This module describes the process of selecting the best available climate projection information and using it to develop “climate-adjusted weather” inputs to be used for modeling climate change impacts. These modeled impacts can be used for planning of future water resources. Specific steps of this process include: 1) Recognizing the general science and terms associated with Atmosphere-ocean General Circulation Models (AOGCMs); 2) Making AOGCMs more regionally applicable through bias correction and downscaling; 3) Determining climate change scenarios based on climate projections and selecting specific projections to inform each scenario; and 4) Developing climate-adjusted weather inputs associated with each climate change scenario.
Determine weather and climate processes that are relevant to the client’s long-term questions about surface hydrology or crop irrigation requirements.
Explain climate change process and recognize terminology
Distinguish between weather and climate
Distinguish between natural climate variability and climate change
Explain emissions scenario versus climate change scenarios
Justify use of climate projection information in study
Identify and explain issues associated with model resolution and regionalizing, especially with respect to downscaling and bias correction.
Locate relevant climate projection information and model data (that may or may not have been downscaled and bias-corrected)
Explain what BCSD data are.
Evaluate the utility of projection information in portraying the relevant processes; defend the approach taken for downscaling and bias correction
Differentiate between dynamic and statistical downscaling
Explain possible limitations of bias correction procedure using bias correction factors derived in historical period
Make big-picture decisions on how climate projections will be incorporated into the report
Identify relevant climate periods (historical and future periods)
Identify sources of uncertainty in the data
Assess the central tendency and spread of projected changes in precipitation and temperature over the region of interest
Choose appropriate time steps for characterizing general climate trends as manifested by precipitation and temperature.
Evaluate central tendency of temperature and precipitation trends for all model projections taken together.
Choose the period change method.
Determine how you will define spread.
Determine climate change scenarios and select projections to inform each climate change scenario
Explain advantages and disadvantages of defining climate change scenarios informed by single projections versus being informed by an ensemble of projections
Develop monthly climate-adjusted weather inputs for future surface water hydrology analysis (or crop irrigation requirements) that reflect an appropriate blend of historical observations with simulated trends.
Recognize attributes of the observed weather inputs used to develop the climate adjusted weather inputs.
Prepare scenarios of future weather inputs corresponding to climate change scenarios, that reflect variability from the observed weather and trends from climate simulations.
Prepare results using both the Delta (single projection informed) and ensemble informed Delta methods.
Disaggregate monthly climate-adjusted weather inputs into daily climate-adjusted weather inputs.
Hydro-climate, Hydro-climate inputs, Climate model, climate projection, climatology, emissions scenario,climate change scenario, climate variability, climate change, water resources planning, climate change impacts, surface water hydrology, crop irrigation requirements, initial value, boundary value, anthropogenic, global climate model, International Panel on Climate Change, IPCC, Assessment Report 4, IPCC AR4, IPCC Assessment Report 5, AR5, IPCC emissions scenario, GCM, AOGCM, coupled atmosphere-ocean general circulation model, general circulation models, global circulation model, global climate model, Special Report on Emissions Scenarios, SRES, RCP, Representative Concentration Pathways,
bias correction, bias adjustment, spatial downscaling, statistical downscaling, dynamic downscaling, Bias Correction and Spatial Downscaling Method, BCSD, climate projection ensembles, projection ensembles, CDF, cumulative distribution function, regional climate model, RCM, wet bias, dry bias, time series, ensemble time series, detrending, SYMAP method,
Central Tendency, Spread, Simulation Mean, Period Change, period change method, temperature time series, precipitation time series, single projection, ensemble of projections, transient method, historical period, future period, climate simulations, historical simulation, climate study, time series trends,
climate impact model, climate impacts model, climate-adjusted weather, climate-adjusted weather inputs, daily climate weather, as if approach, monthly climate weather, delta method, ensemble informed delta method, change factor, daily climate
Part 1 of this 5-part lesson was revised slightly in 2016 to acknowledge the latest information associated with IPCC Assessment Report 5, AR5. The methodologies demonstrated in parts 2-4 are still based on the IPCC AR4 report which used the Coupled Model Intercomparison Project 3 (CMIP3) models. One can use the CMIP5 models associated with IPCC AR5 (2014) and apply the same methodologies described in this lesson.
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