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Dehai Song, Wen Wu, and Qiang Li

Abstract

Bay-shelf exchange is critical to coastal systems as it promotes self-purification or pollution dilution of the systems. In this study, the effects of wave-current interactions on bay-shelf exchange are explored in a micromesotidal system – Daya Bay in southern China. Waves can enlarge the shear-induced seaward transport and reduce the residual-current-induced landward transport, which benefits the bay-shelf exchange; however, tides work oppositely and slow the wave-induced bay-shelf exchange due to vertical mixing and reduced shear-induced exchange. Five wave-current interactions are compared and it is found that the depth-dependent wave radiation stress (WRS) contributes most to the bay-shelf exchange, followed by the wave dissipation as a source term in the turbulence kinetic energy equation, and the mean current advection and refraction of wave energy (CARWE). The vertical transfer of wave-generated pressure to the mean momentum equation (also known as the form drag), and the combined wave-current bottom stress (CWCBS) play minor roles in the bay-shelf exchange. The bay-shelf exchange is faster under southerly wind than that under northerly wind as the bay is facing southeast; the synoptic events like storms enhance the bay-shelf exchange. The CARWE terms are dominant in both seasonal and synoptic variations of the bay-shelf exchange as they can significantly change the distribution of significant wave height. The WRS changes the bay-shelf exchange mainly through altering the flow velocity, whereas the wave dissipation on turbulence alters the vertical mixing. The form drag and the CWCBS have little impact on the bay-shelf exchange as well as its seasonal and synoptic variations.

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K. Dieter Klaes, Jörg Ackermann, Craig Anderson, Yago Andres, Thomas August, Régis Borde, Bojan Bojkov, Leonid Butenko, Alessandra Cacciari, Dorothée Coppens, Marc Crapeau, Stephanie Guedj, Olivier Hautecoeur, Tim Hultberg, Rüdiger Lang, Stefanie Linow, Christian Marquardt, Rosemarie Munro, Carlo Pettirossi, Gabriele Poli, Francesca Ticconi, Olivier Vandermarcq, Mayte Vasquez, and Margarita Vazquez-Navarro

Abstract

After successful launch in November 2018 and successful commissioning of Metop-C, all three satellites of the EUMETSAT Polar System (EPS) are in orbit together and operational. EPS is part of the Initial Joint Polar System (IJPS) with the US (NOAA) and provides the service in the mid-morning orbit. The Metop satellites carry a mission payload of sounding and imaging instruments, which allow provision of support to operational meteorology and climate monitoring which are the main mission objectives for EPS. Applications include Numerical Weather Prediction, atmospheric composition monitoring, and marine meteorology. Climate monitoring is supported through the generation of long time series through the program duration of 20+ years. The payload was developed and contributed by partners, including NOAA, CNES, and ESA. EUMETSAT and ESA developed the space segment in cooperation. The system has proven its value since the first satellite Metop-A, with enhanced products at high reliability for atmospheric sounding, delivered a very strong positive impact on NWP and results beyond expectations for atmospheric composition and chemistry applications. Having multiple satellites in orbit - now three, has enabled enhanced and additional products with increased impact, like atmospheric motion vector products at latitudes not accessible to geostationary observations or increased probability of radio-occultations and hence atmospheric soundings with the GRAS instruments. The paper gives an overview on the system, the embarked payload and discusses the benefits of generated products for applications and services. The conclusions point to the follow-on system, currently under development and assuring continuity for another 20+ years.

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R. M. Samelson, S. P. de Szoeke, E. D. Skyllingstad, P. L. Barbour, and S. M. Durski

Abstract

Fog and low-level stratus during April through September 2009 are examined in a set of coupled ocean-atmosphere numerical simulations of the northern California Current System (CCS). The model configurations differ only in the choice of planetary boundary layer (PBL) parameterization scheme and, in one case, surface flux scheme. The results suggest that fog formation in this region primarily occurs through condensation at the surface induced locally by surface cooling, when moist offshore air is advected over cold upwelled waters and the shallow coastal marine PBL is further stabilized by warm, dry, continental air that extends offshore above the PBL inversion. These results are consistent with some but not all prior hypotheses for fog formation in the CCS region. Fog formation by downward growth of a pre-existing stratus layer is also found in the simulations but dominates only in those simulations with PBL schemes that produce an extensive and evidently unphysical stratus layer at 200-m height, which serves as the source for the downward growth. The stronger fog response in later summer months arises from seasonal warming of offshore SST, which increases the moisture content and temperature of the upstream air mass, while cool coastal SSTs are maintained by upwelling. On synoptic timescales, a similar influence of fog response on upstream conditions is found but controlled instead by changes in wind direction. These results suggest that the critical factors determining the evolution of the coastal fog regime in a warming climate are likely the temperature of upwelling source waters and the offshore flow of continental air.

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Peyman Abbaszadeh, Hamid Moradkhani, Keyhan Gavahi, Sujay Kumar, Christopher Hain, Xiwu Zhan, Qingyun Duan, Christa Peters-Lidard, and Mohammadsepehr Karimiziarani
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Jonathan Poterjoy, Ghassan J. Alaka Jr., and Henry R. Winterbottom

Abstract

Limited-area numerical weather prediction models currently run operationally in the United States follow a “partially-cycled” schedule, where sequential data assimilation is periodically interrupted by replacing model states with solutions interpolated from a global model. While this strategy helps overcome several practical challenges associated with real-time regional forecasting, it is no substitute for a robust sequential data assimilation approach for research-to-operations purposes. Partial cycling can mask systematic errors in weather models, data assimilation systems, and data pre-processing techniques, since it introduces information from a different prediction system. It also adds extra heuristics to the model initialization steps outside the general Bayesian filtering framework from which data assimilation methods are derived. This study uses a research-oriented modeling system, which is self-contained in the operational Hurricane Weather Research and Forecasting (HWRF) model package, to illustrate why next-generation modeling systems should prioritize sequential data assimilation at early stages of development. This framework permits the rigorous examination of all model system components—in a manner that has never been done for the HWRF model. Examples presented in this manuscript show how sequential data assimilation capabilities can accelerate model advancements and increase academic involvement in operational forecasting systems at a time when the United States is developing a new hurricane forecasting system.

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Adam H. Sobel, Janet Sprintall, Eric D. Maloney, Zane K. Martin, Shuguang Wang, Simon P. de Szoeke, Benjamin C. Trabing, and Steven A. Rutledge

Abstract

The Propagation of Intraseasonal Tropical Oscillations (PISTON) experiment conducted a field campaign inAugust-October 2018. The R/V Thomas G. Thompson made two cruises in thewestern North Pacific region north of Palau and east of the Philippines. Using select field observations and global observational and reanalysis data sets, this study describes the large-scale state and evolution of the atmosphere and ocean during these cruises. Intraseasonal variability was weak during the field program, except for a period of suppressed convection in October. Tropical cyclone activity, on the other hand, was strong. Variability at the ship location was characterized by periods of low-level easterly atmospheric flow with embedded westward propagating synoptic-scale atmospheric disturbances, punctuated by periods of strong low-level westerly winds that were both connected to the Asian monsoon westerlies and associated with tropical cyclones. In the most dramatic case, westerlies persisted for days during and after tropical cyclone Jebi had passed to the north of the ship. In these periods, the sea surface temperature was reduced by a couple of degrees by both wind mixing and net surface heat fluxes that were strongly (~200Wm −2) out of the ocean, due to both large latent heat flux and cloud shading associated with widespread deep convection. Underway conductivity-temperature transects showed dramatic cooling and deepening of the ocean mixed layer and erosion of the barrier layer after the passage of Typhoon Mangkhut due to entrainment of cooler water from below. Strong zonal currents observed over at least the upper 400 meters were likely related to the generation and propagation of near-inertial currents.

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Colin M. Zarzycki, Paul A. Ullrich, and Kevin A. Reed

Abstract

This manuscript describes a software suite that can be used for objective evaluation of tropical cyclones (TCs) in gridded climate data. Using cyclone trajectories derived from 6-hourly data, a comprehensive set of metrics is defined to systematically compare and contrast products to one another. In addition to annual TC climatologies, attention is paid to spatial and temporal patterns of storm occurrence and intensity. Assessment can be performed either on the global scale or regional domains. Simple to visualize ‘scorecards’ allow for rapid credibility assessment. We showcase three key findings enabled by this suite. First, we compare the representation of TCs in seven current-generation global reanalyses and conclude that higher resolution models and those with TC-specific assimilation contain more accurate storm climatologies. Second, using a free-running Earth system model (ESM) we find that full basin refinement is required in variable-resolution configurations to adequately simulate North Atlantic TC frequency. Upstream refinement over northern Africa offers little benefit in simulating storm occurrence but spatial genesis patterns are improved. Finally, we show that TCs simulated by ESMs can be highly sensitive to individual parameterizations in climate models, with North Atlantic TC metrics varying greatly depending on version of the Morrison-Gettelman microphysics package.

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David A. Lavers, Shaun Harrigan, and Christel Prudhomme

Abstract

Precipitation is a key component of the global water cycle and plays a crucial role in flooding, droughts, and water supply. One way to manage its socioeconomic effects is based on precipitation forecasts from numerical weather prediction (NWP) models, and an important step to improve precipitation forecasts is by diagnosing NWP biases. In this study, we investigate the biases in precipitation forecasts from the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS). Using the IFS control forecast from 12 June 2019 to 11 June 2020 at 5,219 stations globally, we show that in each of the boreal winter and summer half years, the IFS (1) has an average global wet bias and (2) displays similar bias patterns for forecasts starting at 0000 UTC and 1200 UTC and across forecast days 1 to 5. These biases are dependent on observed (climatological) precipitation; stations with low observed precipitation have an IFS wet bias, while stations with high observed precipitation have an IFS dry bias. Southeast Asia has a wet bias of 1.61 mm day-1 (in boreal summer) and over the study period the precipitation is overestimated by 31.0% on forecast day 3. This is the hydrological signature of several hypothesized processes including issues specifying the IFS snowpack over the Tibetan Plateau which may affect the Meiyu front. These biases have implications for IFS land-atmosphere feedbacks, river discharge, and for ocean circulation in the southeast Asia region. Reducing these biases could lead to more accurate forecasts of the global water cycle.

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Luke Phillipson, Yi Li, and Ralf Toumi

Abstract

The forecast of tropical cyclone (TC) intensity is a significant challenge. In this study, we showcase the impact of strongly coupled data assimilation with hypothetical ocean currents on analyses and forecasts of Typhoon Hato (2017). Several observation simulation system experiments were undertaken with a regional coupled ocean-atmosphere model. We assimilated combinations of (or individually) a hypothetical coastal current HF radar network, a dense array of drifter floats and minimum sea-level pressure. During the assimilation, instant updates of many important atmospheric variables (winds and pressure) are achieved from the assimilation of ocean current observations using the cross-domain error covariance, significantly improving the track and intensity analysis of Typhoon Hato. As compared to a control experiment (with no assimilation), the error of minimum pressure decreased by up to 13 hPa (4 hPa / 57 % on average). The maximum wind speed error decreased by up to 18 knots (5 knots / 41 % on average). By contrast, weakly coupled implementations cannot match these reductions (10% on average). Although traditional atmospheric observations were not assimilated, such improvements indicate there is considerable potential in assimilating ocean currents from coastal HF radar, and surface drifters within a strongly coupled framework for intense landfalling TCs.

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J. V. Lukovich, Julienne Stroeve1, Alex Crawford, Lawrence Hamilton, Michel Tsamados, Harry Heorton, and François Massonnet

Abstract

In this study the impact of extreme cyclones on Arctic sea ice in summer is investigated. Examined in particular are relative thermodynamic and dynamic contributions to sea ice volume budgets in the vicinity of Arctic summer cyclones in 2012 and 2016. Results from this investigation illustrate sea ice loss in the vicinity of the cyclone trajectories during each year were associated with different dominant processes: thermodynamic (melting) in the Pacific sector of the Arctic in 2012, and both thermodynamic and dynamic processes in the Pacific sector of the Arctic in 2016. Comparison of both years further suggests that the Arctic minimum sea ice extent is influenced by not only the strength of the cyclone, but also by the timing and location relative to the sea ice edge. Located near the sea ice edge in early August in 2012, and over the central Arctic later in August in 2016, extreme cyclones contributed to comparable sea ice area (SIA) loss, yet enhanced sea ice volume loss in 2012 relative to 2016.

Central to a characterization of extreme cyclone impacts on Arctic sea ice from the perspective of thermodynamic and dynamic processes, we present an index describing relative thermodynamic and dynamic contributions to sea ice volume changes. This index helps to quantify and improve our understanding of initial sea ice state and dynamical responses to cyclones in a rapidly warming Arctic, with implications for seasonal ice forecasting, marine navigation, coastal community infrastructure and designation of protected and ecologically sensitive marine zones.

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