Zonal Climate Risk Statistics on Administrative Boundaries

Why Admin Boundaries?

Administrative divisions or boundaries are sub-sovereign geographical areas, often with their own system of administration or governance. They frequently coincide with economic zones, or concentrations of economic activity. This is useful with regards to physical risk exposure, as isolating physical risk by zone can lead to greater insights. For example, comparing coastal zones, which could be impacted by cyclones, to interior zones, which might be exposed to heatwaves or water stress, gives a more holistic picture across business interests. Further, this product can be easily integrated into analysis with widely used boundary-native datasets such as US Census data (e.g., county-level GDP) for deeper analysis of climate-driven impacts on society (see our Multimodal Guide for an example).

About the Data

Derived from our industry-leading high-resolution hazard models, Sust Global’s admin boundaries dataset provides zonally-aggregated physical risk exposure scores, and financial impact metrics, to help risk management and risk reporting teams across financial and sustainability organizations assess the impact of climate change on their portfolios, operational assets and supply chains.

For each of our three metrics, physical risk exposure and the resulting structural damage and business interruption, we detail the following:

Two climate scenarios: SSP2-RCP4.5 (Medium Warming) and SSP5-RCP8.5 (High Warming)
Four time horizons: Baseline, 2030, 2050, and 2080
Six physical hazards: Cyclones, Flooding (inland + coastal), Wildfire, Heatwaves, Water Stress, and, Sea Level Rise

Zonal Aggregation Approach

To create our Zonal Statistics dataset, we first translate our high-resolution data to polygon-representative values. The reduction method (e.g., mean, maximum) for each hazard can be found in the Climate Data Guide. From these spatially aggregated hazard values, we then derive the financial impact metrics. For each of the three metrics (hazard exposure, structural damage, business interruption), we represent the inherent uncertainty of climate data by reporting lower and upper bounds of the data (i.e., 84th and 16th percentile respectively). Finally, we represent the geolocation of each administrative boundary by using the latitude and longitude of the centroid.

Supported Countries

Sust Global currently supports the following countries at the admin two, three, and four level:

United States of America
India
China (admin. 2 only)
Australia
Canada
Great Britain
Netherlands
Japan
Spain
Germany
Sweden
Belgium
France

Glossary of boundaries by country:

Code	Country	Admin 2	Admin 3	Admin 4
AUS	Australia	local gov	postal codes	localities
BEL	Belgium	provinces	districts	municipalities
CAN	Canada	counties	districts	census subdivisions
CHN	China	prefecture	-	-
DEU	Germany	districts	municipalities	towns
ESP	Spain	provinces	counties	municipalities
FRA	France	departments	districts	subdivisions
GBR	Great Britain	counties	districts	parishes
IND	India	divisions	districts	subdistricts
JPN	Japan	municipalities	municipalities	sub-municipalities
NLD	Netherlands	municipalities	districts	neighborhoods
SWE	Sweden	municipalities	districts	districts
USA	United States	counties	zip codes	census tracts

Supported Data Layers

The supported data layers span physical risk factors, resilience scores, socioeconomic and demographic features, as well as biodiversity scores and other datasets. The full set of supported data layers is detailed in the Visual Summary Multimodal Guide.

Data Dictionary

Name	Type	Description
ID	STRING	Identifier (is not unique across datasets)
T_ID	STRING	Identifier for tessellated boundaries
COUNTRY	STRING	3 Letter Country Code
ADMIN_PROCESSING_LEVEL	STRING	The admin boundary level to which this dataset corresponds (2,3,4)
LNG	STRING	Longitude of administrative boundary centroid
LAT	STRING	Latitude of administrative boundary centroid
POLYGON	STRING	Boolean indicating whether the input administrative boundary is a polygon
TESSELLATED	STRING	Boolean indicating whether tessellation has been performed within administrative boundary
ADMIN0	STRING	3 Letter Country Code
ADMIN1	STRING	Admin 1 boundary name
ADMIN2	STRING	Admin 2 boundary ID
ADMIN3	STRING	Admin 3 boundary ID (if applicable)
ADMIN4	STRING	Admin 4 boundary ID (if applicable)
LABELS	OBJ	Contains a dictionary of additional dataset metadata
SCENARIO_ANALYTICS	OBJ	Contains the climate scenarios ssp245 and ssp585. Each scenario contains hazards wildfire, cyclone, flood, heatwave, water stress and sea level rise. For each hazard, data is windowed for baseline, 2030, 2050, and 2080. In turn the ubd (upper bound) and lbd (lower bound) values indicate the uncertainty for each window. (Special note on heatwave indicator and business interruption: values are normalized by 365 to give them in percents rather than days)
SUMMARY_SCORE_30YR	STRING	In a 30 year window, the maximum risk exposure
SUMMARY_SCORE_15YR	STRING	In a 15 year window, the maximum risk exposure
SUMMARY_LABEL_30YR	STRING	Low/Medium/High label determined by SUMMARY_SCORE_30YR
SUMMARY_LABEL_15YR	STRING	Low/Medium/High label determined by SUMMARY_SCORE_15YR
INDICATOR_BASELINE	FLOAT	The baseline value for the given physical risk indicator
INDICATOR_BASELINE_LBD	FLOAT	The lower bound baseline value for the given physical risk indicator
INDICATOR_BASELINE_UBD	FLOAT	The upper bound baseline value for the given physical risk indicator
INDICATOR_2030	FLOAT	The value averaged from 2025-2035 for the given physical risk indicator
INDICATOR_2030_LBD	FLOAT	The lower bound value averaged from 2025-2035 for the given physical risk indicator
INDICATOR_2030_UBD	FLOAT	The upper bound value averaged from 2025-2035 for the given physical risk indicator
INDICATOR_2050	FLOAT	The value averaged from 2045-2055 for the given physical risk indicator
INDICATOR_2050_LBD	FLOAT	The lower bound value averaged from 2045-2055 for the given physical risk indicator
INDICATOR_2050_UBD	FLOAT	The upper bound value averaged from 2045-2055 for the given physical risk indicator
INDICATOR_2080	FLOAT	The value averaged from 2075-2085 for the given physical risk indicator
INDICATOR_2080_LBD	FLOAT	The lower bound value averaged from 2075-2085 for the given physical risk indicator
INDICATOR_2080_UBD	FLOAT	The upper bound value averaged from 2075-2085 for the given physical risk indicator
STRUCTURAL_DAMAGE_BASELINE	FLOAT	The baseline value for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_BASELINE_LBD	FLOAT	The lower bound baseline value for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_BASELINE_UBD	FLOAT	The upper bound baseline value for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_2030	FLOAT	The value averaged from 2025-2035 for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_2030_LBD	FLOAT	The lower bound value averaged from 2025-2035 for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_2030_UBD	FLOAT	The upper bound value averaged from 2025-2035 for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_2050	FLOAT	The value averaged from 2045-2055 for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_2050_LBD	FLOAT	The lower bound value averaged from 2045-2055 for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_2050_UBD	FLOAT	The upper bound value averaged from 2045-2055 for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_2080	FLOAT	The value averaged from 2075-2085 for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_2080_LBD	FLOAT	The lower bound value averaged from 2075-2085 for the structural damage resulting from risk exposure
STRUCTURAL_DAMAGE_2080_UBD	FLOAT	The upper bound value averaged from 2075-2085 for the structural damage resulting from risk exposure
BUSINESS_INTERRUPTION_BASELINE	FLOAT	The baseline value for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_BASELINE_LBD	FLOAT	The lower bound baseline value for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_BASELINE_UBD	FLOAT	The upper bound baseline value for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_2030	FLOAT	The value averaged from 2025-2035 for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_2030_LBD	FLOAT	The lower bound value averaged from 2025-2035 for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_2030_UBD	FLOAT	The upper bound value averaged from 2025-2035 for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_2050	FLOAT	The value averaged from 2045-2055 for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_2050_LBD	FLOAT	The lower bound value averaged from 2045-2055 for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_2050_UBD	FLOAT	The upper bound value averaged from 2045-2055 for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_2080	FLOAT	The value averaged from 2075-2085 for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_2080_LBD	FLOAT	The lower bound value averaged from 2075-2085 for the business interruption resulting from risk exposure
BUSINESS_INTERRUPTION_2080_UBD	FLOAT	The upper bound value averaged from 2075-2085 for the business interruption resulting from risk exposure
GEOMETRY	OBJ	The polygonal geometry of the boundary

Scenario Analytics

For more information about individual hazards and climate scenarios, see the Climate Data Guide.

Example

An example of heat mapping power plants in Idaho is available here.

Using the Data

You can purchase the data on Snowflake.