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Visualizzazione dei post da 2017

Yet another tutorial on how to install WRF

Immagine
Several tutorials on how to install WRF are available online. Basically the common root is the Official Tutorial from mmm.ucar . Some other noticeable websites are: WRF on Ubuntu server 16.04 again WRF on Ubuntu server 16.04 WRF on CENTOs WRF on Archlinux (with some nice ncl examples) WRF on a generic Linux machine   WRF Forum (section Installation)   etcetc...   Among the several tutorials you find online I'd like to add another (useless?) guide (or script) I used to automate the compilation of the WRF/WPS systems, with some special notes. It is definitely a non-exhaustive script and it might have some (hopefully non-destructive errors), so....  >>>use at your own risk<<< The prerequisites are: the netcdf libray (version 4.x) successfully compiled and installed (here in /usr/local) gcc, gfortran (version 5.4.0 or higher) #!/bin/bash # It is supposed that you have the following sources files in $SRCDIR # ARWpost_V3.tar.gz mpic

Downscaling ERA-5 reanalysis data for coastal climate applications (and evaluation of uncertainty of coastal data)

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Here's the abstract and the link to the oral presentation I gave this morning at the 5th International Conference on Reanalysys held in Rome, 13-17 November 2017 in the outstanding venue of Angelicum University located in the very centre of Rome. Downscaling ERA-5 reanalysis data for coastal climate applications (and evaluation of uncertainty of coastal data) : The management of coastal zones requires precise data concerning past wind/wave regimes and future climate trends. Many studies have been based on low resolution reanalysis data that cannot allow a detailed description of the variability induced by local conditions. We present a feasibility study where a simple dynamical downscaling of ERA5 reanalysis data is applied through a cascade of regional atmospheric/wave models. A long-term goal of this study is to identify the long-term trends in the last 30-35 years in order to better understand the effects linked to the impact of climate change along the coast. The methodology

Code published via github and zenodo

Today, thanks to my colleague alfcrisci , I found pretty straightforward to connect some of the several (too many??) accounts I have (github, zenodo, orcid) into a comprehensive house to publish and protect the code I developed making it citable. You get this  by following the instructions you find here. valcap/csv2little_r: First release : this is the first trial... valcap/regens: First release of regens : this is the second trial... Hope it will be useful in the future!

How to download, mosaic and resample Modis NDVI data

Immagine
Modis NDVI data are fully described here Briefly: these data are intended to be the continuation of the well-known NOAA-AVHRR Vegetation Index and are currently used in a wide range of applications. The following procedure (very basic!!! use at your own risk! no waranty!!) works only in a Linux environment (even if it has been ported on a Windows machine under Cygwin). Pre-requisities: wget and MRT (Modis Reprojection Tool) that needs to be installed properly (that is MRT's bin directory needs to be added to the environmental variable $PATH) It consists in three Bash script and one auxiliary file, namely: wrapper_ModisNDVI.sh get.ndvi.sh mrt.ndvi.sh custom.env Copy all the files in your workin directory and cd to that directory. Usage: sh wrapper_ModisNDVI.sh YYYY.MM.DD file_env where YYYY.MM.DD is the year.month.day of the NDVI time step you're interested in as listed in https://e4ftl01.cr.usgs.gov/MOLT/MOD13Q1.006/ and the file file_env (custom.env) contai

How to compute SBUs usage on ECMWF cca/ccb

The accounting currency on ECMWF supercomputer is the SBU (System Billing Unit) The accounting system is fully described here: https://software.ecmwf.int/wiki/display/UDOC/HPC+accounting Basically, " To ensure that computing resources are distributed equitably and to discourage irresponsible use users' jobs are charged " and SBU = P * (ELAPSED_TIME) where P = 50365140 / (3617 * 36 * 86400) is a fixed proportionality factor, adjusted so that the system will deliver 50365140 units per day on a "typical" ECMWF job mix on the ccb system (3617 * 36 is the number of physical CPUs of the cray system and 86400 the number of seconds in a day) ELAPSED_TIME is the elapsed time (real time in seconds) recorded for a job, multiplied by the number of physical CPUs used by the job Examples (copied from ECMWF User Documentation): A serial job using 1 hour (3600 seconds) of elapsed time will be charged about 16.11 SBU. A parallel j

How to compile the WRF model on ECMWF cca/ccb

#Prerequisites: #- This has been tested with the GNU compiler suite version 4.9.3 #- You should have all the needed libraries and WRF sources in the $PERM directory. Namely: #  * zlib-1.2.7.tar.gz          (This is a compression library necessary for compiling WPS (specifically ungrib) with GRIB2 capability) #  * libpng-1.2.50.tar.gz       (This is a compression library necessary for compiling WPS (specifically ungrib) with GRIB2 capability) #  * WRFV3.8.1.tar.gz           (WRF model) #  * WPSV3.8.1.tar.gz           (WRF Preprocessing System) #  * DTC_upp_v3.1.tar.gz        (Unified PostProcessing system) #------------------------------------------- # 1. Log in to cca (or ccb) #------------------------------------------- ssh -Y cca #------------------------------------------- # 2. GNU #------------------------------------------- # switch to GNU compilers prgenvswitchto gnu #------------------------------------------- # 3. NETCDF #-------------------------

How to run the WRF model using ERA5 (on model levels) as initial and boundary conditions

This procedure was tested with the WRF model Version 3.8.* and ERA5 data. 1. ERA5 data were downloaded as described in How+to+download+ERA5+data+via+the+ECMWF+Web+API   Here I'm attaching a sample script (launched on ecgate) to download surface data: # General settings Nort='90.0' West='-90.0' Sout='0.0' East='90.0' resX='0.25' resY='0.25' initdate='2012-11-01' paralist='msl/skt/2t/10u/10v/2d/z/lsm/sst/ci/sd/stl1/stl2/stl3/stl4/swvl1/swvl2/swvl3/swvl4' timelist='00:00:00/01:00:00/02:00:00/03:00:00/04:00:00/05:00:00/06:00:00/07:00:00/08:00:00/09:00:00/10:00:00/11:00:00/12:00:00/13:00:00/14:00:00/15:00:00/16:00:00/17:00:00/18:00:00/19:00:00/20:00:00/21:00:00/22 :00:00/23:00:00' gribfile='ERA5_sfc_'${initdate} mars <<EOF retrieve, class=ea, dataset=era5, date=${initdate}, expver=1, levtype=sfc, param=${paralist}, stream=oper, time=${t