Continental Wind Patterns Associated with Colorado Alpine Dust Deposition: An Application of the BLM/USFS RAWS Network

Morgan Phillips Colorado Climate Center Colorado State University/Bureau of Land Management

Nolan Doesken Colorado Climate Center Colorado State University

The purpose of this study was not to look at the impacts of dust deposition on snow but instead sought a better understanding of the sources and the climatological patterns associated with the generation of a dust event. The motivation for this research was to determine the mechanisms that cause dust events in order to protect scarce water resources of the western United States. The 2008-2009 season had high numbers of alpine dust deposition events so it was used as a use case for determining the locations and environmental parameters needed to produce years high with dust deposition. The study used data from the BLM/USFS Remote Automated Weather Station (RAWS) network in the southwestern U.S. to determine wind patterns. The Raw network has been recording interval/ ratio data for approaching 30 years, in 2011, so it can begin to answer climate questions. Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT), an atmospheric trajectory model, along with satellite imagery was used to determine the origin of the sediment being deposited on alpine regions primarily along the Continental Divide in Northern Colorado and the San Juan Mountains in Southwestern Colorado. Using this model back trajectories were generated that used the deposition location to show that the dust could have originated in Northern Arizona/ the Southern Colorado Plateau. The article concluded that for a dust storm to generate and deposit snow in the alpine regions of Colorado wind with a daily mean speed of 15 and daily maximum gusts of 44 mph in a southwesterly direction was required. A linear regression analysis showed a correlation between the Southern Oscillation Index (SOI) and the frequency of these types of high wind periods in the RAWS database. This correlation was determined to be 0.46 for daily mean wind speeds and 0.56 for maximum daily wind gusts during the months of December through April (Phillips, 2011). The 2008-2009 year ranked above the 20-year average in terms of the number of days with high winds but it was not a year with the single highest wind speed so this suggests that other factors, alongside high winds, control dust transport and deposition.

This article showed me the RAWS data set which will be important in adding wind as a controlling variable for years of high avalanche deaths. The RAWS data set is continuously expanding so trends can be further examined and refined. The article also demonstrated the connection between years of high dust deposition and the SOI which I will use to see if the pattern is repeating. The connections between ENSO and dust deposition was not fully developed in the article in terms of attributing direct conclusions about how dust deposition is affected by ENSO however it is clear that a relationship exists. ENSO has impacts further than just wind so it should be investigated in my research to determine if changes in precipitation, generating a drier Arizona/ Southern Colorado Plateau, or changes in temperature influence the generation of dust events. The difficulty with this is that the ENSO does not occur in a linear pattern and thus years that have been labeled as ENSO years will have to be investigated case by case basis in order to determine trends that occur during ENSO years. However, even with that information, ENSO can act in different ways year to year adding to the complexity of making claims about trends impacted by ENSO.

Phillips, M., & Doesken, N. (2011). Continental Wind Patterns Associated with Colorado Alpine Dust Deposition: An Application of the BLM/USFS RAWS Network. Journal of Service Climatology,5(2), 1-11. Retrieved April 2, 2017.

Changes in the Timing of Snowmelt and Streamflow in Colorado: A Response to Recent Warming

David W. Clow from the U.S Geological Survey out of Lakewood, Colorado investigated how SWE (snow water equivalent) and streamflow, are correlated to the rate and timing of snowmelt in Colorado. Monthly air temperatures, snowfall, latitude, and elevation were also used in multiple linear regression models to determine the controls on snowmelt. Interval/ratio data for SWE was collected from Natural Resource Conservation Service (NRCS) snowpack telemetry sites (SNOTEL sites) and the streamflow data was collected from headwater streams. Data from 1978-2007 was collected from the SNOTEL sites with 97% of sites had ≥21 years of data and all sites <18 years being excluded. Daily streamflow data were obtained for 58 headwater streams in Colorado with long-term gauges operated by the U.S. Geological Survey (USGS) or the Colorado Division of Water Resources. The regional Kendall test (RKT) was used to determine changes in trends to air temperature and SWE over the 27 year period. Multiple linear regressions were used to determine how and to what degree the changes impacted the timing of snowmelt.

A benefit of using the RKT is that by grouping data into geographic regions trend detection is increased. The multiple linear regressions were beneficial in determining which variables impacted the timing and degree of melt the greatest. Increasing springtime air temperature and declining SWE explained most, 45%, of the interannual variability in snowmelt timing. Regression coefficients for air temperature were negative, indicating that warm temperatures promote early melt. Regression coefficients for SWE, latitude, and elevation were positive, indicating that abundant snowfall tends to delay snowmelt, and snowmelt tends to occur later at northern latitudes and high elevations (Clow, 2010). The use of these methods demonstrates the strength of more traditional data analysis techniques and how they can be applied to data sets.

The conclusions found in this article will influence my research proposal by demonstrating which variables are most influential in generating melt in a snowpack. Similarly, this research demonstrates how to use variables similar to the variables I will be using a multiple linear regression. The article also validates a portion of my research topic by stating, “It may be useful to include other possible controls on snowmelt timing, such as dust deposition, in regression models in the future.” (Clow, 2010) This article also makes predictions about how Nov-May air temperatures increased by a median of 0.9°C decade−1, while 1 April SWE declined by a median of 4.1 decade−1 and maximum SWE declined 3.6 cm decade−1. This could be utilized in my proposal by investigating if these trends have stayed consistent over the past decade since the research was conducted. Another aspect of this research that I am possibly going to include in my proposal is grouping data by region because certain areas might be influenced by variables in different ways. Using this technique I could determine, for example, if higher temperatures in southwest Colorado and more influential than SWE.  

Clow, D. W. (2010). Changes in the Timing of Snowmelt and Streamflow in Colorado: A Response to Recent Warming. Journal of Climate,23(9), 2293-2306. doi:10.1175/2009jcli2951.1

Forecasting Climate Change Impacts on Conifer Forests of the Intermountain West

This research proposal was developed by David R. Bowling, Greg Maurer, James R. Ehleringer, and Thomas H. Painter through the Departments of Biology and Geography at the University of Utah. The proposal is focused on forests in alpine areas and investigates these areas in regards to the impacts of climate change on the availability of water. Spring melt is the annual event under investigation because it is the timing by which stored water in the form of snowpack melts and is no longer available. The proposal attributes two factors that lead to a shorter snow covered season, both being intensified by climate change. The first is rising mean temperatures leading to an increase in the proportion of precipitation in the form of rain instead of snow. The other is an increase in dust deposition on snow. Dust deposition on snow decreases the albedo, lowering the reflectivity,  of the snow thus accelerating the melt of the snow. The research question presented by the proposal is  “How will climate change influence conifer forest distributions and carbon cycling in the Intermountain West?” The proposed three-year study combines observational and manipulative field experiments to determine the “functioning, distribution, and carbon stocks of conifer forests in the region.” [1] Three forests were selected at different elevations experiencing differing levels of precipitation and ranges of temperature. The observational experiment will be conducted by temporarily installing devices that measure weather, soil moisture and temperature, and tree sap flow. Other devices will be temporarily placed to gauge the degree of carbon cycling occurring in each area. The experimental manipulations will simulate the presence of dust deposition on the snow surface by using a leaf blower and material sourced southern Utah. Dust will be added to the surface of the snow on a weekly recurrence interval. This will simulate future dust deposition on snow and will be used to determine the timing of an early spring melt due to dust deposition.

The proposal clearly discusses what is under investigation, the topic, the question being answered and has a detailed description of how data will be collected. A strength of the proposal was providing alternate sites for conducting the research that had similar attributes to the preferred sites. This enables flexibility for the research in the case a site becomes unavailable. Another strength was citing work done recently to the time of the proposal. This provides up to date information and data about the topic. One aspect of the proposal that could have been expanded upon was more explanation of the problem and why it is important to develop a greater understanding of the subject. The problem is the aspect which gives the proposal merit and thus should be elaborated.

The concepts discussed in this research pertain to my topic on avalanche risk in two ways. Primarily, both proposals are looking at attributing changes in observed patterns to climate change. Secondly, the presence and health of trees decrease the risk of avalanches because trees stabilize the snowpack, inhibiting slides. Declining health of alpine forests could be another trigger for why more fatalities from avalanches are occurring. This proposal also demonstrated how specific observational data can be created in the field by simulating an event, dust deposition in this case, and through the use of control sites conclusions can be made. This is imperative for my proposal because observing the impact of natural dust deposition on layers of snow that have been buried by new snow could be immensely difficult to get the timing right for observations. However, if dust is artificially introduced more variables can be controlled and more accurate results generated.

1. https://www.fs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb5068763.pdf

Snow Avalanche Climatology of the Western United States Mountain Ranges

Cary J. Mock and Karl W. Birkeland

The Western United States contains three climate zones that can produce avalanches; coastal, intermountain, and continental. Each zone has distinct avalanche characteristics. The coastal zone has abundant snowfall, higher snow densities, and higher temperatures and contains the pacific mountain ranges. The continental zone has by lower temperatures, lower snowfall, lower snow densities, higher snow temperature gradients, and a more persistently unstable snowpack resulting from depth hoar. The continental zone contains the Rockies. The intercontinental zone contains mountains in Utah, Montana, and Idaho and has characteristics of both the other zones. The zones generally follow an east to west gradient starting with continental in the Rocky Mountains and moving to the intermountain and then Pacific zone on the west coast. Defining these zones and describing the climate and environmental characteristics that are associated with each zone is imperative for improving forecasts of avalanche danger and preventing avalanches.

The two primary types of avalanches are loose snow slides or slab avalanches. Slab avalanches pose the greatest threat to life due to their greater size, greater distance they can travel and increased degree of unpredictability. Slab avalanches form when a cohesive slab overlays a less cohesive, weak layer. The slab breaks off from the layer beneath when stress is introduced. This stress can come from new or wind-blown snow, falling cornices, explosives, or the weight of a person on a slope.

The question this article was attempting to answer was could zones that can produce environments that avalanche be defined by characteristics unique to each zone. By answering this question it could enable better long-term predictions of avalanche risk and assist with short-term risk management and forecasting.

The researchers used interval/ratio climate data from public and private records of the Westwide Avalanche Network WWAN to calculate means of temperature, precipitation, snowfall, snow depth, and snow density for each of the three climate zones. Data from 45 stations and a few ski resorts from 1969 to 1995 created data sets that the researchers quantitatively analyzed for correlations. The unit of analysis was the same as the unit of observation because the locations the data was collected from was also what parameter for how the correlations were generated, from trends at those locations.

The researchers used a different method for data analysis as well. They used box plots to generate ranges for the snow avalanche climate classification, by comparing the variability of temperature, snowfall, snow water equivalent, snow depth, December temperature gradient, and rainfall for each of the three major avalanche climate regions. For example, this method of analysis visually displayed that coastal zones are characterized by warmer temperatures, ranging from approximately -3 to 0 degrees C on average.

This research provides more of the defining characteristics of the environments I will be investigating for my project. The method was interesting because it used patterns of temperature, precipitation, snowfall, snow depth, and snow density, snow water equivalent (SWE) and others to identify spatially where they are correlated to instead of looking at locations and finding patterns in those locations. It allowed for a greater scope and to not make conclusions about areas that you believe are important before the data has been analyzed.

Another valuable piece of information I learned from this article was that WWAN sites collect more information needed for avalanche hazard research such as snow water equivalent (SWE). However WWAN stations rarely observe backcountry avalanches, so Department of Transportation Data can be used as well.

One question this article prompted for my project was are climates shifting from continental to intermountain? There was little variability of zones demonstrating characteristics of other zones occurred during the data analysis but some areas in the southwestern (Colorado) portion of the continental zone expressed certain intermountain characteristics periodically. Could this variation be amplified by climate change and would that increase or decrease the risk of avalanches in that area?

Mock, C. J., & Birkeland, K. W. (2000). Snow Avalanche Climatology of the Western United States Mountain Ranges. Bulletin of the American Meteorological Society, 81(10), 2367-2392. doi:10.1175/1520-0477(2000)081<2367:sacotw>2.3.co;2

Snow Temperature Changes within a Seasonal Snowpack and Their Relationship to Turbulent Fluxes of Sensible and Latent Heat

Sean P. Burns, Noah P. Molotch, Mark W. Williams, John F. Knowles, Brian Seok, Russell K. Monson, Andrew A. Turnipseed, and Peter D. Blanken

Snowpack in alpine regions is a critical reservoir for water storage. The warming climate is affecting the amount of snow in these areas and the timing for when that snow melts. High elevation areas are particularly vulnerable to changes in the climate. In order to better understand how specific changes in the climate will affect snowpack a better understanding of how energy moves through the snowpack is required. Snowpack’s within forested areas add and an additional level of complexity when investigating heat transfer. The tree canopy blocks incoming shortwave radiation from the sun and shades the snow pack. Trees enhance longwave radiation cooling during the night when shortwave radiation diminishes. Trees also shelter the snowpack from the wind, which decreases changes in temperature at the surface of the snow. Heat is transferred through a snowpack primarily by conduction through the ice crystals. The ice crystals are in contact with one another, allowing heat to transfer from one crystal to another. Changes in snow temperature in a snow pack equate to changes in snow crystal structure. Rapid fluctuations in temperatures can alter the snow grains and affect snowpack cohesion.

This article investigated the changes to internal snowpack temperatures and possible triggers for intensified snowpack warming prior to spring melt. The researchers used ratio data in the form of acts, behaviors, and events collected primarily at the Niwot Ridge Subalpine Forest AmeriFlux site in Colorado. Reports of acts, behaviors, and events in the form of meteorological data from the National Oceanic and Atmospheric Administration was collected as well as data from corresponding studies. Quantitative analysis using equations was used to compare a wide range of variables from snow and soil temperatures to snowpack properties, energy fluxes, wind, and aspect. These were graphed and the information that was collected to describe environmental conditions that could create the conditions required for a warm u event.

One of the conclusions that were made was that “If air with a dewpoint temperature near the snow surface temperature is present, water vapor can condense on the snow surface releasing latent heat and causing the snowpack temperature to rapidly warm.” This article was strong in its evaluation of its own practices and its understanding of the limitations of its conclusions. However, describing the environmental conditions that could create scenarios with similar warm up potential demonstrated the scope the research had and the accuracy of its results.

A connection that I found from this research to my own topic was that the high winds triggering dust events could increase turbulent fluxes at the surface of the snow. If fewer trees are present as a consequence of drought and pine beetle (positive feedback loop kills more trees) then snowpack is less sheltered increasing risk of rapid temperature changes. Changes to internal snowpack temperature modify snow crystal structure, which could produce weaker layers increasing the risk of avalanche and increasing melting rate.

 Burns, S. P., Molotch, N. P., Williams, M. W., Knowles, J. F., Seok, B., Monson, R. K., . . . Blanken, P. D. (2014). Snow Temperature Changes within a Seasonal Snowpack and Their Relationship to Turbulent Fluxes of Sensible and Latent Heat. Journal of Hydrometeorology, 15(1), 117-142. doi:10.1175/jhm-d-13-026.1

Journal Two

Imprint of climate and climate change in alluvial riverbeds: Continental United States, 1950-2011

Louse J. Slater and Michael Bliss Singer

Climate change impacts the levels of precipitation certain areas will receive in the future. For some locations, climate change will increase the amount of precipitation they receive annually while for others it will drastically reduce the level of precipitation they receive. Precipitation, which becomes fluvial discharge, influences the movement of alluvial rivers. Alluvial riverbeds are comprised of mobile sediment that is transported and shapes the river channel during flood events. The article investigated the degree to which stream bed elevation changes due to climate and whether changes to the climate can be observed through riverbeds.

The data was collected through the US Geological Survey streamflow measurements of 915 sites that were minimally impacted by human activities. For each site streambed elevation above the local datum was determined and then Q, streamflow, was calculated from daily flow rates. This uses the data type reports of acts, behaviors or events and uses the data collection method of public and private records. The researchers did not complete the research themselves but used ratio data that was already available to them through the US Geologic Survey to create equations for delineating rates in streambed elevation change. It was concluded that trends in alluvial streambed elevation were influenced by changes in climate.

This research took data that was already in existence and found new ways to use it and found new conclusions that can be drawn from it. This represents a fascinating part of scientific research. You do not always have to be conducting your own research to make new discoveries and to innovate. In fact, with the data already available more time and resources can be spent on properly evaluation and interpreting the results you gain from that data.

The aspect of this article that I would like to highlight for the class is the degree to which all of the physical processes of the earth are connected. When humans adjust the climate it is changing precipitation patterns, which changes how sediment is transported and deposited, which changes the streambed elevation, which changes the likelihood of a rain event causing a flood. The impacts are so vast that research is being done every day to attempt to understand how the changes to climate that we have already observed are impacting the countless systems on earth.

Slater, L. J., & Singer, M. B. (2013). Imprint of climate and climate change in alluvial riverbeds: Continental United States, 1950-2011. Geology, 41(5), 595-598.

Elevated Concentrations of Methyl Mercury in Streams after Forest Clear-cut: A Consequence of Mobilization from Soil or New Methylation?

Ulf Skyllberg, Mattias Björkman Westin, Markus Meili, and Erick Björn
This article, published in the journal Environmental Science and Technology investigates the relationship between neurotoxin Methyl Mercury (MeHg) and forestry practices. Hg is formed from the process of combustion of fossil fuels. Long range transport by the atmosphere moves the Me to other locations where it is deposited. The inorganic Hg transforms into MeHg in areas characterized by wetlands and forested regions. MeHg can bioaccumulation in organisms meaning the toxic MeHg is absorbed faster than the organism can remove it. Increased Hg in the environment has also been linked to forest logging actives. The article’s topic is the impacts of inorganic compounds resulting from forestry practices on environments and organisms.

The question this article seeks to answer is to confirm the causal relationship between clear-cutting forest and increasing MeHg concentrations as well as determining if the elevated concentrations of MeHg were a result of the mobilization of Hg is the soils or from new production of Hg. The authors used acts, behaviors or events and detached observations to measure data in regards to the contents of streams. The data was collected at 47 unique forest stands that were subjected to clear-cutting from 1998-2007 and 10 mature forest stands with trees >70 years old. A criterion for the sites was each had to have a consistent stream with a width of .5-1m at the sampling site. No data about the area draining into the stream was collected.

The sites were sampled once during a two-week period in August of 2007. No major precipitation event took place during the two-week sampling period. The data was analyzed quantitatively using statistical analysis to compare data from the clear-cut areas by age and to the reference site. An ANOVA, Analysis of Variation, was used to determine if the data would be a part of one population. This means it was testing to see if there were any significant differences in the data. It was concluded that there was a significant difference meaning clear-cutting was tied to increases in MeHg.

This research was executed well with detailed descriptions of how data was collected and the procedures that the researchers used. I felt that more data could have been collected during a separate two-week period in order decrease the margin for error. The graphs showed multiple data tables in a succinct manner that made them easy to interpret. Overall I felt the article was clear and concise. The aspect that I would highlight would be that there are many implications for removing forests. Not only does it decrease CO₂ sequestration, increase erosion and increase desertification it adds harmful neurotoxins to the environment which damage organisms in areas downstream from the clear-cutting.

Ulf Skyllberg, Mattias Björkman Westin, Markus Meili, and Erick Björn. Elevated Concentrations of Methyl Mercury in Streams after Forest Clear-cut: A Consequence of Mobilization from Soil or New Methylation? Environ. Sci. Technol. 2009, 43, 8537-8541.