Hide

To give you the best possible experience, this site uses cookies. Continuing to use this site means you agree
to our use of cookies. If you'd like to learn more about the cookies we use please find out more

Session 3.6 abstracts

Symposium home | Session 2 | Session 3 | Session 4 | Abstracts by Author |

 

3.6 Coupled Ocean-Atmosphere-Wave Prediction: en route to combined ocean and atmosphere weather prediction

Session conveners: Gary Brassington, Matt Martin and Hendrik Tolman


The table below lists all abstracts for Session 3.6 by author. To read the full abstract click on the title-link.

The unique reference number (ref. no.) relates to the abstract submission process and must be used in any communications with the organisers.

All abstracts from session 3.6 are available for download - pdf

 Ref.NoPrimary AuthorAffiliationCountryAbstract titlePoster
S3.6-01Akella, SanthaNASAUnited StatesCoupled GEOS-DAS: Via Sea Surface Skin Temperature AssimilationPoster-pdf
S3.6-02De Boisseson, EricECMWFUnited KingdomCERA: The ECMWF Coupled Data Assimilation SystemPoster-pdf
S3.6-03Lea, DanielMet OfficeUnited KingdomThe Met Office Coupled Atmosphere/Land/Ocean/Sea-Ice Data Assimilation SystemPoster-pdf
S3.6-04Li, MingNMEFCChinaArctic ocean-sea ice coupled forecasting experiments in NMEFC Cancelled
S3.6-05Ritchie, HalEnvironment CanadaCanadaStatus of Canadian Regional and Global Coupled Modelling SystemsPoster-pdf
S3.6-06Samson, GuillaumeMercator OceanFranceHigh resolution modeling of tropical cyclones-ocean interactions in the South-West Indian OceanPoster-pdf

 


ID 3.6-01

Coupled GEOS-DAS: Via Sea Surface Skin Temperature Assimilation

S Akella1,2, R Todling2, M Suarez2, and M Rienecker2

1 Science Systems & Applications Inc, 10210 Greenbelt Rd, Lanham, USA

2 Global Modeling and Assimilation Office, Goddard Space Flight Center, Greenbelt, USA

Abstract

Short time scale coupling of the ocean-atmosphere-wave system through assimilation of the ocean surface skin temperature provides accurate description of the near-surface processes and also air-sea fluxes, and therefore improves coupled model forecasts. At the Global Modeling & Assimilation Office (GMAO) work is in progress towards the development of a coupled data assimilation system which includes near ocean surface (diurnal) temperature variations. We directly assimilate IR radiance observations that peak near ocean surface, namely, those in 3, 11, 12 micron range and near-surface temperature observations.

In this talk we will provide a brief overview of our model and analysis, followed by results from different assimilation experiments that illustrate coupling aspects (temperature, wind fields, surface fluxes). We will also highlight some aspects of: satellite bias correction, observing system and problems we are currently working on, including metrics for evaluation.


ID 3.6-02

CERA: The ECMWF Coupled Data Assimilation System

Eric de Boisséson1, Patrick Laloyaux1, Magdalena Balmaseda1, Kristian Mogensen1, Peter Janssen1, Dick Dee1

1European Centre for Medium-Range Weather Forecasts, Shinfield Park,

Reading, RG2 9AX, United Kingdom

eric.boisseson@ecmwf.int

Abstract

A coupled data assimilation system for reanalysis called CERA (Coupled ECMWF ReAnalysis) is being developed at ECMWF. The CERA project aims at generating a self-consistent ocean-atmosphere state by assimilating both atmospheric and oceanic observations within a coupled model. CERA uses the ECMWF coupled model where the atmospheric component is based on the IFS software and the oceanic component is based on the NEMO framework. While the computation of the nonlinear trajectories needed in the data assimilation uses the coupled model, the computation of the increments is still performed separately for the atmosphere and ocean components and any covariance between them are ignored. This framework is aimed at being flexible enough to adapt to the initialization of medium range, monthly and seasonal forecasting activities.

The building of the CERA system follows several intermediate steps. The first task (called CERA-S) consists in introducing a Sea Surface Temperature (SST) constraint in the coupled model to avoid the model drift while allowing the simulation of coupled processes. The second task, called CERA-A, is based on the existing EMCWF atmospheric data assimilation framework but uses a coupled model in the outer loops. Similarly, the third task, CERA-O, is based on the ocean data assimilation framework used at ECMWF but uses a coupled model in the outer loops. The CERA final product will consist in a merge of the CERA-S, CERA-A and CERA-O systems.

This presentation will describe the concept of the different tasks and the first validation and results obtained from each of them.


ID 3.6-03

The Met Office Coupled Atmosphere/Land/Ocean/Sea-Ice Data Assimilation System

Daniel J. Lea1, Isabelle Mirouze1, Matt J. Martin1, Adrian Hines1, Catherine Guiavarch1, Ann Shelly 1

1 Met Office, UK

Abstract

The Met Office has developed a weakly-coupled data assimilation (DA) system using the global coupled model HADGEM3 (Hadley Centre Global Environment Model, version 3). This model combines the atmospheric model UM (Unified Model) at 60 km horizontal resolution on 85 vertical levels, the ocean model NEMO (Nucleus for European Modeling of the Ocean) at 25 km (at the equator) horizontal resolution on 75 vertical levels, and the sea-ice model CICE at the same resolution as NEMO. The atmosphere and the ocean/sea-ice fields are coupled every 1-hour using the OASIS coupler. The coupled model is corrected using two separate 6-hour window data assimilation systems: a 4D-Var for the atmosphere with associated soil moisture content nudging and snow analysis schemes on the one hand, and a 3D-Var FGAT for the ocean and sea-ice on the other hand. The background information in the DA systems comes from a previous 6-hour forecast of the coupled model.

The aim of the work is to see whether the weakly-coupled DA system offers improvements over starting from separate atmosphere/ocean/sea-ice initial conditions. To assess the benefit of the weakly-coupled DA, one-month experiments have been carried out, including 1) a full atmosphere/land/ocean/sea-ice coupled DA run, 2) an atmosphere-only run forced by OSTIA SSTs and sea-ice with atmosphere and land DA, and 3) an ocean-only run forced by atmospheric fields from run 2 with ocean and sea-ice DA. In addition, 5-day forecast runs, started twice a day, have been produced from initial conditions generated by either run 1 or a combination of runs 2 and 3. The different results have been compared to each other and, whenever possible, to other references such as the Met Office atmosphere and ocean operational analyses or the OSTIA data. Evidence of imbalances and initialisation shocks has also been looked for.


ID 3.6-04

Arctic ocean-sea ice coupled forecasting experiments in NMEFC

M. Li1, Q.H. Yang1, J.C Zhao1, B. Zhao1, Q.Z. Sun1, L. Zhang1, C.H. Li1

1 National Marine Environmental Forecasting Center, Beijing, China

Abstract

Numerical forecasting experiments of ocean and sea ice for the Arctic are conducted under an effort of facilitating the Chinese National Arctic Research Expedition (CHINARE). An Arctic forecasting system is now preliminarily built and some forecast products, such as sea ice concentration, thickness, drift and sea surface temperature, salinity, ocean current velocity can be provided.

A regional Arctic configuration of the Massachusetts Institute of Technology general circulation model (MITgcm) is the choice of the coupled ice-ocean model for the Arctic forecast experiments. To initialize the satellite-based sea ice information, two different initialization methods are used: 1) nudging and 2) empirical replacement. The Advanced Microwave Scanning Radiometer 2 (AMSR2) sea ice concentration data is provided by University of Bremen. In addition, two different data sets as atmospheric forcing data are tested: 1) the numerical weather prediction of the National Centers for Environmental Prediction Global Forecast System (NCEP GPS) and 2) the model outputs from the Polar WRF simulations over the Arctic. Forecast skill assessments of the sea ice concentration fields from these numerical experiments are presented.


ID 3.6-05

Status of Canadian Regional and Global Coupled Modelling Systems

H. Ritchie1, G. Smith1, J.-F. Lemieux1, J.-M. Bélanger1, C. Beaudoin1, Z. He1, F. Roy 2, F. Dupont2, M. Reszka2, F. Davidson3, G. Garric4, and C.-E. Testut4

1 Meteorological Research Division, Environment Canada, Dorval, Canada

2 Canadian Meteorological Centre, Environment Canada, Dorval, Canada

3 Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, St. John's, Canada

4 Mercator-Océan, Toulouse, France

Abstract

The Canadian Operational Network of Coupled Environmental PredicTion Systems (CONCEPTS) including Mercator-Océan participation (France) is providing a framework for research and operations on coupled atmosphere-ice-ocean (AIO) prediction. Operational activity is based on coupling the Canadian atmospheric Global Environmental Multi-scale (GEM) model with the Mercator system based on the Nucleus for European Modelling of the Ocean (NEMO), together with the CICE sea ice model. Within CONCEPTS two main systems are under development: a short-range regional coupled prediction system and a global coupled prediction system for medium- to long-range applications.

A fully coupled AIO forecasting system for the Gulf of St. Lawrence (GSL) has been developed (Faucher et al., 2010) and has been running operationally at the Canadian Meteorological Centre (CMC) since June 2011. This system demonstrated the strong impact that dynamic sea ice cover (Smith et al., 2012) can have on 48hr atmospheric forecasts leading to large changes in surface air temperature (up to 10 deg. C), low-level cloud cover, and precipitation. The original Saucier et al. ocean-ice component of this system is currently being replaced by NEMO and CICE, with generally comparable performance. This system is also the basis for the development of an integrated marine Arctic prediction system in support of Canadian METAREA monitoring and warnings. Specifically, a multi-component (atmosphere, land, snow, ice, ocean, wave) regional high resolution marine data assimilation and forecast system is being developed for short-term predictions of near surface atmospheric conditions, sea ice (concentration, pressure, drift, ice edge), freezing spray, waves and ocean conditions (temperature and currents). For more information on the ocean-ice component of this system, see the companion abstract by Davidson et al.

More recently a fully coupled global AIO system is under development. The first step was the Global Ice-Ocean Prediction System (GIOPS) that is described in the companion abstract by Smith et al. A 33 km resolution global version of the GEM model has been interactively coupled with GIOPS on a ¼ degree resolution grid. Coupled and uncoupled medium-range (16-day) forecasts have been made and evaluated over the period Jan.-Mar. 2011. In the tropical atmosphere the coupled forecasts show robust improvements compared to both tropical moored buoys and analyses produced by the European Centre for Medium Range Weather Forecasts. Evaluation against CMC ice analyses in the northern hemisphere marginal ice zone shows the strong impact that a changing ice cover can have on coupled forecasts. In the Arctic, however, the coupled system is very sensitive to the ice lead fraction in pack ice which is predicted rather than being held steady at 3% as in the uncoupled runs. This sensitivity is under further investigation.


ID 3.6-06

High resolution modeling of tropical cyclones-ocean interactions in the South-West Indian Ocean

G. Samson1, J. Chanut1, H. Giordani2, Y. Drillet1

1 Mercator-Ocean, Toulouse, France

2 Meteo-France, Toulouse, France

Abstract

The ocean surface can cool by several degrees during the passage of a tropical cyclone (TC) due to the extreme winds associated with. This cooling decreases the ocean-to-atmosphere heat and moisture supply which can modulate the TC intensity. Hence, atmospheric models need an accurate description of the sea surface temperature (SST) under TCs to correctly predict their intensities. This SST evolution and its feedback on the TC evolution can only be captured by ocean-atmosphere coupled models.

In order to evaluate this potential benefit on TC forecasts in the South West Indian Ocean, Mercator-Ocean has developed a new coupled regional model based on the Meteo-France operational atmospheric model AROME and the NEMO ocean model. Exchanges between the two models are handled by the OASIS3 coupler. AROME is initialized and forced at its lateral boundaries with ALADIN 10km-resolution 6-hourly analysis and is integrated during 96 hours at 2.5km convective-resolving resolution. NEMO is initialized and forced with global 1/4° oceanic analyses performed weekly at Mercator-Ocean and is integrated at 1/12° eddy-resolving resolution.

An ensemble of 25 coupled simulations and 25 atmospheric-only (forced) simulations based on 5 different TCs over the 2008-2013 seasons are then computed to explore the sensitivity of the TC forecasts to the SST. The ensemble is generated by varying the initial forecast time with a 6-hours step. Preliminary results show a clear improvement of the SST evolution under the TCs in the coupled simulations when compared to satellite data. This SST difference directly impacts turbulent latent and sensible heat fluxes spatial distribution and intensities which lead to different intensification rates in the coupled and the forced simulations. A first ensemble of 5 runs shows a significant decrease of the mean intensity forecast error.

This statistical analysis will be extended to the full set of 50 simulations to measure the overall intensity forecast improvement achieved by this new coupled system.