Changelog • harpIO

harpIO 0.2.2

HOTFIX Released 2nd February 2024
New parameters added to OBSOUL reading.
Partial fix of bug that resulted in errors when extracting domain information from WRF output files - care should be taken when reading data from WRF files as this is not fully tested.

harpIO 0.2.1

HOTFIX Released 5th December 2023
This version includes some improvements for reading NetCDF files and bug fixes

Bug fixes

Fix a bug whereby read_point_obs() failed when not all accumulation periods are available in the SQLite file
Add “ws” to list of known parameters in parse_harp_parameter()

NetCDF improvements

When no projection string is available, get the projection information from CF compliant attributes
Get dimension names from variables. In general this means that dimension names no longer need to be set via netcdf_opts()

Documentation improvements

Vignette added to describing how to read point observations from .csv files
Extra note added to help users install the hsf5r package

harpIO 0.2.0

This version was released in November 2023
It includes many internal changes to make your experience smoother and includes more informative error messages.

Breaking changes

Arguments start_date, end_date, and by to read functions are deprecated and replaced by dttm, to be used together with seq_dttm() to generate a sequence of date-time strings. Note that you can still use the old arguments, but will be periodically warned to change.
New column names in outputs to read functions

Old name	New name
fcdate	fcst_dttm
validdate	valid_dttm
leadtime	lead_time

bind_fcst() is deprecated. bind() should be used instead.
get_filenames() is deprecated. generate_filenames() should be used instead.
msub() is deprecated. psub() should be used instead.
read_det_interpolate() and read_eps_interpolate() are defunct. read_forecast(..., transformation = "interpolate") should be used instead.
read_obs_convert() is defunct. read_obs(..., transformation = "...") should be used instead.

Selected new features

Parameters are defined via the internal data list harp_params. This list includes parameter name substitutions for different file formats and the possibility to apply a function to specific parameters at read time.
The parameter list can be added to or modified with add_param_def() and modify_param_def() respectively.
All data read in by harp read functions attain a class - the print method for each class tells you what type of dataset it is. One exception is for read_obs() and read_point_obs(), which both return basic tibbles (data frames).
use_grib_stepRange() is added as a helper to select grib messages via grib_opts(param_find = list(param = use_grib_stepRange(...))). This is useful for determining between accumulated and instantaneous variables with the same grib shortName. {lead_time} can be used to take the current lead time.

harpIO 0.0.9

This is the version that is basically unchanged since late 2021 / early 2022.
It was officially tagged v0.0.9 in November 2023

harpIO 0.0.0.9168

Update of grib and FA handling

This version of harp requires the newest version of meteogrid >= 3.8.5 to work. For reading grib files Rgrib2 >= 1.4.0 to work. It should be noted that Rgrib2 1.4.0 is not backwards compatible with older versions of harpIO.

harpIO 0.0.0.9160

Possible breaking changes

Default file name template changed for from paste0(“fctable_”, fcst_type) to “fctable” in read_point_forecast()
- For fcst_type = “eps” the default template was “fctable_eps”. This separated each lead time out into a separate file and was consistent with files output from read_eps_interpolate() and consisent with HARPv2. read_eps_interpolate() will soon be deprecated and we recommend using read_forecast() instead with output_file_opts = sqlite_opts(...) where the default template is “fctable”, which combines all lead times into a single file. read_point_forecast() is now consistent with read_forecast() in using “fctable” as the default template. To get the previous functionality you need to set file_template = "fctable_eps" in the call to read_point_forecast(). For deterministic data this change has no impact.