A new way of viewing climate impacts is through a more dynamic lens that includes risk perception and societal responses such as through adaptation and policy interventions. Downscaling refers to a range of techniques that allow scientists to bridge the gaps between climate model resolution and that of local-scale processes by taking information from climate models and reworking that information to become useful at the local scale to represent local-scale processes. Climate attribution is the science of determining the causes of unusual climate trends and climate-related events. Climate attribution is particularly linked to human activity, specifically through the burning of fossil fuels that warms the atmosphere. The Agricultural Model Intercomparison and Improvement Project (AgMIP) and the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) are two examples of relevant projects shown below, as well as informational videos on downscaling and attribution.
Climate & Weather Extremes: Attribution and Risk
Speaker: Kevin Trenberth, NCAR
Date aired: 4 July 2016
About: NCAR Distinguished Senior Scientist Kevin Trenberth shares the science of attribution, especially in terms of weather extremes, and notes that scientists strive for 95% confidence level, which is a high burden of proof. Today, he believes, that climate change impacts all weather-related extremes to a certain degree, especially those involving water or lack thereof, and certainly temperature extremes. The question is not “if” but rather “to what degree.”
Downscaling and Uncertainty
Speakers: Hayley Fowler, Newcastle University; Linda Mearns, NCAR
Date aired: 28 July 2014
About: This talk will examine the downscaling concept; providing an overview of different types of downscaling methods and the results from comparative studies, including the relative value and uncertainties of different techniques. We will explore the kind of studies we need to perform to resolve the uncertainties in downscaling and give examples of state-of-the-art studies in both statistical and dynamical downscaling. This will include the weather generator from UKCP09 as an example of statistical downscaling and results from NARCCAP (North American Regional Climate Change Assessment Program) and the Co-ordinated Regional Climate Downscaling Experiment (CORDEX) as examples of multi-model ensembles of regional climate models (RCMs). Some recent results will also be shown that detail uncertainties that can be resolved by increasing model resolution(down to ~2km) using models such as WRF, and the effect of different GCM boundary conditions and initial conditions upon downscaling results, including results from CMIP5.
Climate Change Explained: Human Attribution
Speaker: Friederike Otto, IPCC Lead Author
Date aired: 10 November 2021
About: There is only one way we can explain the rise in global temperatures. When we burn fossil fuels, we have more greenhouse gases in the atmosphere with the property to absorb radiation, making the atmosphere warmer. How do we know that it’s human-caused climate change that is responsible for these observed changes? We can use state-of-the-art climate models and simulate what is possible weather in the world we live in today.
Introduction to the Agricultural Model Intercomparison and Improvement Project (AgMIP).
Date aired: 17 October 2016
About: Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking climate, land use, livestock, and economic models to create integrated assessments of climate change impacts on farming systems, both regionally and globally. It allows for a better historic and futuristic understanding of productivity, adaptation, income, vulnerability, and food security. The goal is to provide consistent, rigorous, and quantifiable information for decision-makers, and develop the next generation of Agricultural Systems Models with a global community. Click here to learn more.
Introducing the Intersectoral Impact Model Intercomparison Project
Speaker: Katja Frieler, Stefan Lange, Jacob Shewe, Matthias Büchner, Jochen Klar, Iliusi Vega del Valle, Potsdam Institute for Climate Impact Research; Inga Menke (Kaylin Lee), Climate Analytics
Date aired: 17 December 2020
About: ISIMIP provides a framework for the collation of a consistent set of climate impact data across sectors and scales. This framework will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity for considering interactions between climate change impacts across sectors through consistent scenarios.
This webinar provides a general introduction to ISIMIP, 2-3 recent scientific highlights of cross-sectoral impact studies, an introduction to the ISIMIP infrastructure and workflow, and an introduction to our climate service platform ISIpedia.