Development and testing of a coupled ocean–atmosphere mesoscale ensemble prediction system

Abstract

A coupled ocean-atmosphere mesoscale ensemble prediction system has been developed by the Naval Research Laboratory. This paper describes the components and implementation of the system and presents baseline results from coupled ensemble simulations for two tropical cyclones. The system is designed to take into account major sources of uncertainty in: (1) non-deterministic dynamics, (2) model error, and (3) initial states. The purpose of the system is to provide mesoscale ensemble forecasts for use in probabilistic products, such as reliability and frequency of occurrence, and in risk management applications. The system components include COAMPS® (Coupled Ocean/ Atmosphere Mesoscale Prediction System) and NCOM (Navy Coastal Ocean Model) for atmosphere and ocean forecasting and NAVDAS (NRL Atmospheric Variational Data Assimilation System) and NCODA (Navy Coupled Ocean Data Assimilation) for atmosphere and ocean data assimilation. NAVDAS and NCODA are 3D-variational (3DVAR) analysis schemes. The ensembles are generated using separate applications of the Ensemble Transform (ET) technique in both the atmosphere (for moving or nonmoving nests) and the ocean. The atmospheric ET is computed using wind, temperature, and moisture variables, while the oceanographic ET is derived from ocean current, temperature, and salinity variables. Estimates of analysis error covariance, which is used as a constraint in the ET, are provided by the ocean and atmosphere 3DVAR assimilation systems. The newly developed system has been successfully tested for a variety of configurations, including differing model resolution, number of members, forecast length, and moving and fixed nest options. Results from relatively coarse resolution (∼27-km) ensemble simulations of Hurricanes Hanna and Ike demonstrate that the ensemble can provide valuable uncertainty information about the storm track and intensity, though the ensemble mean provides only a small amount of improved predictive skill compared to the deterministic control member.

Internal variability of a 3-D ocean model

“…For instance, Melsom (2005) studied the mesoscale variability along the Norwegian coast, using eight ensemble members that were generated by perturbing the initial field in a HYCOM model setup. Furthermore, Holt et al (2011) used a coupled oceanÁatmosphere mesoscale ensemble (33 members) system to provide uncertainty information for tropical cyclones.…”

Progress and challenges in short- to medium-range coupled prediction

“…For regional scales, the air-ocean version of the Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS) (Holt et al 2011) was declared operational in 2011. Air-ocean coupled model runs are routinely performed at the Navy operational production centres.…”

On the effect of model parameters on forecast objects

“…Doyle et al (2011) and Jiang and Doyle (2009) examine the effect of model parameters on mountain waves. Motivated by the work of Holt et al (2011), who studied the effect of 11 model parameters on various characteristics of the forecasts, Marzban et al (2014) used a global, variance-based SA to study the effect of the same parameters and their interactions on the mean (across the forecast domain) and the center-of-gravity of precipitation. By contrast, here the effect of the model parameters is assessed on features of objects within the forecast field.…”

“…The 11 model parameters are shown in Table 1; the choice of these parameters is explained in Holt et al (2011). As mentioned in that paper, these parameters were chosen for their anticipated sensitivity (through model tests and discussions with developers) of the parameterizations in an effort to choose parameters most likely to produce changes in the model output precipitation fields.…”