Estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations
- 1. Univ. Brest
- 2. Univ. Grenoble Alpes
- 3. Ecole Normale Supérieure
Description
This repository contains the estimate of the atmospherically-forced contribution to sea level variability described in Close et al, 2020, and derived from the Ssalto/Duacs altimeter products produced and distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS) (http://www.marine.copernicus.eu).
The files contain successive 5-day averages of sea level anomaly, with the same global coverage and 0.25° grid as the Ssalto/Duacs altimeter products. The estimate is created using a spatial bandpass filter, with cutoff scales of ~1.5° and 10.5°. Zeros in the mask file indicate regions in which it has not been possible to evaluate the quality of the estimate.
The cutoff scales applied to the altimetry data were determined through analysis of output from the OceaniC Chaos – ImPacts, strUcture, predicTability (Penduff et al, 2014) experiment, comprising a 50-member ensemble of ocean-sea ice model hindcasts with 0.25° horizontal resolution (Bessières et al., 2017). The spatiotemporal coherence between the model-based estimates of the atmospherically-forced (ensemble mean) and total simulated sea surface height signals was analysed, and found to exhibit distinct partitioning between the atmospherically-forced and intrinsic contributions in a spatial (but not temporal) sense, thus suggesting that meaningful estimation of the two components can be achieved based on simple spatial filtering. Verification of the method using the model data indicates good accuracy, with a global mean correlation of 0.9 between the estimate based on spatial filtering and the ensemble mean sea surface height. Full details of the methodology and verification may be found in Close et al, 2020.
----
References:
Bessières, L., Leroux, S., Brankart, J.-M., Molines, J.-M., Moine, M.-P., Bouttier, P.-A., Penduff, T., Terray, L., Barnier, B., and Sérazin, G., 2017. Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution, Geosci. Model Dev., 10, 1091–1106, doi: 10.5194/gmd-10-1091-2017.
Close, S., Penduff, T., Speich, S. and Molines J.-M., 2020. A means of estimating the intrinsic and atmospherically-forced contributions to sea surface height variability applied to altimetric observations. Progr. Oceanogr. doi: 10.1016/j.pocean.2020.102314
Penduff, T., Barnier, B. , Terray, L., Bessières, L., Sérazin, G., Grégorio, S., Brankart, J., Moine, M., Molines, J., Brasseur, P., 2014. Ensembles of eddying ocean simulations for climate, CLIVAR Exchanges, Special Issue on High Resolution Ocean Climate Modelling, 19.
Notes
Files
Files
(895.5 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:ba071a0827b644351c9df23cc3dc0bf8
|
35.8 MB | Download |
|
md5:96869eff04bb0dcc925035a669be717c
|
35.5 MB | Download |
|
md5:e4a1938e3f6b35cdde00410beafb14c0
|
35.7 MB | Download |
|
md5:d9c2a43e68b1fd1f2af203aabf05a303
|
35.5 MB | Download |
|
md5:e85f11f3299f867a11cf4a1ffcb2598b
|
36.2 MB | Download |
|
md5:3be7818ecfdd7053142bdda13898994d
|
36.3 MB | Download |
|
md5:d05af8ed1482a927ae949364afd40872
|
35.8 MB | Download |
|
md5:787a0469603b8d08c11c4fb4eb81a804
|
35.8 MB | Download |
|
md5:f28635bde686520110d05e08452ef695
|
35.6 MB | Download |
|
md5:f36637a3f34e699233944e232c389357
|
35.7 MB | Download |
|
md5:5d15edd4a57bf6f5e75b396dd07636b8
|
35.6 MB | Download |
|
md5:b779aa2bf34a83addc7ed3fb0fa6c769
|
35.5 MB | Download |
|
md5:f58982c8c2ea5c26a9a8a4355420eb9b
|
35.7 MB | Download |
|
md5:47209113e3664423cfcbbd42f68edd76
|
35.4 MB | Download |
|
md5:ce7cb7651e014a8e6b69c27f483a9abb
|
35.6 MB | Download |
|
md5:02544dd424e85d8951c486fcef5a8794
|
35.7 MB | Download |
|
md5:81be146718fe491b1e0c95b398c634fb
|
35.6 MB | Download |
|
md5:421c960e5b47b24ceacc8a090020ce5c
|
36.2 MB | Download |
|
md5:e5bbe08f049931c2932dca8d0f725c01
|
36.0 MB | Download |
|
md5:94d27e34c457660e68f905b9c00c34ab
|
35.8 MB | Download |
|
md5:e6644479577a88eb093b60753ce1d512
|
35.7 MB | Download |
|
md5:3881b4e784f73b64a11cf8dc9f77eac6
|
35.9 MB | Download |
|
md5:4bf1666b2d32d30b2c11b20fc0f17c95
|
36.4 MB | Download |
|
md5:e26bb206681fe028094e7cbe6cb4e098
|
36.5 MB | Download |
|
md5:7bdf2642f795d1ede8457b2d96f30cdd
|
36.0 MB | Download |
|
md5:378f3ef918465ded4e2f22a53ea58bfe
|
61.1 kB | Download |
Additional details
Related works
- Is supplement to
- Journal article: 10.1016/j.pocean.2020.102314 (DOI)
Funding
References
- Bessières, L., Leroux, S., Brankart, J.-M., Molines, J.-M., Moine, M.-P., Bouttier, P.-A., Penduff, T., Terray, L., Barnier, B., and Sérazin, G., 2017. Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution, Geosci. Model Dev., 10, 1091–1106, doi: 10.5194/gmd-10-1091-2017.
- Close, S., Penduff, T., Speich, S. and Molines J.-M., 2020. A means of estimating the intrinsic and atmospherically-forced contributions to sea surface height variability applied to altimetric observations. Progr. Oceanogr. doi: 10.1016/j.pocean.2020.102314
- Penduff, T., Barnier, B. , Terray, L., Bessières, L., Sérazin, G., Grégorio, S., Brankart, J., Moine, M., Molines, J., Brasseur, P., 2014. Ensembles of eddying ocean simulations for climate, CLIVAR Exchanges, Special Issue on High Resolution Ocean Climate Modelling, 19.