Oceanography

Numerical Modeling

RSS has the experience to use Regional Oceanic Circulation Model (ROMS) and Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM).  For regional or coastal ocean, a nested modeling approach with increasing spatial resolution and smaller modeling domain is usually applied in order to match the model spatial resolution to the scales of interests (e.g., 1 km or less in order to resolve the submesoscale variability) or the scales of available observations (e.g., 1 km satellite images).  For relatively complex coastlines and most bay/estuary, the SCHISM model with an unstructured grid and variable spatial resolution is usually used

Operational Oceanography

RSS has been maintaining two real-time ocean nowcast/forecast systems: California coastal ocean, Alaska Prince William Sound.  In both cases, near real-time (i.e., within hours behind real-time) observations from both in situ and remote sensing (including both satellite/aircraft and land-based) platforms are assimilated into numerical models to produce nowcast every six hours.  Starting from nowcast, ocean forecast is issued with a lead time from days to weeks (depending upon the predictability of the region of interests), similar to the numerical weather forecast routinely carried out at national centers.

Ocean Information and Services

RSS will provide customers with a user-driven information system that returns the query results in an on-demand workspace.  Users will be able to obtain information on a broad range of oceanographic topics, such as water level or velocity at a particular location (longitude, latitude, and depth).  Value-added products (e.g., sea level rise in future changing climate scenarios) and services (e.g., interactive calculations of drifting trajectories for search and rescue operations) can also be provided to meet user’s individual needs.

Hydrology

Flood Mapping

Enhanced mapping of floodplain heights and inundation using RSS’ state-of-the-art InSAR systems.

Flood Hazard Modeling

Global event-based flood hazard maps from advanced modeling and remote sensing in collaboration with the Google Earth Engine (EE) team.

Flood Event Re-Analysis

Using advanced 2-D inundation modeling and satellite imagery for multi-scale flood event re-analysis.