#reanalysis

Venus Is Dead! New Analysis Shows Phosphine, A Possible Biosignature, Is Absent

“So, what does this all mean? It means that the initial detection of phosphine, as claimed by the Greaves et al. team, is suddenly thrown into tremendous doubt. If they’ve analyzed their data in an unsound fashion, as this new work contends, then this chemical signature might not be present, after all. This new paper still needs to go through the peer review process, and I suspect that the original team will perform a reanalysis themselves to see what conclusions they arrive at.

In the absence of what initially appeared to be extraordinary evidence, we need to return to our default position: Venus has no evidence for being a biologically active world. Unless this new analysis is refuted and the initial work is vindicated, the idea of phosphine on Venus may be as dead as Venus itself.”

Last month, a series of three new papers came out, arguing that they had found evidence for phosphine, a chemical which is only naturally produced biologically on Earth, in great abundance in the atmosphere of Venus. Does this mean that there’s life on Venus? The possibility was fascinating, and led to a firestorm of speculation. But in a new study submitted just 2 days ago, an independent team found that the original analysis was unsound, and concludes that there’s no evidence for phosphine at all. Is Venus truly dead, after all? 

If you don’t learn from your mistakes, you are doomed to repeat them. A saying, or perhaps something more like a warning. In theory Maxie abides by it, in practice however... It hardly matters. He has changed and learned, things are not the same. Now would be a poor time to lose his nerve, at any rate. With so much potential on the line, even if it means working with him, with the both of them, he couldn’t pass it up. Just because this looks similar, feels similar, doesn’t mean it has to end the same way. He’ll make sure of it. But that leaves the question...

Should he call her?

He’s been putting it off. Most of the old Team Magma (the loyal ones at any rate) have already been contacted, many pledging themselves to his cause once again. But he has avoided this call. There’s little reason for his stalling, it’s not as though they’ve spent the last ten years in an icy silence. They are a friends still, even after all this time even after... he sent her away.

And there it is. Maxie told Courtney to leave him, and she’s obeyed his wishes. She has stayed away, and he has never asked her to come back, has never had a reason, the courage. Does she resent him for it? For his cruelty, his selfishness, his mistakes? Does he have any right to ask this of her any longer? And, most importantly, would she come back, if he asked her to?

Should he call her? He doesn’t know. The possibility that she will refuse him looms large in his mind. He doesn’t want to know, if that should be her answer. But the possibility that she will say yes, that she will return to his side... He will never know until he tries; it is worth the risk, and as he said: now is a poor time to lose his nerve.

Maxie stops fidgeting with the phone in his lap at last, choosing to select Courtney’s phone number instead. His foot bounces anxiously as he waits for her to answer. He hopes this isn’t another mistake. He can’t say for sure, his learning curve has always been far too steep.

Send 😎 for my muse to be your muses sugar daddy        

“Well, aren’t you just darling?” With a little hum of amusement, Malva stalked closer, peering at Courtney over her glasses.

✘ = hugging them

She feels fragile. He somehow he never expects it. Courtney has always seemed so much more than her physical body; Maxie forget sometimes that she really is quite a small girl. He knows he doesn’t need to be, but he’s careful when he squeezes his arms around her. He can gentle himself for her, for just a moment. They aren’t often physically affectionate with each other, neither of them is that kind of person but this is- nice. It feels good.

Dhanya & Villarini 2017 An investigation of predictability dynamics of temperature and precipitation in reanalysis datasets over the continental United States

 Explanation of the spatial pattern of the predictability indices by topography and their inter-relationship is good.

 The Chaotic System Indices

1. Maximum predictability

The maximal Lyapunov exponent is a measure of the predictability of a chaotic system. For a highly complex nonlinear system like the atmosphere, the nonlinear finite time Lyapunov exponent (FTLE) was appropriate. So FTLE was used to evaluate the predictability of temperature and precipitation over the continental US.

2. Predicative error (the mean predictive error around saturation)

3. Predictive instability (the random fluctuation of predictive error around a common mean)

Data

Four reanalysis products are evaluated: NCEP-NCAR Reanalysis I, MERRA, ERA-Interim, JRA-55

Results 4.1 General daily precipitation features - Climatological mean daily precipitation is better captured by ERA-Interim, followed by MERRA and JRA-55, and finally Reanalysis I - All the reanalysis datasets underestimate the standard deviation especially over the southeastern United States. This means Reanalysis I's bias is mainly systematic and can be easily corrected. - The signal-to-noise ratio of precipitation is somewhat slightly overestimated by ERA-Interim, MERRA, and JRA-55 in the southeastern US, and severely overestimated by Reanalysis I, which is not surprising given Reanalysis I's overestimation of the climatological mean and underestimation of the standard deviation.

<seasonal performance is missing from this study>

4.2 Predictability features of daily precipitation - All reanalysis products reproduced the overall predictability limit pretty well - Biases by the reanalysis products in simulating predictive error can be attributed to inability to simulate non-rainy days, which are underestimated in the eastern US and overestimated in some parts of the western US - For predicative instability, the biases in reanalysis products exhibit an inverse relationship to the predictive errors, which is expected because predicative instability = standard deviation of fluctuations / predicative error

4.3 and 4.4 are skipped here because they concern temperature and the results are less relevant & clear to me. But MERRA is said to perform the best on the chaotic dynamics indices.

Chen & Liu 2016 Global water vapor variability and trend from the latest 36 year (1979 to 2014) data of ECMWF and NCEP reanalyses, radiosonde, GPS, and microwave satellite

This article looked at global trends in precipitable water vapor in two reanalysis datasets (ECMWF and NCEP-DOE) and three observational datasets (Radiosonde, GPS, microwave satellite). It also looked at the relationship between temperature and PWV, and compared and explained the difference between them and Clausius-Clayperon relationship by moisture divergence & convergence. 

PWV has the larger standard deviation in spring and autumn, and low standard deviation in summer and winter. It's average value is high in summer and low in winter. The standard deviation of PWV is also larger over land than over ocean, and larger in the monsoonal regions. Globally, the trend in PWV is positive. ECMWF's PWV agrees better to the observations than NCEP. The trend in ECMWF is weaker than in NCEP, but the two agreed well after 1992. This is because ECMWF ingested a different dataset after 1992: it overestimated the PWV before then. Temperature is positively correlated with PWV where there is no strong moisture convergence or divergence. Strong moisture divergence remove the moisture, creating a negative relationship. Strong convergence zones, such as the ITCZ, have weak temperature trend, so the correlation also easily became negative. 

The papers conclusion is good!