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Open Access Publications from the University of California

Scholarly Works (2 results)

  • Article
LBL Publications (2006)

In the western United States, more than 30,500 square miles has been converted to irrigated agriculture and urban areas. This study compares the climate responses of four regional climate models (RCMs) to these past land-use changes. The RCMs used two contrasting land cover distributions: potential natural vegetation, and modern land cover that includes agriculture and urban areas. Three of the RCMs represented irrigation by supplementing soil moisture, producing large decreases in August mean (-2.5oF to -5.6oF) and maximum (-5.2oF to -10.1oF) 2-meter temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture also resulted in large increases in relative humidity (9 percent 36 percent absolute change). Only one of the RCMs produced increases in summer minimum temperature. Converting natural vegetation to urban land cover produced modest but discernable climate effects in all models, with the magnitude of the effects dependent upon the preexisting vegetation type. Overall, the RCM results indicate that land use change impacts are most pronounced during the summer months, when surface heating is strongest and differences in surface moisture between irrigated land and natural vegetation are largest. The irrigation effect on summer maximum temperatures is comparable in magnitude (but opposite in sign) to predicted future temperature change due to increasing greenhouse gas concentrations.

    Cover page: Regional climate effects of irrigation and urbanization in the western united states: a model intercomparison
    • Article
    Planning & Evaluation (2008)
    Four dynamic regional climate models (RCMs) and one statistical downscaling approach were used to downscale 10 years of historical climate in California. To isolate possible limitations of the downscaling methods, we used initial and lateral boundary conditions from the NCEP global reanalysis. Results of this downscaling were compared to observations and to an independent, fine-resolution reanalysis (NARR). This evaluation is preparation for simulations of future-climate scenarios, the second phase of this CEC scenarios project. Each model has its own strengths and weaknesses, which are reported here. In general, the dynamic models perform as well as other state-of-the-art dynamical regional climate models, and the statistical model has comparable or superior skill, although for a very limited set of meteorological variables. As is typical, the dynamical models have the most trouble simulating clouds, precipitation, and related processes, especially snow. This suggests that the weakest aspects of the models are parameterized subgrid scale processes, the hydrological cycle, and land surface processes. However, the resulting probabilistic ensemble simulations result in reduced model uncertainty and a better understanding of model spread.
      Cover page: An Analysis Of Simulated California Climate Using Multiple Dynamical And Statistical techniques
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