CCSM3 / HadCM3

•Under predict precipitation rate nearequator regions

•CCSM3under predictsgreater in SEU.S. thanHadCM3

Methodology and Results

•Interpolate data from CCSM3 and HadCM3 with NCEP1•Southeast U.S. region: Lat 24 °N - 41 °N Lon 95 °W - 74 °W•Create global and regional graphs•Statistical analysis MATLAB 2007:

1. Mean2. Standard deviation3. Variance4. Skewness5. Median6. Bias = Observations – Climate models

•Construct plots using Microsoft OfficeExcel 2007

Introduction

Climate change may cause or worsen extreme precipitation events. These events have the potential to produce localized or widespread hydrological processes. However, precipitation remains among the most difficult to predict from climate and atmospheric models.

Objectives

• Use statistical analysis to describe two climate models used by the Intergovernmental Panel on Climate Change (IPCC)

• Obtain uncertainties from climate model simulations and observations

• Compare climate models with observations

Resources

Figure 1: MATLAB 2007 used in statisticalmethods and graphs for climate data.

Figure 2: Microsoft Excel 2007 used incalculations and data plotting.

Reference1. Auroop R. Ganguly, Shih-Chieh Kao, Karsten Steinhaeuser, Esther S. Parish, Marcia L.Branstetter, David J. Erickson III, and Nagendra Singh. Uncertainties in the Assessmentsof Climate Change Impacts on Regional Hydrology and Water Resources. (2009: In Review).2. Intergovernmental Panel on Climate Change (IPCC). Fourth Assessment Report: 2007.

CCSM3CCSM3

HadCM3HadCM3

NCEP1NCEP1

Future Research

• Test accuracy of CCSM3 and HadCM3 in other regions

• Propose safety measures for areas of high precipitation rates

Conclusions

•Global scope1. CCSM3 over predicts2. HadCM3 over predicts3. CCSM3 more accurate

•Southeast U.S.1. CCSM3 under predicts2. HadCM3 under predicts3. HadCM3 more accurate

Figure 6: Average precipitation rate in United States Southeast from 1948 to 1999.

Figure 3: (A, B) Grid based global analyses of the bias(observed minus modeled) in precipitation rates (CCSM3and HadCM3 versus NCEP1). (C, D) Bias in precipitationrates in the SE region of the U.S, based on comparisonsof climate models with observations (reanalysis).

Figure 4: Global and SE U.S. averageprecipitation rates from 1948 to 1999per month.

Figure 5: Global and SE U.S. average precipitation rates per year from 1948 to 1999.

Table 1: Southeast U.S. and global statistical results forCCSM3, HadCM3, and NCEP1 (All values were analyzed from mm/s data).

The Research Alliance in Math and Science program is sponsored by the Office of Advanced Scientific Computing Research, U.S. Department of Energy. The work was performed at the Oak Ridge National Laboratory, which is managed by UT-Battelle, LLC under Contract No. De-AC05- 00OR22725. This work has been authored by a contractor of the U.S. Government, accordingly, the U.S. Government retains a nonexclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for U.S. Government purposes.

I would like to thank Dr. Auroop R. Ganguly for the opportunity to work on this project. Also, I would like to thank Shih-Chieh Kao, Karsten Steinhaeuser, the GIST Group, and Rashida E. Askia for their continued support. Finally, special thanks go to Debbie McCoy, who made provisions for this research experience along with exceptional professional support.

Global and U.S. Southeast Assessment of Precipitation: Comparison of Model Simulations from the Intergovernmental Panel on Climate Change with Reanalysis-based Observations

Eduardo Ponce MojicaPolytechnic University of Puerto RicoResearch Alliance in Math and Sciencehttps://info.ornl.gov/sites/rams09/e_ponce_mojica/Pages/default.aspx

Mentor: Dr. Auroop R. GangulyOak Ridge National Laboratory

Computational Sciences and Engineering DivisionCollaborators: Shih-Chieh Kao and Karsten Steinhaeuser

Climate ModelsCommunity Climate System Model, version 3 (CCSM3)

Hadley CenterCoupled Model,version 3 (HadCM3)

ClimateObservationsNational Center for EnvironmentalPrediction, reanalysis 1(NCEP1)

•CCSM3 underpredicts average precipitation rate in SE U.S.•HadCM3 underpredicts average precipitation rate in SE U.S.

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