jaws 0.6.4

Software to convert idiosyncratic ASCII formats to netCDF formats

Justified Automated Weather Station (JAWS) Software

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News

2018/12/07: Version 0.6.3 released: RIGB adjusted fluxes archived

2018/10/31: Version 0.6 released: RIGB tilt correction

2018/10/08: Version 0.5 released: SCAR stations convertible to netCDF by JAWS

2018/05/23: Version 0.4 released: Pip installable, analysis.py callable from 'jaws' keyword

2018/04/18: Version 0.3 released: Conda installable

2018/01/22: Version 0.2 released: Conversion of GCNet, PROMICE and AAWS networks complete

2017/10/23: Version 0.1 released: Original scripts from Wenshan

About

JAWS is a scientific software workflow to ingest Level 2 (L2) data in the multiple formats now distributed, harmonize it into a common format, and deliver value-added Level 3 (L3) output suitable for distribution by the network operator, analysis by the researcher, and curation by the data center. NASA has funded JAWS (project summary) from 20171001–20190930.

Automated Weather Station (AWS) and AWS-like networks are the primary source of surface-level meteorological data in remote polar regions. These networks have developed organically and independently, and deliver data to researchers in idiosyncratic ASCII formats that hinder automated processing and intercomparison among networks. Moreover, station tilt causes significant biases in polar AWS measurements of radiation and wind direction. Researchers, network operators, and data centers would benefit from AWS-like data in a common format, amenable to automated analysis, and adjusted for known biases.

The immediate target recipient elements are polar AWS network managers, users, and data distributors. L2 borehole data suffers from similar interoperability issues, as does non-polar AWS data. Hence our L3 format will be extensible to global AWS and permafrost networks. JAWS will increase in situ data accessibility and utility, and enable new derived products.

Overview

JAWS consists of:

1) Standardization

Convert L2 data (usually ASCII tables) into a netCDF-based L3 format compliant with metadata conventions (Climate-Forecast and ACDD) that promote automated discovery and analysis.

2) Adjustment

Include value-added L3 features like the Retrospective, Iterative, Geometry-Based (RIGB) tilt angle and direction corrections, solar zenith angle, standardized quality flags, GPS-derived ice velocity, and turbulent fluxes.

3) API

Provide a scriptable API to extend the initial L2-to-L3 conversion to newer AWS-like networks and instruments.

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Installation

Requirements:

• Python 2.7, 3.6, or 3.7 (as of version 0.6.3)

Installing pre-built binaries with conda (Linux, Mac OSX, and Windows)

By far the simplest and recommended way to install JAWS is using conda (which is the wonderful package manager that comes with Anaconda or Miniconda distribution).

You can install JAWS and all its dependencies with:

$ conda install -c conda-forge jaws

Installing from source

If you do not use conda, you can install JAWS from source with:

$ pip install jaws

(which will download the latest stable release from the PyPI repository and trigger the build process.)

pip defaults to installing Python packages to a system directory (such as /usr/local/lib/python2.7). This requires root access.

If you don't have root/administrative access, you can install JAWS using:

$ pip install jaws --user

--user makes pip install packages in your home directory instead, which doesn't require any special privileges.

Update

Users should periodically update JAWS to the latest version using:

$ conda update -c conda-forge jaws

or

$ pip install jaws --upgrade

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Example

JAWS is a command-line tool. Linux/Unix users can run JAWS from terminal and Windows users from Anaconda Prompt.

The current version can translate L2 ASCII data from the following networks to netCDF format:

• Antarctic Automatic Weather Stations (AAWS): Sample raw file can be downloaded from here. Right click on the link and select "Save link as".
• Greenland Climate Network (GCNet): Sample raw file can be downloaded from here
• Institute for Marine and Atmospheric Research (IMAU): Sample raw file for Antarctic stations can be downloaded from here and for Greenland stations can be downloaded from here
• Programme for Monitoring of the Greenland Ice Sheet (PROMICE): Sample raw file can be downloaded from here
• Scientific Committee on Antarctic Research (SCAR): Sample raw file can be downloaded from here

Note:

For PROMICE, input file name must contain station name. e.g. 'PROMICE_KAN-B.txt' or 'KAN-B.txt' or 'Kangerlussuaq-B_abc.txt', etc.

For IMAU, input file name must start with network type(i.e. 'ant' or 'grl'), followed by a underscore and then station number. e.g. 'ant_aws01.txt' or 'ant_aws15_123.txt' or 'grl_aws21abc.txt', etc.

For SCAR, input file name must end with '_aws.dat'

The user provides the input file path. By default, the output file will be stored within the current directory with same name as of input file (e.g. PROMICE_EGP_20160501.nc). The user can optionally give their own output path/name. Execute this to get output file in current directory:

$ jaws ~/Downloads/PROMICE_EGP_20160501.txt

or by specifying longer paths, and with options:

$ jaws -4 -o ~/Desktop/PROMICE_EGP_20160501.nc ~/Downloads/PROMICE_EGP_20160501.txt
$ jaws -4 -o ~/Desktop/GCNet_Summit_20140601.nc ~/Downloads/GCNet_Summit_20140601.txt
$ jaws -4 -o ~/Desktop/AAWS_AGO-4_20161130.nc ~/Downloads/AAWS_AGO-4_20161130.txt

where the argument to the optional -o is the user-defined output filename

A list of all options can be found in docs/options.txt.

To change the timezone, use the -t/--tz/--timezone argument. A list of all the timezones can be found here.

RIGB

Download sample data from here

To run RIGB:

$ jaws ~/Downloads/gcnet_summit_20120817.txt --rigb

RIGB uses climlab package to simulate clear-sky radiation.

Value Added Information

In addition to input variables, JAWS provides following variables in output netCDF file to make data more useful:

• time (seconds since 1970-01-01 00:00:00)
• time_bounds
• sza (solar zenith angle)
• latitude
• longitude
• ice_gps_velocity_x, ice_gps_velocity_y, ice_gps_velocity_total (For stations that archive GPS position)
• year, month, day, hour (if '-d/--drv_tm/--derive_times' option is used)
• adjusetd_fsds (corrected downwelling shortwave flux)

Analysis Example

To perform analysis, the raw data should be converted to netCDF format using '-d/--drv_tm/--derive_times' flag. e.g.:

$ jaws -d ~/Downloads/GCNet_Summit.txt

JAWS can be used to analyse the data in multiple ways such as:

i. Plotting monthly diurnal cycle to see hourly changes for any variable throughout the month.

The user provides input file path, variable name (on which analysis needs to be done) and analysis type (i.e. diurnal, monthly, annual or seasonal). Year and month are optional arguments. If the input file contains data for only single year, then the user doesn't need to provide the '-y' argument. Similar is the case for '-m' argument.

$ jaws -a diurnal -v temperature_tc_1 -y 2002 -m 5 gcnet_summit.nc

ii. Avg, max and min values for each day of a month for any variable

$ jaws --anl=monthly --var=temperature_cs500_1 --anl_yr=2013 --anl_mth=2 gcnet_summit.nc

iii. Annual cycle with daily mean, max and min

Since it is annual plot, user shouldn't provide the '-m' argument

$ jaws --analysis=annual --variable=temperature_tc_1 --analysis_year=2016 gcnet_summit.nc

iv. Climatological seasonal cycle showing variation for each month through multiple years

Since it is seasonal plot, user shouldn't provide both '-y', '-m' argument.

$ jaws -a seasonal -v temperature_tc_1 gcnet_summit.nc

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Statistics

Total number of networks handled by JAWS: 4 (AAWS, GCNet, IMAU, PROMICE)

Total number of stations handled by JAWS: 137

Total number of station-years of data handled by JAWS: 1462

Benchmark

As of version 0.6.3, it takes about 3.5 minutes to process Summit(GCNet) data from 19960512 to 20170524

Credit

This software is being developed by the University of California Irvine under NASA Advanced Information Systems Technology (AIST) Proposal and Project 80NSSC17K0540.

Resources

• Release Notes
• Gallery

Bugs and Feedback

For bugs, questions and discussions please use the GitHub Issues.

Copyright and License

Copyright (C) 2017--2018 Regents of the University of California. You may redistribute and/or modify JAWS under the terms of the Apache License, Version 2.0.