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.
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.
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.
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.
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