Everything You Need to Find CLEAR SKIES

Show video

[Music] From the dawn of time, we astronomers  have had a mortal enemy. This enemy is devious   because it can show up when you least expect  it. The forecast says it will be clear. and then out of nowhere So how do we astronomers avoid that fate? well  we have to get better at interpreting weather   forecasts so that we can get better at knowing  both where and when we will have clear skies   and in this video I'm going to equip you with  lots of tools to do just that and I got some   help in the making of this video from a true  expert on astronomy weather Daniel Fiordalis   who is the creator of Astrospheric this video is  not sponsored by Astrospheric but it does have a   sponsor which is Brilliant and I'm going to  tell you more about brilliant about halfway   through so the first thing that we're going  to go through here and it will do it through   a series of questions is breaking down some of  the terminology and to make sure that once you   start digging into these tools and data sets and  forecasts that you really know how to interpret   them to get the best results out of them and I'm  going to start with this question the forecast   model because it's something that I admittedly  didn't fully understand the last time I made a   video on this topic a weather forecast model  is really complex to make it involves lots of   investment in things like satellites and weather  balloons and supercomputers so it's really only   governments that are making these weather models  and it is the model that creates predictions about   the weather including cloud cover and then all the  different websites and apps are taking information   from a model or sometimes from an API that's sort  of a middleman between the model and the and the   forecast and the website or app chooses what to  display how to display it and so forth so that's   the differences you see but it's important to  understand this because there's no point in   taking time to consult multiple websites and apps  if their predictions are all coming from the same   weather model what we really want to do is compare  predictions coming from multiple models and so   I'm going to break down some of the different  weather models out there and before I do that   let's hear from Daniel from Astrospheric on what  exactly goes into creating a model because I think   you'll find this super interesting like I did on  the left right there there's a few ways that gets   assimilated into the system um they're certainly  kind of like you know radar systems around the   continent that are scanning uh for for cloud  patterns intense weather hail Etc the the other   way is weather balloons it kind of blows me away  like Noah launches like a hundred weather balloons   every 12 hours from dedicated spots around the US  and the same goes on in Canada and other countries   and these provide really accurate um vertical  data that is also accessible if folks want to   look at they they're generally shown in something  called a skew tea graph uh they're really popular   um for like Pilots right like the these  are usually launched relatively near an   airport and can provide some really good  information about the stability of the air   then just scattering the landscape are  uh you know NOAA weather instruments   um and so these kind of provide a set of data  that's um is at ground level and then yeah there's   satellites orbiting us or in geosynchronous orbits  that are sending back data that the models can use   there are other places like um airplanes  uh commercial airplanes flying to the sky   uh actually send in some weather data um and  that can be incorporated into the model and so   um let's see if I can if I can draw on  this here we'll just pull up a blank sheet   um all of these will basically go into what is  called Data assimilation I don't know I have   some chicken scratch handwriting but we'll we'll  go with it for now and so like what that means is   you end up with a ton of data points that are  just really sparse relative to the land mass   and the amount of uh um you know atmosphere above  you and then it's up to these data assimilation   processes which are just you know complex  statistical mathematics that run over this   um to then get you into this which is a nice  grid that covers the entire area that you want   to look at and um you know depending on how much  uh compute resources you have how big your super   computer is kind of determines then when the model  runs how much you can break this down and how   detailed you can get and so there are models that  um divide the Earth every half a degree right of   latitude or longitude and then there's models uh  like the high resolution rapid refresh which I'll   show a bit of today that can divide all the way  down to like uh you know kilometer scale and so   you can get a really high resolution and I think  you know interestingly um let me um see if I can quickly turn this into kind of like an isometric  View not only the grid directly over but this   extends up uh many miles and in fact like  it'll go up uh they basically go off of   what the atmospheric pressure is and it would go  down to like you know 50 bar which is really way   up at the top of the atmosphere and so this then  turns into a really a three-dimensional grid of   Cubes that you can then pull weather data out of  or predict weather data into as it goes forward   there's some Advanced there's like you know  super Advanced things going on where it's   not always a cube that gets generated it  might be you know like a dodecahedron or   some other like shape that helps them increase  resolution and and kind of optimize compute power   um and so I from assimilation you  go into really what the model is um and so that's going to take all that intro  data it's going to initialize the model and run   some Physics over it and produce the next hour or  you know may go out three hours or something like   that and then fundamentally it's just going to  feed that back into itself re-initialize and keep   doing that as far out as the as the model runs and  and different models have different lengths uh the   GFS goes out something like 240 hours like hour by  hour more Others May only go out um like 36 hours   like and again it's it's all about just optimizing  to commute compute and accuracy of the forecast   out of these models comes the data that uh  astrospheric uses and a few other services use and   um there are these binary files that are called  uh grib 2 which stands for gridded binary file   um and it's kind of like the common currency  within uh the weather Community to pass data   around and save data into um and and this is  where it's like okay do I get my data directly   from those or are there apis in between us kind  of like what distance is in between because I   think you know in your weather video you called  out really accurately check multiple sources I   actually think another big one is like try to  get as close to the source as you possibly can   um and so from here on out there's there's  going to be a few things that happen we could   go up into uh some company that runs a weather  API and this would be something like dark sky   um I need to stop calling that it's Apple now  it's Apple weather that runs that and there's   just tons of people that that feed off of those uh  they'll do a bunch of interesting things and and   be able to give you a point forecast really  easily but one thing they're not great at   is delivering map data and so some of these  will go to services that will generate Maps   um and others I will will go to a service like  astrospheric um where we'll generate both Maps   endpoint forecasts okay so looking at the the  important things in a forecast for astronomy   cloud cover is number one right because if  it's cloudy none of the other things matter   um and the way that cloud cover is typically  presented is is it's the percentage of the   sky that's going to be covered in clouds at  a particular time in a particular location   so if it's zero percent that means that that  particular time and location when you look up   it'll be completely clear if it says 25 they're  predicting that a quarter of the total area of   the sky will have clouds now they're not saying  where in the sky those clouds are going to be but   what I see some people misinterpret this as is  25 meaning there's a 25 chance of clouds that's   not what they're saying they're saying there is  a high likelihood that there will be some clouds   somewhere in the sky and they think that it  will cover about 25 of the total Sky area   now that might not be so bad if it's just passing  clouds right like sometimes you'll see a forecast   go from 0 to 25 and back to zero and that  just means there's a few passing clouds to   deal with could still be a perfectly good night  so there's you have to really look at this and   um depending on the website or app you're using  it might not even give you a percentage it might   instead give you a phrase like clear partly cloudy  mostly cloudy so here's the cheat sheet for what   those terms really mean and there's a third  column here with a lesser used unit for cloud   cover measurement called the OCTA OCTA meaning  eight and so zero octas means it's perfectly clear   eight octas meaning completely overcast now  I've long felt that cloud cover predictions   are pretty good A day or two in advance but  a week out they really can't be trusted and   something pretty interesting that I've uncovered  in the making of this video is the weather models   actually agree with me there if you can actually  find some weather models that will give you   error bars showing the level of confidence in any  given prediction so for instance here I'm on the   European Center for medium range forecast website  and if I click on the map I get this handy chart   and you can see as we get further away from the  present these error bars are getting bigger to   the point where a week out the likely range of  outcomes is huge here it's saying that a week   out it's basically a coin flip whether it's clear  or mostly cloudy now we've all probably been in   a situation where you're literally outside the  forecast on your phone says it is clear right   now yet it is cloudy and so that sucks it will  probably happen to you if you're in this hobby   long enough but there is an extra step that I  suggest taking basically for extra assurance   that that doesn't happen and I'd say this step is  probably more critical if you plan to spend time   driving to a dark location and that is to look  through um both real time but also forecasted   map data when you zoom out and you sort of see  how the clouds are predicted to be moving that   is sometimes can give you a much better handle  on just where the forecast may be going wrong   and also if you can expect the clouds that you're  currently under to stick around or to pass over   and so I'll be showing various tools uh  later in the how-to part for viewing map data   so but to wrap up this part about cloud cover a  few takeaways number one cloud cover is typically   presented as a prediction of the percentage of  the sky that will be cloudy number two it's very   difficult to predict more than a couple days out  at a time which is uh you know because clouds are   unpredictable which way they're going to move and  so for a particular location it's really hard to   say and the hours leading up to a trip to a dark  site Beyond just a point forecast I would also   start looking at map data to get an idea of how  the clouds are going to be moving for transparency   and seeing which are two other important factors  for astronomy and an astronomy forecast let's go   back to Daniel for an explanation there aren't  models that produce transparency and seeing   um just directly out of the model it's a bunch  of post-processing on variables that the model   did produce that help us that help us understand  and put them together in interesting ways and so   transparency you actually nailed it in your  weather video what we're looking at is from   the base of the Earth all the way to the top of  the atmosphere sorry the base of the atmosphere   all the way to the top of the atmosphere we're  going up that column and um looking at water   vapor primarily um because exactly as you called  out the the higher the concentration of water   vapor the more things like light pollution from a  nearby City will reflect off of that and the more   um the more that that's in the air it also is  occluding uh light coming through the atmosphere   um the other big factor in our transparency  forecast is smoke which is uh unfortunately   kind of like a necessity now if you really  want to have an accurate transparency forecast um and so we pull data in that comes from the  the wrap model which predicts and forecasts how   aerosols move through our atmosphere and  so we're able to take that and and kind   of integrate it in with transparency and  produce something hopefully a little bit   more accurate although we're like constantly  tuning it and it's it's one of those things   where each summer smoke season outcomes  we're able to tune it a little bit further um and so that that ends up being transparency and  the value you end up getting out of transparency   like out of these uh functions are are basically  something akin to an aerosol Optical depth which   is a value that just indicates how much light  can pass through uh the gas of our atmosphere   and the higher the number the worse it is and  the lower the number the more transparent it is   I think one thing to call out with transparency  uh because I see it on some weather websites   is people use transparency and visibility  interchangeably and it's it's not the same   thing transparency is is a measurement  of uh how clear it is directly above you   and visibility is saying at the surface  how far can I see at the surface level   and the reason this is important is  because it can be very clear at the surface   um but a few miles above your head there could  be you know serious clouds floating over you or   something like that that are actually  going to really destroy transparency   um so that's just like yeah visibility is  generally the horizontal measurements of   how clear the air is and transparency is the  vertical measurement of how clear the air is   for seeing um I actually I was gonna do a  little more drawing for this one I set up   something for this um because seeing is a really  complicated variable um and it's it's one that   combines so many that I think the A good rule  of thumb when you look at seeing is to say like   let me find large spots of good seeing um and  and you know if I just see a tiny really good   spot of seeing like maybe ignore that because  there's so many variables and if there's any   error anywhere in the forecast it just kind of  compounds all the way all the way up the stack   and so um I think the easiest way to illustrate  uh seeing and this is similar for transparency   um is uh you know I'll use one of my favorite  sites I like to go out to the Olympic Peninsula   to take photos uh it's just ridiculously  dark out there and seeing can be okay   um but what happens is uh behind the scenes  you know when when astrospheric or whatever   you know astronomy software that's producing  the seeing data is is coming from it's kind of   looking at a set of cells above your location so  in that case you know I'm out on the coast these   are the cells above me um and so let me just  draw a little bit there's there's a few factors   um a few variables that we look at here and so  let me zoom in just to help with how I draw the   two primary things we're looking at are um the  wind speed and direction and then the temperature   um because what seeing is is a measurement of  uh of turbulence in the air above your current   location and the reason that's important  is because turbulence is caused by you know   mixing of low density and high density air or  warm and cold air and as light travels through   that it uh you know it refracts in funny ways and  we end up going from what used to be a beautiful   just point of light for a Star to something  that grows out um you know much larger and so   let me just do this so so like if I were to  draw on this and say like you know I'm on the   coast definitely at the surface I'm gonna have  a wind that's kind of like coming right at me   um it's usually coming in from the west and then  as we go up this it may be a little bit similar it   may start turning there may be a few Pockets where  things get real wild uh maybe there's a total   reversal and airflow in one of these cells and  then as we go back up it kind of normalizes again   and uh maybe as we get real high we're  starting to really look at the jet stream   right there's these arrows are getting much longer  hopefully they're going in a similar Direction   the ideal situation is they're all pointing the  same way and you have like laminar flow above you   um and and seeing through that type  of atmosphere should be pretty good   the other attribute so this is kind of like a you  know wind is creating a two-dimensional look and   we're looking at where there's wind shear the  other uh the other element we have to look at   is what is the temperature in each one of these  you know at the surface it may be uh real high   and then it will begin to drop off very quickly  and I'll just you know use little dots to show   that it's getting cold as we go up although there  may be a little inversion it gets a little warmer   um than the than the cell below it as we  go up and so what we do at this point is   we combine these together um and produce  what is called a c squared n profile of this column and that's really just saying  like Okay given these wind speeds and these   wind directions and these temperature changes  all these gradients let's um weight this and   produce a number that will allow me to say like  okay I had that point that is a star it's either   going to turn into a little bit bigger of a star  or it's going to turn into just you know chaos   um and and that's that's kind of the final number  that comes out of one of these scene forecasts   so this is a bit complex I'm not going to go  into every model out there in general though   there are two types of models Global models and  Regional models and Global models have to be   more low resolution because they're covering the  entire Earth but they're good for predicting large   weather patterns extreme weather like the path  of hurricanes and they can also be helpful for   clouds and astronomy Regional models though can  be even better because they're typically higher   resolution so you can dial in like your specific  location they usually combine more data sources   like the hundreds of NOAA weather balloons that  Daniel was talking about and they also update   more frequently sometimes but the downside to  these Regional models as the name suggests is   that their domain it usually only covers um you  know one country or a few countries usually the   country trees are always probably the countries  that are making these models that are paying into   them so in the USA where I live we have the  high resolution rapid refresh it's a weather   model that's updated hourly down to a resolution  of three kilometers but its domain its coverage   area doesn't extend much past the USA in terms of  global models the European Center for medium range   forecasts often shortened to just the European  model is probably the best one out there in   terms of a global model and I'll be sharing  more on how to use their website when we get   to the how to's another Global model is noaa's  GFS Global forecast system and it's another one   that's considered pretty accurate now the reason  astrospheric hasn't expanded Beyond North America   is because Daniel draws from Regional models  in addition to Global models and those Regional   models that he's drawing from only cover North  America but he feels some of these especially   the Canadian model are the most accurate in the  U.S and Canada for cloud cover you know the thing   that made me go with the rdps model from Canada  is that they really focused on cloud coverage and   their prediction model is attempting to predict  what you'd see if you just looked from one of the   satellites uh like goes 16 right looking down  on the planet and seeing those clouds and so   what it was trying to do is predict that which  I think is really good for astronomers because   um we kind of want that detail and what clouds  are coming up so in this video as you've seen   I wanted to really dive into the models behind  the forecasts but of course there's always more   to learn about any topic and to truly understand  something as complex as a weather model I think   today's sponsor brilliant is where I'd go  for a deep dive on everything you do need   to know including statistics and probabilities  brilliant.org is a Hands-On way to learn science   and math in a really fun and interactive  way and there are thousands of lessons   with new ones added each month the lessons that  I think could really enhance your understanding   of whether modeling are the ones on probability  and what I'm showing here is the course intro to   probabilities that I've been really enjoying  it has all these interactive activities that   are really fun so to try everything brilliant  has to offer completely free for a full 30 days   visit brilliant.org nebula photos or click on  the link in the description the first 200 will   get 20 off Brilliance annual premium subscription  after the free trial so hopefully you've made it   this far because now that you know all the needed  background on weather models and all that uh stuff   you know cloud cover seeing transparency what  all these things mean we're gonna actually dig   into where to find the data and how to use these  tools to more confidently predict clear and steady   skies for your location okay so the first tool I  want to show you here is the ecmwf European Center   for medium range weather forecasts and of course  I'll put all of the links in the description so   on here there's actually a lot of cool information  that I've been reading but I just want to show you   uh the the most important chart here so to get to  it go to forecasts and then scroll down to charts   and then click into medium range forecast charts  okay and then over here on the left hand side you   can see there's different parameters you  can select and so if we just select cloud it gives us seven different charts that we can  look at and these simulated images are might be   what you're looking for those are are really  good for just sort of seeing the cloud fronts   but I find them a little bit hard to see like the  the thinner um low altitude clouds on these images   and it's a little bit easier with this total  cloud cover map so I would suggest this one   it's the one I'm going to show here and because  this is the European Center it starts with the   European area the European region but this  is a global forecast so you can change it to   wherever you live or you can look at the whole  the entire Globe um there is a legend down here   it's a little bit confusing but basically what  this is saying is that um low clouds are this   beige color medium clouds are the magenta  color and uh high clouds are the blue and   so where they're all uh where you have all three  types of clouds you get this sort of dark grayish   black and where it's perfectly clear in the you  know anywhere that's perfectly clear it's going   to be white you're just seeing down to the base  map so I can quickly see here that right now or   pretty close to right now um it's clear throughout  much of India throughout the Midwest area of the   United States uh through a big part of Argentina  many countries in Africa looks like all of   France is clear so it's pretty interesting  just to look at a Global Perspective here   but of course you can click in here into the  region where you live so let's just pick uh   Northwest Europe and I will say for Europeans I'm  guessing that uh this is more useful than for some   other places because for instance I noticed like  in Europe it breaks it down by many different   regions while uh in North America it's just all  of North America so uh this is probably the one   I think to look at uh if you are in Europe or  the UK okay so what is this telling us here   we can see sort of the cloud patterns um and  then we can advance it by three hours at a time to see how those uh clouds are going to move  every three hours and so I can see 12 hours from   now ish now I I should stop saying now because  this is actually today at uh 12 universal time   so you'd have to do a little bit of math to  figure out uh you know what that means uh   if you're actually in the UK it's very close to  the universal time uh but let's just say for the   ease of this tutorial that right now  it is 12 noon universal time so in 12   hours at around midnight I can see that the  south of England here is perfectly clear now   what happens if I actually click on a  location so let's say I live right there   okay so let's look at how to actually read this  in a little bit more depth here so we're going to   be looking at this first chart right here total  cloud cover in octas and remember from earlier   OCTA is a term that means uh zero octaves would  be perfectly clear sky so that's at the bottom   of the chart eight octas is perfectly cloudy  overcast and so we can see right now in that   part of the UK it's perfectly clear if I go out  one hash mark six hours there's just a tiny chance   of a cloud or a few clouds if I go out 12 hours  they're very sure they're going to be no clouds so   that's great because uh six hours from now would  be 6 PM so that's sort of the start of the night   12 hours from now would be midnight so this looks  like it's going to be a clear night then 6 A.M  

we're again showing some probability of some  clouds coming back in now how do you actually   read this probability um it's easier to see down  here how the boxes work but basically the bigger   box contains 50 percent of the outcomes from 25  to 75 percent in a confidence interval and then   this smaller box extends down to 90 percent  of the outcomes and then the line coming up   from that is the maximum number of outcomes 100  so what this one is saying right here is that   foreign in most outcomes and about the majority of  outcomes it looks like it's going to be clear or   maybe just uh one OCTA so just a  few passing clouds like 10 clouds   um and then in 90 of the outcomes it's clear  or scattered clouds you know like 20 percent   of the of the sky covered and then in  all outcomes it's either clear or up to   5.5 octas so 5.5 octaves would be like half more  than half the sky covered in clouds so that's not   good but there's only about a 10 percent or less  chance of that happening by 6 am okay so hopefully   that made sense um you can see then as we get  further out here they really just don't know   uh you know all of these ones are saying it's more  likely to be cloudy than clear but you can see the   range of possible outcomes gets pretty crazy well  in here uh and then you know the next few days   they're saying that uh it's it's going to be  they're pretty sure it's going to be cloudy   it's only like a 10 chance uh that it won't be  or something like that so I do find this useful   I do think it is a little hard to read Because  you if to actually find like what time a certain   uh probability is talking about you basically  have to just sort of count the hash marks each   one representing six hours and for some reason  they're not marked so uh but I wanted to show you   how to read that because I think it is pretty  cool that they even have this data available   but the main way that I think uh this website is  really useful is to be able to go into your area   and just use this map data to see how  the clouds are moving and at what speed   okay next I want to show you astrospheric and  I just have up the free edition here just to   show you how useful even the free edition  is if you live in North America I live here   this isn't my actual location but I'm just  going to pick up spot here in New Hampshire   I'll click get new forecast and now you can see  that red target Mark is what this forecast is for   this is the location marked and then if I want  to save that I can just go over here and type in   H for New Hampshire click save and it's that  easy I now have one of my favorites marked   and whenever I log back into astrospheric that  favorite will come up whether it's on the app   or the website so how do we read this so one  thing I really like about astrospheric is that   it presents a lot of information in a compact  way so once you get good at reading it it's   really nice just to glance at it and understand  what's going on so up here of course we have   the map of the clouds and we can animate that  to show what the clouds are going to be doing down here we have a point forecast with cloud  cover transparency and seeing and then he's   also put in uh the what the Sun and Moon are  doing so when they're rising and setting along   with ISS passes and we have dew point and  temperature and if you click on any spot so   let's go to Tuesday night here at 10 pm it gives  you the stats down here cloud cover zero percent   transparency average seeing average wind 1 miles  per hour temperature 21 degrees Fahrenheit and if   I look up at the map I can see how far away that  cloud bank is and then if I Advance it I can see   this particular model rdps predicts that it  will be hitting me at right around 1am and by   4 AM I'll be in the thick of it now one thing to  keep in mind with these predictions is I found   that a lot of times they don't get quite when  the clouds will reach you right but it this at   least gives you an idea that probably some  part of the night on Tuesday is going to be   clear and then at some point maybe it'll be  1am like predicted or maybe it'll be 11 pm   This Cloud bank is going to hit my location  right so I really like the combination of uh   the point forecast down here with the map up here  which updates when I click on the point forecast okay uh what else to say about this so the the  free one just comes with one model loaded uh   rdps which is the Canadian model but uh if you  update to professional which is 299 per month or   if you belong to an astro society that meets the  conditions to get the Astro Society Edition you   get all the additional models uh like let's see  here what is available today rdps Nam nbm and GFS   so you get all of those and you can do some really  cool stuff that I'll let Daniel explain here   if I just look at live data right now this is  for a spot I love to go view in Central Oregon   um you can see uh if I click this Cloud later  this is just the rdps model and let's look at uh   you know right right about now um and  so this is already ps's prediction   um but I can quickly switch over to The Ensemble  here and it kind of turns into a like a Christmas   tree of lights here but what we're seeing is  each model and it's showing what it thinks the   the clouds are going to be at that time and so  the legend which is maybe a little bit small off   to the side is red is the GFS green is the North  American mesoscale and then blue is the rdps model   um so we can kind of blow this up look at this and it lets us like pretty quickly  take a look at this and say uh yeah like things   are green versus things are pretty out of whack  they're like very much out of agreement let   me back up a little here and so um you know this  this large structure that's moving through kind of   um coming off the West Coast likely we'll be  moving East here we can see how each of the models   feels that's going to move across you know you  have the GFS kind of having its Leading Edge a   little bit further out than um the the other two  and then where they all agree it'll turn white   it's just like yep we everyone agrees and then  where they all agree there won't be clouds it's   just uh clear all the way down to the down to the  ground one this is really I think crucial um in   various parts of the country and I think the west  coast is a is a great place to kind of show it off   I found over time the rdps model doesn't do  an awesome job predicting uh the clouds that   exist just over the Marine layer basically  that exists over the Pacific um here and I   I actually am curious if we just kind of flip  over and take a look at the satellite right now   Marine layer is kind of like these sets of  clouds that form and it can get absolutely   massive it can be a shelf that exists and  kind of like covers an entire almost uh   continent size area off to the off  the west coast and I found over time   you know the rdps Model cycle maybe let me  sync these up it's uh 5 30 here right now   um won't always catch these things so if I  kind of like toggle quickly between these   okay interesting right like these these kind of  clouds here we're kind of seeing those pop up   um however I found that the North American  mesoscope does a great job of certainly yeah   um picking out and and trying to find these  Marine layers which end up impacting folks   that are trying to uh uh view down in like Los  Angeles areas where it's like you're low enough   that this Marine layer can actually flow in a ways  and that totally you know ruin a night of viewing   and so that's pretty interesting right like  each model again has kind of like um a sets   of things that's really good ads that's a thing  that it's it's still learning I guess I'll say   okay this uh last one uh this last tool that we're  going to show in this video is Noah's weather and   climate toolkit it does feel a little bit U.S  Centric when you first open it but it can open   these grip 2 files from any um data source so  it it does have maps for the whole world if you   find uh grip files on you know non-us sites but  and I'm mostly going to let Daniel explain how   do you actually use this uh program but I just  wanted to explain something really quickly here   which is this is a Java program so you do need to  install a Java runtime on your computer in order   to use this and if you happen to be on Mac like  I am it's a little bit confusing because if you   don't already have the right run time installed  you might do what I did and just Google Java Mac   and this first result is not what you want um  it will bring you to java.com with downloads  

and it's the wrong thing what you actually want  is on oracle's website um and to get Java 17   go down here go to Mac OS and either install  this x64 or arm 64 DMG installer now if you are   on an M1 or M2 Mac like the mac Apple silicon  you're going to want the arm one if you're on   an Intel Mac you'd probably want this x64 one um  but anyways you just then download this DMG file   installed the Java 17 runtime and then when you  download noaa's weather and climate toolkit it   should actually run giving uh if you just follow  the instructions that are included in the zipped   bundle there so hopefully that helps get you  set up if you're on Mac I assume that uh it's a   similar situation with Linux you can get the right  Java runtime from oracle's website and then run   it this way and again Windows uh maybe that's the  same thing I think Windows is usually better about   already having a Java installed all right so now  I'm going to turn it back over to Daniel to show   how to actually use this toolkit which I think is  really something I've never seen and it seems very   powerful uh Noah's weather and climate tool kit  and this is a a great program I think for being   able to get directly to the model data and it does  a bunch of other stuff too it's a really kind of   like versatile tools to slice and dice and look  at data and generally you know before we introduce   any new data onto astrospheric it's been months in  uh in the weather and climate toolkit and looking   at it and animating it and changing uh Legends  ever so slightly and making sure that we're like   really dialing it for for public consumption so  this is definitely I think a great tool to use   and it has some built-in functionality that makes  uh things kind of easy to get at so like it can   connect directly to NOAA big data which apparently  is stored on Amazon these days um but you could if   you wanted um just pull up a Nexrad radar of your  local area and um just grab the latest data from   it and look at it you know directly on the map  and so um I don't know we could we could look at   I wonder if there's any out on the East Coast  I mean I'm sure there are unfortunately it's   here let's take a look at Albany here so  I can say yep I want to look at data from   today let's list these files and still go out  and it'll chew through everything everything   in here is usually in like UTC time so you'll  have to convert to whatever time zone you're   in but generally at the very bottom is the  newest data and then going back all the way   um to like the initial data from that day and yeah  a quick double click on that we'll download it   um and usually Zoom you right into  where you need to be looking and so as you can see um looks like some  thunderstorms rolling across uh   Massachusetts and uh Vermont main area right  now so heads up uh the the other thing is   um you can change things like the elevation of the  radar you're looking at so this is like one thing   it can do the other is it can pull apart grid  files which is like the handiest thing because   um unless you're writing special software to help  uh automate a bunch of stuff it can be kind of a   pain in the butt to view these things and so where  I go for grid data is somewhere you know anyone   can go it's the nomads um kind of like Central  distribution center of many many models um and   so this whole list each one of these represents  either a different model that's running or some   sub-domain of a of a larger model or maybe just a  model running a different uh resolutions overall   and it's broken out into things like there are  Global models and in here you'll see you know the   GFS is is represented here several times over um  and a lot of the differences are the resolution of   its um this s flux is usually that's the highest  resolution that you can get from GFS right now   um as well as um uh parts of the model that they  run separately like uh the chemistry section of   the GFS which is more predictive of um aerosols  and things like that in the air which I think   is kind of interesting folks not in the US or  in Canada you could technically grab data from   this and look at what the GFS thinks kind  of the aerosol Optical depth is above your   location based on uh forest fire smoke Etc  then we get into the regional models and and   um this is just a fantastic list of everything  that you could possibly want to look at   we'll focus on a few here and most of the time  when you go to a weather website or or get weather   data in the US at least you're probably looking  at this which is the high resolution rapid refresh   um you may be getting data from uh  the North American mesoscale model   um or um let's see the the rapid refresh  is also one that's uh sometimes used and   so these are kind of like three big models  that you'll end up seeing over and over again   um there's a few new ones that are popping up here  and there and I'll show some data from them um I   think a really interesting one and one that we're  excited to start working with just at astrospheric   is um the national blend model so this is the  NDM and this is a a model that runs hourly but   incorporates data from like over 40 other models  and builds up an ensemble based on that and so   I think that's actually a really interesting  thing let's start with um the national blind   model because I think this is one that probably  not many people see um really ever uh that that's   out there kind of like looking at either civilian  weather or certainly astronomy weather so the way   to do this is I think for starters at least you  can use this um nice script that knows written   that allows you to look at the grid file and kind  of pull apart and pull out exactly what you want   um over time especially if you're writing  scripts or code against these to grab the   models automatically you may switch  over and just go directly against they   just have big directory listings where you  can get this for today we're gonna uh use   the grip filter and again so this is the  national blend model it's being computed   hourly and it goes out 36 hours hour by hour  and then they kind of decrease the temporal   um resolution of it so okay we clicked there and  we say all right we want um this is like common   formatting you have the first four digits of  the year follow that a month followed by the day   um let's go with 12 because there'll be plenty of  data in there nope sorry I take that back let's   go to 13. today's the 13th um and then we can  look at this and say like okay subdirectories   now we're getting into the hour right so this this  is run a lot uh I'm going to choose the 18th hour   um and we're basically just traveling through a  directory structure at this point so this is where   um the the meat of it is and so what this program  has done or this website is it's gone through   that grid and it's pulled out all the available  variables inside of it and you can select just   one of them and download it or I can click Start  download so if I don't know what these variables   mean like if I don't know what uh tcdc is I  can just say start this download uh this will   be for the model that started at 18z so what  is that that's like it's 11 A.M Pacific time   um and it's the first hour of that model  and if we click this we can see like 18z   then produced a second hour or a third  and so on and so forth out into the future   um and it goes aways and you can see at 36 it  stops being hourly by hourly and skips to every   three hours this is again this helps just save  on compute and making sure they can go out of   ways here so we'll just take the first hour here  and I'll start the download and we're basically   going to download the whole thing um annoyingly  it didn't say how big it was but I think if I open   up my folder here so this is like 105 megabytes  okay um and so from here um I'm just gonna put   this on my desktop and then take the handy dandy  weather and climate toolkits and say I've got a   file on the local disk it's actually just on  my desktop let's take a look and list those   files and so there it is there's the you know  blend.t18z etc etc here down to the group 2 file   and I can open that and it will just load up and  so what I end up with is this grid file contains   this list of variables and we'll pick out a few  interesting ones here in a moment you can see   the domain that it's covering it covers basically  the uh the continental US minus Alaska here and   pretty big chunks of Canada as well at least um  covers a lot of the population of Canada at least   um and it really lets us quickly zoom in and  say like oh you know what this is actually a   pretty high resolution model right I'm actually  seeing like valleys in the mountains that this   is predicting we're looking at apparent  temperature height above ground right now   um and so we can just go up to the filter  and say like okay well [Music] um maybe I   want to know just what the temperature  is right like tell me the temperature   and we're going to take a look at the height  here and so it's saying the temperature at   two meters above the ground and just to kind of  put things in perspective this is at 12 o'clock   so this is noon uh Pacific time so the sun  should have been pretty high in the sky for us   and if I take my mouse now and hover over any  part of this you'll see down in this cell that   that totally just disappeared you'll see latitude  and longitude and then the value um and then we   can look at the legend and know that that value  is being reported and Kelvin so then at that   point you can convert 296.4 Kelvin to your your  favorite unit of measurement for temperature

um and just like that uh we we can look at  data directly out of this model there's been   no kind of like processing in between by  any websites or apps or anything like that   um and and just see what the model is  producing and I think I think this is   really cool I'm very much a data nerd so I  get the this won't be cool to everyone but   um I hope that someone finds it's exciting  at least as we go into the dark cold months   there's just gigabytes of data out there to be  played with okay so we we originally went into   this model to look at it's it's clouds um and  so uh we are going to look at a variable uh   called total cloud cover at the surface and so  this would be if I'm at the surface looking up   what percentage of like cloud is going to be  directly above me it doesn't really care about   where that cloud is it could be fog it could be  it could be really high up in the upper atmosphere and so this is going to show me that um and again  we'll take a look at the legend dark blue is clear   um there are a lot of options for what layers  you use and so like these colors actually kind   of like hurt my eyes um so you could easily go  into grayscale here and say great now you know if   it's black it's actually um totally clear and then  white is predicted to be very thick clouds so this   is producing a very high resolution prediction  of what it thinks the clouds are going to be at   um or we're at at 12 noon [Music] um and so to save us the pain of uh me downloading  tons of files I I preemptively downloaded uh   gigabytes of data the other nights and produced  some animations because one thing that we can do um is we can actually tell this  program to look at a bunch of grid   files and kind of run through them in  a Time series and produce an animation   so let me uh let me tee that up so I have weather  data nbm cloud view data if I open this and list   um I have a just a ton of NDM files that I've  stored I think these were from yesterday so   unfortunately I'm not predicting anyone's weather  tonight although if this video comes out in the   future it doesn't really matter anyways um and  again I can click through these I'm actually   gonna disable this reset zoom and you can see  if I if I slowly click through them you'll   see okay the clouds kind of move cool this  is this is great this is you know okay how   can I make an animation of this so in this  software if I click the first one and then   uh shift click the rest I can select them all and  then this animation option becomes available to me   um and I can say okay do I want to load an  animation directly here or do something else   I can produce kind of like a video right  away um I'll do here this may take a while   um and it's just going to run through each of  those files and generate an animation I will   say as this animates there are some interesting  things that you can see just based on what's going   on here and the the first one that catches  my eye the primary thing that catches my eye   these clouds look really high resolution  like they're very detailed I can't zoom in   while it animates but if you look up just  above this kind there's like a line of   things here things get a little uh a little  fuzzier maybe lower resolution and this is   um this is a property of this forecast model  the national blend of models is uh literally   taking different models um and statistically  blending them together to make a ton of sense   and not all models are of the same resolution  and so something that's covering um say the   US here is probably pulling from the high  resolution rapid refresh where something up here   um maybe pulling from a lower resolution model  so that's kind of why you're seeing those lines   and so a lot of these models come with little  little quirks like that that you can either   see right away or you learn about as you begin  using it and so um you know relatively quickly   I can build up an animation and see what the NVM  is projecting and so if I were using this data   for the night if I was you know really traveling  somewhere and I this is very important to me and   um you know let's say uh this is the area  that I was gonna go somewhere in Virginia here   um I can then you know take a quick look at   this model and uh exactly how things uh how  these clouds may be moving and again you're   probably not going to find this model on any other  website at this time or really any other service   um so this I think is a kind of a cool thing to be  able to do but the time of this is off I I don't   think this is at night but regardless conceptually  it's the same you just download the appropriate   ribs that that um that cover the time period that  you'd want to be able to look at and is this uh   is what we're seeing a visualization or is this  using actual photography total visualization okay   can I I love that question because it's like  this model is getting high res enough and like   obviously if I zoom in we can we can start to see  um the pixels and I'll do that actually over here   but it's getting high enough resolution to where  this you know you could pretty easily fool someone   into thinking this came right from a satellite  you know just from one of the ghost satellites   um if we zoom in we'll start to we'll start  to see the pixelation and I guess technically   you can do this with satellite data as well but  the interesting thing maybe to look at um again   because this is a grid if you look uh right here  in this cell when I hover over it's going to tell   you where in the grid I am I am I'm 162 grid  um cells from from the left edge of this and   I'm 686 uh cells up from from the bottom of this  and so this is the native resolution of this model   um which again I think is really cool because you  know even on astrospheric it's computationally   expensive to produce imagery at Native resolutions  and so sometimes we have to we we de-resident a   bit you know to make the to make the system go a  little bit faster and kind of decrease the amount   of data we have to send to everyone's phones but  uh with this app you can absolutely uh tear your   computer apart and zoom in and see kind of like  actual native resolutions of of the weather models   so you're now seeing the names of everyone who  supports this YouTube channel over on patreon.com   nebula photos it's an excellent community  of dedicated amateur astrophotographers just   people who want to learn and are very willing  to share their own expertise we have over 800   members now there's an active Discord that  you can get involved in and I can't thank my   patreon members enough because I'm now doing this  full-time thanks to all of you and it is what has   allowed me to make these videos and to really  pursue this as my own business so thank you so   much to all my current patreon members and if you  enjoy this channel I think you will get a lot of   benefit out of joining my patreon community  it starts at just one dollar a month and for   that you get a bunch of perks including direct  messaging support with me on Zoom chat with the   whole Community a monthly Imaging challenge  organized on Discord where we pick different   targets every month and a whole lot more  so if interested head over to patreon.com   nebula photos till next time this has  been Nico Carver clear skies [Music]

2023-02-17

Show video