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AWS Solutions Library

Guidance for Physical Climate Risk Assessment on AWS

Overview

This Guidance provides a technical foundation to visualize and monitor key performance indicators (KPIs) for reporting on climate-related physical risks to your operations. In particular, it demonstrates how you can enrich physical assets using large-scale, high-quality climate projection datasets made available through the Amazon Sustainability Data Initiative (ASDI). Physical climate risk assessment provides critical insights into the expected impacts of climate change to businesses, organizations, and communities. Understanding the potential risks and consequences of climate change empowers decision-makers to create and execute effective strategies for adaptation and resilience.

How it works

These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.

Download the architecture diagram PDF 

Well-Architected Pillars

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

You can use Athena to query custom metrics for additional insights, which can then be implemented in a QuickSight dashboard for reporting or a custom widget in a web application. These insights can also help you infer which additional climate scenarios and metrics to include as part of the input.

Read the Operational Excellence whitepaper

Resources are protected by AWS Identity and Access Management (IAM) policies and roles, following the least-privilege access principle. Data ingested to the AWS Cloud is encrypted and transferred over HTTPS. AWS Key Management Service (AWS KMS) encrypts and protects data-at-rest.

Read the Security whitepaper

This Guidance follows an event-driven architecture with loosely coupled dependencies, making it easy to isolate behaviors and increase resilience and agility. It uses managed serverless services such as Step Functions and Lambda to orchestrate the loosely coupled dependencies. 

Read the Reliability whitepaper 

Services selected for this architecture are purpose-built. For example, Step Functions Distributed Map orchestrates large-scale parallel workloads. In this Guidance, it orchestrates data enrichment using large-scale raster datasets from ASDI. Additionally, QuickSight is a purpose-built business intelligence tool. It allows you to create charts with geographic locations. 

Read the Performance Efficiency whitepaper

Step Functions and Lambda only run when invoked by an event and automatically scale based on workload demand. You can also use the Amazon S3 Intelligent-Tiering storage class to automatically move data to the most cost-effective access tier in Amazon S3.

Read the Cost Optimization whitepaper

AWS hosts a broad variety of large-scale high-quality sustainability datasets through public S3 buckets. This Guidance uses cloud-optimized open data directly from these S3 buckets to enrich your location data. This means you don't need to store large datasets in your AWS environment, reducing your overhead maintenance.

Read the Sustainability whitepaper

Related Content

Blog

Estimating physical climate heat risk with NASA Global Daily Downscaled Projections on ASDI

This post shows an example architecture to query the downscaled climate projection data for locations, calculate cooling degree day (CDD) metrics, and visualize the output with Amazon QuickSight.

Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.