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The most common method for managing beaches, referred to as the “persistence model”, assumes that fecal indicator bacteria (FIB) concentrations, such as E. coli, from yesterday are representative of today, due to the 24-hour time requirement for analyzing FIB.  The assumption of using day old data for managing public beaches may result in over-conservative or under-conservative beach advisories. For several years, beach managers in the Great Lakes have expressed interest in predictive beach water quality tools that will help them better manage beaches.

Researchers at the Cooperative Institute for Limnology and Ecosystems Research (CILER) are collaborating with NOAA’s Great Lakes Environmental Research Laboratory (GLERL) and NOAA’s Center of Excellence for Great Lakes and Human Health (CEGLHH) to develop a beach water quality forecasting system. The system links watershed land use and runoff from precipitation, forecasts of river discharge and near-shore currents, and biological processes to predict and simulate concentrations of fecal indicator bacteria at beaches impacted by river discharge using GLERL’s Huron-Erie Connecting Waterways Forecasting System (HECWFS). Nearly two seasons of intensive monitoring have been completed for the beaches impacted by the Michigan’s Clinton River, and provide the basis for this decision support tool.

In addition to providing a new tool for determining safety of Great Lakes beaches, this program represents a major contribution to near-shore ecological forecasting by demonstrating the use of linked models to simulate pollutant fate and transport. This work supports CEGLHH’s goal of understanding of ecosystem processes, particularly hydrodynamics and the influence of abiotic factors on the fate, transport of sources and loadings of bacteria and microbial contaminants to assist in environmental decision-making and reduce human health risks.

Contact Information: Lauren Fry, CILER Research Fellow

Recent Yukon River flooding underscores the importance of accurately predicting snowmelt and river ice breakup in Alaska. Residents of Galena were evacuated with little warning as their community of 400 was inundated with water and ice on Memorial Day weekend. Cooperative Institute for Alaska Research (CIFAR) researchers Katrina Bennett and Jessica Cherry are working with the National Weather Service’s Alaska-Pacific River Forecast Center (APRFC) to improve the accuracy of snowmelt processes in the models used by the APRFC. The High Latitude Proving Ground, an effort by National Oceanic and Atmospheric Administration (NOAA)-National Environmental Satellite, Data and Information Service (NESDIS), supports this project to develop and implement next-generation remote sensing products into weather and river forecast offices’ modeling protocol.

Background:  Bennett, a PhD student at the University of Alaska Fairbanks, is working with the APRFC to update snow conditions in the temperature-index snow accumulation and melt model SNOW-17 using snow cover data from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. Currently, snow cover in the model is generated using a sparse observational network and algorithms that calculate mean areal temperature and precipitation. This and other forms of data assimilation with remote sensing products are one way to update information in our modeling systems. Cherry and other members of her research team are trying to balance progress in assimilation and observational data management with a move toward more physically based land surface and systems models.    

Significance:  As hydro-climate systems regimes shift and extreme events become more frequent, it’s increasingly important that model predictions simulate the Earth system response accurately. In the Far North, spring snowmelt is the most dramatic hydrologic event of the year, and the mostly likely time for flooding to occur. Given Alaska’s vast territory and sparse ground-based observing networks, remote sensing is an obvious place to turn to improve the prediction of spring snowmelt and river ice breakup. CIFAR’s work relates to NOAA’s Climate Adaptation and Mitigation goal.

Contact: Dr. Jessica Cherry (jcherry@iarc.uaf.edu) 

Using an idealized experiment where atmospheric carbon dioxide doubles from its 1990 value over 70 years, a new Geophysical Fluid Dynamics Laboratory (GFDL) high-resolution climate model, CM2.5, predicts an increase in snowfall for the Earth’s polar regions and highest mountains, but an overall drop in snowfall for the globe.  A recent study currently in press and available online in the Journal of Climate, led by Cooperative Institute for Climate Science – Princeton (CICS-P) Scientist Sarah Kapnick and coauthored with Thomas Delworth, a senior physical scientist at GFDL and Princeton lecturer; found that CM2.5 better captures various snow variables when compared to previous models.

Background:

CM2.5 is unique in that its resolution allows it to capture complex mountain ranges. This makes a difference in places like the western U.S. where a single plateau in coarse models is transformed into several distinct mountain ranges in CM2.5 (e.g. California Sierras, Cascades, and Rockies).  This is important for having snow fall in the correct regions and collect as snowpack (seasonal snow on the ground).

Significance:

Over the United States, the future climate experiment exhibits significant reductions in average annual snowfall. Figure 1 represents the geographic distribution of snowfall change in response to CO2 doubling. The vast majority of the U.S. experiences snowfall loss, with the greatest percentages occurring in the south, along the eastern coast, and the Pacific Northwest. This will lead to fundamental changes in the availability of water from spring and summer snowmelt. The continental interior experiences fewer reductions. While this study focuses on mean annual snow variables, future work will focus on exploring changes in extreme snowfall events, such as the frequency and strength of blizzards, and changes in seasonality.  This work relates to the National Oceanic and Atmospheric’s (NOAA) Climate Goal: Understand Climate Variability and Change to Enhance Society’s Ability to Plan and Respond.

Contact Information:  Sarah Kapnick at (609) 452-6548 or skapnick@princeton.edu:

Researchers at the Cooperative Institute for Climate and Satellites led by Christopher Hain, along with colleagues from the National Oceanic and Atmospheric Administration (NOAA) and the United States Department of Agriculture (USDA) Agricultural Research Service, developed a unique satellite based methodology for mapping drought over the United States. The tool is currently being evaluated for use as a part of the decision making process at the National Drought Mitigation Center in support of their monthly drought briefing.  

Background:

The Evaporative Stress Index (ESI) provides objective, high-resolution information related to evaporation of water from land surface. Anomalies in how much water is used by crops and vegetation  are especially important during conditions of drought. Signatures of vegetation stress can be detected by determining how fast the land surface heats up before any deterioration in vegetation occurs, in contrast to others methods which only look at how “green” vegetation is to determine its health. ESI can also provide an effective early warning signal of impending “flash droughts”, which can be brought on by extended periods of hot, dry and windy conditions leading to a rapid loss of soil moisture. This has been demonstrated by the ability of ESI to capture the 2012 “flash drought” over the central United States, where ESI showed developing drought conditions before it was shown in other drought indicators.

Significance:

ESI provides additional assessment of current drought conditions, supplementing precipitation and modeling-based indices and provides an invaluable resource to decision-makers who usually depend on a convergence of information in the decision making process.  This work supports NOAA’s goal of climate adaptation and mitigation, improved freshwater resource management and reducing loss of life, property, and disruption from high-impact events.  ESI maps are distributed during the growing season through the Drought Portal (www.drought.gov) maintained by the National Integrated Drought Information Service.

ESI Website: http://hrsl.arsusda.gov/drought/

Researchers at the Cooperative Institute for Climate and Satellites led by Christopher Hain, along with colleagues from the National Oceanic and Atmospheric Administration (NOAA) and the United States Department of Agriculture (USDA) Agricultural Research Service, developed a unique satellite based methodology for mapping drought over the United States. The tool is currently being evaluated for use as a part of the decision making process at the National Drought Mitigation Center in support of their monthly drought briefing.  

Background:

The Evaporative Stress Index (ESI) provides objective, high-resolution information related to evaporation of water from land surface. Anomalies in how much water is used by crops and vegetation  are especially important during conditions of drought. Signatures of vegetation stress can be detected by determining how fast the land surface heats up before any deterioration in vegetation occurs, in contrast to others methods which only look at how “green” vegetation is to determine its health. ESI can also provide an effective early warning signal of impending “flash droughts”, which can be brought on by extended periods of hot, dry and windy conditions leading to a rapid loss of soil moisture. This has been demonstrated by the ability of ESI to capture the 2012 “flash drought” over the central United States, where ESI showed developing drought conditions before it was shown in other drought indicators.

Significance:

ESI provides additional assessment of current drought conditions, supplementing precipitation and modeling-based indices and provides an invaluable resource to decision-makers who usually depend on a convergence of information in the decision making process.  This work supports NOAA’s goal of climate adaptation and mitigation, improved freshwater resource management and reducing loss of life, property, and disruption from high-impact events.  ESI maps are distributed during the growing season through the Drought Portal (www.drought.gov) maintained by the National Integrated Drought Information Service.

ESI Website: http://hrsl.arsusda.gov/drought/