Category: Publications2020

Publications that published in 2020

Amplification of synoptic to annual variability of West African summer monsoon rainfall under global warming

Akinsanola, A. A., W. Zhou, T. Zhou, N. Keenlyside, 2020: Amplification of synoptic to annual variability of West African summer monsoon rainfall under global warming. npj Clim Atmos Sci. https://doi.org/10.1038/s41612-020-0125-1 .

Summary: Increased knowledge of future changes in rainfall variability is needed to reduce vulnerability to potential impacts of global warming, especially in highly vulnerable regions like West Africa. While changes in mean and extreme rainfall have been studied extensively, rainfall variability has received less attention, despite its importance. In this study, future changes in West African summer monsoon (WASM) rainfall variability were investigated using data from two regional climate models that participated in the Coordinated Regional Climate Downscaling Experiment (CORDEX). The daily rainfall data were band-pass filtered to isolate variability at a wide range of timescales. Under global warming, WASM rainfall variability is projected to increase by about 10–28% over the entire region and is remarkably robust over a wide range of timescales. We found that changes in mean rainfall significantly explain the majority of intermodel spread in projected WASM rainfall variability. The role of increased atmospheric moisture is examined by estimating the change due to an idealized local thermodynamic enhancement. Analysis reveals that increased atmospheric moisture with respect to warming following the Clausius–Clapeyron relationship can explain the majority of the projected changes in rainfall variability at all timescales.

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Reduced efficiency of the Barents Sea cooling machine

Skagseth, Ø., Eldevik, T., Årthun, M., Asbjørnsen, H., Lien, V. S., Smedsrud, LH. 2020: Reduced efficiency of the Barents Sea cooling machine. Nature Climate Change. https://doi.org/10.1038/s41558-020-0772-6 .

Summary: Dense water masses from the Barents Sea are an important part of the Arctic thermohaline system. Here, using hydrographic observations from 1971 to 2018, we show that the Barents Sea climate system has reached a point where ‘the Barents Sea cooling machine’—warmer Atlantic inflow, less sea ice, more regional ocean heat loss—has changed towards less-efficient cooling. Present change is dominated by reduced ocean heat loss over the southern Barents Sea as a result of anomalous southerly winds. The outflows have accordingly become warmer. Outflow densities have nevertheless remained relatively unperturbed as increasing salinity appears to have compensated the warming inflow. However, as the upstream Atlantic Water is now observed to freshen while still relatively warm, we speculate that the Barents Sea within a few years may export water masses of record-low density to the adjacent basins and deep ocean circulation.

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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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Seasonal to decadal predictions of regional Arctic sea ice by assimilating sea surface temperature in the Norwegian Climate Prediction Model

Dai, P., Gao, Y., Counillon, F., Wang, Y., Kimmritz, M., Langehaug, H.R. 2020: Seasonal to decadal predictions of regional Arctic sea ice by assimilating sea surface temperature in the Norwegian Climate Prediction Model. Clim Dyn 54, 3863–3878. https://doi.org/10.1007/s00382-020-05196-4 .

Summary: The version of the Norwegian Climate Prediction Model (NorCPM) that only assimilates sea surface temperature (SST) with the Ensemble Kalman Filter has been used to investigate the seasonal to decadal prediction skill of regional Arctic sea ice extent (SIE). Based on a suite of NorCPM retrospective forecasts, we show that seasonal prediction of pan-Arctic SIE is skillful at lead times up to 12 months, which outperforms the anomaly persistence forecast. The SIE skill varies seasonally and regionally. Among the five Arctic marginal seas, the Barents Sea has the highest SIE prediction skill, which is up to 10–11 lead months for winter target months. In the Barents Sea, the skill during summer is largely controlled by the variability of solar heat flux and the skill during winter is mostly constrained by the upper ocean heat content/SST and also related to the heat transport through the Barents Sea Opening. Compared with several state-of-the-art dynamical prediction systems, NorCPM has comparable regional SIE skill in winter due to the improved upper ocean heat content. The relatively low skill of summer SIE in NorCPM suggests that SST anomalies are not sufficient to constrain summer SIE variability and further assimilation of sea ice thickness or atmospheric data is expected to increase the skill.

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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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On Temporal Scale Separation in Coupled Data Assimilation with the Ensemble Kalman Filter

Tondeur, M., Carrassi, A., Vannitsem, S., Bocquet, M. 2020: On Temporal Scale Separation in Coupled Data Assimilation with the Ensemble Kalman Filter. J Stat Phys 179, 1161–1185. https://doi.org/10.1007/s10955-020-02525-z .

Summary: Data assimilation for systems possessing many scales of motions is a substantial methodological and technological challenge. Systems with these features are found in many areas of computational physics and are becoming common thanks to increased computational power allowing to resolve finer scales and to couple together several sub-components. Coupled data assimilation (CDA) distinctively appears as a main concern in numerical weather and climate prediction with major efforts put forward by meteo services worldwide. The core issue is the scale separation acting as a barrier that hampers the propagation of the information across model components (e.g. ocean and atmosphere). We provide a brief survey of CDA, and then focus on CDA using the ensemble Kalman filter (EnKF), a widely used Monte Carlo Gaussian method. Our goal is to elucidate the mechanisms behind information propagation across model components. We consider first a coupled system of equations with temporal scale difference, and deduce that: (i) cross components effects are strong from the slow to the fast scale, but, (ii) intra-component effects are much stronger in the fast scale. While observing the slow scale is desirable and benefits the fast, the latter must be observed with high frequency otherwise the error will grow up to affect the slow scale. Numerical experiments are performed using the atmosphere-ocean model, MAOOAM. Six configurations are considered, differing for the strength of the atmosphere-ocean coupling and/or the number of model modes. The performance of the EnKF depends on the model configuration, i.e. on its dynamical features. A comprehensive dynamical characterisation of the model configurations is provided by examining the Lyapunov spectrum, Kolmogorov entropy and Kaplan–Yorke attractor dimension. We also compute the covariant Lyapunov vectors and use them to explain how model instabilities act on different model’s modes according to the coupling strength. The experiments confirm the importance of observing the fast scale, but show also that, despite its slow temporal scale, frequent observations in the ocean are beneficial. The relation between the ensemble size, N, and the unstable subspace dimension, n0, has been studied. Results largely ratify what known for uncoupled system: the condition N≥n0 is necessary for the EnKF to work satisfactorily. Nevertheless the quasi-degeneracy of the Lyapunov spectrum of MAOOAM, with many near-zero exponents, is potentially the cause of the smooth gradual reduction of the analysis error observed for some model configurations, even when N>n0. Future prospects for the EnKF in the context of coupled ocean-atmosphere systems are finally discussed.

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Climate Change and New Potential Spawning Sites for Northeast Arctic cod

Sandø, A.B., Johansen, G.O., Aglen, A., Stiansen, J.E., Renner, A.H.H. 2020: Climate Change and New Potential Spawning Sites for Northeast Arctic cod. Front. Mar. Sci. https://doi.org/10.3389/fmars.2020.00028

Summary: In this study we investigate both historical and potential future changes in the spatial distribution of spawning habitats for Northeast Arctic cod (NEA cod) based on a literature study on spawning habitats and different physical factors from a downscaled climate model. The approach to use a high resolution regional ocean model to analyze spawning sites is new and provides more details about crucial physical factors than a global low resolution model can. The model is evaluated with respect to temperature and salinity along the Norwegian coast during the last decades and shows acceptable agreement with observations. However, the model does not take into consideration biological or evolutionary factors which also have impact on choice of spawning sites. Our results from the downscaled RCP4.5 scenario suggest that the spawning sites will be shifted further northeastwards, with new locations at the Russian coast close to Murmansk over the next 50 years, where low temperatures for many decades in the last century were a limiting factor on spawning during spring. The regional model gives future temperatures above the chosen lower critical minimum value in larger areas than today and indicates that spawning will be more extensive there. Dependent on the chosen upper temperature boundary, future temperatures may become a limiting factor for spawning habitats at traditional spawning sites south of Lofoten. Finally, the observed long-term latitudinal shifts in spawning habitats along the Norwegian coast the recent decades may be indirectly linked to temperature through the latitudinal shift of the sea ice edge and the corresponding shift in available ice-free predation habitats, which control the average migration distance to the spawning sites. We therefore acknowledge that physical limitations for defining the spawning sites might be proxies for other biophysically related factors.

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