8

Indeed, airlines are equipped to measure atmospheric data and then put into weather models. The WorldMeteorological Organization's program is called AMDAR. Several articles highlight the impact that the lack of flights have had on the initialization of weather models. https://www.npr.org/sections/coronavirus-live-updates/2020/04/03/826848818/one-more-...


6

Probability is used in weather forecasting. I will only highlight some examples due to my lack of knowledge in some areas. Before initializing a forecast model the data needs to be assimilated. That means we need to somehow put measurements from ground based stations, satellites etc. into the model and fit this data to the grid. We then have an "...


5

This is a topic of almost continual discussion in the South China Morning Post, scmp.com , an English language newspaper in Hong Kong. This is both because air quality is a major problem in China (but one to which they are paying a good deal of attention) and because massive economic interruptions are relatively frequent. The Olympics were a big one, ...


4

I think you are asking a question with a variety of different constraints. I'll tackle a couple of them. What is the simplest atmospheric model to operate? That would be the Zero-dimensional energy balance model. It has almost zero resolution and no temporal capacity. What is an atmospheric model that can be easily installed and run? The Weather ...


3

Rainbows are the result of water droplets in the atmosphere reflecting, refracting and dispersing light resulting in a spectrum of light in an arched shape in the sky. The water droplets in the atmosphere act the same way prisms do when they split white light into its component colors, hence the spectrum of light. The fact that the phenomenon is called a ...


3

The forecast hour of the product is the hour after the model cycle runtime that the forecast is valid at. For example, if the the cycle runtime is 12Z and the forecast hour is 9, then the the forecast is valid for 21Z. If the cycle runtime is 6Z and the forecast hour is 48, then the forecast is valid at 6Z two days later.


3

You can compare verification scores using this application from ECMWF made from guidelines by the WMO. The example below fits nicely with what is widely known, namely that IFS (the ECMFWF global model) scores generally best. In recent year the UK Met Office global model have also scored better than GFS. The figure shows the root mean square error of MSLP. ...


2

You can try the R package eixport, with wrf_put # example # Read the array emissions, CO <- wrf_get(file = "Path_to_WRFCHEMI", name = "E_CO") # Change the values, here you should use your data CO[] = rnorm(length(CO)) # Inyect your emissions into the wrfchemi wrf_put(file = "Path_to_WRFCHEMI", name = "E_CO", POL = CO) How to deal with the speciation (...


2

Maybe you can use infrared satellite images to get the cloud-top temperatures and estimate the height of them over vertical temperature profiles (e.g. radiosondes). But this ís just workingg for the clouds at the top. You can't see what's beneath them unfortunately.


2

The GSD file is just a text (ASCII) file, which you can read with almost anything you want. Since you are using python I would recommend looking at Pandas and especially the pandas.read_csv functionality. I am using this URL as an example now: https://rucsoundings.noaa.gov/get_soundings.cgi?data_source=Op40&latest=latest&start_year=2019&...


2

When I visit that link, the first option at the top ("Data Product") defaults to inst3_3d_asm_Np, which is atmospheric variables in pressure levels. I suspect you need to change that dropdown option to inst1_2d_asm_Nx, which is surface and near-surface variables. The list is shows me for that option is, DISPH = zero plane displacement height PS = surface ...


2

The highest temperature of the day typically occurs well before sunset but well after local noon (which in summertime is about 1:00 PM in areas that use daylight savings time). The reason for the lag between noon and the time at which temperature reaches a maximum is because is that the Sun continues to warm the ground, water, and air well after noon has ...


1

I am going to pause and say I don't know anything about SMHI. Therefore I can't comment on their competency. But I am sure they don't appreciate being called incompetent. If you are so passionate about rain, have you considered looking at weather prediction, and trying to beat them? It is well known that the limit for predictability of weather is 2 weeks. ...


1

The "feels like" value is calculated based on temperature, but altered depending on wind (cold temperatures) or humidity (hot temperatures). Think of it this way: 1) if it's freezing cold outside, the wind will make if seem even colder because any body heat you have will be blown away quickly. 2) if it's hot outside, high humidity will make it seem even ...


1

There is a parameter ice water mixing ratio in the gfs.t<hour>z.pgrb2.0p25.f<step> file given at isobaric levels.


1

It is likely that the forecast is made using an ensemble of runs from a weather model. As weather is chaotic (deterministic, but heavily dependent on initial conditions), each run will show a different pattern of precipitation, and the probability is likely to be simply the proportion of model runs that exhibited precipitation in that location during that ...


1

Given only this information and nothing else, there isn't really a definitively correct answer. In reality, it depends on the nature of the precipitation. 61% could mean that there is a 61 percent chance of a thunderstorm between 4 and 5 PM, but since thunderstorms are short-lived, it might only be raining for 10 out of 60 minutes. 61% could also mean that ...


1

Your question is extremely broad and it would be comprehensive to answer in detail. How it is done varies from one application to another. But in general, all weather forecasts come from a numerical prediction which is based on an analysis. The analysis is created by combining a prior (the previous forecast) with observations. There are many ways this can be ...


1

You can build a machine learning algorithm with skill but you will need several parameters such as day of year, time of day, cloud cover, wind speed, and precipitation. However, keep in mind that your algorithm will need to be trained on several years of previous data. For projects like this, you typically want about 5 years of observations to "train" the ...


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