neueste Paper

2020

Lembo, V., Lucarini, V. & Ragone, F., 2020: Beyond Forcing Scenarios: Predicting Climate Change through Response Operators in a Coupled General Circulation Model. Sci Rep 10, 8668, https://doi.org/10.1038/s41598-020-65297-2

Abstract
Global Climate Models are key tools for predicting the future response of the climate system to a variety of natural and anthropogenic forcings. Here we show how to use statistical mechanics to construct operators able to flexibly predict climate change. We perform our study using a fully coupled model - MPI-ESM v.1.2 - and for the first time we prove the effectiveness of response theory in predicting future climate response to CO2 increase on a vast range of temporal scales, from inter-annual to centennial, and for very diverse climatic variables. We investigate within a unified perspective the transient climate response and the equilibrium climate sensitivity, and assess the role of fast and slow processes. The prediction of the ocean heat uptake highlights the very slow relaxation to a newly established steady state. The change in the Atlantic Meridional Overturning Circulation (AMOC) and of the Antarctic Circumpolar Current (ACC) is accurately predicted. The AMOC strength is initially reduced and then undergoes a slow and partial recovery. The ACC strength initially increases due to changes in the wind stress, then undergoes a slowdown, followed by a recovery leading to a overshoot with respect to the initial value. Finally, we are able to predict accurately the temperature change in the North Atlantic.

Zaplotnik Ž, Žagar N, Benedetti A, Semane N, 2020: Inferring atmospheric dynamics from aerosol observations in 4D-Var. Q.J.R. Meteorol. Soc.,146, 1403–1422, https://doi.org/10.1002/qj.3743

In current 4D-Var systems for Numerical Weather Prediction (for example, at ECMWF), aerosols are treated as passive scalars meaning that their impact on the analysis increments of other variables, for
example, wind, is turned off. This study assessed the potential of aerosol observations to improve wind analyses in 4D-Var systems.
The potential impact strongly depends on the tracer relative spatial gradients in the background field. We showed, using CAMS (Copernicus Atmosphere Monitoring Service) data, that the mean magnitude of the relative horizontal gradients of the total aerosol mass mixing ratio is more than twice as large as the specific humidity relative gradients throughout the troposphere and stratosphere. In the stratosphere, aerosol relative gradients are comparable to ozone relative gradients (figure).
The main result is that a combined assimilation of the aerosol and humidity data in 4D-Var improves the analysis with respect to only humidity data, while assimilating also temperature data additionally improves the wind analysis. The improvement is significantly smaller with respect to that obtained by assimilating direct wind observations, meaning that direct wind observations are
indispensable. However, in the global observing system missing direct wind observations and with an increasing number of observations of atmospheric composition, the aerosol effects in 4D-Var are worth further investigation for the purpose of operational weather forecasting.

Žagar, N. and I. Szunyogh, 2020: Comments on “What Is the Predictability Limit of Midlatitude Weather?”. J. Atmos. Sci., 77(2). 781-785, https://doi.org/10.1175/JAS-D-19-0166.1

Growth of the forecast uncertainty toward saturation in the operational ECMWF ENS. The normalized ensemble variance at various zonal wavenumbers starting with k=5 (bottom blue curve) up to k=100 (top red curve), plotted every third wavenumber.
At the smaller scales shown in the figure, the errors are initially large compared to their saturation value and grow rapidly toward saturation. In contrast, at the larger scales (e.g., k=5 and k=8), the errors are initially small compared to their saturation values (around 1% of Emax) and evolve in time by a multistage error growth process discussed in previous studies.
In its criticism of the paper published in J. Atmos. Sci. in 2019, this paper shows that significant advancement of the practical predictability in the coming years can be expected at the subsynoptic scales. However, these improvements are unlikely to lead to further considerable improvements of the predictability at the synoptic scales. A potential source of significant gains in practical predictability is further improvement of the predictions at the large (planetary) scales, where processes are heavily influenced by ocean–atmosphere, land–atmosphere and tropical– extratropical interactions. In a current-day state-of- the-science model, these interactions are simulated with considerable errors.