wisc summary report of task 5.1 oasis user case study · 5.1 format conversion 5 5.2 data treatment...

ECMWF COPERNICUS REPORT

Copernicus Climate Change Service

WISC Summary Report of Task 5.1 - OASIS User Case Study

Issued by: Ben Hayes, OASIS

Date: 31/01/2018

Ref: C3S_441_Lot3_WISC_SC2-D5.1-CGI-RP-17-0101

Official reference number service contract: 2017/C3S_441_Lot3_CGI/SC2


(C3S_441_Lot3_WISC_SC2-D5.1-CGI-RP-17-0101) (OASIS Case Study) (1.0) Page iii

Contributors

OASIS PALM TREE LTD

Ben Hayes

Dickie Whittaker

CATINSIGHT

Richard Dixon

CGI IT UK LTD

Alan Whitelaw

This document has been produced in the context of the Copernicus Climate Change Service (C3S).

The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation Agreement signed on 11/11/2014). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.

The user thereof uses the information at its sole risk and liability. For the avoidance of all doubts, the European Commission and the European Centre for Medium-Range Weather Forecasts has no liability in respect of this document, which is merely representing the authors view.


(C3S_441_Lot3_WISC_SC2-D5.1-CGI-RP-17-0101) (OASIS Case Study) (1.0) Page iv

Table of Contents

1. Introduction and background 1

1.1 WISC and C3S 1

1.2 Information provided by WISC 1

1.3 Oasis 2

2. Case study rationale 2

3. Approach 3

4. Overview of the Oasis LMF 4

5. WISC - Oasis Integration 5

5.1 Format conversion 5

5.2 Data treatment 7

5.3 Configuration 7

5.4 Storage and availability 8

6. Review of tests on WISC based model data 10

7. Use of WISC data in Oasis by insurers 10

8. Conclusions and recommendations 11

9. Final note 11


(C3S_441_Lot3_WISC_SC2-D5.1-CGI-RP-17-0101) (OASIS Case Study) (1.0) Page 1 of 11

1. Introduction and background

This document is deliverable D5.1 ‘Oasis User Case Study’ from the C3S ECMWF Proof of Concept Sectoral Information Service project Windstorm Climate Service (WISC). It is delivered under the ECMWF Service Contract No 2017/C3S_441_Lot3_CGI/SC2, implementing Framework Agreement No 2015/C3S_441_Lot3/CGI.

1.1 WISC and C3S

WISC (Windstorm Information System – Copernicus) is a Copernicus Climate Change System (C3S) activity funded by the European Commission and managed by ECMWF. The project team, led by CGI IT UK Ltd, consists of University of Reading, UK Met Office, VU Amsterdam, KNMI, Oasis, Swiss Re, ETH Zurich and Telespazio Vega UK.

The project provides storm tracks and footprints from historical Extra Tropical Cyclones affecting Europe to improve baseline information available to the insurance industry in decision making related to windstorms. In addition, a synthetic event set generated from historical data has been developed, together with a variety of indicators, vulnerability and estimated loss values. The data are now available for use and can be accessed via the WISC portal at:

https://wisc.climate.copernicus.eu/wisc/#/help/products;

and in the longer term via the C3S Climate Data Store (CDS) at

https://climate.copernicus.eu/climate-data-store

With the data available WISC is working with users to undertake case study trials of the information to assess the properties of the data and to gauge its impact in operational use. In addition, WISC is working to embed the data in formats extensively accessed by the user community to encourage user uptake. This is the emphasis for this case study which aims to embed the data in the OASIS environment.

1.2 Information provided by WISC

WISC provides the following information

Historical storm information

Reanalysis Data Sources: 1940 – 1979: ERA-20C; 1979 – 2014;

ERA-INT; ERA5 (initial release): 2010 – 2016

Tracks: 1940 - 2014

Footprints: 1940 – 2014

o 4km resolution, downscaled using UKMO Unified Model

o 96 from ERA-20C, 55 from ERA-INT

o Two ERA5 storms (Xynthia and Imogen) from with 10 ensemble members in each

case

https://wisc.climate.copernicus.eu/wisc/#/help/products

https://climate.copernicus.eu/climate-data-store



Synthetic storm information

Source: Simulations undertaken by the UPSCALE project covering the period 1985-2011.

Resulting Event Set:

o 7,660 storms at 25km resolution

o Based on perturbation of physically realistic historical storm assessments

Tier 1 and Tier 3 indicators:

Tier 1:

o Total number of windstorms per period, Average max wind speed, Average storm

severity, Decadal variability

o Derived from the information above

Tier 3:

o Total sectoral insured losses, Total windstorm risk per sector per year

o Using Open Street Map (OSM) building data with CORINE Land cover, NUTS regions,

building type classifications and re-building costs to estimate storm based losses per

hazard input (historical or synthetic storm).

1.3 Oasis

The Oasis Loss Modelling Framework (LMF) is an open source catastrophe (cat) modelling platform which is free to use by anyone. It is also a community that seeks to unlock and change the world around cat modelling to better understand risk in insurance and beyond. While its development is largely driven by the global (re-)insurance community, it also seeks to provide tools and utility to all. It is constituted as a not for profit company, and their team seeks to empower users globally to better understand risk and uncertainty The Oasis ecosystem currently consists of more than 12 suppliers covering over 70 models in 2017.

It is clear therefore that the Oasis LMF presents a highly suitable basis to optimize the use and accessibility of the WISC products by the insurance community. Accordingly this case study seeks to perform this integration and to assess the outcomes of some of the WISC products in this environment.

2. Case study rationale

The intention for WISC has been to provide reference quality climate information of value to the insurance sector, specifically risk / loss modellers.

To show the value of the products and promote uptake by a wider range of users, WISC has embarked on a series of case studies to assess the impact and value of the data products in everyday use and to make the data as widely available as possible. This will help to meet the following goals:



Make available and promote WISC outputs to a wider user audience and stimulate user

uptake

Raise awareness of the wider C3S activities and the wide range of reference information

available from these

Help provide feedback on use of WISC data to refine future use

Provide feedback which will help define future priorities in this activity.

The specific rationale for this Oasis case study is to make the WISC data available to users on the Oasis platform and to make some initial assessments in a user context. This will enhance access for users operating in the insurance sector, which is the primary focus for the WISC project. The emphasis for this work has been on the WISC Event Set and also on the Tier 3 indicators as identified above. Making the data available in this way will involve some modifications which are also set out in this document. Finally, some initial assessments have also been carried out using the data on the Oasis platform and these are also described.

It should be noted that only limited publically available insurance loss data have been available to WISC team because loss data is generally proprietary. The intention is that by providing detailed building blocks, users will be able to combine this with their own proprietary information and hence building their own analysis.

3. Approach

The aims of the WISC Oasis case study have been as follows:

Integration of a WISC Oasis cat model, based on the Oasis LMF and using the event set,

vulnerability and exposure data provided, respectively by Met Office and VU

Provision of a suitable front end for the WISC Oasis cat model (i.e. the WISC Event Set) to

allow for effective use in WISC case studies, but also for later use in general Oasis activities if

useful

Support to CGI by identifying and giving introductions to appropriate users for promotion of

WISC to potential users.

This may also be followed up in due course by support for promotion of the WISC Oasis model through organisation and hosting of a workshop in London. This could also focus on the wider WISC historic portfolio in addition to the Event Set and Tier 3 information.

Hazard information / event set

OASIS is a platform for catastrophe, or cat, models. These cat models as used by insurance companies are normally based on large stochastically generated event sets of possible catastrophe scenarios provided by commercial providers or developed internally. These are then used to assess the probabilistic risk of loss at particular locations to guide premium setting and capital requirements.



As a publicly funded activity, it is not the role of WISC to provide a competing alternative to these existing offerings but rather to try to enhance the diversity of pre-competitive information available that can raise the baseline level for all players. Accordingly, in addition to the historical storm tracks and high resolution footprints, WISC, and in particular the UK Met Office, has developed a synthetic event set based on the UPSCALE data set covering storms between 1985 and 2011 with 5 ensembles. The WISC event set seeks to provide a comparator to the stochastic sets in which the storms are generated in a way that ensures that they are physically plausible as well as estimating extreme conditions.

Tier 3 indicators

In addition to the WISC hazard data contained in the event set, WISC has also generated Tier 3 indicators and in particular building blocks for this information that can also be incorporated into Oasis as a foundation for future developments.

4. Overview of the Oasis LMF

The Oasis Loss Modelling Framework provides an open source platform for developing, deploying and executing catastrophe models. It uses a full simulation engine and makes no restrictions on the modelling approach. Models are packaged in a standard format and the components can be from any source, such as model vendors, academic and research groups. The platform provides:

A platform for running catastrophe models, including an API for integration with other

systems (Oasis Loss Modelling Framework)

Core components for executing catastrophe models at scale and standard data formats for

hazard and vulnerability (Oasis ktools)

An exposure/results database and a web based user interface (Flamingo)

Toolkit for developing, testing and deploying catastrophe models (Oasis Model Development

Toolkit).



Figure 1: The Oasis Architecture for Deployment

5. WISC - Oasis Integration

5.1 Format conversion

The WISC model data provided has been converted to Oasis LMF model data format and the hazard and vulnerability components have been calibrated to sit in the same frame of reference so that the model can work as a whole. The Oasis model format defines a hazard module based around a footprint, which describes the intensity distribution of events by area peril and the vulnerability module which describes the damage factor probability distribution that is applicable to an exposure for a given intensity and vulnerability function.

Figure 2 demonstrates the relationship between these modules (and files) at a high level:

Flamingo UIModel 1

Keys ServerFlamingo Server

Model 1Keys Server

Flamingo DB

Oasis API

Model 2Analysis Worker

Model 1Analysis Worker

Temporary Datastore

Message Broker

Flamingo – UIFlamingo -

ServerMid-tier Ktools



Figure 2: Relationship between Oasis modules and files at a high level

Further to this, below is an example implementation of a (very simple) model in the Oasis format:

Figure 3: Example implementation of a simple model in the Oasis format

This example shows a small windstorm model with two events affecting two area perils. The areas are defined as point lat/long positions and there are three intensity bins representing wind-speeds 50-60, 60-70 and 70-80 m/s. There are two vulnerability functions defined for the model based on construction schemes. All of the secondary uncertainty in the model is represented in the vulnerability functions.



5.2 Data treatment

Areas of the model that would never create a loss were identified based on wind-speeds that were below the threshold at which the vulnerability functions provided kicked in. This eliminated approximately 80% of the model data but will produce the same results when run as a complete model. After further conversion to the Oasis binary formats, the resulting model data is approximately 5% of the physical size of the original model. This is important for distribution and performance but the original model data has been retained and can be used as a foundation for future changes, should alternative vulnerability functions be developed which have a lower wind-speed threshold for damage.

5.3 Configuration

The configuration assets that are required to run the WISC model in Flamingo - the default user front end for Oasis – have been created so that users of Flamingo can run the model in this environment. Flamingo is available to all Oasis members and anyone else by invitation but in the near future it will become fully open sourced and so will be available to anyone to download for free. These configuration assets are also common to – and therefore also usable in - the Oasis Model Development Toolkit which will enable insurance companies to build on the model.

Figure 4 below shows the data transformation process that is required for a user of Oasis to go from a set of exposure data files in a native format to the abstracted set of Oasis exposure files that are required to run against an Oasis model.

Figure 4: Oasis data transformation process for native format exposure files to be used in Oasis



The steps involved are:

1) Source Location and Contract data files conversion to Canonical Location and Contract data

files

2) Canonical Location and Contract data files to Canonical Data Model

3) Canonical Location file to Model Location file conversion

4) Model specific oasis key files (matching and non-matching location files)

5) Canonical data model to Oasis file format

In order to facilitate the running of a model in Oasis via Flamingo, there are a number of assets (that have been produced and are provided as part of this project) to fit into this framework:

XSDs/XSLTs to define the data transforms from source to canonical and from canonical to

model lookup format

A SQL script to load the model configuration data into the Flamingo database

A “keys server” program to map the source exposure data into the Oasis keys representing

the specific geographical area and vulnerability characteristics of the exposures in the model

data

5.4 Storage and availability

The assets that make up a deployable model in Oasis fall into three categories:

Code – including the specific keys server code that is required for the mapping of a user’s

exposure data to the area and vulnerability categorisations in the model itself, and the

Flamingo configuration code required to represent a model in the Flamingo front end

Data – both the data that represents the model itself – i.e. the hazard and vulnerability

components of the catastrophe model – and the lookup data that is required to sit behind

the keys service

Docker image(s) – Docker is a containerisation technology which Oasis uses to deploy

models and environments. Images are used to represent a deployable piece of code.

A GitHub repository to house all of the code has been created using the Oasis model standards and is hosted in the Oasis LMF area. This is a private repository at the moment (meaning that access has to be granted to developers) but the intention is that this will be made open source at the end of the project so that anyone can download the code for their own use

The model data itself – in Oasis format – will be stored in the Oasis Model Library. This is a model data repository, hosted in AWS, to which SFTP access can be granted to model developers. The models in the Oasis Model Library will also be included in the Continuous Integration (CI) development process in Oasis, ensuring that any future changes to the model data itself, or the Oasis software, do not adversely affect the modelled outputs. The data will also be provided back to WISC to host alongside the original hazard data.



The Docker image for the keys server is also hosted by Oasis and can be made available to anyone wishing to deploy the model as a whole.

Figure 5 shows a typical development cycle for a model in Oasis and demonstrates how the various model assets are distributed.

Figure 5: Typical development cycle for a model in Oasis

There is also a proposal to host the complete, deployed model in the Simplitium hosted environment. Simplitium provides a hosted, managed platform to the insurance industry based on the Oasis Loss Modelling Framework and Flamingo Front End. They offer a live, production environment to run catastrophe models as well as an evaluation area to which new and existing customers alike can connect and review models in real time using their own exposure data without the need for any installation themselves – either of the software or the model specific components.

Workstation

Oasis Model Developer Toolkit

Source model data

Model Developer

Step 1. The modeller developer checks out the latest model developer toolkit code.

Step 2. The model developer builds, tests and validates the Oasis model files and code on their workstation.

Step 3. The model developer publishes the model deployment package.

Step 4. The model version is deployed to the Oasis test environment.

Step 5. The model developer validates the operation of the model version within Flamingo.

Oasis Data Repository

Oasis Test Environment

Model Deployment Package

Keys ServerKeys Server

Model DataModel Data

Exposure Data

Transforms

Exposure Data

Transforms

Model Execution

Model Execution

Model Validation Test Data

Model Validation Test Data

Flamingo Install Script

Flamingo Install Script

Oasis Respositories

Model Repository

Oasis Respositories

Model RepositoryDockerHub



6. Review of tests on WISC based model data

Oasis Palm Tree engaged with an independent consultant, Ricard Dixon of CatInsight, to review the data in the model. Concerns were raised about the usefulness of the data in its own right on the basis of this review as it is neither big enough to be used stochastically and nor is it an historic representation of hazard. The model itself was seen to be pseudo-historic, representing a relatively short period in near history but with synthetic events.

That said, there are many datasets available to understand historical events but having "alternative histories" of recent climate similar to what WISC has provided with its event set. This is becoming an attractive way of understand risk deployed by some of the more sophisticated insurance companies and affiliates. This is especially so if there are trends in historical data such that we can look at re-simulations of current climate to understand whether what we have seen in history is actually a trend or just the capriciousness of natural atmospheric variability.

Suggested improvements for WISC might include expanding the event set to get a better, probabilistic view of risk by perturbing the existing event set. Providing the historical data itself as a distinct Oasis model might also be useful for insurers.

7. Use of WISC data in Oasis by insurers

Due to the limited nature of the event set data by catastrophe model standards, the model is unlikely to be directly applicable as a catastrophe model in its own right for the majority of insurance companies’ usage. However, it is possible that elements of the hazard data in the event set model could be employed as a tool to better understand and validate the assumptions made in existing risk models for European windstorm by some of the more sophisticated modelling teams within certain (re)insurance companies.

The vulnerability module provided in the model is most likely too basic to be usable in its own right again but it is a necessary component in the Oasis architecture for use in conjunction with the hazard module to produce losses. For this reason, it is necessary to have something in place by way of a vulnerability module – but it is recognised that the vulnerability functions are rather too blunt to be used in practice. That said, insurers often have their own view on vulnerability based on in-house, historical claims data and so replacing the vulnerability module (given the intensity bin frame of reference) is not unfeasible.

As a complete model in its own right, it will be instantly usable for anyone that has an Oasis installation but the caveats that the hazard data is neither stochastically relevant nor representative of historical events should be made clear to anyone wishing to use the data. It should also be made clear that the vulnerability functions provided are, in their present form, simplistic and provided out of necessity rather than as a true representation of vulnerability. It should also be made clear that there is no secondary uncertainty built into the model – i.e. both the hazard footprint and the vulnerability module have no probability distributions – and so the only uncertainty is in the event set itself and its representation of reality.



8. Conclusions and recommendations

The model data provided is not deemed fit for purpose as a stochastic catastrophe model in its own right but could be an interesting foundation from which to validate existing models or build a new catastrophe model. The event set is too small, the vulnerability functions too basic and it contains no uncertainty or validation against actual claims data. That said, by making the data available in the Oasis format and making it easily accessible to the insurance markets, it is more likely to be used and improved upon by certain companies and individuals.

In order to make the data more directly usable, the recommendations are:

Expand the event set in order to present more statistical relevance

Provide the actual historical event sets in Oasis format

Work with insurance companies to build a more representative set of vulnerability functions

to be combined with the expanded event set and validated against loss data

Build secondary uncertainty into the model – probably in the form of uncertainty

distributions around the vulnerability functions

9. Final note

On the basis of the observations made in this and other case studies, the WISC event set is being increased in size and calibrated against historical events. This will help to address some of the issues raised, though with the caveat that the WISC data does not set out to provide a stochastic event set as a direct alternative to those commercially available at present.

The resulting output will be described in the UK Met Office WISC case study, D5.5, which is planned to be available in mid-February 2018.


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ECMWF - Shinfield Park, Reading RG2 9AX, UK

Contact: [email protected]

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