Seasonal predictions initialised by assimilating sea surface temperature observations with the EnKF

Wang, Y., F. Counillon, N. Keenlyside, L. Svendsen, S. Gleixner, M. Kimmritz, P. Dai, and Y. Gao, 2019: Seasonal predictions initialised by assimilating sea surface temperature observations with the EnKF. Climate Dynamics. https://doi.org/10.1007/s00382-019-04897-9 .

Summary:This study demonstrates that assimilating SST with an advanced data assimilation method yields prediction skill level with the best state-of-the-art systems. We employ the Norwegian Climate Prediction Model (NorCPM)—a fully-coupled forecasting system—to assimilate SST observations with the ensemble Kalman filter. Predictions of NorCPM are compared to predictions from the North American Multimodel Ensemble (NMME) project. The global prediction skill of NorCPM at 6- and 12-month lead times is higher than the averaged skill of the NMME. A new metric is introduced for ranking model skill. According to the metric, NorCPM is one of the most skilful systems among the NMME in predicting SST in most regions. Confronting the skill to a large historical ensemble without assimilation, shows that the skill is largely derived from the initialisation rather than from the external forcing. NorCPM achieves good skill in predicting El Niño–Southern Oscillation (ENSO) up to 12 months ahead and achieves skill over land via teleconnections. However, NorCPM has a more pronounced reduction in skill in May than the NMME systems. An analysis of ENSO dynamics indicates that the skill reduction is mainly caused by model deficiencies in representing the thermocline feedback in February and March. We also show that NorCPM has skill in predicting sea ice extent at the Arctic entrance adjacent to the north Atlantic; this skill is highly related to the initialisation of upper ocean heat content.

Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Observational needs for improving ocean and coupled reanalysis, S2S Prediction, and decadal prediction

Penny SG et al. 2019: Observational needs for improving ocean and coupled reanalysis, S2S Prediction, and decadal prediction. Front Mar Sci. https://doi.org/10.3389/fmars.2019.00391 .

Summary: Developments in observing system technologies and ocean data assimilation (DA) are symbiotic. New observation types lead to new DA methods and new DA methods, such as coupled DA, can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners of DA are encouraged to make better use of observations that are already available, for example, taking advantage of strongly coupled DA so that ocean observations can be used to improve atmospheric analyses and vice versa. Ocean reanalyses are useful for the analysis of climate as well as the initialization of operational long-range prediction models. There are many remaining challenges for ocean reanalyses due to biases and abrupt changes in the ocean-observing system throughout its history, the presence of biases and drifts in models, and the simplifying assumptions made in DA solution methods. From a governance point of view, more support is needed to bring the ocean-observing and DA communities together. For prediction applications, there is wide agreement that protocols are needed for rapid communication of ocean-observing data on numerical weather prediction (NWP) timescales. There is potential for new observation types to enhance the observing system by supporting prediction on multiple timescales, ranging from the typical timescale of NWP, covering hours to weeks, out to multiple decades. Better communication between DA and observation communities is encouraged in order to allow operational prediction centers the ability to provide guidance for the design of a sustained and adaptive observing network.

Link to review article. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Workshop in June

In Bergen, on June 5-7th 2019, we will host for the third time running the workshop on Climate Prediction in the Arctic and North Atlantic sector. See the agenda here.

This year, we are joined by the EU H2020 modelling cluster, to discuss mechanisms of, and limitations to, predictability, and the challenges to developing climate services. Streaming link will be provided beforehand.

Mechanisms of ocean heat anomalies in the Norwegian Sea

Asbjørnsen, H., M. Årthun, Ø. Skagseth, Eldevik, T. 2019: Mechanisms of ocean heat anomalies in the Norwegian Sea. JGR Oceans. https://doi.org/10.1029/2018JC014649

Summary: Ocean heat content in the Norwegian Sea exhibits pronounced variability on interannual to decadal time scales. These ocean heat anomalies are known to influence Arctic sea ice extent, marine ecosystems, and continental climate. It nevertheless remains unknown to what extent such heat anomalies are produced locally within the Norwegian Sea, and to what extent the region is more of a passive receiver of anomalies formed elsewhere. A main practical challenge has been the lack of closed heat budget diagnostics. In order to address this issue, a regional heat budget is calculated for the Norwegian Sea using the ECCOv4 ocean state estimate—a dynamically and kinematically consistent model framework fitted to ocean observations for the period 1992–2015. The depth-integrated Norwegian Sea heat budget shows that both ocean advection and air-sea heat fluxes play an active role in the formation of interannual heat content anomalies. A spatial analysis of the individual heat budget terms shows that ocean advection is the primary contributor to heat content variability in the Atlantic domain of the Norwegian Sea. Anomalous heat advection furthermore depends on the strength of the Atlantic water inflow, which is related to large-scale circulation changes in the subpolar North Atlantic. This result suggests a potential for predicting Norwegian Sea heat content based on upstream conditions. However, local surface forcing (air-sea heat fluxes and Ekman forcing) within the Norwegian Sea substantially modifies the phase and amplitude of ocean heat anomalies along their poleward pathway, and, hence, acts to limit predictability.

Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.