Energy
21 columns
100 rows
8 formats

Climate Data for Long-Term Planning and Resilience

This dataset provides comprehensive historical and projected climate data—including temperature, precipitation, and extreme events—across diverse geographic locations. It supports infrastructure planning, flood and wildfire risk mapping, and grid resilience investment analysis, making it invaluable for long-term climate adaptation and risk management strategies.

last updated 2 Nov 2025
by GoMask

The brief that made it

Infrastructure resilience and investment planning

Sample rows

preview · 8 of 100 rows · all 21 columns

record_idstring	flood_risk_levelstring	precipitation_mmfloat	extreme_event_typestring	location_namestring	location_latitudefloat	location_longitudefloat	location_countrystring	data_sourcestring	data_typestring	scenariostring	date_recordeddate	temperature_mean_cfloat	temperature_min_cfloat	temperature_max_cfloat	extreme_event_severitystring	extreme_event_duration_daysfloat	wildfire_zone_levelstring	grid_resilience_scorefloat	infrastructure_investment_needed_usdfloat	notesstring
CLIM-00001	low	2.4	blank	Los Angeles	34.05	-118.25	United States	NOAA	historical	blank	2015-07-15	26.1	18.7	35.4	blank	blank	high	82.5	2100000	Dry summer, elevated wildfire risk.
CLIM-00002	severe	207.8	storm	Miami	25.76	-80.19	United States	IPCC	projection	RCP8.5	2035-08-01	31.4	26.6	36.2	high	6	low	68.2	5000000	Projection includes hurricane season peak.
CLIM-00003	moderate	40.5	blank	Berlin	52.52	13.405	Germany	NOAA	historical	blank	2016-03-20	8.6	2.1	15.3	blank	blank	none	87.1	1200000	Spring rainfall above average.
CLIM-00004	low	57.2	wildfire	Sydney	-33.87	151.21	Australia	IPCC	projection	SSP2-4.5	2040-01-10	29.7	20.8	39.2	catastrophic	13.5	extreme	61.6	8700000	Projection based on increased fire risk.
CLIM-00005	high	143.9	flood	Shanghai	31.23	121.47	China	NOAA	historical	blank	2014-09-05	26.8	21	33.5	moderate	4.2	none	77	3550000	Urban flooding event, moderate severity.
CLIM-00006	none	10.1	drought	Cape Town	-33.92	18.42	South Africa	Other	historical	blank	2017-02-14	21.2	14.3	28.7	high	90	moderate	73	4100000	Drought emergency declared.
CLIM-00007	low	52.5	storm	Toronto	43.65	-79.38	Canada	NOAA	historical	blank	2019-01-21	-5.2	-14.1	1.5	moderate	2	none	90.3	700000	Winter storm affected transportation.
CLIM-00008	moderate	74.8	heatwave	Mexico City	19.43	-99.13	Mexico	IPCC	projection	RCP4.5	2030-05-11	22.5	16.7	28.3	high	8	moderate	65.8	4100000	Projection shows increased heatwave frequency.
CLIM-00009	moderate	88.4	blank	London	51.51	-0.13	United Kingdom	NOAA	historical	blank	2018-10-03	14.6	8.2	20.9	blank	blank	none	85.2	1500000	Wet autumn, above average rainfall.
CLIM-00010	low	12	heatwave	Delhi	28.61	77.21	India	IPCC	projection	RCP8.5	2045-06-23	34.9	28.5	41.3	catastrophic	18	none	59.7	7200000	Extreme heat projected under RCP8.5.
CLIM-00011	moderate	110.5	storm	São Paulo	-23.55	-46.63	Brazil	Other	historical	blank	2013-11-02	22.7	16.2	28.9	high	3.5	low	71.5	2950000	Severe thunderstorms caused flooding.
CLIM-00012	low	32.3	heatwave	Paris	48.85	2.35	France	IPCC	projection	SSP2-4.5	2037-07-19	23.9	18.3	29.2	high	7	none	76	2600000	Heatwave projected for Paris.
CLIM-00013	none	30.7	blank	Moscow	55.75	37.62	Russia	NOAA	historical	blank	2012-01-13	-10.4	-18.6	-3.2	blank	blank	none	88.8	950000	Severe winter, low precipitation.
CLIM-00014	severe	178.3	flood	Bangkok	13.75	100.5	Thailand	IPCC	projection	RCP4.5	2032-09-22	30.2	24.7	35.6	high	5.7	none	62.8	6150000	Flood risk increases in projections.
CLIM-00015	none	4.7	heatwave	Madrid	40.42	-3.7	Spain	Other	historical	blank	2018-07-05	29	21.3	37.2	moderate	6	high	74.1	2200000	Heatwave event noted.
CLIM-00016	moderate	71.3	storm	Tokyo	35.68	139.76	Japan	NOAA	historical	blank	2015-04-27	16.7	10.5	22.9	low	1	none	89.4	1250000	Spring storms, moderate grid resilience.
CLIM-00017	low	93.1	drought	Nairobi	-1.29	36.82	Kenya	IPCC	projection	SSP2-4.5	2042-03-16	23.4	16.8	29.5	moderate	45	moderate	67.1	3400000	Projected moderate drought.
CLIM-00018	high	186.1	storm	Vancouver	49.28	-123.12	Canada	Other	historical	blank	2019-11-05	7.9	2.5	13.2	moderate	2.5	low	80	1600000	Heavy autumn storms.
CLIM-00019	none	0.5	heatwave	Dubai	25.27	55.3	UAE	IPCC	projection	RCP8.5	2047-08-21	39.3	29.4	49.6	catastrophic	23	none	53.9	9500000	Severe heatwave projected.
CLIM-00020	none	0	drought	Cairo	30.04	31.23	Egypt	NOAA	historical	blank	2012-05-08	25.8	18.2	33.7	moderate	60	low	70.2	1900000	Extended dry period.

What the 100 rows show

from the 100-row sample

Severe (flood risk level) stands out: mean precipitation_mm is 204.8, against 60.6 for the rest.

68.4median precipitation_mm
2data types
3data sources
3scenarios
4extreme event severities
5wildfire zone levels

Mean precipitation_mm by flood_risk_level100 rows

precipitation_mm100 rows, in bands of 50

Median 68.4, from 0.0 to 320.0.

extreme_event_type82 rows with a value · 18 left blank

storm29
flood20
heatwave20
drought9
wildfire3
other1

21 columns by typefrom the column list below

string 11
float 9
date 1

Columns

21 columns in three groups

blueprint · 21 columns
column	type	description	example
Text 11 columns
`record_id`	string	Unique identifier for each climate data recordunique	CLIM-00001
`location_name`	string	Name of the geographic location (city, region, or site)	Los Angeles
`location_country`	string	Country where the location is situated	United States
`data_source`	string	Source of the climate data (e.g., NOAA, IPCC)NOAA · IPCC · Other	NOAA
`data_type`	string	Type of climate data (historical, projection)historical · projection	historical
`scenario`	string	Climate scenario for projections (e.g., RCP4.5, RCP8.5, SSP2-4.5)3 scenarios · optional	RCP8.5
`extreme_event_type`	string	Type of extreme event (e.g., flood, wildfire, heatwave, drought)6 values · optional	storm
`extreme_event_severity`	string	Severity of the extreme event (e.g., low, moderate, high, catastrophic)low · moderate · high · catastrophic · optional	high
`flood_risk_level`	string	Flood risk level for the location (e.g., none, low, moderate, high, severe)none · low · moderate · high · severe · optional	low
`wildfire_zone_level`	string	Wildfire risk zone classification (e.g., none, low, moderate, high, extreme)none · low · moderate · high · extreme · optional	high
`notes`	string	Additional notes or comments about the recordoptional	Heatwave event noted.
Numbers 9 columns
`location_latitude`	float	Latitude coordinate of the location-90 to 90	34.05
`location_longitude`	float	Longitude coordinate of the location-180 to 180	-118.25
`temperature_mean_c`	float	Mean temperature in degrees Celsiusoptional	26.1
`temperature_min_c`	float	Minimum temperature in degrees Celsiusoptional	18.7
`temperature_max_c`	float	Maximum temperature in degrees Celsiusoptional	35.4
`precipitation_mm`	float	Total precipitation in millimeters0 or more · optional	2.4
`extreme_event_duration_days`	float	Duration of the extreme event in days0 or more · optional	6
`grid_resilience_score`	float	Score indicating infrastructure/grid resilience (0-100 scale)0 to 100 · optional	82.5
`infrastructure_investment_needed_usd`	float	Estimated investment needed for resilience in USD0 or more · optional	2100000
Dates and times 1 column
`date_recorded`	date	Date when the climate data was recorded or projected for	2015-07-15

Use it for

An energy dashboard
Precipitation_mm by flood_risk_level and a breakdown of extreme_event_type. Excel, Power BI or Tableau.
Why do the 17 severe rows have a mean precipitation_mm of 204.8?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Records100
CLIM-000012.4low
CLIM-00002207.8severe
CLIM-0000340.5moderate
A software demo
Believable records with location_name, location_latitude and location_longitude to fill a screen in front of a buyer.

This dataset100 rows21 columns

Yours1,000 rows21 columnslocation_name: UK only

blueprint · climate-data-for-long-term-planning-and-resilience

Behind this dataset

Same schema. As many rows as you need.

These 100 rows came out of a blueprint — 21 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Historical period (e.g., 1991-2020) and future scenario (RCP 4.5, RCP 8.5)
Temperature trends: annual average, extreme heat days (>95°F)
Precipitation changes: total annual, intense rainfall events, drought frequency
Sea level rise projections (feet) for coastal substations and flooding
Wildfire risk index and expansion of high-risk zones
Hurricane intensity and frequency projections
Cooling degree day increases and peak load growth
Infrastructure hardening investments: undergrounding, flood barriers, fire-resistant poles

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: climate-data-for-long-term-planning-and-resilience

What should your data show?

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Sample rows

What the 100 rows show

Columns

Use it for

An energy dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Energy

What should your data show?