Farm Enterprise Analysis: Has It Lost Its Usefulness?

Farm enterprise analysis is a term that has traditionally been used to describe the process of determining costs associated with farm business enterprises and enterprise profitability. A key challenge to those who would know their costs has been the lack of guidance on cost accounting principles and the application of those principles to agriculture. However, that recently changed with the publication of the Farm Financial Standards Council’s Management Accounting Principles for Agricultural Producers, which has led to questions about the usefulness of enterprise analysis. The differences between the two approaches to determining costs for farm business enterprises are discussed as they relate to the usefulness of the output to managers for decision making.Productivity Analysis,

Final Report: California water resources research and applicationscenter

The California Water Resources RESAC objectives were toutilize NASA data to provide state-of-the-art real-time and forecastinformation (observation and simulation) on hydroclimate, water quantityand quality, and runoff related hazards to water resources managers(e.g., NWS, CA Dept. of Water Resources, USBR), the insurance industry,emergency response agencies, policy decision-makers, and the generalpublic. In addition, the RESAC acts as an umbrella organization fosteringgrowing collaborations and partnerships. It was built on the foundationestablished through the U.S. Global Change Research Program and theNational and California Assessments. It is designed to support theongoing regional and national assessment process by improving ourunderstanding of specific regional features of the climate system and itsimpacts, and facilitating the dissemination of these results throughdata, publications, and outreach.The California Water Resources RESACproduces three types of regional climate products that are enhanced byincorporation of NASA satellite data: (1) short-term (2-3 day) weatherand streamflow forecasts, (2) seasonal hydroclimate, and (3) long-termclimate change scenarios and hydrologic impacts. Our team has built anexcellent record in providing quantitative precipitation and streamflowforecasts to the water resources and weather prediction communities. Wehave been working with scientists from various University of Californiainstitutions and government agencies to improve weather and streamflowpredictions and studies of regional hydroclimate, and its impacts onwater resources, the environment, and the economy

Ursinus College Alumni Journal, Spring 1942

Current comment • President\u27s page • Accelerated program data • Commencement advanced to May 15-18 weekend • Woman\u27s Club corner • Accelerated program puts May pageant in April • Noted speakers address campus organizations • College defense council formed • Students raise $200 for foreign student relief • Distinguished British scholar serves as visiting professor • Freshman customs changed • Alumni Association nominees • With the Grizzlies: Intramural program; Football to continue; Girls basketball; Varsity basketball; Freshman basketball; Wrestling • Publications choose editors • Miss Moll joins Army Nurses Corps • About ourselveshttps://digitalcommons.ursinus.edu/alumnijournal/1014/thumbnail.jp

Ursinus College Alumni Journal, Autumn 1941

Current comment • President\u27s page • Messages to the alumni • A new humanism: An address delivered by Dr. F. Cyril James, Principal and Vice-Chancellor of McGill University, to the Founders Day convocation at Ursinus College • 1941-42 enrollment data • Fall sports • About ourselves • Alumni Association officershttps://digitalcommons.ursinus.edu/alumnijournal/1013/thumbnail.jp

Ursinus College Alumni Journal, Autumn 1941

Current comment • President\u27s page • Messages to the alumni • A new humanism: An address delivered by Dr. F. Cyril James, Principal and Vice-Chancellor of McGill University, to the Founders Day convocation at Ursinus College • 1941-42 enrollment data • Fall sports • About ourselves • Alumni Association officershttps://digitalcommons.ursinus.edu/alumnijournal/1013/thumbnail.jp

Sensitivity Study of Four Land Surface Schemes in the WRF Model

The Weather Research and Forecasting (WRF) model version 3.0 developed by the National Center for Atmospheric Research (NCAR) includes three land surface schemes: the simple soil thermal diffusion (STD) scheme, the Noah scheme, and the Rapid Update Cycle (RUC) scheme. We have recently coupled the sophisticated NCAR Community Land Model version 3 (CLM3) into WRF to better characterize land surface processes. Among these four land surface schemes, the STD scheme is the simplest in both structure and process physics. The Noah and RUC schemes are at the intermediate level of complexity. CLM3 includes the most sophisticated snow, soil, and vegetation physics among these land surface schemes. WRF simulations with all four land surface schemes over the western United States (WUS) were carried out for the 1 October 1995 through 30 September 1996. The results show that land surface processes strongly affect temperature simulations over the (WUS). As compared to observations, WRF-CLM3 with the highest complexity level significantly improves temperature simulations, except for the wintertime maximum temperature. Precipitation is dramatically overestimated by WRF with all four land surface schemes over the (WUS) analyzed in this study and does not show a close relationship with land surface processes

The Key Role of Heavy Precipitation Events in Climate Model Disagreements of Future Annual Precipitation Changes in California

Climate model simulations disagree on whether future precipitation will increase or decrease over California, which has impeded efforts to anticipate and adapt to human-induced climate change. This disagreement is explored in terms of daily precipitation frequency and intensity. It is found that divergent model projections of changes in the incidence of rare heavy (\u3e60 mm day−1) daily precipitation events explain much of the model disagreement on annual time scales, yet represent only 0.3% of precipitating days and 9% of annual precipitation volume. Of the 25 downscaled model projections examined here, 21 agree that precipitation frequency will decrease by the 2060s, with a mean reduction of 6–14 days yr−1. This reduces California\u27s mean annual precipitation by about 5.7%. Partly offsetting this, 16 of the 25 projections agree that daily precipitation intensity will increase, which accounts for a model average 5.3% increase in annual precipitation. Between these conflicting tendencies, 12 projections show drier annual conditions by the 2060s and 13 show wetter. These results are obtained from 16 global general circulation models downscaled with different combinations of dynamical methods [Weather Research and Forecasting (WRF), Regional Spectral Model (RSM), and version 3 of the Regional Climate Model (RegCM3)] and statistical methods [bias correction with spatial disaggregation (BCSD) and bias correction with constructed analogs (BCCA)], although not all downscaling methods were applied to each global model. Model disagreements in the projected change in occurrence of the heaviest precipitation days (\u3e60 mm day−1) account for the majority of disagreement in the projected change in annual precipitation, and occur preferentially over the Sierra Nevada and Northern California. When such events are excluded, nearly twice as many projections show drier future conditions

Probabilistic estimates of future changes in California temperature and precipitation usingstatistical and dynamical downscaling

Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s. The global models were downscaled with two statistical techniques and three nested dynamical regional climate models, although not all global models were downscaled with all techniques. Both monthly and daily timescale changes in T and P are addressed, the latter being important for a range of applications in energy use, water management, and agriculture. The T changes tend to agree more across downscaling techniques than the P changes. Year-to-year natural internal climate variability is roughly of similar magnitude to the projected T changes. In the monthly average, July temperatures shift enough that that the hottest July found in any simulation over the historical period becomes a modestly cool July in the future period. Januarys as cold as any found in the historical period are still found in the 2060s, but the median and maximum monthly average temperatures increase notably. Annual and seasonal P changes are small compared to interannual or intermodel variability. However, the annual change is composed of seasonally varying changes that are themselves much larger, but tend to cancel in the annual mean. Winters show modestly wetter conditions in the North of the state, while spring and autumn show less precipitation. The dynamical downscaling techniques project increasing precipitation in the Southeastern part of the state, which is influenced by the North American monsoon, a feature that is not captured by the statistical downscaling