Statistical Analysis and Climate Analytics

Supporting Climate Adaptation and Mitigation Efforts with Expertly Modeled, Analyzed and Interpreted Climate Projections  

Although climate models are constantly being improved, they are not yet good enough to predict future climate conditions with a degree of confidence which would allow precise adaptation decisions to be made. Uncertainties in climate variability, future society, the scale of future greenhouse gas emissions, and scientific knowledge on how components of the climate system interact, all lead to uncertainty in climate projections. Outputs from different climate models can disagree on both the degree and sign of change in a climate variable, presenting users with a wide range of possible climate futures to deal with.

Should engineers try to choose and use what they regard as the best projection? Or should they use all the projections to build infrastructure that is prepared for anything that may come, even though it may prove more costly? Currently, an increasing societal demand to anticipate the future impacts and costs of climate change challenges the practice community since projections of climate change impacts should be based on a robust and reliable climatological input. To estimate the bandwidth of possible future design values, a balanced and unbiased estimate of the entire distribution of possible future changes is required. This bandwidth is often estimated by driving impact models with few selected climate scenarios, the selection being largely subjective or determined by practical reasoning such as availability. Such uninformed practice can lead to biased results or not addressing the pertinent uncertainties at all, thus, a poorly informed adaptation response.

There are many types of climate change projections data available and choosing the right data for the right purpose is an important part of undertaking impact assessments. At CLIMALOGIK, we develop project-specific statistical and analytical tools for selecting the climate input for climate change impact assessments in a more objective way, which aims to avoid sampling biases, to properly account for uncertainties and to save computational resources. Data is acquired by taking measurements, reviewing historical records, producing climate model output, or by examining indirect information, such as tree rings. For every project we gather the required data, or work with the data you provide.

Our areas of expertise include:

• Exploring, Analyzing, and Visualizing Large Multidimensional Climate Model Outputs
• Bias Correction of Climate Projections
• Statistical Extrapolation of Historical Climate for Projects of <15 years Design Life
• Univariate and Multivariate Climate Time Series Analysis
• Analysis of Diurnal, Seasonal and Interannual Climate Variability  
• Identification of Project-based Future Planning Horizons (e.g., 2050s, 2080s)
• Selection of Appropriate Climate Scenarios and Models
• Bayesian Model Averaging and Uncertainty Analysis of Climate Projections
• Integration of Climate Data Sources and Indices into Risk Assessment Frameworks
• Development of Climate Risk Assessment Software