities, including fishing, shipping and recreation. Due to the socioeconomic and ecological importance of these areas, predicting relevant indicators of the ecosystem state on sub-seasonal to interannual timescales is gaining increasing attention. Depending on the application, forecasts may be sought for variables and indicators spanning physics (e.g., sea level, temperature, currents), chemistry (e.g., nutrients, oxygen, pH), and biology (from viruses to top predators). Many components of the marine ecosystem are known to be influenced by leading modes of climate variability, which provide a physical basis for predictability. However, prediction capabilities remain limited by the lack of a clear understanding of the physical and biological processes involved, as well as by insufficient observations for forecast initialization and verification. The situation is further complicated by the influence of climate change on ocean conditions along coastal areas, including sea level rise, increased stratification, and shoaling of oxygen minimum zones. Observations are thus vital to all aspects of marine forecasting: statistical and/or dynamical model development, forecast initialization, and forecast validation, each of which has different observational requirements, which may be also specific to the study region. Here, we use examples from United States (U.S.) coastal applications to identify and describe the key requirements for an observational network that is needed to facilitate improved process understanding, as well as for sustaining operational ecosystem forecasting. We also describe new holistic observational approaches, e.g., approaches based on acoustics, inspired by Tara Oceans or by landscape ecology, which have the potential to support and expand ecosystem modeling and forecasting activities by bridging global and local observations.

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Effect of eddy-wind interaction on Ekman pumping and eddy kinetic energy : a regional coupled modeling study for the California Current System

2015 , Seo, Hyodae , Miller, Arthur J. , Norris, Joel R.

The California Current system (CCS) is characterized by the energetic summertime mesoscale and filamentary eddies with typical anomalies in sea surface temperature (SST) and surface current exceeding 2˚C and 0.5 cms–1, respectively. Recent satellite observations show that both SST and surface current at oceanic mesoscales significantly influence the Ekman pumping velocity, suggestive of a subsequent dynamical feedback effect on the eddy energetics. The extent to which this mesoscale coupling is important for the Ekman pumping and the eddy kinetic energy (EKE) budget in the CCS is the focus of this study.

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Impact of extratropical Northeast Pacific SST on U.S. West Coast Precipitation

2023-02-08 , Beaudin, Élise , Di Lorenzo, Emanuele , Miller, Arthur J. , Seo, Hyodae , Joh, Youngji

The rainfall over the U.S. West Coast is known to be highly influenced by large‐scale atmospheric circulation and tropical climate teleconnections. However, the role of North Pacific oceanic variability is less understood. Using high‐resolution regional atmospheric model simulations forced by sustained positive and negative phases of the extratropical Pacific Decadal Oscillation sea surface temperature anomalies (SSTa), we diagnose the precipitation changes over the U.S. West Coast during 2010–2020. We find that precipitation anomalies are up to 60% stronger (weaker) for the warm (cold) cases, especially over Northern and Central California during wintertime, and Baja California in the summertime. In both seasons, precipitation is predominantly modulated through changes in the water vapor flux, which are directed toward the coast in wintertime and away from the coast during summertime. These flux anomalies are primarily driven by large‐scale changes in the wind associated with the atmospheric adjustment to the strong ocean SSTa.Plain Language SummaryThis study examines how ocean temperature in the Northeast Pacific affects rainfall in the U.S. West Coast using computer model simulations over the period 2010–2020. Rainfall generally increases when coastal waters are warmer and vice versa. This is especially true in Northern and Central California during wintertime and in Baja California during summertime. The amount of rain is mainly affected by changes in the water vapor that moves toward the coast in the winter and away from the coast in the summer. These changes in water vapor are caused by changes in the wind, which are linked to changes in the surface ocean temperature.Key PointsWarming along the U.S. West Coast can induce wind‐driven vapor fluxes changes leading to enhanced precipitationExtratropical sea surface temperature (SST) forcing can impact large‐scale atmospheric circulationU.S. West Coast precipitation are impacted by extratropical Northeast Pacific SST

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Coupled ocean–atmosphere modeling and predictions

2017-05-01 , Miller, Arthur J. , Collins, Matthew , Gualdi, Silvio , Jensen, Tommy G. , Misra, Vasu , Pezzi, Luciano Ponzi , Pierce, David W. , Putrasahan, Dian , Seo, Hyodae , Tseng, Yu-Heng

Key aspects of the current state of the ability of global and regional climate models to represent dynamical processes and precipitation variations are summarized. Interannual, decadal, and global-warming timescales, wherein the influence of the oceans is relevant and the potential for predictability is highest, are emphasized. Oceanic influences on climate occur throughout the ocean and extend over land to affect many types of climate variations, including monsoons, the El Niño Southern Oscillation, decadal oscillations, and the response to greenhouse gas emissions. The fundamental ideas of coupling between the ocean-atmosphere-land system are explained for these modes in both global and regional contexts. Global coupled climate models are needed to represent and understand the complicated processes involved and allow us to make predictions over land and sea. Regional coupled climate models are needed to enhance our interpretation of the fine-scale response. The mechanisms by which large-scale, low-frequency variations can influence shorter timescale variations and drive regionalscale effects are also discussed. In this light of these processes, the prospects for practical climate predictability are also presented.

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Eddy–wind interaction in the California Current System : dynamics and impacts

2015-11-30 , Seo, Hyodae , Miller, Arthur J. , Norris, Joel R.

The summertime California Current System (CCS) is characterized by energetic mesoscale eddies, whose sea surface temperature (SST) and surface current can significantly modify the wind stress and Ekman pumping. Relative importance of the eddy–wind interactions via SST and surface current in the CCS is examined using a high-resolution (7 km) regional coupled model with a novel coupling approach to isolate the small-scale air–sea coupling by SST and surface current. Results show that when the eddy-induced surface current is allowed to modify the wind stress, the spatially averaged surface eddy kinetic energy (EKE) is reduced by 42%, and this is primarily due to enhanced surface eddy drag and reduced wind energy transfer. In contrast, the eddy-induced SST–wind coupling has no significant impact on the EKE. Furthermore, eddy-induced SST and surface current modify the Ekman pumping via their crosswind SST gradient and surface vorticity gradient, respectively. The resultant magnitudes of the Ekman pumping velocity are comparable, but the implied feedback effects on the eddy statistics are different. The surface current-induced Ekman pumping mainly attenuates the amplitude of cyclonic and anticyclonic eddies, acting to reduce the eddy activity, while the SST-induced Ekman pumping primarily affects the propagation. Time mean–rectified change in SST is determined by the altered offshore temperature advection by the mean and eddy currents, but the magnitude of the mean SST change is greater with the eddy-induced current effect. The demonstrated remarkably strong dynamical response in the CCS system to the eddy-induced current–wind coupling indicates that eddy-induced current should play an important role in the regional coupled ocean–atmosphere system.

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Coupled ocean-atmosphere forecasting at short and medium time scales

2017-11-01 , Pullen, Julie , Allard, Richard , Seo, Hyodae , Miller, Arthur J. , Chen, Shuyi , Pezzi, Luciano Ponzi , Smith, Travis , Chu, Philip , Alves, José , Caldeira, Rui

Recent technological advances over the past few decades have enabled the development of fully coupled atmosphere-ocean modeling prediction systems that are used today to support short-term (days to weeks) and medium-term (10–21 days) needs for both the operational and research communities. We overview the coupling framework, including model components and grid resolution considerations, as well as the coupling physics by examining heat fluxes between atmosphere and ocean, momentum transfer, and freshwater fluxes. These modeling systems can be run as fully coupled atmosphere-ocean and atmosphere-ocean-wave configurations. Examples of several modeling systems applied to complex coastal regions including Madeira Island, Adriatic Sea, Coastal California, Gulf of Mexico, Brazil, and the Maritime Continent are presented. In many of these studies, a variety of field campaigns have contributed to a better understanding of the underlying physics associated with the atmosphere-ocean feedbacks. Examples of improvements in predictive skill when run in coupled mode versus standalone are shown. Coupled model challenges such as model initialization, data assimilation, and earth system prediction are discussed.

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