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Drought has affected much of the western United States since about the year 2000, including the Upper Colorado River Basin (UCRB). Using a time series of UCRB streamflow derived from a tree‐ring based reconstruction of UCRB streamflow for the years 1 CE through 1905 CE, together with naturalized UCRB streamflow values for 1906 CE through 2021 CE, we identify 51 drought events, including the 2000–2021 drought. Although the recent 2000–2021 drought has been relatively severe, it is not the most severe of the UCRB drought events we identified. Results also indicate that natural variability combined with projected climate warming can result in UCRB drought events that are more severe than any drought since 1 CE. Plain Language Summary: A long and severe drought has affected much of the western United States since about the year 2000 CE, including the Upper Colorado River Basin (UCRB). Comparing this drought to past UCRB droughts (during 1 CE through 2021 CE), we find that the 2000–2021 drought is not the most severe UCRB drought. The results also suggest that natural variability combined with projected climate warming could result in UCRB drought events that are more severe than any drought since 1 CE. Key Points: We identify 51 drought events for the years 1 CE through 2021 CE for the Upper Colorado River Basin (UCRB)Twelve of the 51 UCRB droughts we identify were more severe than the 2000–2021 droughtNatural variability and/or a 1°C temperature increase can trigger UCRB droughts that are more severe than the 2000–2021 drought [ABSTRACT FROM AUTHOR]

The evidence for cannabis's treatment efficacy across different conditions varies widely, and comprehensive data on the conditions for which people use cannabis are lacking. We analyzed state registry data to provide nationwide estimates characterizing the qualifying conditions for which patients are licensed to use cannabis medically. We also compared the prevalence of medical cannabis qualifying conditions to recent evidence from the National Academies of Sciences, Engineering, and Medicine report on cannabis's efficacy in treating each condition. Twenty states and the District of Columbia had available registry data on patient numbers, and fifteen states had data on patient-reported qualifying conditions. Chronic pain is currently and historically the most common qualifying condition reported by medical cannabis patients (64.9 percent in 2016). Of all patient-reported qualifying conditions, 85.5 percent had either substantial or conclusive evidence of therapeutic efficacy. As medical cannabis use continues to increase, creating a nationwide patient registry would facilitate better understanding of trends in use and of its potential effectiveness. [ABSTRACT FROM AUTHOR]

The current drought over the Colorado River Basin has raised concerns that the US Department of the Interior, Bureau of Reclamation (Reclamation) may impose water shortages over the lower portion of the basin for the first time in history. The guidelines that determine levels of shortage are affected by relatively short-term (3 to 7month) forecasts determined by the Colorado Basin River Forecast Center (CBRFC) using the National Weather Service (NWS) River Forecasting System (RFS) hydrologic model. While these forecasts by the CBRFC are useful, water managers within the basin are interested in long-term projections of streamflow, particularly under changing climate conditions. In this study, a bias-corrected, statistically downscaled dataset of projected climate is used to force the NWS RFS utilized by the CBRFC to derive projections of streamflow over the Green, Gunnison, and San Juan River headwater basins located within the Colorado River Basin. This study evaluates the impact of changing climate to evapotranspiration rates and contributes to a better understanding of how hydrologic processes change under varying climate conditions. The impact to evapotranspiration rates is taken into consideration and incorporated into the development of streamflow projections over Colorado River headwater basins in this study. Additionally, the NWS RFS is modified to account for impacts to evapotranspiration due to changing temperature over the basin. Adjusting evapotranspiration demands resulted in a 6% to 13% average decrease in runoff over the Gunnison River Basin when compared to static evapotranspiration rates. Streamflow projections derived using projections of future climate and the NWS RFS provided by the CBRFC resulted in decreased runoff in 2 of the 3 basins considered. Over the Gunnison and San Juan River basins, a 10% to 15% average decrease in basin runoff is projected through the year 2099. However, over the Green River basin, a 5% to 8% increase in basin runoff is projected through 2099. Evidence of nonstationary behavior is apparent over the Gunnison and San Juan River basins. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the economic attributes of household investment to the business cycle in the U.S. The study aims to determine the cause of economic changes in household sector. An overview of the cyclical behavior of household and business investment is also offered. The study reveals that the cycle in household sector is greatly influenced by the changes in house pricing.

Abstract: This work presents a procedure for developing a high-resolution, regional climatology estimate, named RClimo, off the coast of central California. This high-resolution climatology may provide an alternative way to initialize numerical nowcast/forecast exercises in coastal regions. The methodology includes two primary steps: (1) averaging available data on a high-resolution grid and (2) objective interpolating the resulting average profiles onto a regular grid. The first step involves the computation of averages over density layers in the vertical and allowing for data gaps in the horizontal if data are unavailable at a high resolution. The OA in the second step uses anisotropic correlation length scales derived from the data themselves and an averaging radius to preserve the scales and variability of the synoptic fields. The dataset used to compute this climatology includes the archived CalCOFI dataset, the Autonomous Ocean Sampling Network (AOSN) 2003 experiments near Monterey Bay, and many other previously undocumented profiles from various sources. As part of the climatology product, associated uncertainty is also generated through density averaging and employing the Gauss–Markov minimum error variance during Objective Analysis. The final climatology estimate is hence subject to greater error for larger mapping-grid size or lower data density, suggesting uncertainties that vary in space. The maximum value of the resulting error distribution for the RClimo estimate from the 50-km bins is less than 11% of the temperature estimate and 1% of the salinity estimate, whereas those for the 20-km-bin RClimo are 11% and 0.9%, respectively. We have conducted comparisons between the RClimo and 1/4° Levitus climatology fields via numerical simulations initialized with each field. Simulations were performed using Regional Ocean Modeling System (ROMS) and for the month of August, a peak period of upwelling-favorable wind, with and without the atmospheric forcing. The RClimo simulations produced reasonably realistic features like filaments, fronts, meanders, eddies, alongshore currents (∼50cms−1) and inshore undercurrents (∼15cms−1) under typical upwelling-favorable winds. In contrast, the Levitus simulations showed insignificant evolution over most of the domain, with or without winds. In the future, one could apply this methodology for other months and seasons in Monterey Bay, as well as develop similar high-resolution climatology for other coastal regions. [Copyright &y& Elsevier]

Explains why some firms voluntarily overcomply with environmental regulation. Consumers' identification of clean firms; Firms' participation in a two-stage duopoly game where they choose their levels of cleaning technology and engage in price competition.

Paleohydrologic records can provide unique, long-term perspectives on streamflow variability and hydroclimate for use in water resource planning. Such long-term records can also play a key role in placing both present day events and projected future conditions into a broader context than that offered by instrumental observations. However, relative to other major river basins across the western United States, a paucity of streamflow reconstructions has to date prevented the full application of such paleohydrologic information in the Upper Missouri River Basin. Here we utilize a set of naturalized streamflow records for the Upper Missouri and an expanded network of tree-ring records to reconstruct streamflow at thirty-one gaging locations across the major headwaters of the basin. The reconstructions explain an average of 68% of the variability in the observed streamflow records and extend available records of streamflow back to 886 CE on average. Basin-wide analyses suggest unprecedented hydroclimatic variability over the region during the Medieval period, similar to that observed in the Upper Colorado River Basin, and show considerable synchrony of persistent wet-dry phasing with the Colorado River over the last 1200 years. Streamflow estimates in individual sub-basins of the Upper Missouri demonstrate increased spatial variability in discharge during the Little Ice Age (∼1400–1850 CE) compared with the Medieval Climate Anomaly (∼800–1400 CE). The network of streamflow reconstructions presented here fills a major geographical void in paleohydrologic understanding and now allows for a long-term assessment of hydrological variability over the majority of the western U.S. • Upper Missouri River streamflow is reconstructed using tree-rings. • Persistent wet-dry cycles in the Upper Missouri track those in the Upper Colorado. • Medieval, Little Ice Age, and 20th century streamflow variability differed. [ABSTRACT FROM AUTHOR]

This article discusses how data warehousing, data mining, and decision support systems can reduce the national cancer burden or the oral complications of cancer therapies, especially as related to oral and pharyngeal cancers. An information system is presented that will deliver the necessary information technology to clinical, administrative, and policy researchers and analysts in an effective and efficient manner. The system will deliver the technology and knowledge that users need to readily: (1) organize relevant claims data, (2) detect cancer patterns in general and special populations, (3) formulate models that explain the patterns, and (4) evaluate the efficacy of specified treatments and interventions with the formulations. Such a system can be developed through a proven adaptive design strategy, and the implemented system can be tested on State of Maryland Medicaid data (which includes women, minorities, and children).

Mounting costs have escalated the pressure on health care providers and payers to improve decision making and control expenses. Transactions to form the needed decision data will routinely flow, often electronically, between the affected parties. Conventional health care information systems facilitate flow, process transactions, and generate useful decision information. Typically, such support is offered through a series of stand-alone systems that lose much useful decision knowledge and wisdom during health care electronic commerce (e-commerce). Integrating the stand-alone functions can enhance the quality and efficiency of the segmented support, create synergistic effects, and augment decision-making performance and value for both providers and payers. This article presents an information system that can provide complete and integrated support for e-commerce-based health care decision making. The article describes health care e-commerce, presents the system, examines the system's potential use and benefits, and draws implications for health care management and practice.