Validating climate models for computing evapotranspiration in hydrologic studies: how relevant are climate model simulations over Florida?
- 314 Downloads
A non-stationary climate requires a new paradigm in the current practice of using past observations for future planning. Next to precipitation, evapotranspiration is the most important variable in water budgets of regions such as Florida, the location of this study. Dynamical simulations using Regional Climate Models (RCMs) provide all the variables necessary to compute potential or reference crop evapotranspiration (RET) for hydrologic modeling under climate change scenarios. Data sets for the variables necessary to compute RET using the Penman–Monteith model were obtained from RCMs provided by the North American Regional Climate Change Assessment Program to evaluate their skills in estimating RET during the late twentieth century simulations. Comparison of RET values simulated from RCMs with those computed from a high-resolution weather-monitoring network and satellite data show significant biases in spatial patterns and seasonality. In particular, seasonal patterns of RET computed from RCMs show a phase shift with peak values occurring during mid-summer months, whereas observed data show earlier peaks in May and June. The phase shift reflects similar behavior in model predictions of incoming solar radiation. In addition, relative humidity values estimated from RCMs are significantly higher than observed values and the wind speed estimates from many RCMs have a significant bias during dry season months. Further improvements to RCMs may be needed before they can be used effectively for hydrologic modeling under future climate change scenarios.
KeywordsEvapotranspiration Climate change Regional Climate Models Hydrologic modeling
We wish to thank the NARCCAP for providing the data used in this paper. NARCCAP is funded by the National Science Foundation, U.S. Department of Energy, the National Oceanic and Atmospheric Administration, and the U.S. Environmental Protection Agency Office of Research and Development. The author wishes to acknowledge the valuable assistance from Michelle Irizarry and Joel VanArman at South Florida Water Management District. Comments from the reviewers and the editors are also appreciated.
- Abtew W (1995) Lysimeter study of evapotranspiration of cattails and comparison of three estimation methods. Trans Am Soc Ag Eng 38(1):121–129Google Scholar
- Abtew W, Obeysekera J, Irizarry-Ortiz M, Lyons D, Reardon A (2003) Evapotranspiration estimation for South Florida. In: Bizier P, DeBarry P (eds) Proceedings of the world water and environmental congress 2003, ASCE, Reston, VAGoogle Scholar
- Allen R (2005) Penman–Monteith Equation. Elsevier, Encyclopedia of SoilsGoogle Scholar
- Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration—guidelines for computing crop water requirements. FAO irrigation and drainage paper 56, Food and Agriculture Organization of the United Nations, Rome, ItalyGoogle Scholar
- IPCC (2007) Climate change 2007—the physical science basis. In: Solomon S et al (eds) Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
- German ER (2000) Regional evaluation of evapotranspiration in the Everglades, U.S. Geological Survey Water Resources Investigations Report 00-4217, p 48Google Scholar
- Irizarry-Ortiz M, Said W, Trimble P, Trimble B, Brown M, Ali A, Obeysekera J, Tarboton K, Newton T (2007) Estimation of long-term reference evapotranspiration from regional climate model datasets.In: Proceedings of the world environmental and water resources congress 2007: restoring our natural habitat, May 15–19. Tampa, FL, USAGoogle Scholar
- Jacobs J, Mecikalski J, Paech S (2008) Satellite-based solar radiation, net radiation, and potential and reference evapotranspiration estimates over Florida. Report prepared for the South Florida Water Management District, p 138Google Scholar
- Obeysekera J, Park J, Irizarry-Ortiz M, Trimble P, Barnes J, VanArman J, Said W, Gadzinski E (2011b) Past and projected trends in climate and sea level for South Florida. Interdepartmental Climate Change Group, South Florida Water Management District, West Palm Beach, Florida. Hydrologic and Environmental Systems Modeling Technical Report, July 5, 2011Google Scholar
- R Foundation for Statistical Computing (2008) R: a language and environment for statistical computing, R Development Core Team, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org, R version 2.7.2 accessed October 22, 2009
- Shoemaker B, Lopez CD, and Duever MJ (2011) Evapotranspiration over spatially extensive plant communities in the Big Cypress National Preserve, Southern Florida, 2007–2010. U.S. Geological Survey Scientific Investigations Report 2011-5212Google Scholar
- Stefanova L, Misra V, Chan SC, Griffin M, O’Brien JJ, Smith TJ III (2011) A proxy for high-resolution regional reanalysis for the Southeast United States: assessment of precipitation variability in dynamically downscaled reanalyses. Clim Dyn 38(11–12):2449–2466. doi: 10.1007/s00382-011-1230-y Google Scholar
- Sumner DM (1996) Evapotranspiration form successional vegetation in a deforested area of the Lake Wales Ridge, Florida. U.S. Geological Survey Water Resources Investigations Report 96-4244Google Scholar