Emulation is worse for the physically extreme drop scenario, as expected, but is generally close to the optimal value of 1 in most inhabited regions. Shown are the (top) slow and (bottom) drop scenarios. Low I 2 means there is little trend relative to noise and the I 1 index is not informative, even if close to 100 (optimal emulation). The value in large font is the “emulation optimality” index I 1 (×100) and in small font below is the trend index I 2. The bands are very narrow, especially for temperature, highlighting the ability of the emulator to capture the mean trend with very high precision.Įmulation indices for all regions for the regional temperature emulation described in the text and shown in Fig. In (e),(f), the mean across the five CCSM3 realizations of the slow scenario is shown in gray, and the dashed red lines represent the pointwise 95% confidence bands based on the emulator. Empirical coverage is 0.9531 for (c) and 0.9545 for (d), very close to the nominal 95% level. In (c),(d), the five superimposed CCSM3 realizations are shown in gray, and the dashed red lines denote the 95% prediction bands from the emulator.
![ocean king 2 emulator ocean king 2 emulator](https://i.ytimg.com/vi/S4cWAk54g-Q/maxresdefault.jpg)
The actual runs and those simulated via the emulator appear to be qualitatively similar. The gray lines represent the five CCSM3 realizations and the red lines represent the five emulated realizations (with an offset of 1☌ for temperature and 1000 mm yr −1 for precipitation). In (a),(b), an example of emulated realizations is shown. The emulator was trained by one realization each of the fast and jump scenarios. All panels show the emulated slow scenario. Values of ( I 1, I 2) for the emulations shown here in (a)–(d) are (1.01, 11.23), (1.94, 35.82), (1.02, 1.18), and (1.09, 1.41), respectively I 2 is much larger for temperature, as expected.Įxamples of uncertainty quantification (a),(c),(e) for temperature in the North Pacific west (NPW) region and (b),(d),(f) for precipitation emulation for the equatorial Pacific west (EPW) region. We define diagnostics of emulation goodness-of-fit I 1 and trend-vs-variability I 2 in section 4a.
![ocean king 2 emulator ocean king 2 emulator](http://www.oceankingarcade.com/wp-content/uploads/2015/11/drill-crab-11.jpg)
Note that the trend in temperature is larger relative to stochastic variability than it is for precipitation. Emulation captures expected transient precipitation behavior in which precipitation anomaly is a function of the rate of change in radiative forcing. The solid red line represents the emulated mean function and the gray lines show the five CCSM3 realizations for the scenarios.
![ocean king 2 emulator ocean king 2 emulator](https://realfishmoney.com/wp-content/uploads/2021/04/logo-new.png)
Panels (a) and (c) show the emulated slow scenario, and (b) and (d) show the drop scenario.
![ocean king 2 emulator ocean king 2 emulator](https://cdn-www.bluestacks.com/bs-images/BlueStacks-Macros_King-of-Avalon_EN_4.jpg)
Some scenarios extend beyond the range shown here: slow, moderate, and fast end at year 2449, whereas jump ends at 2199 and drop ends at 2399.Įxamples of (a),(b) temperature emulation for the North Pacific west (NPW) region, chosen as representative of a region with significant change, and (c),(d) precipitation emulation for the equatorial Pacific west (EPW) region, chosen to highlight interesting transient precipitation behavior. We refer to these throughout the paper as the 1) slow, 2) moderate, 3) fast, 4) jump, and 5) drop scenarios. The CO 2 scenarios used for building the collection of runs.