Is there a direct way to download a full coverage, actual (2017), cloudless, mosaic of Sentinel-2 satellite imagery to a whole country (with the size like Portugal) ?
If it isn't possible, then can you advise me recipes to do it?
[GIS] Sentinel-2 mosaic (RGB bands) to a country
pyqgispythonremote sensingsentinel-2sentinel-snap
Related Solutions
In optical remote sensing in the visible spectrum you cannot see through clouds. So there is nothing you can do, except to wait for images without clouds.
Cloud masks are (as far as i know) used to exclude clouded areas from (for example) landcover classification, because results there would be incorrect anyways.
edit
As Aaron mentioned, you can sometimes use a cloud mask to insert cloud-free imagery into a cloudy image, but that only works if you a) do have cloud free imagery and b) you don't care that the resulting image is now a mosaic of images from different acquisition dates, and thus you cannot compute change detection etc. on it.
For images of the same location but different dates, I would rather talk about compositing than mosaicing (which combines images from different extents into a larger image). You will find a lot of details if you search "compositing" keyword, but here is a short summary:
There are two main approaches for the compositing of time series:
Best available pixel approach (select the "best" pixel at each location based on a given criteria, e.g. use the pixel with the maximum NDVI value or closest non cloud pixel to the central date of the compositing period). An example with Landsat can be found here
Combined pixel approach (e.g. take the average of all pixels at the same location (mean compositing) or use a temporal regression to interpolate "missing" pixels at some dates (gap filling) ). Note that gap filling potentially creates one image at any date (and you decide the one you keep), while compositing gives only one image per compositing period (you can use a sliding temporal window, but it is less "precise" temporally).
"Mean compositing" has been used in several successfull projects with MERIS and SPOT VGT (see here). "Max NDVI" compositing is used for the MODIS composite. Interpolation at some dates of interest has been done here with Sentinel-2 images. Personnally, I prefer the "combined pixel" type approach.
Now you must be aware that the quality of your compositing depends a lot on the quality of your inputs, especially if you don't have a large number of input data (sentinel-2 is "only" every 5 days, not every day like Sentinel-3) :
good cloud mask (including cloud detection, haze detection, cirrus (high altitude thin cloud) detection and cloud shadow detection.
top of canopy reflectance : convert Digital Numbers from the satellite into meaningful reflectance values, including corrections from BRDF (the light is not homogeneously reflected in all directions and there is an impact of the surface on the differences), atmospheric correction and topographic correction.
good registration between the different images. pixels must represent the same location as much as possible.
sometimes also: temporary event detection (floods and snow)
Note that a software has been developed in the frame of an ESA project (SEN2AGRI) for creating cloud free composites.
Bonus: examples of global composites
with Sentinel-2 (WMS only)
with MERIS, SPOT VGT and AVHRR surface reflectance (can be downloaded)
with Landsat circa 2000 and circa 2014 (median value using full Landsat archive)
Best Answer
Creating a mosaic can be quite a complex topic - you have to select each individual pixel based on chosen parameters, either creating a median value, darkest pixel, average, ... Depending on this you will get more or less consistent images, e.g. neighboring pixels might be chosen from separate dates, one showing harvested field and one still growing vegetation.
I suggest you check Sentinel-2 cloudless (https://s2maps.eu/) - here you can download the data for free.
Alternatively you might want to check Sentinel Hub services (http://www.sentinel-hub.com/develop/capabilities/wms) where you can get a pretty decent approximation for cloudless mosaic by e.g. setting "get data from 2017-01-01 to 2017-12-31, priority = least cloud coverage". The benefit here is that you could get up-to-date data as well, if you would need that. (note that Sentinel Hub services are not free).
Disclaimer: I am working at Sinergise, company behind Sentinel Hub services.