Timeseries¶

The Timeseries endpoints are used to generate time series data for the datasets available in Climate Engine.

There are three groups of Timeseries endpoints:

/timeseries/native - The native endpoints are used to generate ‘raw’ time series data over points/polygons/features for Climate Engine datasets.
/timeseries/interannual - The interannual endpoints are used to generate time series of yearly values of the dataset variable summarized over a season.
/timeseries/regression - The regression endpoints are used to perform regression analysis of the dataset variable summarized over a season.

NOTES:

- The ‘forecasts’ endpoints are only available for forecast datasets (i.e. CFS_GRIDMET and FRET).

/timeseries/native/points¶

Generates timeseries of values of the dataset variable and timeperiod between start_date and end_date at a point location.

Returns: json

Resource url example:

/timeseries/native/points?dataset=GRIDMET&variable=pr&start_date=2014-01-01&end_date=2014-02-01&coordinates=[[-119.96,39.57]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
start_date	yes			2019-01-01
end_date	yes			2019-12-31
coordinates	yes	List of point coordinates		[[-119.96,39.57]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/native/forecasts/points¶

Generates timeseries of forecast values of the dataset variable and timeperiod between start_date and end_date at a point location.

Returns: json

Resource url example:

/timeseries/native/forecasts/points?dataset=CFS_GRIDMET&variable=pr&start_day=day01&end_day=day28&coordinates=[[-119.96,39.57]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes		CFS_GRIDMET	CFS_GRIDMET
variable	yes	pet, pr, tmmn, tmmx		pr
model	yes	ens01 to en<xx> for individual models (see documentation), ens_min, ens_max, ens_mean, ens_median	ens_mean	ens_max
start_day	yes	day01 to day 28, start_day <= end_day	day01	day02
end_day	yes	day01 to day28, end_day >= start_day	day28	day15
coordinates	yes	List of point coordinates		[[-119.96,39.57]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/native/polygons¶

Generates timeseries of values of the dataset variable and timeperiod between start_date and end_date for a polygon.
The values are averaged over the pixels lying within the polygon.
Returns: json

Resource url example:

/timeseries/native/polygons?dataset=LANDSAT7_TOA&variable=NDVI&start_date=2014-01-01&end_date=2018-12-30&coordinates=[[[-121.61,38.78],[-121.52,38.78],[-121.52,38.83],[-121.61,38.83],[-121.61,38.78]]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
start_date	yes			2019-01-01
end_date	yes			2019-12-31
coordinates	yes	List of polygon coordinates		[[[-121.61,38.78], [-121.52,38.78],[-121.52,38.83],[-121.61,38.83],[-121.61,38.78]]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/native/forecasts/polygons¶

Generates timeseries of forecast values of the dataset variable and timeperiod between start_date and end_date for a polygon.
The values are averaged over the pixels lying within the polygon.
Returns: json

Resource url example:

/timeseries/native/forecasts/polygons?dataset=CFS_GRIDMET&variable=tmmx&start_day=day01&end_day=day28&coordinates=[[[-121.61,38.78],[-121.52,38.78],[-121.52,38.83],[-121.61,38.83],[-121.61,38.78]]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes		CFS_GRIDMET	CFS_GRIDMET
variable	yes	pet, pr, tmmn, tmmx		tmmx
model	yes	ens01 to en<xx> for individual models (see documentation), ens_min, ens_max, ens_mean, ens_median	ens_mean	ens_max
start_day	yes	day01 to day 28, start_day <= end_day	day01	day02
end_day	yes	day01 to day28, end_day >= start_day	day28	day15
coordinates	yes	List of polygon coordinates		[[[-121.61,38.78], [-121.52,38.78],[-121.52,38.83],[-121.61,38.83],[-121.61,38.78]]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/native/climate_engine_asset¶

Generates timeseries of values of the dataset variable and time period between start_date and end_date for the features of a Climate Engine feature collection asset.
The values are averaged over the pixels lying within each feature of the feature collection.
For a list of available assets see the Climate Engine Assets section.
Returns: json

Resource url example:

/timeseries/native/climate_engine_asset?dataset=LANDSAT7_TOA&variable=NDVI&start_date=2014-01-01&end_date=2018-12-30&region=counties&sub_choices= ["ME - Aroostook"]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
start_date	yes			2019-01-01
end_date	yes			2019-12-31
region	yes	Type of feature collection		states
filter_by	no	Attribute to filter by, e.g. name		Name
sub_choices	no	List of features to use in analysis, must be strings		[“New York”]
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/native/forecasts/climate_engine_asset¶

Generates timeseries of forecast values of the dataset variable and timeperiod between start_date and end_date for the features of a Climate Engine feature collection asset.
The values are averaged over the pixels lying within each feature of the feature collection.
For a list of available assets see the Climate Engine Assets section.
Returns: json

Resource url example:

/timeseries/native/forecasts/climate_engine_asset?dataset=CFS_GRIDMET&variable=tmmn&start_day=day01&end_day=day28&region=counties&sub_choices= ["ME - Aroostook"]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes		CFS_GRIDMET	CFS_GRIDMET
variable	yes	pet, pr, tmmn, tmmx		tmmn
model	yes	ens01 to en<xx> for individual models (see documentation), ens_min, ens_max, ens_mean, ens_median	ens_mean	ens_max
start_day	yes	day01 to day 28, start_day <= end_day	day01	day02
end_day	yes	day01 to day28, end_day >= start_day	day28	day15
region	yes	Type of feature collection		states
filter_by	no	Attribute to filter by, e.g. name		Name
sub_choices	no	List of features to use in analysis, must be strings		[“Maine”]
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/native/custom_asset¶

Generates timeseries of values of the dataset variable and timeperiod between start_date and end_date for the features of a custom feature collection asset.
The values are averaged over the pixels lying within each feature of the feature collection.
Permissions on custom asset must be such that it is readable by anyone.
Returns: json

Resource url example:

/timeseries/native/custom_asset?dataset=LANDSAT7_TOA&variable=NDVI&start_date=2014-01-01&end_date=2014-02-01&asset_id=WCMC/WDPA/current/points&sub_choices= ["Golden Gate"]&filter_by=NAME

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
start_date	yes			2019-01-01
end_date	yes			2019-12-31
asset_id	yes	Path to Earth Engine asset		WCMC/WDPA/current/points
sub_choices	no	List of features to use in analysis, must be strings		[“Golden Gate”]
filter_by	no	Property name to filter sub-choices		NAME
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/native/forecasts/custom_asset¶

Generates timeseries of forecast values of the dataset variable and timeperiod between start_date and end_date for the features of a custom feature collection asset.
The values are averaged over the pixels lying within each feature of the feature collection.
Permissions on custom asset must be such that it is readable by anyone.
Returns: json

Resource url example:

/timeseries/native/forecasts/custom_asset?dataset=CFS_GRIDMET&variable=pet&start_day=day01&end_day=day28&asset_id=WCMC/WDPA/current/points&sub_choices= ["Golden Gate"]&filter_by=NAME

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes		CFS_GRIDMET	CFS_GRIDMET
variable	yes	pet, pr, tmmn, tmmx		pet
model	yes	ens01 to en<xx> for individual models (see documentation), ens_min, ens_max, ens_mean, ens_median	ens_mean	ens_max
start_day	yes	day01 to day 28, start_day <= end_day	day01	day02
end_day	yes	day01 to day28, end_day >= start_day	day28	day15
asset_id	yes	Path to Earth Engine asset		WCMC/WDPA/current/points
sub_choices	no	List of features to use in analysis, must be strings		[“Golden Gate”]
filter_by	no	Property name to filter sub-choices		NAME
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/interannual/points¶

Generates timeseries of yearly values of the dataset variable summarized over a season at a point location.

Returns: json

Resource url example:

/timeseries/interannual/points?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&start_year=2016&end_year=2018&coordinates=[[-119.96,39.57], [-119, 39]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
temporal_statistic	yes			mean
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
start_year	yes			2016
end_year	yes			2018
coordinates	yes	List of point coordinates		[[-119.96,39.57]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/interannual/polygons¶

Generates timeseries of yearly values of the dataset variable summarized over a season for a polygon.
The values are averaged over the pixels lying within the polygon.
Returns: json

Resource url example:

/timeseries/interannual/polygons?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&start_year=2016&end_year=2018&coordinates=[[[-121.61,38.78], [-121.52,38.78],[-121.52,38.83],[-121.61,38.83],[-121.61,38.78]]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
temporal_statistic	yes			mean
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
start_year	yes			2016
end_year	yes			2018
coordinates	yes	List of polygons coordinates		[[[-121.61,38.78], [-121.52,38.78],[-121.52,38.83],[-121.61,38.83],[-121.61,38.78]]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/interannual/climate_engine_asset¶

Generates timeseries of yearly values of the dataset variable summarized over a season for the features of a Climate Engine feature collection asset.
The values are averaged over the pixels lying within each feature of the feature collection.
For a list of available assets see the Climate Engine Assets section.
Returns: json

Resource url example:

/timeseries/interannual/climate_engine_asset?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&start_year=2016&end_year=2016&region=counties&sub_choices=["AL - Dale"]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
temporal_statistic	yes			mean
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
start_year	yes			2016
end_year	yes			2018
region	yes	Type of feature collection		states
filter_by	no	Attribute to filter by, e.g. name		Name
sub_choices	no	List of features to use in analysis, must be strings		[“Rhode Island”]
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/interannual/custom_asset¶

Generates timeseries of yearly values of the dataset variable summarized over a season for the features of a custom feature collection asset.
The values are averaged over the pixels lying within each feature of the feature collection.
Permissions on custom asset must be such that it is readable by anyone.
Returns: json

Resource url example:

/timeseries/interannual/custom_asset?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&start_year=2014&end_year=2018&asset_id=WCMC/WDPA/current/points&sub_choices=["Golden Gate"]&filter_by=NAME

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
temporal_statistic	yes			mean
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
start_year	yes			2016
end_year	yes			2018
asset_id	yes	Path to Earth Engine asset		WCMC/WDPA/current/points
sub_choices	no	List of features to use in analysis, must be strings		[“Golden Gate”]
filter_by	no	Property name to filter sub-choices		NAME
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/regression/points¶

Performs regression analysis of the dataset variable summarized over a season at a point location.

Returns: json

Resource url example:

/timeseries/regression/points?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&var2_dataset=LANDSAT7_TOA&var2_variable=NDSI&var2_temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&var2_start_day=01&var2_end_day=30&var2_start_month=01&var2_end_month=12&start_year=2016&end_year=2018&coordinates=[[-119.96,39.57]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes			NDVI
temporal_statistic	yes			mean
var2_dataset	yes			LANDSAT7_TOA
variable	yes			NDSI
temporal_statistic	yes			mean
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
var2_start_day	yes			01
var2_end_day	yes			30
var2_start_month	yes			01
var2_end_month	yes			12
start_year	yes			2016
end_year	yes			2018
coordinates	yes	List of point coordinates		[[-119.96,39.57]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/regression/polygons¶

Performs regression analysis of the dataset variable summarized over a season for a polygon.
The values are averaged over the pixels lying within the polygon.
Returns: json

Resource url example:

/timeseries/regression/polygons?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&var2_dataset=LANDSAT7_TOA&var2_variable=NDSI&var2_temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&var2_start_day=01&var2_end_day=30&var2_start_month=01&var2_end_month=12&start_year=2016&end_year=2018&coordinates=[[[-121.61,38.78], [-121.52,38.78],[-121.52,38.83],[-121.61,38.83],[-121.61,38.78]]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes			NDVI
temporal_statistic	yes			mean
var2_dataset	yes			LANDSAT7_TOA
variable	yes			NDSI
temporal_statistic	yes			mean
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
var2_start_day	yes			01
var2_end_day	yes			30
var2_start_month	yes			01
var2_end_month	yes			12
start_year	yes			2016
end_year	yes			2018
coordinates	yes	List of point coordinates		[[[-121.61,38.78], [-121.52,38.78],[-121.52,38.83],[-121.61,38.83],[-121.61,38.78]]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/regression/climate_engine_asset¶

Performs regression analysis of the dataset variable summarized over a season for the features of a Climate Engine feature collection asset.
The values are averaged over the pixels lying within each feature of the feature collection.
For a list of available assets see the Climate Engine Assets section.
Returns: json

Resource url example:

/timeseries/regression/climate_engine_asset?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&var2_dataset=LANDSAT7_TOA&var2_variable=NDSI&var2_temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&var2_start_day=01&var2_end_day=30&var2_start_month=01&var2_end_month=12&start_year=2016&end_year=2018&region=counties&sub_choices= ["ME - Aroostook"]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes			NDVI
temporal_statistic	yes			mean
var2_dataset	yes			LANDSAT7_TOA
variable	yes			NDSI
temporal_statistic	yes			mean
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
var2_start_day	yes			01
var2_end_day	yes			30
var2_start_month	yes			01
var2_end_month	yes			12
start_year	yes			2016
end_year	yes			2018
region	yes	Type of feature collection		states
filter_by	no	Attribute to filter by, e.g. name		Name
sub_choices	no	List of features to use in analysis, must be strings		[“Maine”]
area_reducer	yes	Statistic over region	mean	mean, median, min, max
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/regression/custom_asset¶

Performs regression analysis of the dataset variable summarized over a season for the features of a custom feature collection asset.
The values are averaged over the pixels lying within each feature of the feature collection.
Permissions on custom asset must be such that it is readable by anyone.
Returns: json

Resource url example:

/timeseries/regression/custom_asset?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&var2_dataset=LANDSAT7_TOA&var2_variable=NDSI&var2_temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&var2_start_day=01&var2_end_day=30&var2_start_month=01&var2_end_month=12&start_year=2016&end_year=2018&asset_id=USGS/WBD/2017/HUC08&sub_choices=["Animas"]&filter_by=name

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes			LANDSAT7_TOA
variable	yes			NDVI
temporal_statistic	yes			mean
var2_dataset	yes			LANDSAT7_TOA
variable	yes			NDSI
temporal_statistic	yes			mean
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
var2_start_day	yes			01
var2_end_day	yes			30
var2_start_month	yes			01
var2_end_month	yes			12
start_year	yes			2016
end_year	yes			2018
asset_id	yes	Path to Earth Engine asset		USGS/WBD/2017/HUC08
sub_choices	no	List of features to use in analysis, must be strings		[“Animas”]
filter_by	no	Property name to filter sub-choices		name
area_reducer	yes	Statistic over region	mean	mean, median, min, max
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/standard_index/points¶

Generates timeseries of standard index based on inputs and a list points.
Standard Precipitation Index (SPI) for example is the standard index of precipitation. To calculate SPI, you would use precipitation as the variable.
Similarly, the Standardized Precipitation Evapotranspiration Index (SPEI) potential water deficit (precipitation minus potential evapotranspiration) would be used as the variable.
In the case of a buffer, the values are reduced over the pixels lying within the point before calculating the standard index.
Note: Cannot use pre-calculated drought indices, i.e. GridMET Drought as dataset/variable.
Available variables: spi, spei, eddi, speih, edddih
Returns: json

Resource url example:

/timeseries/standard_index/points?dataset=PRISM_MONTHLY&variable=ppt&area_reducer=mean&start_date=1991-01-01&end_date=2020-12-31&start_year=1991&end_year=2020&accumulation=3&distribution=loglogistic&coordinates=%5B%5B-121.61%2C38.78%5D%5D

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes	Dataset of interest	PRISM_MONTHLY	PRISM_MONTHLY, GRIDMET
variable	yes	Variable of interest	spi	spi, spei, eddi, speih, eddih
area_reducer	yes	Statistic over region	mean	mean, median, min, max
start_date	yes	Start date for timeseries	1991-01-01	2019-01-01
end_date	yes	End date for timeseries	2020-12-31	2019-12-31
start_year	yes	Start year for climatology	1991	1990
end_year	yes	End year for climatology	2020	2020
accumulation	yes	Accumulation period for index. Same unit as dataset.	3	3, 30, 12, 365
distribution	yes	The distribution used to calculate the standard index	loglogistic	loglogistic, gamma, nonparametric
coordinates	yes	List of point coordinates		[[-121.61,38.78]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/standard_index/polygons¶

Generates timeseries of standard index based on inputs and a list polygons.
Standard Precipitation Index (SPI) for example is the standard index of precipitation. To calculate SPI, you would use precipitation as the variable.
Similarly, the Standardized Precipitation Evapotranspiration Index (SPEI) potential water deficit (precipitation minus potential evapotranspiration) would be used as the variable.
The values are reduced over the pixels lying within the polygon before calculating the standard index.
Note: Cannot use pre-calculated drought indices, i.e. GridMET Drought as dataset/variable.
Available variables: spi, spei, eddi, speih, edddih
Returns: json

Resource url example:

/timeseries/standard_index/polygons?dataset=PRISM_MONTHLY&variable=ppt&area_reducer=mean&start_date=1991-01-01&end_date=2020-12-31&start_year=1991&end_year=2020&accumulation=3&distribution=loglogistic&coordinates=%5B%5B%5B-121.61%2C38.78%5D%2C%5B-121.52%2C38.78%5D%2C%5B-121.52%2C38.83%5D%2C%5B-121.61%2C38.83%5D%2C%5B-121.61%2C38.78%5D%5D%5D

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes	Dataset of interest	PRISM_MONTHLY	PRISM_MONTHLY, GRIDMET
variable	yes	Variable of interest	spi	spi, spei, eddi, speih, edddih
area_reducer	yes	Reducer over the polygon	mean	mean, median, min, max
start_date	yes	Start date for timeseries	1991-01-01	2019-01-01
end_date	yes	End date for timeseries	2020-12-31	2019-12-31
start_year	yes	Start year for climatology	1991	1990
end_year	yes	End year for climatology	2020	2020
accumulation	yes	Accumulation period for index. Same unit as dataset.	3	3, 30, 12, 365
distribution	yes	The distribution used to calculate the standard index	loglogistic	loglogistic, gamma, nonparametric
coordinates	yes	List of polygon coordinates		[[[-121.61,38.78], [-121.52,38.78],[-121.52,38.83],[-121.61,38.83],[-121.61,38.78]]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/standard_index/climate_engine_asset¶

Generates timeseries of standard index based on inputs for a climate engine asset (such as counties or states).
Standard Precipitation Index (SPI) for example is the standard index of precipitation. To calculate SPI, you would use precipitation as the variable.
Similarly, the Standardized Precipitation Evapotranspiration Index (SPEI) potential water deficit (precipitation minus potential evapotranspiration) would be used as the variable.
The values are reduced over the pixels lying within the polygon before calculating the standard index.
Note: Cannot use pre-calculated drought indices, i.e. GridMET Drought as dataset/variable.
Available variables: spi, spei, eddi, speih, edddih
Returns: json

Resource url example:

/timeseries/standard_index/climate_engine_asset?dataset=PRISM_MONTHLY&variable=ppt&area_reducer=mean&start_date=1991-01-01&end_date=2020-12-31&start_year=1991&end_year=2020&accumulation=3&distribution=loglogistic&region=states

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes	Dataset of interest	PRISM_MONTHLY	PRISM_MONTHLY, GRIDMET
variable	yes	Variable of interest	spi	spi, spei, eddi, speih, edddih
area_reducer	yes	Reducer over the polygon	mean	mean, median, min, max
start_date	yes	Start date for timeseries	1991-01-01	2019-01-01
end_date	yes	End date for timeseries	2020-12-31	2019-12-31
start_year	yes	Start year for climatology	1991	1990
end_year	yes	End year for climatology	2020	2020
accumulation	yes	Accumulation period for index. Same unit as dataset.	3	3, 30, 12, 365
distribution	yes	The distribution used to calculate the standard index	loglogistic	loglogistic, gamma, nonparametric
region	yes	Name of Climate Engine Asset	states	states
filter_by	no	Attribute to filter by, e.g. name		Name
sub_choices	no	List of features you are interested in		[“California”]
filter_by	no	Name of the property you want to filter by		State_Name
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/standard_index/custom_asset¶

Generates timeseries of standard index based on inputs for a custom earth engine asset.
Standard Precipitation Index (SPI) for example is the standard index of precipitation. To calculate SPI, you would use precipitation as the variable.
Similarly, the Standardized Precipitation Evapotranspiration Index (SPEI) potential water deficit (precipitation minus potential evapotranspiration) would be used as the variable.
The values are reduced over the pixels lying within the feature before calculating the standard index.
Note: Cannot use pre-calculated drought indices, i.e. GridMET Drought as dataset/variable.
Available variables: spi, spei, eddi, speih, edddih
Returns: json

Resource url example:

/timeseries/standard_index/custom_asset?dataset=PRISM_MONTHLY&variable=ppt&area_reducer=mean&start_date=1991-01-01&end_date=2020-12-31&start_year=1991&end_year=2020&accumulation=3&distribution=loglogistic&asset_id=USGS%2FWBD%2F2017%2FHUC08

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
dataset	yes	Dataset of interest	PRISM_MONTHLY	PRISM_MONTHLY, GRIDMET
variable	yes	Variable of interest	spi	spi, spei, eddi, speih, edddih
area_reducer	yes	Reducer over the polygon	mean	mean, median, min, max
start_date	yes	Start date for timeseries	1991-01-01	2019-01-01
end_date	yes	End date for timeseries	2020-12-31	2019-12-31
start_year	yes	Start year for climatology	1991	1990
end_year	yes	End year for climatology	2020	2020
accumulation	yes	Accumulation period for index. Same unit as dataset.	3	3, 30, 12, 365
distribution	yes	The distribution used to calculate the standard index	loglogistic	loglogistic, gamma, nonparametric
asset_id	yes	Earth Engine assetId of a feature Collection	USGS/WBD/2017/HUC08
sub_choices	no	List of features you are interested in		‘California’
filter_by	no	Name of the property you want to filter by		State_Name
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json