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Adam Terando, William E. Easterling, Klaus Keller, and David R. Easterling

Abstract

The authors examine recent changes in three agro-climate indices (frost days, thermal time, and heat stress index) in North America (centered around the continental United States) using observations from a historical climate network and an ensemble of 17 global climate models (GCMs) from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Agro-climate indices provide the basis for analyzing agricultural time series that are unbiased by long-term technological intervention. Observations from the last 60 years (1951–2010) confirm conclusions of previous studies showing continuing declines in the number of frost days and increases in thermal time. Increases in heat stress are largely confined to the western half of the continent. The authors do not observe accelerating agro-climate warming trends in the most recent decade of observations. The spatial variability of the temporal trends in GCMs is lower compared to the observed patterns, which still show some regional cooling trends. GCM skill, defined as the ability to reproduce observed patterns (i.e., correlation and error) and variability, is highest for frost days and lowest for heat stress patterns. Individual GCM skill is incorporated into two model weighting schemes to gauge their ability to reduce predictive uncertainty for agro-climate indices. The two weighted GCM ensembles do not substantially improve results compared to the unweighted ensemble mean. The lack of agreement between simulated and observed heat stress is relatively robust with respect to how the heuristic is defined and appears to reflect a weakness in the ability of this last generation of GCMs to reproduce this impact-relevant aspect of the climate system. However, it remains a question for future work as to whether the discrepancies between observed and simulated trends primarily reflect fundamental errors in model physics or an incomplete treatment of relevant regional climate forcings.

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Scott A. Isard and William E. Easterling

Abstract

Palmer's z-index, calculated to reflect only the planting-emergence and anthesis-grainfill stages of the growing season, is related with detrended corn yields to produce a predictive model for Illinois corn production. The model is evaluated to see how well it can predict mean bushel per acre corn yields for large areas (state of Illinois). Results suggest the z-index, if calculated to emphasize moisture-sensitive periods in corn production, is a reliable predictor of yields, and, moreover, this predictive ability improves with more extreme moisture conditions.

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Elena A. Tsvetsinskaya, Linda O. Mearns, and William E. Easterling

Abstract

The authors examine the effect of seasonal crop development and growth on the warm-season mesoscale heat, moisture, and momentum fluxes over the central Great Plains region of North America. The effect of crop growth and development on the atmospheric boundary layer is addressed in a follow-up paper (Part II). Energy, moisture, and momentum fluxes are studied over a maize agroecosystem at the scale of a 90-km atmospheric grid cell. Daily plant development and growth functions incorporated into the surface flux calculations are based on a physiological crop growth model CERES-Maize version 3.0. CERES-Maize simulates daily plant growth and development as a function of both environmental conditions (temperature, precipitation, solar radiation, and soil moisture) and plant-specific genetic parameters. Plant growth and development functions from CERES were incorporated into the Biosphere–Atmosphere Transfer Scheme (BATS), and selected crop parameters [i.e., Leaf Area Index (LAI) and crop height] were validated against field data. The sensitivity of sensible (H) and latent (LE) heat fluxes, and momentum flux (τ) to interactively simulated LAI and canopy height was quantified.

During the extremely dry season of 1988, 20%–35% changes in sensible heat and 30%–45% changes in latent heat occurred in response to LAI changes from 5 to 1 (the values simulated in the control and interactive experiments, respectively). These changes are statistically significant (at the 0.05 level) for all the locations and years under consideration. Relative contributions of evaporation and transpiration to the latent heat flux were also strongly affected by these LAI changes. This effect had a distinct diurnal pattern, with the strongest signal seen in midafternoon hours, and was more pronounced during the dry years (e.g., 1988 and 1989) compared to the favorably moist years (e.g., 1991, 1993).

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Elena A. Tsvetsinskaya, Linda O. Mearns, and William E. Easterling

Abstract

The authors examine the effect of seasonal crop development and growth on the atmospheric boundary layer in the warm season over the central Great Plains region of North America. They introduced daily crop development and growth functions into the Biosphere–Atmosphere Transfer Scheme (BATS) coupled to the National Center for Atmospheric Research Regional Climate Model version 2 (NCAR RegCM2). Coupled RegCM/BATS simulations were performed over the conterminous United States for a dry (1988) and favorably moist (1991) growing seasons at a spatial resolution of 90 km × 90 km. Largest differences between the control and interactive runs occurred in 1988, when up to 45% differences in surface latent and sensible heat fluxes were simulated in response to different Leaf Area Index (LAI) parameterizations employed by the models (in June and July, LAI was about 5 in the control cases and between 1 and 2 in the interactive cases). Two to four °C differences in air temperatures resulted in response to such changes in surface fluxes. Mixing ratio, lower atmospheric winds, and precipitation were also affected. These effects had a distinct diurnal pattern with the largest differences seen in midafternoon hours and smallest differences seen at night. The differences between the control and interactive simulations were largest near the surface and dampened with height. The boundary layer stratification (i.e., vertical profiles of equivalent potential temperature) produced with interactive runs was more stable compared to the control runs. Anemometer height maximum daily temperature and precipitation simulated in the interactive runs agreed better with observations compared to those of the control runs.

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