Package 'epwshiftr'

Description

Query, download climate change projection data from the CMIP6 (Coupled Model Intercomparison Project Phase 6) project in the ESGF (Earth System Grid Federation) platform, and create future EnergyPlus Weather (EPW) files adjusted from climate changes using data from Global Climate Models (GCM).

Package options

• epwshiftr.verbose: If TRUE, more detailed message will be printed. Default: FALSE.

• epwshiftr.threshold_alpha: the threshold of the absolute value for alpha, i.e. monthly-mean fractional change, when performing morphing operations. The default value is set to 3. If the morphing methods are set "stretch" or "combined", and the absolute alpha exceeds the threshold value, warnings are issued and the morphing method fallbacks to "shift" to avoid unrealistic morphed values.

• epwshiftr.dir: The directory to store package data, including CMIP6 model output file index and etc. If not set, the current user data directory will be used.

Author(s)

Hongyuan Jia

See Also

Useful links:

• https://github.com/ideas-lab-nus/epwshiftr

• Report bugs at https://github.com/ideas-lab-nus/epwshiftr/issues

Description

The Cmip6Dict object provides functionalities to fetch the latest CMIP6 Controlled Vocabularies (CVs) and Data Request (DReq) information.

Usage

cmip6_dict()

Details

The CMIP6 CVs gives a well-defined set of global attributes that are recorded in each CMIP6 model output, providing information necessary for interpreting the data. The data of CMIP6 CVs is stored as JSON files in the WCRP-CMIP GitHub Repo.

The CMIP6 DReq defines all the quantities from CMIP6 simulations that should be archived. This includes both quantities of general interest needed from most of the CMIP6-endorsed model intercomparison projects (MIPs) and quantities that are more specialized and only of interest to a single endorsed MIP. The raw data of DReq is stored a Microsoft Excel file (CMIP6_MIP_tables.xlsx) in a Subversion repo. The Cmip6Dict object uses the parsed DReq data that is stored in the GitHub Repo.

For more information, please see:

• CMIP6 Global Attributes, DRS, Filenames, Directory Structure, and CV's

• CMIP6 Data Request

Methods

Public methods

• Cmip6Dict$version()

• Cmip6Dict$is_empty()

• Cmip6Dict$timestamp()

• Cmip6Dict$built_time()

• Cmip6Dict$build()

• Cmip6Dict$get()

• Cmip6Dict$save()

• Cmip6Dict$load()

• Cmip6Dict$print()

Method version()

Get the version of CVs and Data Request

Usage

Cmip6Dict$version()

Returns

A list of two element:

• cvs: A numeric_version object giving the version of CVs

• dreq: A numeric_version object giving the version of Data Request

Method is_empty()

Is it an empty Cmip6Dict?

⁠$is_empty()⁠ checks if this Cmip6Dict is empty, i.e. the ⁠$build() ⁠ or ⁠$load()⁠ method hasn't been called yet and there is no data of CVs and Data Request.

Usage

Cmip6Dict$is_empty()

Returns

A single logical value of TRUE or FALSE.

Method timestamp()

Get the last modified time for CVs

Usage

Cmip6Dict$timestamp()

Returns

A list of 14 DateTimes:

• "cvs": The last modified time for the whole CV collection

• "drs": The last modified time for Data Reference Syntax (DRS)

• "activity_id": The last modified time for Activity ID

• "experiment_id": The last modified time for Experiment ID

• "frequency": The last modified time for Frequency

• "grid_label": The last modified time for Grid Label

• "institution_id": The last modified time for Institution ID

• "nominal_resolution": The last modified time for Nominal Resolution

• "realm": The last modified time for Realm

• "required_global_attributes": The last modified time for Required Global Attributes

• "source_id": The last modified time for Source ID

• "source_type": The last modified time for Source Type

• "sub_experiment_id": The last modified time for Sub-Experiment ID

• "table_id": The last modified time for Table ID

Method built_time()

Get the time when the dictionary was built

Usage

Cmip6Dict$built_time()

Returns

A DateTime

Method build()

Fetch and parse all data of CVs and Data Request

Usage

Cmip6Dict$build(token = NULL, force = FALSE)

Arguments

Returns

The updated Cmip6Dict itself.

Method get()

Get the data for a specific CV or Data Request

Usage

Cmip6Dict$get(type)

Arguments

Returns

For "drs", "activity_id"⁠, ⁠"frequency"⁠, ⁠"grid_label"⁠, ⁠"institution_id"⁠, ⁠"source_type"and"sub_experiment_id"', a list.

For "experiment_id", "source_id" and "dreq", a data.table.

For "nominal_resolution", "required_global_attributes" and "table_id", a character vector.

Method save()

Save the Cmip6Dict object

⁠$save()⁠ stores all the core data of current Cmip6Dict object into an RDS file named CMIP6DICT in the specified folder. This file can be reloaded via ⁠$load()⁠ method to restore the last state of current Cmip6Dict object.

Usage

Cmip6Dict$save(dir = getOption("epwshiftr.dir", "."))

Arguments

Returns

A single string giving the full path of the RDS file.

Method load()

Load the saved Cmip6Dict object from file

⁠$load()⁠ loads the RDS file named CMIP6DICT that is created using ⁠$save()⁠ method.

Please note that the file should be exactly the same as CMIP6DICT without file extension.

Usage

Cmip6Dict$load(dir = getOption("epwshiftr.dir", "."))

Arguments

Returns

A single string giving the full path of the RDS file.

Method print()

Print a summary of the current Cmip6Dict object

⁠$print()⁠ gives the summary of current Cmip6Dict object including the version of CVs and Data Request, and the last built time.

Usage

Cmip6Dict$print()

Returns

The Cmip6Dict object itself, invisibly.

Author(s)

Hongyuan Jia

Examples

## Not run: 

# create a new Cmip6Dict object
dict <- cmip6_dict()

# by default, there is no data when the Cmip6Dict was created
dict$is_empty()

# fetch and parse all CVs and Data Request data
dict$build()

# get the version of CVs nand Data Request
dict$version()

# get the last modified time for each CV and Data Request
dict$timestamp()

# get the time when the dict was built
dict$built_time()

# get the data of CVs and DReq
dict$get("activity_id")
dict$get("experiment_id")
dict$get("sub_experiment_id")
dict$get("institution_id")
dict$get("source_id")
dict$get("table_id")
dict$get("frequency")
dict$get("grid_label")
dict$get("realm")
dict$get("source_type")
dict$get("dreq")

# save the dict object for later usage
# default location is the value of global option "epwshiftr.dir"
dict$save()

# the saved dict object can be reloaded
new_dict <- cmip6_dict()
new_dict$load()

# print will show the version summary and the last built time
dict$print()

## End(Not run)

Description

Query CMIP6 data using ESGF search RESTful API

Usage

esgf_query(
  activity = "ScenarioMIP",
  variable = c("tas", "tasmax", "tasmin", "hurs", "hursmax", "hursmin", "pr", "rsds",
    "rlds", "psl", "sfcWind", "clt"),
  frequency = "day",
  experiment = c("ssp126", "ssp245", "ssp370", "ssp585"),
  source = c("AWI-CM-1-1-MR", "BCC-CSM2-MR", "CESM2", "CESM2-WACCM", "EC-Earth3",
    "EC-Earth3-Veg", "GFDL-ESM4", "INM-CM4-8", "INM-CM5-0", "MPI-ESM1-2-HR",
    "MRI-ESM2-0"),
  variant = "r1i1p1f1",
  replica = FALSE,
  latest = TRUE,
  resolution = c("100 km", "50 km"),
  type = "Dataset",
  limit = 10000L,
  data_node = NULL
)

Arguments

Details

The Earth System Grid Federation (ESGF) is an international collaboration for the software that powers most global climate change research, notably assessments by the Intergovernmental Panel on Climate Change (IPCC).

The ESGF search service exposes a RESTful URL that can be used by clients to query the contents of the underlying search index, and return results matching the given constraints. With the distributed capabilities of the ESGF search, the URL at any Index Node can be used to query that Node only, or all Nodes in the ESGF system. esgf_query() uses the LLNL (Lawrence Livermore National Laboratory) Index Node.

The core Controlled Vocabularies (CVs) for use in CMIP6, including all activities, experiment, sources (GCMs), frequencies can be found at the WCRP-CMIP/CMIP6_CVs GitHub repo.

Value

A data.table::data.table with an attribute named response which is a list converted from json response. If no matched data is found, an empty data.table is returned. Otherwise, the columns of returned data varies based on the type:

• If "Dataset", returned columns are:

  No.	Column	Type	Description
  1	dataset_id	Character	Dataset universal identifier
  2	mip_era	Character	Activity's associated CMIP cycle. Will always be "CMIP6"
  3	activity_drs	Character	Activity DRS (Data Reference Syntax)
  4	institution_id	Character	Institution identifier
  5	source_id	Character	Model identifier
  6	experiment_id	Character	Root experiment identifier
  7	member_id	Character	A compound construction from sub_experiment_id and variant_label
  8	table_id	Character	Table identifier, i.e. sampling frequency identifier
  9	frequency	Character	Sampling frequency
  10	grid_label	Character	Grid identifier
  11	version	Character	Approximate date of model output file
  12	nominal_resolution	Character	Approximate horizontal resolution
  13	variable_id	Character	Variable identifier
  14	variable_long_name	Character	Variable long name
  15	variable_units	Character	Units of variable
  16	data_node	Character	Data node to download the model output file
  17	dataset_pid	Character	A unique string that helps identify the dataset

• If "File", returned columns are:

  No.	Column	Type	Description
  1	file_id	Character	Model output file universal identifier
  2	dataset_id	Character	Dataset universal identifier
  3	mip_era	Character	Activity's associated CMIP cycle. Will always be "CMIP6"
  4	activity_drs	Character	Activity DRS (Data Reference Syntax)
  5	institution_id	Character	Institution identifier
  6	source_id	Character	Model identifier
  7	experiment_id	Character	Root experiment identifier
  8	member_id	Character	A compound construction from sub_experiment_id and variant_label
  9	table_id	Character	Table identifier, i.e. sampling frequency identifier
  10	frequency	Character	Sampling frequency
  11	grid_label	Character	Grid identifier
  12	version	Character	Approximate date of model output file
  13	nominal_resolution	Character	Approximate horizontal resolution
  14	variable_id	Character	Variable identifier
  15	variable_long_name	Character	Variable long name
  16	variable_units	Character	Units of variable
  17	datetime_start	POSIXct	Start date and time of simulation
  18	datetime_end	POSIXct	End date and time of simulation
  19	file_size	Character	Model output file size in Bytes
  20	data_node	Character	Data node to download the model output file
  21	file_url	Character	Model output file download url from HTTP server
  22	tracking_id	Character	A unique string that helps identify the output file

References

https://github.com/ESGF/esgf.github.io/wiki/ESGF_Search_REST_API

Examples

## Not run: 
esgf_query(variable = "rss", experiment = "ssp126", resolution = "100 km", limit = 1)

esgf_query(variable = "rss", experiment = "ssp126", type = "File", limit = 1)

## End(Not run)

Description

The Earth System Grid Federation (ESGF) is an international collaboration for the software that powers most global climate change research, notably assessments by the Intergovernmental Panel on Climate Change (IPCC).

The ESGF search service exposes RESTful APIs that can be used by clients to query the contents of the underlying search index, and return results matching the given constraints. The documentation of the APIs can be found using this link

EsgfQuery is the workhorse for dealing with ESGF search services.

Usage

query_esgf(host = "https://esgf-node.llnl.gov/esg-search")

Arguments

EsgfQuery object

query_esgf() returns an EsgfQuery object, which is an R6 object with quite a few methods that can be classified into 3 categories:

• Value listing: methods to list all possible values of facets, shards, etc.

• Parameter getter & setter: methods to get the query parameter values or set them before sending the actual query to the ESGF search services.

• Query responses: methods to collect results for the query response.

Value listing

When creating an EsgfQuery object, a facet listing query is sent to the index node to get all available facets and shards for the default project (CMIP6). EsgfQuery object provides three value-listing methods to extract data from the response of the facet listing query:

• EsgfQuery$list_all_facets(): List all available facet names.

• EsgfQuery$list_all_shards(): List all available shards.

• EsgfQuery$list_all_values(): List all available values of a specific facet.

Parameter getter & setter

The ESGF search services support a lot of parameters. The EsgfQuery contains dedicated methods to set values for most of them, including:

• Most common keywords: facets, offset, limit, fields, type, replica, latest, distrib and shards.

• Most common facets: project, activity_id, experiment_id, source_id, variable_id, frequency, variant_label, nominal_resolution and data_node.

All methods act in a similar way:

• If input is given, the corresponding parameter is set and the updated EsgfQuery object is returned.

  • This makes it possible to chain different parameter setters, e.g. EsgfQuery$project("CMIP6")$frequency("day")$limit(1) sets the parameter project, frequency and limit sequentially.

  • For parameters that want character inputs, you can put a preceding ! to negate the constraints, e.g. EsgfQuery$project(!"CMIP6") searches for all projects except for CMIP6.

• If no input is given, the current parameter value is returned. For example, directly calling EsgfQuery$project() returns the current value of the project parameter. The returned value can be two types:

  • NULL, i.e. there is no constraint on the corresponding parameter

  • An EsgfQueryParam object which is essentially a list of three elements:

    • value: The input values

    • negate: Whether there is a preceding ! in the input

    • name: The parameter name

Despite methods for specific keywords and facets, you can specify arbitrary query parameters using EsgfQuery$params() method. For details on the usage, please see the documentation.

Query responses

The query is not sent unless related methods are called:

• EsgfQuery$count(): Count the total number of records that match the query.

  • You can return only the total number of matched record by calling EsgfQuery$count(facets = FALSE)

  • You can also count the matched records for specified facets, e.g. EsgfQuery$count(facets = c("source_id", "activity_id"))

• EsgfQuery$collect(): Collect the query results and format it into a data.table

Other helpers

EsgfQuery object also provide several other helper functions:

• EsgfQuery$build_cache(): By default, EsgfQuery$build_cache() is called when initialize a new EsgfQuery object. So in general, there is no need to call this separately. Basically, EsgfQuery$build_cahce() sends a facet listing query to the index node and stores the response internally. The response contains all available facets and shards and is used as a source for validating user input for parameter setters.

• EsgfQuery$url(): Returns the actual query URL or the wget script URL which can be used to download all files matching the given constraints..

• EsgfQuery$response(): Returns the actual response of EsgfQuery$count() and EsgfQuery$collect(). It is a named list generated from the JSON response using jsonlite::fromJSON().

• EsgfQuery$print(): Print a summary of the current EsgfQuery object including the host URL, the built time of facet cache and all query parameters.

Methods

Public methods

• EsgfQuery$new()

• EsgfQuery$build_cache()

• EsgfQuery$list_all_facets()

• EsgfQuery$list_all_shards()

• EsgfQuery$list_all_values()

• EsgfQuery$project()

• EsgfQuery$activity_id()

• EsgfQuery$experiment_id()

• EsgfQuery$source_id()

• EsgfQuery$variable_id()

• EsgfQuery$frequency()

• EsgfQuery$variant_label()

• EsgfQuery$nominal_resolution()

• EsgfQuery$data_node()

• EsgfQuery$facets()

• EsgfQuery$fields()

• EsgfQuery$shards()

• EsgfQuery$replica()

• EsgfQuery$latest()

• EsgfQuery$type()

• EsgfQuery$limit()

• EsgfQuery$offset()

• EsgfQuery$distrib()

• EsgfQuery$params()

• EsgfQuery$url()

• EsgfQuery$count()

• EsgfQuery$collect()

• EsgfQuery$response()

• EsgfQuery$print()

Method new()

Create a new EsgfQuery object

When initialization, a facet listing query is sent to the index node to get all available facets and shards. This information will be used to validate inputs for activity_id, scource_id facets and etc.

Usage

EsgfQuery$new(host = "https://esgf-node.llnl.gov/esg-search")

Arguments

Returns

An EsgfQuery object.

Examples

\dontrun{
q <- EsgfQuery$new(host = "https://esgf-node.llnl.gov/esg-search")
q
}

Method build_cache()

Build facet cache used for input validation

A facet cache is data that is fetched using a facet listing query to the index node. It contains all available facets and shards that can be used as parameter values within a specific project.

By default, ⁠$build_cache()⁠ is called when initialize a new EsgfQuery object for the default project (CMIP6). So in general, there is no need to call this method, unless that you want to rebuild the cache again with different projects after calling $project().

Usage

EsgfQuery$build_cache()

Returns

The modified EsgfQuery object.

Examples

\dontrun{
q$build_cache()
}

Method list_all_facets()

List all available facet names

Usage

EsgfQuery$list_all_facets()

Returns

A character vector.

Examples

\dontrun{
q$list_all_facets()
}

Method list_all_shards()

List all available shards

Usage

EsgfQuery$list_all_shards()

Returns

A character vector.

Examples

\dontrun{
q$list_all_shards()
}

Method list_all_values()

List all available values of a specific facet

Usage

EsgfQuery$list_all_values(facet)

Arguments

Returns

A named character vector.

Examples

\dontrun{
q$list_all_values()
}

Method project()

Get or set the project facet parameter.

Usage

EsgfQuery$project(value = "CMIP6")

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$project()

# set the parameter
q$project("CMIP6")

# negate the project constraints
q$project(!"CMIP6")

# remove the parameter
q$project(NULL)
}

Method activity_id()

Get or set the activity_id facet parameter.

Usage

EsgfQuery$activity_id(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$activity_id()

# set the parameter
q$activity_id("ScenarioMIP")

# negate the constraints
q$activity_id(!c("CFMIP", "ScenarioMIP"))

# remove the parameter
q$activity_id(NULL)
}

Method experiment_id()

Get or set the experiment_id facet parameter.

Usage

EsgfQuery$experiment_id(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$experiment_id()

# set the parameter
q$experiment_id(c("ssp126", "ssp585"))

# negate the constraints
q$experiment_id(!c("ssp126", "ssp585"))

# remove the parameter
q$experiment_id(NULL)
}

Method source_id()

Get or set the source_id facet parameter.

Usage

EsgfQuery$source_id(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$source_id()

# set the parameter
q$source_id(c("BCC-CSM2-MR", "CESM2"))

# negate the constraints
q$source_id(!c("BCC-CSM2-MR", "CESM2"))

# remove the parameter
q$source_id(NULL)
}

Method variable_id()

Get or set the variable_id facet parameter.

Usage

EsgfQuery$variable_id(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$variable_id()

# set the parameter
q$variable_id(c("tas", "pr"))

# negate the constraints
q$variable_id(!c("tas", "pr"))

# remove the parameter
q$variable_id(NULL)
}

Method frequency()

Get or set the frequency facet parameter.

Usage

EsgfQuery$frequency(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$frequency()

# set the parameter
q$frequency(c("1hr", "day"))

# negate the constraints
q$frequency(!c("1hr", "day"))

# remove the parameter
q$frequency(NULL)
}

Method variant_label()

Get or set the variant_label facet parameter.

Usage

EsgfQuery$variant_label(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$variant_label()

# set the parameter
q$variant_label(c("r1i1p1f1", "r1i2p1f1"))

# negate the constraints
q$variant_label(!c("r1i1p1f1", "r1i2p1f1"))

# remove the parameter
q$variant_label(NULL)
}

Method nominal_resolution()

Get or set the nominal_resolution facet parameter.

Usage

EsgfQuery$nominal_resolution(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$nominal_resolution()

# set the parameter
q$nominal_resolution(c("100 km", "1x1 degree"))

# negate the constraints
q$nominal_resolution(!c("100 km", "1x1 degree"))

# remove the parameter
q$nominal_resolution(NULL)
}

Method data_node()

Get or set the data_node parameter.

Usage

EsgfQuery$data_node(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$data_node()

# set the parameter
q$data_node("esg.lasg.ac.cn")

# negate the constraints
q$data_node(!"esg.lasg.ac.cn")

# remove the parameter
q$data_node(NULL)
}

Method facets()

Get or set the facets parameter for facet counting query.

Note that ⁠$facets()⁠ only affects $count() method when sending a query of facet counting.

Usage

EsgfQuery$facets(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$facets()

# set the facets
q$facets(c("activity_id", "source_id"))

# use all available facets
q$facets("*")
}

Method fields()

Get or set the fields parameter.

By default, all available metadata fields are returned for each query. ⁠$facets()⁠ can be used to limit the number of fields returned in the query response.

Usage

EsgfQuery$fields(value = "*")

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$fields()

# set the fields
q$fields(c("activity_id", "source_id"))

# use all available fields
q$fields("*")

# remove the parameter
# act the same as above because the default `fields` in ESGF search
# services is `*` if `fields` is not specified
q$fields(NULL)
}

Method shards()

Get or set the shards parameter.

By default, a distributed query targets all ESGF Nodes. ⁠$shards()⁠ can be used to execute a distributed search that targets only one or more specific nodes.

All available shards can be retrieved using $list_all_shards() method.

Usage

EsgfQuery$shards(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$shards()

# set the parameter
q$shards("localhost:8983/solr/datasets")

# negate the constraints
q$shards(!"localhost:8983/solr/datasets")

# only applicable for distributed queries
q$distrib(FALSE)$shards("localhost:8983/solr/datasets") # Error

# remove the parameter
q$shards(NULL)
}

Method replica()

Get or set the replica parameter.

By default, a query returns all records (masters and replicas) matching the search criteria, i.e. ⁠$replica(NULL)⁠. To return only master records, use ⁠$replica(FALSE)⁠; to return only replicas, use ⁠$replica(TRUE)⁠.

Usage

EsgfQuery$replica(value)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$replica()

# set the parameter
q$replica(TRUE)

# remove the parameter
q$replica(NULL)
}

Method latest()

Get or set the latest parameter.

By default, a query to the ESGF search services returns only the very last, up-to-date version of the matching records, i.e. ⁠$latest(TRUE)⁠. You can use ⁠$latest(FALSE)⁠ to return all versions.

Usage

EsgfQuery$latest(value = TRUE)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$latest()

# set the parameter
q$latest(TRUE)
}

Method type()

Get or set the type parameter.

There are three types in total: Dataset, File or Aggregation.

Usage

EsgfQuery$type(value = "Dataset")

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$type()

# set the parameter
q$type("Dataset")
}

Method limit()

Get or set the limit parameter.

⁠$limit()⁠ can be used to limit the number of records to return. Note that the maximum number of records to return per query for ESGF search services is 10,000. A warning is issued if input value is greater than that. In this case, limit will be reset to 10,000.

Usage

EsgfQuery$limit(value = 10L)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$limit()

# set the parameter
q$limit(10L)

# `limit` is reset to 10,000 if input is greater than that
q$limit(10000L) # warning
}

Method offset()

Get or set the offset parameter.

If the query returns records that exceed the limit number, ⁠$offset()⁠ can be used to paginate through the available results.

Usage

EsgfQuery$offset(value = 0L)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$offset()

# set the parameter
q$offset(0L)
}

Method distrib()

Get or set the distrib facet

By default, the query is sent to all ESGF Nodes, i.e. ⁠$distrib(TRUE)⁠. ⁠$distrib(FALSE)⁠ can be used to execute the query only on the target node.

Usage

EsgfQuery$distrib(value = TRUE)

Arguments

Returns

• If value is given, the modified EsgfQuery object.

• Otherwise, an EsgfQueryParam object which is essentially a list of three elements:

  • value: input values.

  • negate: Whether there is a preceding !.

  • name: Parameter name.

Examples

\dontrun{
# get current value
q$distrib()

# set the parameter
q$distrib(TRUE)
}

Method params()

Get or set other parameters.

⁠$params()⁠ can be used to specify other parameters that do not have a dedicated method, e.g. version, master_id, etc. It can also be used to overwrite existing parameter values specified using methods like $activity_id().

Usage

EsgfQuery$params(...)

Arguments

Returns

• If parameters are specified, the modified EsgfQuery object, invisibly.

• Otherwise, an empty list for ⁠$params(NULL)⁠ or a list of EsgfQueryParam objects.

Examples

\dontrun{
# get current values
# default is an empty list (`list()`)
q$params()

# set the parameter
q$params(table_id = c("3hr", "day"), member_id = "00")
q$params()

# reset existing parameters
q$frequency("day")
q$params(frequency = "mon")
q$frequency() # frequency value has been changed using $params()

# negating the constraints is also supported
q$params(table_id = !c("3hr", "day"))

# use NULL to remove all parameters
q$params(NULL)$params()
}

Method url()

Get the URL of actual query or wget script

Usage

EsgfQuery$url(wget = FALSE)

Arguments

Returns

A single string.

Examples

\dontrun{
q$url()

# get the wget script URL
q$url(wget = TRUE)

# You can download the wget script using the URL directly. For
# example, the code below downloads the script and save it as
# 'wget.sh' in R's temporary folder:
download.file(q$url(TRUE), file.path(tempdir(), "wget.sh"), mode = "wb")

}

Method count()

Send a query of facet counting and fetch the results

Usage

EsgfQuery$count(facets = TRUE)

Arguments

Returns

• If facets equals NULL or FALSE, or ⁠$facets()⁠ returns NULL, an integer.

• Otherwise, a named list with the first element always being total which is the total number of matched records. Other elements have the same length as input facets and are all named integer vectors.

Examples

\dontrun{
# get the total number of matched records
q$count(NULL) # or q$count(facets = FALSE)

# count records for specific facets
q$facets(c("activity_id", "source_id"))$count()

# same as above
q$count(facets = c("activity_id", "source_id"))
}

Method collect()

Send the actual query and fetch the results

⁠$collect()⁠ sends the actual query to the ESGF search services and returns the results in a data.table::data.table. The columns depend on the value of query type and fields parameter.

Usage

EsgfQuery$collect()

Returns

A data.table.

Examples

\dontrun{
q$fields("source_id")
q$collect()
}

Method response()

Get the response of last sent query

The response of the last sent query is always stored internally and can be retrieved using ⁠$response()⁠. It is a named list generated from the JSON response using jsonlite::fromJSON().

Usage

EsgfQuery$response()

Returns

A named list.

Examples

\dontrun{
q$response()
}

Method print()

Print a summary of the current EsgfQuery object

⁠$print()⁠ gives the summary of current EsgfQuery object including the host URL, the built time of facet cache and all query parameters.

Usage

EsgfQuery$print()

Returns

The EsgfQuery object itself, invisibly.

Examples

\dontrun{
q$print()
}

Author(s)

Hongyuan Jia

Examples

## ------------------------------------------------
## Method `EsgfQuery$new`
## ------------------------------------------------

## Not run: 
q <- EsgfQuery$new(host = "https://esgf-node.llnl.gov/esg-search")
q

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$build_cache`
## ------------------------------------------------

## Not run: 
q$build_cache()

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$list_all_facets`
## ------------------------------------------------

## Not run: 
q$list_all_facets()

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$list_all_shards`
## ------------------------------------------------

## Not run: 
q$list_all_shards()

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$list_all_values`
## ------------------------------------------------

## Not run: 
q$list_all_values()

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$project`
## ------------------------------------------------

## Not run: 
# get current value
q$project()

# set the parameter
q$project("CMIP6")

# negate the project constraints
q$project(!"CMIP6")

# remove the parameter
q$project(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$activity_id`
## ------------------------------------------------

## Not run: 
# get current value
q$activity_id()

# set the parameter
q$activity_id("ScenarioMIP")

# negate the constraints
q$activity_id(!c("CFMIP", "ScenarioMIP"))

# remove the parameter
q$activity_id(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$experiment_id`
## ------------------------------------------------

## Not run: 
# get current value
q$experiment_id()

# set the parameter
q$experiment_id(c("ssp126", "ssp585"))

# negate the constraints
q$experiment_id(!c("ssp126", "ssp585"))

# remove the parameter
q$experiment_id(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$source_id`
## ------------------------------------------------

## Not run: 
# get current value
q$source_id()

# set the parameter
q$source_id(c("BCC-CSM2-MR", "CESM2"))

# negate the constraints
q$source_id(!c("BCC-CSM2-MR", "CESM2"))

# remove the parameter
q$source_id(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$variable_id`
## ------------------------------------------------

## Not run: 
# get current value
q$variable_id()

# set the parameter
q$variable_id(c("tas", "pr"))

# negate the constraints
q$variable_id(!c("tas", "pr"))

# remove the parameter
q$variable_id(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$frequency`
## ------------------------------------------------

## Not run: 
# get current value
q$frequency()

# set the parameter
q$frequency(c("1hr", "day"))

# negate the constraints
q$frequency(!c("1hr", "day"))

# remove the parameter
q$frequency(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$variant_label`
## ------------------------------------------------

## Not run: 
# get current value
q$variant_label()

# set the parameter
q$variant_label(c("r1i1p1f1", "r1i2p1f1"))

# negate the constraints
q$variant_label(!c("r1i1p1f1", "r1i2p1f1"))

# remove the parameter
q$variant_label(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$nominal_resolution`
## ------------------------------------------------

## Not run: 
# get current value
q$nominal_resolution()

# set the parameter
q$nominal_resolution(c("100 km", "1x1 degree"))

# negate the constraints
q$nominal_resolution(!c("100 km", "1x1 degree"))

# remove the parameter
q$nominal_resolution(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$data_node`
## ------------------------------------------------

## Not run: 
# get current value
q$data_node()

# set the parameter
q$data_node("esg.lasg.ac.cn")

# negate the constraints
q$data_node(!"esg.lasg.ac.cn")

# remove the parameter
q$data_node(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$facets`
## ------------------------------------------------

## Not run: 
# get current value
q$facets()

# set the facets
q$facets(c("activity_id", "source_id"))

# use all available facets
q$facets("*")

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$fields`
## ------------------------------------------------

## Not run: 
# get current value
q$fields()

# set the fields
q$fields(c("activity_id", "source_id"))

# use all available fields
q$fields("*")

# remove the parameter
# act the same as above because the default `fields` in ESGF search
# services is `*` if `fields` is not specified
q$fields(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$shards`
## ------------------------------------------------

## Not run: 
# get current value
q$shards()

# set the parameter
q$shards("localhost:8983/solr/datasets")

# negate the constraints
q$shards(!"localhost:8983/solr/datasets")

# only applicable for distributed queries
q$distrib(FALSE)$shards("localhost:8983/solr/datasets") # Error

# remove the parameter
q$shards(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$replica`
## ------------------------------------------------

## Not run: 
# get current value
q$replica()

# set the parameter
q$replica(TRUE)

# remove the parameter
q$replica(NULL)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$latest`
## ------------------------------------------------

## Not run: 
# get current value
q$latest()

# set the parameter
q$latest(TRUE)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$type`
## ------------------------------------------------

## Not run: 
# get current value
q$type()

# set the parameter
q$type("Dataset")

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$limit`
## ------------------------------------------------

## Not run: 
# get current value
q$limit()

# set the parameter
q$limit(10L)

# `limit` is reset to 10,000 if input is greater than that
q$limit(10000L) # warning

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$offset`
## ------------------------------------------------

## Not run: 
# get current value
q$offset()

# set the parameter
q$offset(0L)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$distrib`
## ------------------------------------------------

## Not run: 
# get current value
q$distrib()

# set the parameter
q$distrib(TRUE)

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$params`
## ------------------------------------------------

## Not run: 
# get current values
# default is an empty list (`list()`)
q$params()

# set the parameter
q$params(table_id = c("3hr", "day"), member_id = "00")
q$params()

# reset existing parameters
q$frequency("day")
q$params(frequency = "mon")
q$frequency() # frequency value has been changed using $params()

# negating the constraints is also supported
q$params(table_id = !c("3hr", "day"))

# use NULL to remove all parameters
q$params(NULL)$params()

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$url`
## ------------------------------------------------

## Not run: 
q$url()

# get the wget script URL
q$url(wget = TRUE)

# You can download the wget script using the URL directly. For
# example, the code below downloads the script and save it as
# 'wget.sh' in R's temporary folder:
download.file(q$url(TRUE), file.path(tempdir(), "wget.sh"), mode = "wb")


## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$count`
## ------------------------------------------------

## Not run: 
# get the total number of matched records
q$count(NULL) # or q$count(facets = FALSE)

# count records for specific facets
q$facets(c("activity_id", "source_id"))$count()

# same as above
q$count(facets = c("activity_id", "source_id"))

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$collect`
## ------------------------------------------------

## Not run: 
q$fields("source_id")
q$collect()

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$response`
## ------------------------------------------------

## Not run: 
q$response()

## End(Not run)

## ------------------------------------------------
## Method `EsgfQuery$print`
## ------------------------------------------------

## Not run: 
q$print()

## End(Not run)

Description

extract_data() takes an epw_cmip6_coord object generated using match_coord() and extracts CMIP6 data using the coordinates and years of interest specified.

Usage

extract_data(
  coord,
  years = NULL,
  unit = FALSE,
  out_dir = NULL,
  by = NULL,
  keep = is.null(out_dir),
  compress = 100
)

Arguments

Details

extract_data() supports common calendars, including ⁠365_day⁠ and ⁠360_day⁠, thanks to the PCICt package.

extract_data() uses future.apply underneath. You can use your preferable future backend to speed up data extraction in parallel. By default, extract_data() uses future::sequential backend, which runs things in sequential.

Value

An epw_cmip6_data object, which is basically a list of 3 elements:

• epw: An eplusr::Epw object whose longitude and latitude are used to extract CMIP6 data. It is the same object as created in match_coord()

• meta: A list containing basic metadata of input EPW, including city, state_province, country, latitude and longitude.

• data: An empty data.table::data.table() if keep is FALSE or a data.table::data.table() of 14 columns if keep is TRUE:

  No.	Column	Type	Description
  1	activity_drs	Character	Activity DRS (Data Reference Syntax)
  2	institution_id	Character	Institution identifier
  3	source_id	Character	Model identifier
  4	experiment_id	Character	Root experiment identifier
  5	member_id	Character	A compound construction from sub_experiment_id and variant_label
  6	table_id	Character	Table identifier
  7	lon	Double	Longitude of extracted location
  8	lat	Double	Latitude of extracted location
  9	dist	Double	The spherical distance in km between EPW location and grid coordinates
  10	datetime	POSIXct	Datetime for the predicted value
  11	variable	Character	Variable identifier
  12	description	Character	Variable long name
  13	units	Character	Units of variable
  14	value	Double	The actual predicted value

Examples

## Not run: 
coord <- match_coord("path_to_an_EPW")
extract_data(coord, years = 2030:2060)

## End(Not run)

Description

Create future EPW files using morphed data

Usage

future_epw(
  morphed,
  by = c("experiment", "source", "interval"),
  dir = ".",
  separate = TRUE,
  overwrite = FALSE,
  full = FALSE
)

Arguments

Value

If full is FALSE, which is the default, a list of generated eplusr::Epw objects, invisibly. Otherwise, a data.table with columns:

• specified by the by value

• epw: a list of eplusr::Epw

• path: full paths of the generated EPW files

Description

If option epwshiftr.dir is set, use it. Otherwise, get package data storage directory using rappdirs::user_data_dir().

Usage

get_data_dir()

Value

A single string.

Examples

options(epwshiftr.dir = tempdir())
get_data_dir()

Description

Get data nodes which store CMIP6 output

Usage

get_data_node(speed_test = FALSE, timeout = 3)

Arguments

Value

A data.table::data.table() of 2 or 3 (when speed_test is TRUE) columns:

Examples

## Not run: 
get_data_node()

## End(Not run)

Description

init_cmip6_index() will search the CMIP6 model output file using esgf_query() , return a data.table::data.table() containing the actual NetCDF file url to download, and store it into user data directory for future use.

Usage

init_cmip6_index(
  activity = "ScenarioMIP",
  variable = c("tas", "tasmax", "tasmin", "hurs", "hursmax", "hursmin", "pr", "rsds",
    "rlds", "psl", "sfcWind", "clt"),
  frequency = "day",
  experiment = c("ssp126", "ssp245", "ssp370", "ssp585"),
  source = c("AWI-CM-1-1-MR", "BCC-CSM2-MR", "CESM2", "CESM2-WACCM", "EC-Earth3",
    "EC-Earth3-Veg", "GFDL-ESM4", "INM-CM4-8", "INM-CM5-0", "MPI-ESM1-2-HR",
    "MRI-ESM2-0"),
  variant = "r1i1p1f1",
  replica = FALSE,
  latest = TRUE,
  resolution = c("100 km", "50 km"),
  limit = 10000L,
  data_node = NULL,
  years = NULL,
  save = FALSE
)

Arguments

Details

For details on where the file index is stored, see rappdirs::user_data_dir().

Value

A data.table::data.table with 22 columns:

Note

Argument limit will only apply to Dataset query. init_cmip6_index() will try to get all model output files which match the dataset id.

Examples

## Not run: 
init_cmip6_index()

## End(Not run)

Description

Load previously stored CMIP6 experiment output file index

Usage

load_cmip6_index(force = FALSE)

Arguments

Value

A data.table::data.table with 20 columns. For detail description on column, see init_cmip6_index().

Examples

## Not run: 
load_cmip6_index()

## End(Not run)

Description

match_coord() takes an EPW and uses its longitude and latitude to calculate the distance between the EPW location and the global grid points in NetCDF files.

Usage

match_coord(epw, threshold = list(lon = 1, lat = 1), max_num = NULL)

Arguments

Details

match_coord() uses future.apply underneath. You can use your preferable future backend to speed up data extraction in parallel. By default, match_coord() uses future::sequential backend, which runs things in sequential.

Value

An epw_cmip6_coord object, which is basically a list of 3 elements:

• epw: An eplusr::Epw object parsed from input epw argument

• meta: A list containing basic meta data of input EPW, including city, state_province, country, latitute and longitude.

• coord: A data.table::data.table() which is basically CMIP6 index database with an appending new list column coord that contains matched latitudes and longitudes in each NetCDF file. Each element in coord is a data.table::data.table() of 6 columns describing the matched coordinates.

  • index: the indices of matched coordinates

  • ind_lon, ind_lat: The value indices of longitude or latitude in the NetCDF coordinate grids. These values are used to extract the corresponding variable values

  • lon, lat: the actual longitude or latitude in the NetCDF coordinate grids

  • dist: the distance in km between the coordinate values in NetCDF and input EPW

Geographical distance calculation

match_coord() calculates the geographical distances based formulas of spherical trigonometry:

$\Delta{X}=\cos(\phi_2)\cos(\lambda_2) - \cos(\phi_1)\cos(\lambda_1)$

$\Delta{Y}=\cos(\phi_2)\sin(\lambda_2) - \cos(\phi_1)\sin(\lambda_1)$

$\Delta{Z}=\sin(\phi_2) - \sin(\phi_1)$

$C_h=\sqrt{(\Delta{X})^2 + (\Delta{Y})^2 + (\Delta{Z})^2}$

where $phi$ is the latitude and $lambda$ is the longitude. This formula treats the Earth as a sphere. The geographical distance between points on the surface of a spherical Earth is $D = RC_h$.

For more details, please see this Wikipedia

Examples

## Not run: 
# download an EPW from EnergyPlus website
epw <- eplusr::download_weather("los angeles.*TMY3", dir = tempdir(),
    type = "EPW", ask = FALSE)

match_coord(epw, threshold = list(lon = 1.0, lat = 1.0))

## End(Not run)

Description

morphing_epw() takes an epw_cmip6_data object generated using extract_data() and calculates future core EPW weather variables using Morphing Method.

Usage

morphing_epw(
  data,
  years = NULL,
  labels = NULL,
  methods = NULL,
  warning = FALSE
)

Arguments

Details

The EPW weather variables that get morphed are listed in details.

Value

An epw_cmip6_morphed object, which is basically a list of 12 elements:

Each data.table::data.table() listed above contains 19 columns below or an empty data.table::data.table() if the corresponding variables cannot be found in the input epw_cmip6_data object.

The Morphing procedure

Here Morphing is an algorithm proposed by Belcher etc. 2005 used to morph the present-day observed weather files (here the EPWs) to produce future climate weather files. The EPW data is used as the 'baseline climate'.

The first step before morphing is to calculate the monthly means of climatological variables in the EPW file, denoted by $<x_0>_m$. The subscript '0' is to denote the present day weather record, and 'm' is to denote the month.

The morphing involves three generic operations, i.e. 1) a shift; 2) a linear stretch (scaling factor); and 3) a shift and a stretch:

$\textrm{Shift: } x = x_0 + \Delta x_m$

$\textrm{Stretch: }x = \alpha_m x_m$

$\textrm{Shift + Stretch: } x = x_0 + \Delta x_m + \alpha_m (x_0 - <x_0>_m)$

Shift

If using a shift, for each month, a shift $\Delta x_m$ is applied to $x_0$. $\Delta x_m$ is the absolute change in the monthly mean value of the variable for the month $m$, i.e. $\Delta x_m = <x_0>_m - <x>_m$. Here the monthly variance of the variable is unchanged.

Stretch

If using a stretch, for each month, a stretch $\alpha _m$ is applied to $x_0$, where $\alpha _m$ is the fractional change in the monthly-mean value of a variable, i.e. $\alpha _m = <x>_m / <x_0>_m$. In this case, the variance will be multiplied by to $\alpha^2_m$

Combined Shift and Stretch

When using a combined shift and stretch factor, both the mean and the variance will be switched off altogether.

For more details about morphing, please see (Belcher etc. 2005)

References

Belcher, S., Hacker, J., Powell, D., 2005. Constructing design weather data for future climates. Building Services Engineering Research and Technology 26, 49–61. https://doi.org/10.1191/0143624405bt112oa

Description

set_cmip6_index() takes a data.table::data.table() as input and set it as current index.

Usage

set_cmip6_index(index, save = FALSE)

Arguments

Details

set_cmip6_index() is useful when init_cmip6_index() may give you too much cases of which only some are of interest.

Value

A data.table::data.table().

Description

summary_database() scans the directory specified and returns a data.table() containing summary information about all the CMIP6 files available against the output file index loaded using load_cmip6_index().

Usage

summary_database(
  dir,
  by = c("activity", "experiment", "variant", "frequency", "variable", "source",
    "resolution"),
  mult = c("skip", "latest"),
  append = FALSE,
  miss = c("keep", "overwrite"),
  recursive = FALSE,
  update = FALSE,
  warning = TRUE
)

Arguments

Details

The database here can be any directory that stores the NetCDF files for CMIP6 GCMs. It can be also be the same as get_data_dir() where epwshiftr stores the output file index, if you want to save the output file index and output files in the same place.

summary_database() uses the tracking_id, datetime_start and datetime_end global attributes of each NetCDF file to match against the output file index. So the names of NetCDF files do not necessarily follow the CMIP6 file name encoding.

summary_database() will append 5 columns in the CMIP6 output file index:

• file_path: the full path of matched NetCDF file for every case.

summary_database() uses future.apply underneath to speed up the data processing if applicable. You can use your preferable future backend to speed up data extraction in parallel. By default, summary_database() uses future::sequential backend, which runs things in sequential.

Value

A data.table::data.table() containing corresponding grouping columns plus:

Also 2 extra data.table::data.table() are attached as attributes:

• not_found: A data.table::data.table() that contains metadata for those CMIP6 outputs that are listed in current CMIP6 output file index but the existing file paths are not valid now and cannot be found in current database.

• not_matched: A data.table::data.table() that contains metadata for those CMIP6 output files that are found in current database but not listed in current CMIP6 output file index.

For the meaning of grouping columns, see init_cmip6_index().

Examples

## Not run: 
summary_database()

summary_database(by = "experiment")

## End(Not run)