Probabilistic Sea Level Rise Flood Projections Using a Localized Ocean Reference Surface

Projecting sea level rise (SLR) impacts requires defining ocean surface variability as a source of uncertainty. We analyze data from a Regional Ocean Modeling System (ROMS) reanalysis for the region surrounding the main Hawaiian Islands to incorporate the ocean surface uncertainty in mapping SLR flood probabilities. By analyzing the ocean surface height component of the ROMS reanalysis, we create an ocean surface reference (ORS) as a proxy for MHHW. We model the NOAA Intermediate, Intermediate-high and High regional SLR scenarios for the years 2050 and 2100 at three field sites around Oʻahu; Waikīkī, Hauʻula, Haleʻiwa. We calculate a probability density function (PDF) by convolving the PDF of water level derived from the ROMS reanalysis data with the PDF of error associated with a digital elevation model of the study sites. The resulting joint-PDF of flood depth allows us to create two types of probability-based flood projections: (1) Maps illustrating varying flood depths for a given probability threshold and, (2) maps illustrating varying probability for a specific flood depth. We compare 80% probability flood projections using our ORS approach to projections using the TCARI grid, the standard NOAA method. We highlight the importance of uncertainty and user-defined probability in identifying pixels that function as tipping points distinguishing flooding styles.

ROMSPath v1.0: Offline Particle Tracking for the Regional Ocean Modeling System (ROMS)

Offline particle tracking (OPT) is a widely used tool for the analysis of data in oceanographic research. Given the output of a hydrodynamic model, OPT can provide answers to a wide variety of research questions involving fluid kinematics, zooplankton transport, the dispersion of pollutants, and the fate of chemical tracers, among others. In this paper, we introduce ROMSPath, an OPT model designed to complement the Regional Ocean Modelling System (ROMS). Based on the Lagrangian TRANSport (LTRANS) model (North et al., 2008), ROMSPath is written in Fortran 90 and provides advancements in functionality and efficiency compared to LTRANS. First, ROMSPath now calculates particle trajectories using the ROMS native grid, which provides advantages in interpolation, masking, and boundary interaction, while improving accuracy. Second, ROMSPath enables simulated particles to pass between nested ROMS grids, which are an increasingly popular tool to simulate the ocean over multiple scales. Third, the ROMSPath vertical turbulence module enables the turbulent (diffusion) time step and advection time step to be specified separately, adding flexibility and improving computational efficiency. Lastly, ROMSPath includes new infrastructure enabling input of auxiliary parameters for added functionality. In particular, Stokes drift can be input and added to particle advection. Here we describe the details of these updates and improvements.

Seasonal-To-Interannual Variability of Sea-Surface Temperatures in The Inter-Americas Seas: Pattern-Dependent Biases in The Regional Ocean Modeling System

The Inter-Americas Seas (IAS), involving the Gulf of Mexico, the Caribbean and a section of the eastern tropical Pacific Ocean bordering Central America, Colombia and Ecuador, exhibits very active ocean-land-atmosphere interactions that impact socio-economic activities within and beyond the region, and that are still not well understood or represented in state-of-the-art models. On seasonal-to-interannual timescales, the main source of variability of this geographical area is related to interactions between the Pacific and the Atlantic oceans, involving to anomalous sea-surface temperature (SST) patterns like El Niño-Southern Oscillation (ENSO), and regional features in the Caribbean linked to the bi-modal seasonality of the Caribbean Low-Level Jet. This study investigates seasonal-to-interannual IAS surface-temperature anomalies in observations, and their representation in am eddy-permitting, 1/9o-resolution simulation using the Regional Ocean Modeling System (ROMS), interannually-forced by the Climate Forecast System Reanalysis. Here, rather than analyzing model biases locally (i.e., gridbox-by-gridbox), a non-local SST pattern-based diagnostic was conducted via a principal component analysis. The approach allowed to identify magnitude, variance and spatial systematic errors in SST patterns related to the Western Hemisphere Warm Pool, ENSO, the Inter-American Seas Dipole, and several other variability modes. These biases are mainly related to errors in surface heat fluxes, misrepresentation of air-sea interactions impacting surface latent cooling in the Caribbean, and too strong sub-surface thermal stratification, mostly off the coast of Ecuador and northern Peru.

Performance of the Adriatic Sea and Coast (AdriSC) climate component – a COAWST V3.3-based one-way coupled atmosphere–ocean modelling suite: ocean results

In this study, the Adriatic Sea and Coast (AdriSC) kilometre-scale atmosphere–ocean climate model covering the Adriatic Sea and northern Ionian Sea is presented. The AdriSC ocean results of a 31-year-long (i.e. 1987–2017) climate simulation, derived with the Regional Ocean Modeling System (ROMS) 3 km and 1 km models, are evaluated with respect to a comprehensive collection of remote sensing and in situ observational data. In general, it is found that the AdriSC model is capable of reproducing the observed sea surface properties, daily temperatures and salinities, and the hourly ocean currents with good accuracy. In particular, the AdriSC ROMS 3 km model demonstrates skill in reproducing the main variabilities of the sea surface height and the sea surface temperature, despite a persistent negative bias within the Adriatic Sea. Furthermore, the AdriSC ROMS 1 km model is found to be more capable of reproducing the observed thermohaline and dynamical properties than the AdriSC ROMS 3 km model. For the temperature and salinity, better results are obtained in the deeper parts than in the shallow shelf and coastal parts, particularly for the surface layer of the Adriatic Sea. The AdriSC ROMS 1 km model is also found to perform well in reproducing the seasonal thermohaline properties of the water masses over the entire Adriatic–Ionian domain. The evaluation of the modelled ocean currents revealed better results at locations along the eastern coast and especially the northeastern shelf than in the middle eastern coastal area and the deepest part of the Adriatic Sea. Finally, the AdriSC climate component is found to be a more suitable modelling framework to study the dense water formation and long-term thermohaline circulation of the Adriatic–Ionian basin than the available Mediterranean regional climate models.

Properties and evolution of a submesoscale cyclonic spiral

The evolution of a submesoscale cyclonic spiral of 1 km in diameter is simulated with ROMS (Regional Ocean Modeling System) using 33.3 m horizontal resolution in a triple-nested configuration. The generation of the spiral starts from a dense filament that is rolled into a vortex and detaches from the filament. During spin-up, extreme values are attained by various quantities, that are organized in single-arm and multi-arm spirals. The spin-down starts when the cyclone separates from the filament. At the same time, the horizontal speed develops a dipole-like pattern and isotachs form closed contours around the vortex center. The amplitudes of most quantities decrease significantly, but the instantaneous vertical velocity w exhibits high-frequency oscillations and more pronounced extremes than during spin-up. The oscillations are due to vortex Rossby waves (VRWs), that circle the eddy counterclockwise and generate multi-arm spirals with alternating signs by means of azimuthal vorticity advection. Experiments with virtual surface drifters and isopycnal floats indicate downwelling everywhere near the surface. The downwelling is most intense in the center of the spiral at all depth levels, leading to a radial outflow in the thermocline and weak upwelling at the periphery. This overturning circulation is driven by convergent near-surface flow and associated subduction of isopycnals. While the downwelling in the center may support the export of particulate organic carbon from the mixed layer into the main thermocline, the upwelling at the periphery effectuates an upward isopycnal transport of nutrients, enhancing the growth of phytoplankton in the euphotic zone.

Propagation of a Meteotsunami from the Yellow Sea to the Korea Strait in April 2019

A meteotsunami with a wave height of 0.1–0.9 m and a period of 60 min was observed at tide gauges along the Korea Strait on 7 April 2019, while a train of two to four atmospheric pressure disturbances with disturbance heights of 1.5–3.9 hPa moved eastward from the Yellow Sea to the Korea Strait. Analysis of observational data indicated that isobar lines of the atmospheric pressure disturbances had angles of 75–83° counterclockwise due east and propagated with a velocity of 26.5–31.0 m/s. The generation and propagation process of the meteotsunami was investigated using the Regional Ocean Modeling System. The long ocean waves were amplified due to Proudman resonance in the southwestern Yellow Sea, where the water is deeper than 75 m; here, the long ocean waves were refracted toward the coast on the shallow coastal region of the northern Korea Strait. Refraction and reflection by offshore islands significantly affect the wave heights at the coast. To investigate the effects of an eastward-moving velocity and angle of atmospheric pressure disturbance on the height of a long ocean wave, sensitivity simulations were performed. This result will be useful for the real-time prediction system of meteotsunamis in the Korea Strait.

CAPS v1.0: An improved regional coupled modeling system for Arctic sea ice and climate simulation and prediction

The updated Coupled Arctic Prediction System (CAPS) is evaluated, which is built on new versions of Weather Research and Forecasting model (WRF), the Regional Ocean Modeling System (ROMS), the Community Ice CodE (CICE), and a data assimilation based on the Local Error Subspace Transform Kalman Filter. A set of Pan-Arctic prediction experiments with improved/changed physical parameterizations in WRF, ROMS and CICE as well as different configurations are performed for the year 2018 to assess their impacts on the predictive skill of Arctic sea ice at seasonal timescale. The key improvements of WRF, including cumulus, boundary layer, and land surface schemes, result in improved simulation in near surface air temperature and downward radiation. The major changes of ROMS, including tracer advection and vertical mixing schemes, lead to improved evolution of the predicted total ice extent (particularly correcting the late ice recovery issue in the previous CAPS), and reduced biases in sea surface temperature. The changes of CICE, that include improved ice thermodynamics and assimilation of new sea ice thickness product, have noticeable influences on the predicted ice thickness and the timing of ice recovery. Results from the prediction experiments suggest that the updated CAPS can better predict the evolution of total ice extent compared with its predecessor, though the predictions still have certain biases at the regional scale. We further show that the CAPS can remain skillful beyond the melting season, which may have potential values for stakeholders making decisions for socioeconomical activities in the Arctic.