No abstract

The National Weather Service's Cooperative Observer Program (COOP) is a valuable climate data resource that provides manually observed information on temperature and precipitation across the nation. These data are part of the climate dataset and continue to be used in evaluating weather and climate models. Increasingly, weather and climate information is also available from automated weather stations. A comparison between these two observing methods is performed in North Carolina, where 13 of these stations are collocated. Results indicate that, without correcting the data for differing observation times, daily temperature observations are generally in good agreement (0.96 Pearson product–moment correlation for minimum temperature, 0.89 for maximum temperature). Daily rainfall values recorded by the two different systems correlate poorly (0.44), but the correlations are improved (to 0.91) when corrections are made for the differences in observation times between the COOP and automated stations. Daily rainfall correlations especially improve with rainfall amounts less than 50 mm day−1. Temperature and rainfall have high correlation (nearly 1.00 for maximum and minimum temperatures, 0.97 for rainfall) when monthly averages are used. Differences of the data between the two platforms consistently indicate that COOP instruments may be recording warmer maximum temperatures, cooler minimum temperatures, and larger amounts of rainfall, especially with higher rainfall rates. Root-mean-square errors are reduced by up to 71% with the day-shift and hourly corrections. This study shows that COOP and automated data [such as from the North Carolina Environment and Climate Observing Network (NCECONet)] can, with simple corrections, be used in conjunction for various climate analysis applications such as climate change and site-to-site comparisons. This allows a higher spatial density of data and a larger density of environmental parameters, thus potentially improving the accuracy of the data that are relayed to the public and used in climate studies.

Precipitation structures within Kelvin and mixed Rossby-gravity (MRG) wave troughs near KwajaleinAtoll during the 1999-2003 rainy seasons are analyzed using three-dimensional ground-based radar data and upper-air sounding data. Consistent with previous work, wave troughs are preferred locations for precipitation and typically yield 1.3 times more rain area compared to the overall rainy season climatology.Although the contiguous areas of cold cloudiness associated with tropical wave troughs are large and long lived, the underlying precipitation structure is most frequently small, isolated convection from mixed-phase clouds. This mismatch in instantaneous cold cloudiness area versus radar-observed precipitation area indicates differences in the rate and nature of evolution between the mesoscale anvil cloud and the underlying precipitating portion of the cloud.Mesoscale convective systems (MCSs) were identified during portions of 32 of the 39 wave trough events examined. Convective cells are frequently embedded within stratiform regions. Reflectivity holes or pores in contiguous radar echo have been frequently observed in other regions but are quantified for the first time in this study. Based on characteristics such as total size of precipitating area and occurrence of convective lines, MCSs within Kelvin troughs are slightly more organized than those occurring within MRG troughs.Similar to the west Pacific warm pool region, there is a well-defined separation between observed and unobserved stratiform area fraction and convective precipitation area, each as a function of total precipitation area. At precipitation area sizes near 40% of the radar domain, the maximum observed convective area changes from increasing to decreasing with increasing precipitation area. The maximum observed convective precipitation area occupied ϳ20% of the radar domain. These characteristics suggest that the atmosphere in the west Pacific can sustain a limited area of updrafts capable of supporting precipitation growth by collision/coalescence and riming.

By utilizing daily normal ranges, weathercasters and others could better communicate to the public the natural expected variability of day-to-day temperatures-a variability not suggested by normals derived from smoothed trend lines.

Methods used to develop the Bioethanol Feedstock Geospatial Database (BFGD) provide a means of estimating the amount and location of U.S. corn harvested for use as U.S. bioethanol feedstock. Such estimates of geospatial feedstock production may be used to evaluate environmental impacts of bioethanol production and to identify conservation priorities. The BFGD is available for 2005-2010, and the methods may be applied to additional years, locations, and potentially other biofuels and feedstocks.