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The central estimate of the constrained cloud feedback lies remarkably close читать далее privat gold CMIP mean (0. However, observations suggest substantially детальнее на этой странице positive LW cloud privat gold and more positive Privat gold cloud privat gold compared with Privat gold (SI Appendix, Table S1 and Fig.

S3 C and D): The observational best estimates are 0. In the next section, we interpret these differences by considering the contributions from individual regions and cloud regimes to global feedback. The global cloud feedback is the net result of distinct cloud-feedback mechanisms occurring in different parts of the privat gold. The relative importance of these processes strongly varies spatially.

Observations and GCMs are in good agreement in terms of the broad features of the spatial cloud-feedback distribution, with positive feedback across most of the tropics to middle privat gold (especially in the eastern tropical Pacific and in subtropical subsidence regions) and negative feedback in high-latitude privat gold. This pattern results from large and opposing LW and SW changes, particularly in the tropical Pacific (SI Appendix, Fig.

S5 E and F). Much of this signal is dynamically driven, reflecting an eastward shift of the ascending branch of the Walker circulation (and associated humidity changes) privat gold effect is not captured by the prediction (SI Appendix, Fig.

We have verified that the spatial patterns of tropical LW and SW feedback are very well predicted if RH and vertical velocity are included as extra predictors in Eq.

This dynamical signal largely cancels out for the net feedback (Fig. Dynamical signals also tend to cancel out in the нажмите чтобы узнать больше mean (36), privat gold why our prediction captures the global LW and SW feedbacks well (SI Appendix, Fig. S8 and S9) and multiplying by privat gold CMIP mean changes in controlling factors (SI Appendix, Fig.

Http:// A and B).

In A, hatching denotes regions ссылка на страницу the sign of the prediction is consistent for any choice of the set of sensitivities (based on one of four reanalyses) and controlling factor responses (based on one of 52 CMIP models). Correlation maps of actual vs. Privat gold B and C). We note that the spatial pattern of net cloud feedback (SW plus LW) is determined primarily by the SW cloud-radiative sensitivity to surface temperature (SI Appendix, Figs.

Further discussion of these sensitivities privat gold given in SI Appendix. Consistent with previous privat gold studies (7, 8, 10, 15, 16), the dominant Tsfc-mediated cloud response is partly counteracted by changes in EIS, which increases with warming across most of the tropics (38), promoting low-cloud formation and, thus, enhanced SW reflection (SI Appendix, Figs. In addition to being calculated globally, as in Fig.

We privat gold between low- and nonlow-cloud regions in the tropics and extratropics and identify these regions according to the relative magnitudes of LW and SW cloud feedbacks in the GCMs (5, 39) privat gold Appendix, Fig. Privat gold design, LW cloud feedback is privat gold zero in low-cloud regions. The regime breakdown in SI Appendix, Fig. S11 shows that the differences in LW and SW global cloud feedbacks between models and observations arise primarily from tropical and extratropical nonlow clouds (SI Appendix, Fig.

S11 F and G), with a minor additional contribution from low clouds over tropical land (compare SI Appendix, Fig. S11 C and D). The observationally inferred aida farid LW and SW feedbacks are suggestive of a decrease in high-cloud area with warming, a possibility privat gold by observations and theory (40, 41), but thought to be underestimated by GCMs (42).

Near-neutral LW feedback is also consistent with expert judgment that the LW radiative impacts of changing high-cloud altitude and area will approximately cancel out (3). For low clouds, our observational constraint points toward weakly positive feedback (SI Appendix, Fig.

Our low-cloud-feedback estimate thus appears inconsistent with the large positive values simulated by some CMIP6 models, particularly in privat gold extratropics (5). Further comparison of our results with prior low-cloud-feedback studies is provided in SI Privat gold. We now consider how our revised range for the cloud feedback translates into reduced uncertainty for global warming projections. The observational constraint translates into a probability distribution for ECS (Materials and Methods) with central value 3.

Importantly, the constraint also confirms that ECS lower than 2 K is extremely unlikely (0. Note that the y axis on the right-hand side privat gold in units of ECS. No central ECS estimate was provided in the IPCC AR5 report.

Our results demonstrate that a careful process-oriented statistical learning analysis of observed monthly variations in clouds and meteorology over a relatively short period (fewer than 20 y) can provide a powerful constraint on global and regional cloud feedbacks.

Our global constraint privat gold that a globally positive cloud feedback is virtually certain, thus strengthening prior theoretical and modeling evidence that clouds will provide a moderate amplifying feedback on global warming through a combination of LW and SW changes.

This positive cloud privat gold renders ECS lower than 2 K extremely unlikely, confirming scientific understanding that sustained greenhouse gas emissions will cause substantial future warming and privat gold dangerous climate change. The CERES record is characterized by its high temporal stability (45), which makes it suitable for climate studies. We analyze top-of-atmosphere LW and SW cloud-radiative effect, estimated in a manner consistent with GCMs (46). For the controlling factors, we use monthly surface- and privat gold data from four reanalyses: Climate Forecast System Reanalysis (CFSR) (47), European Centre for Medium-Range Weather Forecasts Reanalysis Version 5 (ERA5) (48), Japanese Meteorological Privat gold Reanalysis 55 (JRA-55) (49), and Modern-Era Retrospective Analysis for Research and Applications 2 (MERRA2) (50).

The calculation of the cloud-radiative sensitivities for GCMs and observations is увидеть больше on the period March 2000 to September 2019, to match the period available for CERES observations at the time of writing.

We therefore concatenate the historical and RCP4. Privat gold, we introduce the specific measures of LW and SW cloud-radiative anomalies used in our statistical learning analysis.



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