Category: PublicationsRA3

Ocean Biogeochemical Predictions—Initialization and Limits of Predictability

Fransner, F., Counillon, F., Bethke, I., Tjiputra, J., Samuelsen, A., Nummelin, A., Olsen, A. 2020: Ocean Biogeochemical Predictions—Initialization and Limits of Predictability. Front Mar Sci. https://doi.org/10.3389/fmars.2020.00386 .

Summary: Predictions of ocean biogeochemistry, such as primary productivity and CO2 uptake, would help to understand the changing marine environment and the global climate. There is an emerging number of studies where initialization of ocean physics has led to successful predictions of ocean biogeochemistry. It is, however, unclear how much these predictions could be improved by also assimilating biogeochemical data to reduce uncertainties of the initial conditions. Further, the mechanisms that lead to biogeochemical predictability are poorly understood. Here we perform a suite of idealized twin experiments with an Earth System Model (ESM) with the aim to (i) investigate the role of biogeochemical tracers’ initial conditions on their predictability, and (ii) understand the physical processes that give rise to, or limit, predictability of ocean carbon uptake and export production. Our results suggest that initialization of the biogeochemical state does not significantly improve interannual-to-decadal predictions, which we relate to the strong control ocean physics exerts on the biogeochemical variability on these time scales. The predictability of ocean carbon uptake generally agrees well with the predictability of the mixed layer depth (MLD), suggesting that the predictable signal comes from the exchange of dissolved inorganic carbon (DIC) with deep-waters. The longest predictability is found in winter in at high latitudes, as for sea surface temperature and salinity, but the predictability of the MLD and carbon exchange is lower as it is more directly influenced by the atmospheric variability, e.g., the wind. The predictability of the annual mean export production is, on the contrary, nearly non-existing at high latitudes, despite the strong predictive skill for annual mean nutrient concentrations in these regions. This is related to the low predictability of the physical state of the summer surface ocean. Due to the shallow mixed layer it is decoupled from the ocean below and therefore strongly influenced by the chaotic atmosphere. Our results show that future studies need to target the predictability of the mixed layer to get a better understanding of the real-world predictability of ocean biogeochemistry.

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Ocean–atmosphere coupled Pacific Decadal variability simulated by a climate model

Luo H, Zheng F, Keenlyside N, Zhu J. 2020: Ocean–atmosphere coupled Pacific Decadal variability simulated by a climate model. Clim Dyn. https://doi.org/10.1007/s00382-020-05248-9 .

Summary: Currently, the mechanisms for Pacific Decadal Oscillation (PDO) are still disputed, and in particular the atmosphere response to the ocean in the mid-latitude remains a key uncertainty. In this study, we investigate two potential feedbacks—a local positive and a delayed negative—for the PDO based on a long-term control simulation using the ECHAM5/MPI-OM coupled model, which is selected because of reproduces well the variability of PDO. The positive feedback is as follows. In the PDO positive phase, the meridional sea surface temperature (SST) gradient is intensified and this strengthens the lower level atmospheric baroclinicity in the mid-latitudes, leading to the enhancement of Aleutian low and zonal wind. These atmospheric changes reinforce the meridional SST temperature gradient through the divergence of ocean surface currents. The increased heat flux loss over the anomalously warm water and decreased heat flux loss over the anomalously cold water in turn reinforce the lower atmospheric meridional temperature gradient, baroclinicity and atmospheric circulation anomalies, forming a local positive feedback for the PDO. The delayed negative feedback arises, because the intensified meridional SST gradient also generates an anticyclonic wind stress in the central North Pacific, warming the upper ocean by Ekman convergence. The warm upper ocean anomalies then propagate westward and are transported to the mid-latitudes in the western North Pacific by the western boundary current. This finally reduces the meridional SST gradient, 18 years after the peak PDO phase. These results demonstrate the significant contributions of the meridional SST gradient to the PDO’s evolution.

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Impact of late spring Siberian snow on summer rainfall in South-Central China

Shen H., Li F., He S., Orsolini Y.J., Li J. 2020: Impact of late spring Siberian snow on summer rainfall in South-Central China. Clim. Dyn. 54: 3803–3818. DOI: https://doi.org/10.1007/s00382-020-05206-5 .
Summary: Located in the Yangtze River Valley and surrounded by mountains, South-Central China (SCC) frequently suffered from natural disasters such as torrential precipitation, landslide and debris flow. Here we provide corroborative evidence for a link between the late spring (May) snow water equivalent (SWE) over Siberia and the summer (July–August, abbr. JA) rainfall in SCC. We show that, in May, anomalously low SWE over Siberia is robustly related to a large warming from the surface to the mid-troposphere, and to a stationary Rossby wave train from Siberia eastward toward the North Atlantic. On the one hand, over the North Atlantic there exhibits a tripole pattern response of sea surface temperature anomalies in May. It persists to some extent in JA and in turn triggers a wave train propagating downstream across Eurasia and along the Asian jet, as the so-called Silk Road pattern (SRP). On the other hand, over northern Siberia the drier soil occurs in JA, accompanied by an overlying anomalous anticyclone through the positive feedback. This anomalous anticyclone favors the tropospheric cooling over southern Siberia, and the meridional (northward) displacement of the Asian jet (JMD) due to the change in the meridional temperature gradient. The combination of the SRP and the JMD facilitates less water vapor transport from the tropical oceans and anomalous descending motion over SCC, and thus suppresses the precipitation. These findings indicate that May Siberian SWE can be exploited for seasonal predictability of SCC precipitation.

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The Mean State and Variability of the North At-lantic Circulation: A Perspective From Ocean Reanalyses

Jackson, L.C., Dubois C., Forget G., Haines, K., Harrison, M., Iovino, D., Köhl, A., Mignac, D., Masina, S., Peterson, K.A., Piecuch, C.G., Roberts, C.D., Robson, J., Storto, A., Toyoda, T., Valivieso, M., Wilson, C., Wang, Y., Zuo, H. 2019: The Mean State and Variability of the North Atlantic Circulation: A Perspective From Ocean Reanalyses. JGR Oceans. https://doi.org/10.1029/2019JC015210 .

Summary: The observational network around the North Atlantic has improved significantly over the last few decades revealing changes over decadal time scales in the North Atlantic, including in heat content, heat transport, and the circulation. However, there are still significant gaps in the observational coverage. Ocean reanalyses fill in these gaps by combining the observations with a computer model of the ocean to give consistent estimates of the ocean state. These reanalyses are potentially useful tools that can be used to understand the observed changes; however, their skill must also be assessed. We use an ensemble of global ocean reanalyses in order to examine the mean state and variability of the North Atlantic ocean since 1993. In particular, we examine the convection, circulation, transports of heat and fresh water, and temperature and salinity changes. We find that reanalyses show some consistency in their results, suggesting that they may be useful for understanding circulation changes in regions and times where there are no observations. We also show improvements in some aspects of the ocean circulation as the observational coverage has improved. This highlights the importance of continuing observational campaigns.

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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.

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