High-resolution research data for climate change studies

In collaboration with a broad range of public and private laboratories and universities, the mission of the Regional Integrated Science Collective (RISC) is to generate high-quality regional-scale scenarios of projected climate change, then develop tools and methods for analyzing impacts, vulnerability, and adaptation options. RISC’s placement in IMAGe shows the close ties between evaluating climate models and quantifying uncertainty using statistics. RISC also reaches out to the broader decision-making and policy communities by integrating mathematical analyses into a more immediate and pragmatic realm. RISC has responsibility for serving large and multifaceted numerical experiments, so it is well aligned with CISL’s mission of data support to the climate science community.

A centerpiece of RISC’s activity has been its leadership of the North American Regional Climate Change Assessment Program (NARCCAP). NARCCAP is systematically investigating the uncertainties in regional-scale projections of future climate. It is unique in its balanced design that allows for isolating the influence of individual regional and global models on the resultant climate simulations. The overall goal of NARCCAP is to produce high-resolution (50 km) climate change scenarios using six regional climate models (RCMs) nested within four atmosphere-ocean general circulation models (AOGCMs) forced with the A2 SRES emission scenario, over a domain covering the conterminous U.S., northern Mexico, and most of Canada. The project also includes an evaluation arm whereby the participating RCMs are forced by reanalysis data sets. The resulting regional climate model runs and time slices form the basis for multiple high-resolution climate scenarios that can be used in climate change impacts assessments in the U.S. and Canada. In FY2015, work related to NARCCAP has entailed further application of the data to numerous adaptation contexts (see below).

Further analyses and data products development using NARCCAP

RISC’s activities include the development of a number of data products and services to support the users of data from NARCCAP. These will also be useful for future anticipated high-resolution regional climate simulations such as those being developed in North American CORDEX (see below). Seth McGinnis has been collaborating with CISL’s VETS group to help guide the development of next-generation data services that will enable users of output from Big Data projects like NARCCAP to access the data they need without downloading large volumes of unwanted data to get it. These new service capabilities include spatial and temporal subsetting, file spanning, aggregation, and format conversion.

Simulation data bias correction

Having identified bias correction as an important need of NARCCAP users, especially for impacts analysis, RISC has been working to bias-correct NARCCAP output using distribution mapping techniques. This work breaks new ground by applying the methods to daily data rather than monthly or seasonal climatologies. Seth McGinnis has developed a novel technique for distribution mapping called Kernel Density Distribution Mapping (KDDM). KDDM makes use of well-established statistical methods to perform distribution mapping using non-parametric estimates of the probability distributions underlying the data sets to be bias-corrected. This technique has been evaluated against existing techniques by use of an oracle analysis, wherein each technique is used to bias-correct synthetic data and the result is compared to a perfect correction, or “oracle.” KDDM performs very well according to multiple metrics, and has the best performance on non-idealized data. It is also fast, robust, flexible, and conceptually straightforward. These results have been published in the proceedings volume for the 2014 Climate Informatics Workshop, and plans have been developed to improve on basic KDDM by refining the correction of extremes of daily temperature and precipitation.

Evaluation of the North American Monsoon in the NARCCAP simulations

Melissa Bukovsky has led, in collaboration with Dave Gochis in RAL, the evaluation of how well the NARCCAP models reproduce characteristics of the North American Monsoon (Bukovsky et al., 2013, J. Climate) and has pursued an investigation of the effect of model errors on the future projections of climate in this area. New findings this year (Bukovsky et al., 2015) include the fact that the least-credible models produce the largest decreases in precipitation, whereas the “best model” produces little change in precipitation (see figure below). This result is particularly noteworthy since strong relationships between biases in current period simulations vs. changes in precipitation in the future are rarely seen.

Heat stress

RISC scientists continue to collaborate with scientists from the IAM group in CGD to produce analyses of heat waves based on CESM simulations. The new study (Anderson et al., 2015), part of the BRACE series of papers, finds that considerable reduction in urban heat waves are found when following the RCP4.5 scenario as opposed to RCP8.5. The role of RISC was to apply the KDDM bias correction method to the CESM output (S. McGinnis).

Development and provision of climate information including uncertainty measures for adaptation research

RISC is currently engaged in three different research projects concerning adaptation to climate change at local and regional scales. These projects include one funded from NSF EaSM, “Informing Climate Related Decisions with Earth System Models,” led by RAND; and two funded through the DoD Strategic Environmental Research and Development Program (SERDP): “Decision-Scaling: A Decision Framework for DoD Climate Risk Assessment and Adaptation Planning,” led by U. Massachusetts, and “Understanding Data Needs for Vulnerability Assessment and Decision-making to Manage Vulnerable DoD Installations to Climate Change,” led by PNNL. All three concern decision-making and more specifically risk management under various conditions of uncertainty, including that of climate. All three projects rely to some degree on the NARCCAP simulations in various resource management contexts. The EaSM project specifically considers ecological and water resources in the U.S. East and West, while the two SERDP projects consider a range of resources and climate conditions relevant to U.S. military bases (in the Southeast, mid-Atlantic, Texas, the Front Range of Colorado, and southern California) such as heat stress, flooding, changes in available water resources, and wildfire potential. A Climate Outlook for the mid-Atlantic region has been completed, which is relevant to four of the sites being investigated. It is a challenging area for the development of future climate scenarios, since it is a region of transition between wetter future scenarios to the north and drier scenarios farther south.

Drought analysis
Box plots of change in number of days when the KBDI (see text) exceeds 600 (severe fire danger) at Fort Hood, Texas using four different methods to downscale and/or bias-correct the NARCCAP climate information. The four methods are raw, using NARCCAP output directly (no correction); fix, bias-corrected NARCCAP data using KDDM; delta, adding mean monthly climate changes to daily observed data (using the standard delta method); and SDSM, using a linear regression approach relating large-scale features from driving GCMs to local daily climate.

An additional aspect of the work in the Decision Scaling SERDP project is comparing the effect of using different downscaling methods to determine changes in impacts. The effect of different downscaling methods on climate impacts has been underexplored in the literature. Rachel McCrary has led the effort to look at the effect of different methods on the determination of future wildfire potential. The Keetch-Byram Drought Index (KBDI), used by the USDA Forestry Service, was calculated for current and future conditions using the 12 NARCCAP simulations as the basic climate information. The four methods investigated included: 1) using the raw output of the regional climate models, 2) using the “delta” approach, 3) using the RCM data corrected via KDDM, and 4) using SDSM, a regression-based method that relates large-scale climate variables from the four GCMs used to drive the NARCCAP RCMs to local-scale daily temperature and precipitation. The figure below shows changes in the number of days with extreme fire danger (KBDI > 600) for Ft. Hood, Texas. Note that while the medians for the four methods are similar, the SDSM method produces much larger variability. Analysis is underway to determine the causes of the method-based differences.

Development of NA-CORDEX

The Co-ordinated Regional Climate Downscaling Experiment (CORDEX) has been ongoing for several years. North America CORDEX, while in existence for three years, has been slow to advance through production of simulations due to lack of sufficient funding from U.S. funding agencies, yet simulations continue to be performed. (Linda Mearns and William Gutowski of Iowa State are co-Chairs of NA-CORDEX.) In collaboration with Iowa State and the University of Arizona, simulations are being performed for a 150-year time period (1950-2100) over approximately the same domain as that of NARCCAP, with two different regional climate models, at both 50- and 25-km resolutions, using ERA-Interim boundary conditions, and boundary conditions for three different GCMs that span the equilibrium climate sensitivity of the CMIP5 collection of global climate models. Specifically in RISC, Melissa Bukovsky has produced RCM simulations at 25 and 50 km using the Max Planck Institute global model boundary conditions for the RCP 8.5 concentration pathway. This results in a 2 x 2 x 3 matrix of simulations. Other simulations have been produced by other groups, most notably in Canada using the Canadian regional climate model (CRCM). The NA-CORDEX website (na-cordex.org) lists all simulations being performed. Plans have been made to develop an archive of surface variables from all simulations at NCAR next year.

WCIASP

RISC also maintains and develops the Weather and Climate Impacts Assessment Science Program (WCIASP). WCIASP has three primary thrusts: investigating uncertainty in climate change research, studying extreme weather and climate events and their impacts, and supporting the Climate and Health Workshop series. WCIASP funded projects throughout NCAR, particularly in CGD, RAL, and in IMAGe.

Funding

The Regional Integrated Science Collective (RISC) and Weather and Climate Impacts Assessment Science Program (WCIASP) are primarily supported by NSF Core funding as well as interagency support for NARCCAP and the use of NARCCAP results for adaptation planning from NSF, NOAA, NASA, and DoD.