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ZineQx Climate Change
Introduction Climate Change
Risk Losses

Modelling Climate Change Risks

Committed To Securing Livelihoods


Simulating Current & Future Impacts Associated With Climate Change

Climate change is undoubtedly the greatest threat humanity is facing. Degradation of terrestrial and marine ecosystems as a result of increase frequency, duration and intensity of droughts, wild fires and hydro-meteorological disasters that are invariably associated with local urbanisation, global industrialisation, anthropogenic emissions and ultimately global warming and climate change. To mitigate the risk and vulnerability associated with the effects of climate change and global warming governments, institutions and industries must embrace (international) climate policy as highlighted by the IPCC (Intergovernmental Panel on Climate Change). The development of these policies requires long-term planning and scenarios-based modelling that take the human and environmental inertia into account. Ultimately goal is resilience, which can be obtained through adaption and by limiting future warming and reducing emissions.

Our ZineQx is a data driven innovative science-based solutions or integrated assessment, mitigation and adaptation framework that  

analyses the socio-economic effects of climate change induced and natural hazards in situations where outcomes are uncertain. Our assessments models compare risk under intermediate, near-future and far-future climate conditions across various sectors and industries in the global interconnected economy.

Infinite Observations has various coupled datasets such as climate, atmospheric concentration of greenhouse gases, variation in sea surface temperatures (SST’s) as a result of El Nino & La Nina (ENSO), Atlantic Multidecadal Oscillation (AMO), Teleconnections, population, socio-economic, infrastructural and much more datasets. These large coupled data set are needed to onderstand the increasing losses from physical, transitional, and liability issues related to climate risk and thoughtfully prepare emergency, operational and strategic resilience responses that meet the challenges and needs of governments and every other type of organisation.

Climate Catastrophe Modelling

Assessing and Quantify Climate Change Current and Future Impacts

We understand the crucial role that data and technology play in climate risk mitigation and your ability to accurately assess and economic implications the risk. ZineQx, Infinite Observations event risk modeling platform, can help you quantify the threats you’re facing from the current and near-future climate. Find out which perils are your main loss drivers, where your risk is increasing, and what it will look like in 10, 20, or 30 years. The first three topics: Types Of Models, Model Computational Technology, Model Validation covers Climate Models. The other 6 topics considers Catastrophe Modelling. No climate or catastrophe model are currently capable of covering every peril in every region.  Models can be put to different uses. Modelling results can be used to develop insight about a particular hazard or system or to make projections of future climate scenario’s. Often a suit of catastrophe models or an ensemble of climate models are used rather than a single model because of the acknowledged limits and/or uncertainties in individual models.

Types Of Models

First there is the Energy-Balance Model (EBM), based on the simple principle that incoming and outgoing radiation must be in equilibrium. Then there are the more complex Global Circulation Models (GCM’s) these are sophisticated  models with horizontal and vertical grids (of both atmosphere and ocean) that uses mathematical dynamical equations to describe the flow of physical quantities, i.e. heat or vapour fluid, of climate processes. Powerful high-performance computing (HPC) is needed the equations, which are typically are intractable with analytical methods.

Model Computation Technology

In essence climate modelling is an extension of weather forecasting that focuses on changes over decades rather than hours. There are currently a number of complex climate models, which are under continuous development by leading national agencies and institutions like NASA or the Swiss National Supercomputing Centre (CSCS) that have HPC facilities. Early computer models were too coarse inhibiting the modelling capabilities. Increase computational power over the years, i.e. GPU technology, has enabled the incorporation of smaller scale processes because of their higher resolution all at lower cost.

Model Validation

Assessing and validation of the performance of models during the historical period, quantifications of the causes of spread in future projections of model outputs and having idealized experiments to increase understanding of the responses of models are some of the objectives of the Coupled Model Intercomparison Project (CMIP). A suite of other stand and non-standard experiments for each climate model, i.e. the predictability of the climate system on various spatial and/or temporal scales, making predictions regarding observed climate states as well as making (multi-)model output publicly available (see IPCC publications).

Climate Conditioned Catalogues

Climate conditioning means that a climate hazard (cyclone, drought, flood, wildfire, windstorm, tornado, etc.) is dependent on climate scenarios predicted by the ensemble climate models. The hazard model will generate new stochastic events and in turn this collection of stochastic events forms a climate conditioned catalogue for a particular hazard.

Probabilistic Risk Assessment

When spatial and temporal factors are taken into consideration climate conditioned catalogues can be used for probabilistic risk assessment. The model yields a variety of economic results, the most common of which are the Annual Average Loss (AAL), probable maximum loss (PML) for different return periods and the Exceedance Probability (EP) Curve.  

Industry Specific Exposure Data

To analyse the risk more accurately characteristics of a particular geographic location and reference period in the future such as population (human and/or livestock), dwelling, building counts, contents, inventory, and income and classification, structural characteristics, structural and industry classes, building codes, regulations, elevation and vegetation are necessary to quantify losses.

Climate Change Vulnerability Indices

Assets of region or countries can be ranked to what extent they have been or can be affected by climate related extreme hazards.  These indices can be used to evaluate the vulnerability, resilience, adaptation and mitigation strategies or the coping capacity or robustness, of human populations and environment to extreme climate events that corresponds to projection over the next 10, 30, 50 or 80 years. These indices can be used by government and investors to quantify future risk from climate change.

Macro Economic Scenarios

Climate change is an adverse external shock to any economy. Unlike weather, which is temporary, the trend of climate change is expected to be associated with greater volatility. It will likely have a downward effect on output, an upward pressure on prices and influence demand and supply of products. In the short-term adaptation measures may boost infrastructure investments. However, in the long-term trade may be affected by transportation and infrastructure disruptions. Income prospects and other macro-economic indicators may be adversely  effected as well. 

Stress Testing

Both  climate and catastrophe models can be stress tested. The use of stress testing, which is one of the key methodologies, to measure climate-related risks is a relatively new development and one, which should be actively explored. The objective of climate change stress testing, in the case of a hazard model, is to assess how various climate scenarios derived from modified exceedance probability (EP) curves translate into climate-related risks and how these risks impact geographical locations, country, governments, organisations, businesses, societal factors, etc. 


Climate Catastrophe Modelling

Identifying & Quantifying Climate Risks

Climate change is increasingly influencing the frequency and intensity of the impact of natural catastrophes hazards on assets, society, and the financial ecosystem, known as physical climate risk which creates both acute and chronic threats. These acute threats are caused by extreme weather events and can be categorise as Meteorological: tropical cyclones or hurricanes, severe thunderstorms, extratropical cyclones or winter storms, etc. Hydrological: storm surge, riverine (fluvial) and rain induced (fluvial) flooding. Climatological: extreme heat or cold spells, drought, wildfire, etc. Chronic threats are related to shifts in climate related patterns which impact cascading effects on food production, real estate valuation, water scarcity and population migration. They can be categorised as sea Level Rise: coastal inundation, Precipitation: chronic flood, dearth of water (or abnormally low rainfall) and Temperature: sustained shifts in cold or heat.

Accurate Data Driven Models

Understanding how climate change will impact assets, society, and the financial ecosystem, both now and into the future under multiple climate change scenarios up to the end of the century is an extra ordinary task. This information is crucial for longer-term decision making and planning to prepare for catastrophes. The first challenge is to translate natural hazards as a result of climate change into metrics that describes physical climate risk exposure, sustainability risk, and climate transition. Those insights will also be needed to capture future climate change risk with specific time horizons in combination with Representative Concentration Pathway (RCP) scenario for future greenhouse gas concentrations that will help drive strategic decision-making. Our models are calibrated to represent the scientific consensus on climate risk drivers and outcomes related to specific time horizons and emission pathways. Levels of uncertainty in our models are also taken into consideration. Our models increases confidence of our clients in their ability to effectively manage climate change risk using the conventional average annual loss metric, which is the industry loss standard.

Associated Perils

Infinite Observations offers a broad spectrum of climate change related solutions and insights from the identification of climate risk to the quantification and validation of associated losses as well as analytics.


Global trade in the agriculture plays a crucial role in delivering clothing and food to consumers worldwide and it played a vital role in reducing food insecurity. However, this and many …


Large commercial construction projects, civil structures (bridges, levees and tunnels) as well as private homes are exposed natural and man-made disasters. Estimate the losses …


Tropical cyclones, which are also known regionally as hurricane, cyclones or typhoons contribute significantly to the global annual natural disaster losses. Infinite Observations …


Rain-fed agriculture, crop yield, livestock, food security, hydroelectricity, biomass and other economic and social sectors are impacted by altered precipitation patterns as a result of …


Flood damage accounts for an increasing amount of catastrophe losses as a result of our changing climate. As more and more of the global population and wealth are …


Primarily North America, Europe and Northern Asia are affected by hazards such as winter storms and blizzards. The damage as a consequence of a major winter storm can …

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Explore Our Catastrophe Solutions To Manage Climate Risk