Marcin Borkowsi has a nice post on how to capture the current file’s location and copy it to the system clipboard. It’s just what you need for sharing information about data in a file with a colleague. By file location he means the path to the file and the line number within that file.

That doesn’t seem too hard but there are some wrinkles. First of all you want the absolute line number within the file not just the number of the line visible in the buffer. That’s pretty easy but the second problem is a bit trickier.

Sometimes, just the name of the file is not enough. It may be that two files within a project have the same name but lives under a different subdirectory. Your first thought is probably to capture the full path to the file but that isn’t optimal either. As Borkowski says, there’s no point in showing the full path on his machine. What’s needed is the path relative to the current project.

That means the path relative to the current VC repository. It’s pretty easy to get that with the vc-root-dir function. Borkowski has some code that captures the file path and line number and copies it to the system clipboard. It’s simple and can be copied and used as is or modified to meet your particular needs.

The post is definitely worth a read if only to discover how to deal with the various issues.

UPDATE [2022-06-26 Sun 14:40]: Added missing link to Borkowski’s post.

Two opinion pieces (Slingo et al., and Hewitt et al.) and a supportive Nature Climate Change editorial were published this week, extolling the prospects for what they call “k-scale” climate modeling. These are models that would have grid boxes around 1 to 2 km in the horizontal – some 50 times smaller than what was used in the CMIP6 models. This would be an enormous technical challenge and, while it undoubtedly would propel the science forward, the proclaimed benefits and timeline are perhaps being somewhat oversold.

---

The technical wall to climb

Climate model resolution has always lagged the finest-scale weather model resolution which, for instance, at ECMWF is now around 9km. This follows from the need to run for much longer simulation periods (centuries, as opposed to days) (a factor of ~5000 more computation), and to include more components of the climate system (the full ocean, atmospheric chemistry, aerosols, bio-geochemistry, ice sheets etc.) (another factor of 2). These additional cost factors (~10000) for climate models can be expressed in the resolution, since each doubling of resolution leads to about a factor of 10 increase in cost (2 horizontal dimensions, half the timestep, and a not-quite proportionate increase in vertical resolution and/or complexity). Thus you expect climate model resolutions to be around 2⁴ times larger than current weather models (and lo, 16*9km is ~144km).

For standard climate models to get to ~1 km resolution then, we need at least a 10⁶ increase in computation. For reference, effective computational capacity is increasing at about a factor of 10 per decade. At face value then, one would not expect k-scale climate models to be standard before around 2080. Of course, special efforts can be made to push the boundaries well before then and indeed these efforts are underway and referenced in the papers linked above. But, to be clear, many things will need to be sacrificed to get there early (initial condition ensembles, forcing ensembles, parameter ensembles, interactive chemistry, biogeochemical cycles, paleoclimate etc.) which are currently thought of as essential in order to bracket internal and structural uncertainties.

Both the Slingo and Hewitt papers suggest some shortcuts that could help – machine learning to replace computationally expensive parameterizations for instance, but since part of the attraction in k-scale modeling is that many parameterizations will no longer be needed, there is a limited role there for this. More dedicated hardware has also been posited instead of using general purpose computing and that has historically helped (temporarily) in other fields of physics. Unfortunately, the market for climate modeling supercomputers is not large enough to really drive the industry forward on its own, and so it’s almost inevitable that general purpose computing will advance faster than application-specific bespoke machines.

The ‘ask’ is therefore considerable.

Potential breakthroughs

Increasing resolution in climate models has, historically, allowed for new emergent behaviour and improved climatology. However, the big question in climate prediction is the sensitivity to changing drivers and this has not shown much correlation (if any) with resolution. Conceptually, it’s easy to imagine cases where an improved background climate sharpens the predictions of change, e.g. in regions with strong precipitation gradients. Similarly, one can imagine (as the authors of Hewitt et al. do) that the sensitivity of ocean circulation will be radically different when mesoscale eddies are explicitly included. Indeed, the worth of these models will rely almost entirely on these kinds of new rectification effects where the inclusion of smaller scales makes the larger scale response different. If the k-scale models produce similar dynamic sensitivities of the North Atlantic overturning circulation or the jet stream position as current models, that would be interesting and confirming, but I think would also be slightly disappointing.

There are real and important targets for these models at regional scales. One would be the interaction of the ocean and the ice sheets in the ice shelf cavity regions around Antarctica, but note we are still ignorant of key boundary conditions (like the shape of the cavities!), and so more observations would also be needed. In the atmosphere, the mesoscale organization of convection would clearly be another target. Indeed, there are multiple other areas where such models could be tapped to provide insight or parametrizations for the more standard models. All of this is interesting and relevant.

Missing context?

But neither of the comments nor the editorial discuss the issue of climate sensitivity in the standard sense (the warming of the planet if CO₂ is doubled). The reason is obvious. The sensitivity variations in the existing CMIP6 ensemble are both broader than the observational constraints and are mostly due to variations in cloud micro-physics which would still need to parameterized in k-scale models. Thus there is no expectation (as far as I can tell) that k-scale models would lead to models converging on the ‘right’ value of the climate sensitivity. Similarly, aerosol-cloud interactions are the most important forcing uncertainty and, again, this is a micro-physical issue that will not be much affected by better dynamics. Since these are the biggest structural uncertainties at present (IMO), we can’t look to k-scale models to help reduce them. Note too, that it will be much longer before k-scale models are used in the paleo-climate configurations (e.g. Zhu et al., 2022) that have proved so useful in building credibility (or not) for the shifts predicted by current climate models.

More subtly, I often get the impression from these kinds of articles that progress in climate modeling has otherwise come to a standstill. Indeed, in the Slingo et al. paper, they use Fieldler et al. (2020) (in Box 1) to suggest that rainfall biases in response to El Niño have ‘remained largely unchanged over two decades’. However, Fieldler et al. actually say that “CMIP5 witnessed a marked improvement in the amplitude of the precipitation signal for the composite El Niño events. This improvement is maintained by CMIP6, which additionally shows a slight improvement in the spatial pattern”. This result is consistent with results from just the US models (Orbe et al., 2020), where the correlations related to ENSO and PDO have markedly improved in the latest round of models.

Perhaps this is a glass half-full issue, and while I agree there is a ways to go, the models have already come far. Based on previous successes, I assume that this progress will continue even with the normal process of model improvement.

A hybrid way forward?

Some modeling groups will continue to prioritize higher model resolution and that’s fine. We may even see cross-group and cross-nation initiatives to accelerate progress (though it probably won’t be as rapid as implied). But we are not going to be in a situation where these efforts can be the only approaches for many decades. Thus, in my view, we should be planning for an integrated effort that supports cutting edge higher resolution work, but that also improves the pipeline for parameterisation development, calibration and tuning for the standard models (which will be naturally increasing their resolution over time though at a slower rate). We should also be investing in hybrid efforts, where for instance, the highest resolution operational weather model ensemble (currently at 18km resolution) could be run with snapshots of ocean temperatures and sea ice from 1.5ºC or 2ºC worlds derived from the coupled climate models. Do these simulations give different statistics for extremes than the originating coupled climate model? Can we show that the hybrid set-up is more skillful in hindcast mode? We could learn an enormous amount using existing technology with only minimal additional investment. Indeed, these simulations could be key ‘proof of concept’ test that could support some of the more speculative statements being used to justify a full k-scale effort.

And so…

Back in 1997, the Japanese Earth Simulator came online with similar ambitions to the aims outlined in these papers. Much progress was made with the technology, with the IO, and with the performance of the climate model. Beautiful visualizations were created. Yet I have the impression that the impact on the wider climate model effort has not been that profound. Are there any parameterizations in use that used the ES as the source of the high resolution data? (My knowledge of how the various Japanese climate modeling efforts intersect is scant, so I may be wrong on this. If so, please let me know).

I worry that these new proposed efforts will be focused more on exercising flashy new hardware than on providing insight and usable datasets. I worry that implicit claims that climate model prediction will be as improved by higher resolution as weather forecasts have been will backfire. I also worry that the excitement of shiny new models will lead to a neglect of the workhorse climate model systems that we will still need for many years (decades!) to come.

Over the years, we have heard frequent claims that paradigm-shattering high resolution climate models are just around the corner and that they will revolutionize climate modeling. At some point this will be true – but perhaps not quite yet.

References

1. J. Slingo, P. Bates, P. Bauer, S. Belcher, T. Palmer, G. Stephens, B. Stevens, T. Stocker, and G. Teutsch, "Ambitious partnership needed for reliable climate prediction", Nature Climate Change, vol. 12, pp. 499-503, 2022. http://dx.doi.org/10.1038/s41558-022-01384-8
2. H. Hewitt, B. Fox-Kemper, B. Pearson, M. Roberts, and D. Klocke, "The small scales of the ocean may hold the key to surprises", Nature Climate Change, vol. 12, pp. 496-499, 2022. http://dx.doi.org/10.1038/s41558-022-01386-6
3. "Think big and model small", Nature Climate Change, vol. 12, pp. 493-493, 2022. http://dx.doi.org/10.1038/s41558-022-01399-1
4. J. Zhu, B.L. Otto‐Bliesner, E.C. Brady, A. Gettelman, J.T. Bacmeister, R.B. Neale, C.J. Poulsen, J.K. Shaw, Z.S. McGraw, and J.E. Kay, "LGM Paleoclimate Constraints Inform Cloud Parameterizations and Equilibrium Climate Sensitivity in CESM2", Journal of Advances in Modeling Earth Systems, vol. 14, 2022. http://dx.doi.org/10.1029/2021MS002776
5. S. Fiedler, T. Crueger, R. D’Agostino, K. Peters, T. Becker, D. Leutwyler, L. Paccini, J. Burdanowitz, S.A. Buehler, A.U. Cortes, T. Dauhut, D. Dommenget, K. Fraedrich, L. Jungandreas, N. Maher, A.K. Naumann, M. Rugenstein, M. Sakradzija, H. Schmidt, F. Sielmann, C. Stephan, C. Timmreck, X. Zhu, and B. Stevens, "Simulated Tropical Precipitation Assessed across Three Major Phases of the Coupled Model Intercomparison Project (CMIP)", Monthly Weather Review, vol. 148, pp. 3653-3680, 2020. http://dx.doi.org/10.1175/MWR-D-19-0404.1
6. C. Orbe, L. Van Roekel, �.F. Adames, A. Dezfuli, J. Fasullo, P.J. Gleckler, J. Lee, W. Li, L. Nazarenko, G.A. Schmidt, K.R. Sperber, and M. Zhao, "Representation of Modes of Variability in Six U.S. Climate Models", Journal of Climate, vol. 33, pp. 7591-7617, 2020. http://dx.doi.org/10.1175/JCLI-D-19-0956.1

The post Mmm-k scale climate models first appeared on RealClimate.

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How to view GitHub Pull Request branches locally in the cloned repo, and more importantly, how to do that automatically from within Emacs.

I have a few public projects in git repos, but I don’t get that much traffic in Pull Requests (PR) Gitlab calls these Merge Requests or MRs. . So when I need to add additional commits to a PR, I would just add the PR author’s remote to my local repo, check out their PR branch, add my own commits and then merge that to my project’s main branch.

As these occurrences were few and far apart, I didn’t have a need to view the PR branches directly from within Emacs/Magit. Though, I somehow knew that each GitHub Pull Request’s HEAD got assigned a git reference. But I didn’t need to use that knowledge until today 😃.

Today, when discussing PR # 20 on Prot’s Denote package’s GitHub mirror Prot uses SourceHut as the primary git forge for his Emacs packages. But I am glad that he doesn’t mind the activity in Issues and Pull Requests on the GitHub mirror. , he wrote this comment:

Now I just need to figure out how best to incorporate your changes into the org-id branch so I can add the final bits. I am not too familiar with the PR workflow …

.. and that inspired this post today.

Locally creating a branch for a PR #

From the GitHub docs, the git command to create a local branch for a PR is this:

git fetch origin pull/ID/head:BRANCHNAME

I have the denote package cloned from its GitHub mirror. So the origin remote’s url is https://github.com/protesilaos/denote.

When I ran the below command, I got a new branch pr-20 pointing to the latest commit of that PR:

git fetch origin pull/20/head:pr-20

Awesome!

Getting references to all Pull Requests #

Now that I was on that quest of “I want more”, it didn’t take me long to re-discover this 7-year old nugget by Oleh Krehel. Here are the relevant bits from that post:

1. Open the local repo’s .git/config file.
2. Find the [remote "origin"] section
3. Modify it by adding this one line with pull refs. This is the same for all GitHub repositories.

   [remote "origin"]
       url = https://github.com/USER/REPO.git
       fetch = +refs/heads/*:refs/remotes/origin/*
       fetch = +refs/pull/*/head:refs/pull/origin/*
   

With that edit in place, when I did l a (show the log for all git references), followed by f a (fetch all the remotes) in the Magit, I could see the references to the denote repo’s PRs!

Figure 1: Viewing PR references from denote package’s GitHub repo

Automatically adding PR refs #

Of course, I wasn’t the first one to think of this!

Another Emacs veteran Artur Malabarba had already had this covered also around 7 years back. Coincidentally, that post was written as a response to that same blog post by Oleh where he shared the above .git/config tip.

In that post, Artur shares an Emacs Lisp function that uses Magit functions like magit-get, magit-get-all and magit-git-string to auto-add the fetch = +refs/pull/*/head:refs/pull/origin/* line in the .git/config. This magic happens after checking that the origin remote points to a GitHub repo, and if that line doesn’t already exist.

Here, I am lightly modifying the function shared in that post so that the origin remote name is not hard-coded The reason is that sometimes, I name the original remote as upstream and my fork as fork, and I might have no remote named origin. . Credit for the main logic in this code still goes to Artur.

(defun modi/add-PR-fetch-ref (&optional remote-name)
  "If refs/pull is not defined on a GH repo, define it.

If REMOTE-NAME is not specified, it defaults to the `remote' set
for the \"main\" or \"master\" branch."
  (let* ((remote-name (or remote-name
                          (magit-get "branch" "main" "remote")
                          (magit-get "branch" "master" "remote")))
         (remote-url (magit-get "remote" remote-name "url"))
         (fetch-refs (and (stringp remote-url)
                          (string-match "github" remote-url)
                          (magit-get-all "remote" remote-name "fetch")))
         ;; https://oremacs.com/2015/03/11/git-tricks/
         (fetch-address (format "+refs/pull/*/head:refs/pull/%s/*" remote-name)))
    (unless (member fetch-address fetch-refs)
      (magit-git-string "config"
                        "--add"
                        (format "remote.%s.fetch" remote-name)
                        fetch-address))))
(add-hook 'magit-mode-hook #'modi/add-PR-fetch-ref)

Summary #

With the above snippet added to your Emacs config and evaluated, each time you visit a repo cloned from GitHub in the Magit Status buffer (M-x magit-status), the PR refs will get auto-added to that repo’s .git/config if needed.

After that, you can easily view the commits from all the PRs by doing l a f a.

References #

• oremacs – Some git/magit/github tricks
• endlessparentheses – Automatically configure Magit to access Github PRs
• GitHub – Checking out PR branches locally

Will the California nuclear power plant blow up, taking most of Southern California with it? Or will the problem just go away? Who could possibly guess?

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Author and journalist Jefferson Morley joins the boys to talk about his new book “Scorpions' Dance: The President, the Spymaster, and Watergate” which examines the CIA’s role in Watergate and the ensuing power struggle between Nixon and his DCI Richard Helms. Morley breaks down “The Cuban Thing” and “who shot John”, as well as the the past, present and future of The Agency and the fun and colorful biographies of CIA all-stars Howard Hunt and James Jesus Angleton.

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Someone or other is having an affair or something, and there's a nuclear war brewing between China and Russia or somesuch shit... Also, even after all those farewell tears AND a new Diesel Boots song... we have a brand new Psaki Bomb. How is this even possible!

On this week’s episode of Lever Time: David speaks with Alex Lawson, the executive director of Social Security Works, to discuss Lindsey Graham’s recent comments on entitlement reform and whether the Biden administration will capitulate to Republicans (5:07). He’s then joined by Andrew Perez, whose recent Lever story explored a free medical clinic filling critical health care gaps in Sen. Manchin’s home state of West Virginia, after the corporate Democrat blocked Medicare expansion (27:40). Finally, Julia Rock interviews climate organizer Pete Sikora, a campaign director for New York Communities for Change, about New York Dems’ recent efforts to kill a renewable energy bill (45:50).

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June 16, 2022 Ellora Derenoncourt, co-author of this paper, on the racial wealth gap, 1860–2020 • David Gelles, author of The Man Who Broke Capitalism, on Jack Welch, CEO of GE from 1981–2001

Long before the "metaverse" loomed over us, David Cronenberg's EXISTENZ (1999) imagined a completely immersive virtual environment that is even less cozy than our own. We discuss the film's porous boundary between reality and unreality, and explain why Cronenberg is one of the few Canadian filmmakers who really "gets" Canada. PLUS: Looking back at a moral panic over right-wing art from the early '90s.

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Nick and Ciarán return to talk shite about Bera, the posting Habsburg, Russian Fast Food, the German Greens and Draghi looking like shit.

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Democracy Now! 2022-06-21 Tuesday

• Headlines for June 21, 2022
• Colombia Elects 1st Leftist President Gustavo Petro & 1st Black VP Francia Márquez. Can They Deliver?
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I was just watching Prot's explanation of his new package denote, a very elegant note-taking system with a stress on simplicity and, as the author puts it, low-tech requirements. Now, those are excellent qualities in my book, and i think i'd quickly become a denote user if it weren't for the fact that i already have a homegrown set of utilities following a similar philosophy. Inevitably, they differ in some details, as is to be expected from software that has grown with me, as Prot's with him, during more than a decade, but they are similar in important ways.

I've had in mind writing a brief note on my notes utilities for a while, so i guess this is a good time for it: i can, after showing you mine, point you to a polished package following a similar philosophy and sidestep any temptation of doing anything similar with my little functions :)

As you'll see in a moment, in some ways, my note taking system is even simpler than Prot's, while in others i rely on more sophisticated software, essentially meaning that where denote is happy to use dired and filenames, i am using grep over the front-matter of the notes. So if you loved the filename-as-metadata idea in denote, you can skip the rest of this post!

These are the main ideas around which i built my note-taking workflow:

• Personally, i have such a dislike for non-human readable identifiers, that i cannot even stand those 20221234T142312 prefixes (for some reason, i find them quite hard to read and distracting). When i evolved my notes collection, i wanted my files to be named by their title and nothing more. I am also pretty happy to limit myself to org-mode files. So i wanted a directory of (often short) notes with names like the-lisp-machine.org, david-foster-wallace.org or combinator-parsing-a-short-tutorial.org.¹
• I like tags, so all my notes, besides a title, are going to have attached a list of them (denote puts them in the filename and inside the file's headers; i'm content with the latter, because, as you'll see in a moment, i have an easy way of searching through that contents).
• I'm not totally averse to hierarchies: besides tagging, i put my notes in a subdirectory indicating their broad category. I can then quickly narrow my searches to a general theme if needed².
• As mentioned, i want to be able to search by the title and tag (besides more broadly by contents) of my notes. Since that's all information available in plain text in the files, grep and family (via their emacs lovely helpers) are all that is needed; but i can easily go a step further and use other indexers of plain text like, say, recoll (via my consult-recoll package).
• It must be easy to quickly create notes that link to any contents i'm seeing in my emacs session, be it text, web, pdf, email, or any other. That comes for free thanks to org and org-capture.
• I want the code i have to write to accomplish all the above to be short and sweet, let's say well below two hundred lines of code.

Turns out that i was able to write a little emacs lisp library doing all the above, thanks to the magic of org-mode and consult: you can find it over at my repo by the name of jao-org-notes.el. The implementation is quite simple and is based on having all note files in a parent directory (jao-org-notes-dir) with a subfolder for each of the main top-level categories, and, inside each of them, note files in org mode with a preamble that has the structure of this example:

#+title: magit tips
#+date: <2021-07-22 Thu>
#+filetags: git tips

The header above corresponds to the note in the file emacs/magit-tips.org. Now, it's very easy to write a new command to ask for a top-level category and a list of tags and insert a header like that in a new file: it's called jao-org-notes-open-or-create in my little lib, and with it one can define a new org template:

("N" "Note" plain (file jao-org-notes-open-or-create)
 "\n- %a\n  %i"
 :jump-to-captured t)

that one can then add to org-capture-templates (above, i'm using "N" as its shortcut; in the package, this is done by jao-org-notes-setup, which takes the desired shortcut as a parameter). I maintain a simple list of possible tags in the variable jao-org-notes--tags, whose value is persisted in the file denoted by the value jao-org-notes-tags-cache-file, so that we can remember newly-added tags; with that and the magic of emacs's completing read, handling tags is a breeze.

Now for search. These are text files, so if i want to search for contents, i just need grepping, for instance with M-x rgrep or, even better, M-x consult-ripgrep. That is what the command jao-org-notes-grep does.

But it is also very useful to be able to limit searches to the title and tags of the notes: that's what the command jao-org-notes-open does using consult and ripgrep by the very simple device of searching for regular expressions in the first few lines of each file that start with either #+title: or #+filetags: followed by the terms we're looking for. That's something one could already do with rgrep alone; what consult adds to the party is the ability of displaying the matching results nicely formatted:

Links between notes are simply org file: links, and having a simple "backlinks" command is, well, simple if you don't want anything fancy³. A command to insert a new link to another note is so boring to almost not meriting mention (okay, almost: jao-org-notes-insert-link).

And that's about it. With those simple commands and in about 160 lines of code i find myself comfortably managing plain text notes, and easily finding contents within them. I add a bit of icing by asking Recoll to index my notes directory (as well as my email and PDFs): it is clever enough to parse org files, and give you back pointers to the sections in the files, and then issue queries with the comfort of a consult asynchronous command thanks to consult-recoll (the screenshot in the introduction is just me using it). It's a nice use case of how having little, uncomplicated packages that don't try to be too sophisticated and center on the functionality one really needs makes it very easy to combine solutions in beatiful ways⁴.

Krystal and Saagar and their collaborators discuss causes of inflation, Fed policy, artificial intelligence, woke activism, union busting tactics, crypto scam, oil markets, Depp-Heard trial, & more!

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Just added to my radio archive (click on date for link):

June 2, 2022 Forrest Hylton on the first round of the Colombian presidential election, which was bad news for the leftist Petro • Olúfẹ́mi Táíwò, author of Elite Capture, on how the ruling class has debased identity politics, and how we could reconstitute it

Just added to my radio archive (click on date for link, and apologies for the late posting):

May 26, 2022 Heather Berg, author of Porn Work, on relations of production in sex work • Kevin Young and Leonard Seabrooke, co-authors of this paper, on the contrasting collegial styles of the Chicago and Charles River schools of economics

On the inaugural episode of Lever Time, David speaks with civil rights lawyer and founder of Civil Rights Corps, Alec Karakatsanis, about how police in the US are not legally obligated to protect its citizens (10:10). Next, The Lever's Julia Rock discusses her reporting on the landmark climate justice lawsuit Juliana v. United States in which a group of teenagers are suing the federal government for the right to a livable planet (35:40). Then, renowned comedian and filmmaker Judd Apatow joins us to talk about his new HBO documentary, George Carlin's American Dream (55.40).

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On this week’s episode of Lever Time: David is joined by author and professor Roger Stahl to discuss the “military-entertainment complex” as it relates to the recent success of Top Gun: Maverick (3:10). Then The Lever’s Matthew Cunningham-Cook stops by to talk through his recent piece about how the Biden administration is hiking the price of Medicare premiums and funneling the money to private insurers (35:58). Finally, in light of the national trend of corporate interests flooding Democratic primaries with campaign cash, David sits down with Elisabeth Epps — a progressive candidate running for a house seat in the Colorado state legislature — to talk about the monied interests attempting to crush her campaign (50:58). 

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Elisabeth Epps’ campaign website: https://www.elisabethepps.com/