We believe it is critical for Climate Wizard users to familiarize themselves with the strengths and limitations of the available data and the appropriateness of applying Climate Wizard’s various analytical techniques to any particular data set.
- What is Climate Wizard?
- Who can I contact for additional information?
- How do I move the map and zoom in and out?
- Can I change the base map?
- Can I change the map transparency
- What is Analysis Area?
- What is Historical Climate (Past 50 years)?
- What is Future Climate (Mid-Century and End-Century)?
- Why are the dates 2050s and 2080s for future maps?
- What is map of Average?
- What is Map of Change?
- How do I download and import map images in ArcGIS?
- What is IPCC Fourth Assessment?
- What are Emission Scenarios?
- What are General Circulation Models and where can I find more information?
- What is Ensemble in the General Circulation Models list?
- What does the graph show and what do the colored lines represent?
- How do I cite the data used in the Climate Wizard?
- What is the resolution, projection, and units of the data I downloaded?
- What is downscaling?
- I downloaded the data - How do I interpret the file names?
Developed through collaboration between The Nature Conservancy, The University of Washington, and The University of Southern Mississippi, the Climate Wizard enables technical and non-technical audiences alike to easily and intuitively access leading climate change information and visualize the impacts anywhere on Earth.
The first generation of this web-based program—which was recently launched at www.climatewizard.org—allows the user to choose a state or country and see both the climate change that has occurred to date and the climate change that is predicted to occur. Simply put, Climate Wizard can be used to assess how climate has changed over time and to project what future changes are likely to occur in a given area. Climate Wizard represents the first time ever the full range of climate history and impacts for a landscape have been brought together in a user-friendly format.
For general questions and information on development staff, please email firstname.lastname@example.org
Press the icon located to the upper left of the map. Then click and drag your cursor on the map to pan the image. You can also press the icon located in the upper left corner of the map. To zoom in double-click the map in the area you which to zoom. You can also press the icon located in the upper left corner of the map to zoom in and out and refresh the map to its original extent
Press the plus symbol located on the upper right of the map to reveal base map layer options such as satellite or streets view.
Drag the slider to reduce or increase the transparency of the climate map layer to reveal the elements of the base map image below
Use the pull-down arrow to quickly move to another state or country in the current map view.
We use the term historical when we refer to the real or actual climate conditions of the past. Maps created from thousands of geographically distinct recording stations using the PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate mapping system, developed by Dr. Christopher Daly, PRISM Group director. PRISM is a unique knowledge-based system that uses point measurements of precipitation, temperature, and other climatic factors to produce continuous, digital grid estimates of monthly, yearly, and event-based climatic parameters. For mor information please visit http://www.prism.oregonstate.edu.
We use the term future climate when we refer to projections of future temperature and precipitation regimes as modeled by complex mathematical representations of the general circulation of the planets atmosphere. Most models today relate temperature to emissions of greenhouse gasses and their corresponding concentrations in the atmosphere.
Meaningful statistical representations of modeled future climate predictions are best achieved by examining a range of time rather that a single year. We have chosen the time period 2040-2069 and 2070-2099 to provide the user with a range that most accurately describes the predicted conditions for the mid century (2050) and the end of the century (2100) respectively. Please read the Use and Misuse of Climate Data and Analysis for more information.
The map of average shows the mean temperature or precipitation value for the time period.
For maps showing the historical climate (present day and before) the “change” describes how climate has generally changed over time. This is a trend analyses that describes the average change in climate per year over a given entire period.
For maps showing the future predicted climate (present day and beyond) the “change” is a comparison between the future climate to a baseline time period (climatic departures). In the case of the Climate Wizard the baseline is the present-day conditions or more accurately the average temperature and precipitation between 1961 and 1990 -- (how different will the conditions be in the future from today?).
Data (GIS format) – This download option allows the user to save a GIS ready file to their computer. The format of the file is ASCII (float) which can be imported in most GIS applications. To import the data into ArcGIS follow the directions below:
1. In ClimateWizard, display exactly the data you want to download, then click the Data option from ClimateWiz menu. Save the file with .asc extension (if you don’t have this option, save as .txt and then rename the file with the extension changed to .asc).
2. In ArcGIS, open ArcCatalog, then open ArcToolbox.
3. In ArcToolbox, go to Conversion Tools→To Raster→ASCII to Raster→Input
ASCII Raster File. Navigate to your downloaded .asc file. Your Output Raster file
should be renamed with 13 letters or less, leaving the extension blank (this will give
you a GRID file, which is easiest to use for math). The Output Data Type must be
set to FLOAT.
4. In the ArcToolbox, go to Data Management→Tools→Projections and
Transformations→Define Projection. Select your new file for input.
5. Under Coordinate System, select Geographic Coordinate
6. The file is now ready to add to your ArcGIS project using the Add Data button.
Map Image – You can click on map image to open a separate web browser window showing only the climate map and legend (without the Google Earth background) or you can right-click on map image and save the graphics file to your computer.
The IPCC was established to provide the decision-makers and others interested in climate change with an objective source of information about climate change. The IPCC does not conduct any research nor does it monitor climate related data or parameters. Its role is to assess on a comprehensive, objective, open and transparent basis the latest scientific, technical and socio-economic literature produced worldwide relevant to the understanding of the risk of human-induced climate change, its observed and projected impacts and options for adaptation and mitigation http://www.ipcc.ch/. A suite of international modeling groups provided modeled climate projections that was used in this report; published in 2008.
A scenario is a coherent, internally consistent and plausible description of a possible future state of the world. It is not a forecast; rather, each scenario is one alternative image of how the future can unfold. A projection may serve as the raw material for a scenario, but scenarios often require additional information (e.g., about baseline conditions). A set of scenarios is often adopted to reflect, as well as possible, the range of uncertainty in projections. Other terms that have been used as synonyms for scenario are "characterization", "storyline" and "construction". (http://www.ipcc-data.org/ddc_definitions.html). Look here or more information on Emission Scenarios
Climate models use quantitative methods to simulate the interactions of the atmosphere, oceans, land surface, and ice. They are used for a variety of purposes from study of the dynamics of the weather and climate system to projections of future climate. All climate models balance, or very nearly balance, incoming energy as short wave electromagnetic radiation (visible and ultraviolet) to the earth with outgoing energy as long wave (infrared) electromagnetic radiation from the earth. Any imbalance results in a change in the average temperature of the earth. Look here or more information on General Circulation Models. The following is a list of the models presented in the Climate Wizard. This list is extracted from the information provided by the Program for Climate Model Diagnosis and Intercomparison Coupled Model Intercomparison Project (CMIP3) Climate Model Documentation website.
|BCCR-BCM2.0||Norway||Bjerknes Centre for Climate Research|
|CGCM3.1(T47)||Canada||Canadian Centre for Climate Modelling & Analysis|
|CNRM-CM3||France||Météo-France / Centre National de Recherches Météorologiques|
|CSIRO-Mk3.0||Australia||CSIRO Atmospheric Research|
|GFDL-CM2.0||USA||US Dept. of Commerce / NOAA / Geophysical Fluid Dynamics Laboratory|
|GFDL-CM2.1||USA||US Dept. of Commerce / NOAA / Geophysical Fluid Dynamics Laboratory|
|GISS-ER||USA||NASA / Goddard Institute for Space Studies|
|INM-CM3.0||Russia||Institute for Numerical Mathematics|
|IPSL-CM4||France||Institut Pierre Simon Laplace|
|MIROC3.2(medres)||Japan||Center for Climate System Research (The University of Tokyo), National Institute for Environmental Studies, and Frontier Research Center for Global Change (JAMSTEC)|
|ECHO-G||Germany / Korea||Meteorological Institute of the University of Bonn, Meteorological Research Institute of KMA, and Model and Data group.|
|ECHAM5/MPI-OM||Germany||Max Planck Institute for Meteorology|
|MRI-CGCM2.3.2||Japan||Meteorological Research Institute|
|CCSM3||USA||National Center for Atmospheric Research|
|PCM||USA||National Center for Atmospheric Research|
|UKMO-HadCM3||UK||Hadley Centre for Climate Prediction and Research / Met Office|
Climate change analysis becomes more complex for the future than the past because there is not one time-series of climate, but rather many future projections from different GCMs run with a range of CO2 emissions scenarios (IPCC 2007b). It is important not to analyze only one GCM for any given emission scenario, but rather to use ensemble analysis to combine the analyses of multiple GCMs and quantify the range of possibilities for future climates under different emissions scenarios. There are many approaches for doing ensemble analysis ranging from simple averaging approaches to more complex and computationally intensive probability estimation approaches (Dettinger 2006, Araujo and New 2007). Here, we used a fairly simple, yet informative non-parametric quantile-rank approach that maps out the 0 (minimum), 20, 40, 50 (median), 60, 80, and 100th (maximum) percentiles (Figures 6 and 7). While all models agree that mean temperatures will increase everywhere in the world (Figure 6), they often do not agree on the magnitude of that increase. The term Ensemble Average located in the General Circulation Model (GCM) pull-down list on the ClimateWizard home page displays the 50th percentile or median prediction of all subsequent GCMs listed.
The graph shows the yearly values of the climate variable selected. The blue line is the 5-year rolling average. The red line is the shows the trend or rate of change over the time period shown (see FAQ 10)
The primary citation for the Climate Wizard Custom Analysis Application can be found here - Applied Climate-Change Analysis: The Climate Wizard Tool. Please see the citations page available form the Climate Wizard home page. AboutUs.html For further questions please contact email@example.com
The grid cell resolution of the GIS data is indicated on the Climate Wizard data information page documentation.html. The projection and units correspond to Geographic, WGS 84.
The following was taken from Maurer, E. P., L. Brekke, T. Pruitt, and P. B. Duffy (2007), Fine-resolution climate projections enhance regional climate change impact studies, Eos Trans. AGU, 88(47), 504 and describes the data presented the the ClimateWizard:
A statistical technique was used to generate gridded fields of precipitation and surface air temperature over the conterminous United States and portions of Canada and Mexico. The method involves (1) a quantilemapping approach that corrects for GCM biases, based on observations of 1950–1999; and (2) interpolation of monthly bias-corrected GCM anomalies onto a fine-scale grid of historical climate data, producing a monthly time series at each 1/8-degree grid cell. The method has been used extensively for hydrologic impact studies (including many with ensembles of GCMs) and in a variety of climate change impact studies on systems as diverse as wine grape cultivation, habitat migration, and air quality.
The downscaled data are freely available for download at the Green Data Oasis, a large data store at LLNL for sharing scientific data (http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/).
Users can specify particular models, emissions scenarios, time periods, geographical areas, and raw data or summary statistics. All data are archived in a standard netCDF format, a self-describing machine-independent format for sharing gridded scientific data. The full text of this article can be found in the electronic supplement to this EOS issue (http://www.agu.org/eos_elec/).
The ascii files you download follow the naming conventions described below:
Historical analyses: name = DataType_VariableName_Month_StartYr_EndYr
Future analyses: name = DataType_ModelName_ScenarioName_VariableName_Month_StartYr_EndYr
|Month Number||Month Name|
Variable names, abreviations, and units
|Variable||Abbrevation||Metric Units||English Units|
|AET (Actual Evapotranspiration)||aetHam||Millimeters||Inches|
|PET (Potential Evapotranspiration)||petHam||Millimeters||Inches|