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• 1. [Article] Thermal controls of Yellowstone cutthroat trout and invasive fishes under climate change

  To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. The published article is copyrighted by Wiley-Blackwell and can be found at: http:...

  Citation × Citation Citation Abstract Copy Title: Thermal controls of Yellowstone cutthroat trout and invasive fishes under climate change Author: Hostetler, Steven, Gresswell, Robert, Alder, Jay R., Shepard, Bradley, Al-Chokhachy, Robert To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. The published article is copyrighted by Wiley-Blackwell and can be found at: http://onlinelibrary.wiley.com/. Title: Thermal controls of Yellowstone cutthroat trout and invasive fishes under climate change Author: Hostetler, Steven, Gresswell, Robert, Alder, Jay R., Shepard, Bradley, Al-Chokhachy, Robert To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. The published article is copyrighted by Wiley-Blackwell and can be found at: http://onlinelibrary.wiley.com/. Close

• 2. [Article] Improving Projections of Tidal Marsh Persistence under Climate Change with Remote Sensing and Site-Specific Data

  Tidal marshes are dynamic ecosystems that are threatened by climate change and sea-level rise. To characterize baseline condition and historic climate sensitivities, and improve projections into the future, ...

  Citation × Citation Citation Abstract Copy Title: Improving Projections of Tidal Marsh Persistence under Climate Change with Remote Sensing and Site-Specific Data Author: Buffington, Kevin John Tidal marshes are dynamic ecosystems that are threatened by climate change and sea-level rise. To characterize baseline condition and historic climate sensitivities, and improve projections into the future, new methods are required that integrate data from the field and remote sensing platforms. Marsh elevation response models can be calibrated with site-specific data to determine the vulnerability of a marsh to sea-level rise and help guide management decisions. Elevation models are sensitive to initial elevation, the rate of accretion, and aboveground biomass. The overarching goal of this dissertation was to develop techniques to improve these important model inputs and evaluate the range of spatial and temporal variation. Light detection and ranging (lidar) is an invaluable tool for collecting elevation data, however dense vegetation prevents the accurate measurement of the tidal marsh surface. In Chapter 2, I describe the development of a technique to calibrate lidar digital elevation models with survey elevation data using readily available multispectral aerial imagery from the National Agricultural Inventory Program (NAIP). Using survey elevation data across 17 Pacific Coast tidal marshes, I demonstrated the utility of the Lidar Elevation Adjustment with NDVI (LEAN) technique to account for the positive bias in lidar due to vegetation. LEAN reduced error from an average of 23.1 cm to 7.2 cm root mean squared error and removed the positive bias caused by vegetation. This increase in accuracy will facilitate more accurate assessments of current and future vulnerability to sea-level rise. The phenology of aboveground biomass in tidal marsh plants in relation to climate variation has not been explored in the Pacific Northwest (PNW). In Chapter 3 I explain how I leveraged the Landsat archive and cloud computing capabilities to assess how Tasseled Cap Greenness (TCG, a proxy for aboveground biomass) in three PNW tidal marshes has responded to recent variation in climate to characterize sensitivity to climate change. Through analysis of over 3700 Landsat images obtained from 1984-2015, I found increased annual precipitation resulted in a higher peak TCG, while warmer May temperatures resulted in an earlier day of peak TCG. These results also demonstrate how time-series analysis of remote sensing data can be used to examine the sensitivity of tidal marsh plants to climate variability and directional change. The range of variation in tidal marsh accretion rates has not been characterized across the PNW. For Chapter 4, I collected and analyzed twenty-two soil cores from eight estuaries to estimate historic accretion rates with radioisotope dating techniques and evaluated the amount and source of variation across estuaries. I found that tidal marshes across the PNW had accretion rates greater than the current rate of sea-level rise, ranging from 2.3 – 7.3 mm yr⁻¹. Using a watershed-scale analysis, I found that long-term average annual fluvial discharge was the top predictor of tidal marsh accretion rates. Additionally, I found that calibrating the Wetland Accretion Rate Model for Ecosystem Resilience (WARMER) with accretion rate data from nearby estuaries can result in uncertainties of up to 41% (50 cm) after 100 years. Finally, in Chapter 5, I demonstrate that a range of 62 cm of error is possible in WARMER models after a 100 year simulation when both uncorrected lidar and non-local accretion rates are used, fundamentally changing the interpretation of the results. Altogether, this dissertation illustrates the importance of collecting site-specific wetland vegetation and elevation data and demonstrates how lidar and multispectral remote sensing data can be leveraged to improve our understanding of how climate variability and change impacts coastal ecosystems. Title: Improving Projections of Tidal Marsh Persistence under Climate Change with Remote Sensing and Site-Specific Data Author: Buffington, Kevin John Tidal marshes are dynamic ecosystems that are threatened by climate change and sea-level rise. To characterize baseline condition and historic climate sensitivities, and improve projections into the future, new methods are required that integrate data from the field and remote sensing platforms. Marsh elevation response models can be calibrated with site-specific data to determine the vulnerability of a marsh to sea-level rise and help guide management decisions. Elevation models are sensitive to initial elevation, the rate of accretion, and aboveground biomass. The overarching goal of this dissertation was to develop techniques to improve these important model inputs and evaluate the range of spatial and temporal variation. Light detection and ranging (lidar) is an invaluable tool for collecting elevation data, however dense vegetation prevents the accurate measurement of the tidal marsh surface. In Chapter 2, I describe the development of a technique to calibrate lidar digital elevation models with survey elevation data using readily available multispectral aerial imagery from the National Agricultural Inventory Program (NAIP). Using survey elevation data across 17 Pacific Coast tidal marshes, I demonstrated the utility of the Lidar Elevation Adjustment with NDVI (LEAN) technique to account for the positive bias in lidar due to vegetation. LEAN reduced error from an average of 23.1 cm to 7.2 cm root mean squared error and removed the positive bias caused by vegetation. This increase in accuracy will facilitate more accurate assessments of current and future vulnerability to sea-level rise. The phenology of aboveground biomass in tidal marsh plants in relation to climate variation has not been explored in the Pacific Northwest (PNW). In Chapter 3 I explain how I leveraged the Landsat archive and cloud computing capabilities to assess how Tasseled Cap Greenness (TCG, a proxy for aboveground biomass) in three PNW tidal marshes has responded to recent variation in climate to characterize sensitivity to climate change. Through analysis of over 3700 Landsat images obtained from 1984-2015, I found increased annual precipitation resulted in a higher peak TCG, while warmer May temperatures resulted in an earlier day of peak TCG. These results also demonstrate how time-series analysis of remote sensing data can be used to examine the sensitivity of tidal marsh plants to climate variability and directional change. The range of variation in tidal marsh accretion rates has not been characterized across the PNW. For Chapter 4, I collected and analyzed twenty-two soil cores from eight estuaries to estimate historic accretion rates with radioisotope dating techniques and evaluated the amount and source of variation across estuaries. I found that tidal marshes across the PNW had accretion rates greater than the current rate of sea-level rise, ranging from 2.3 – 7.3 mm yr⁻¹. Using a watershed-scale analysis, I found that long-term average annual fluvial discharge was the top predictor of tidal marsh accretion rates. Additionally, I found that calibrating the Wetland Accretion Rate Model for Ecosystem Resilience (WARMER) with accretion rate data from nearby estuaries can result in uncertainties of up to 41% (50 cm) after 100 years. Finally, in Chapter 5, I demonstrate that a range of 62 cm of error is possible in WARMER models after a 100 year simulation when both uncorrected lidar and non-local accretion rates are used, fundamentally changing the interpretation of the results. Altogether, this dissertation illustrates the importance of collecting site-specific wetland vegetation and elevation data and demonstrates how lidar and multispectral remote sensing data can be leveraged to improve our understanding of how climate variability and change impacts coastal ecosystems. Close

• 3. [Article] Predicting landscape sensitivity to present and future floods in the Pacific Northwest, USA

  Supporting information is available online at: http://onlinelibrary.wiley.com/doi/10.1002/hyp.10553/suppinfo

  Citation × Citation Citation Abstract Copy Title: Predicting landscape sensitivity to present and future floods in the Pacific Northwest, USA Author: Lewis, Sarah L., Safeeq, Mohammad, Staab, Brian, Grant, Gordon E. Supporting information is available online at: http://onlinelibrary.wiley.com/doi/10.1002/hyp.10553/suppinfo Title: Predicting landscape sensitivity to present and future floods in the Pacific Northwest, USA Author: Lewis, Sarah L., Safeeq, Mohammad, Staab, Brian, Grant, Gordon E. Supporting information is available online at: http://onlinelibrary.wiley.com/doi/10.1002/hyp.10553/suppinfo Close

• 4. [Article] Simulating past, present, and future changes in ENSO : a model evaluation and data-model comparison

  This thesis presents the results of a formal evaluation of a new AOGCM, GENMOM, demonstrating its ability to simulate present-day climate and ENSO dynamics. The model is applied to simulate climate for ...

  Citation × Citation Citation Abstract Copy Title: Simulating past, present, and future changes in ENSO : a model evaluation and data-model comparison Author: Alder, Jay R. This thesis presents the results of a formal evaluation of a new AOGCM, GENMOM, demonstrating its ability to simulate present-day climate and ENSO dynamics. The model is applied to simulate climate for the Last Glacial Maximum, deglacial, and Holocene time periods. The model output is evaluated against the best available proxy reconstructions in a detailed data-model comparison. ENSO strength is analyzed in seven paleo simulations and compared to coral and laminated lake sediment proxy records to provide an understanding of how ENSO related mechanisms varied in the past and how they vary under increased atmospheric CO₂ forced global warming. The GENMOM simulated present-day is found to be on par with three models used in the IPCC AR4 assessment and is comparable with reanalysis products (e.g, NCEP2). Atmospheric features such as the jet stream structure and major semipermanent sea level pressure centers are well simulated as is the mean planetary-scale wind structure that is needed to produce the correct position of stormtracks. Most ocean surface currents are reproduced except where they are not resolvable at T31 resolution. Overall, GENMOM captures the observed gradients and spatial distributions of annual surface temperature and precipitation and the simulations are on par with other AOGCMs. Deficiencies in the GENMOM present-day simulation include a warm bias in the surface temperature over the southern oceans, a split in the ITCZ and weaker-thanobserved overturning circulation. GENMOM produces a global temperature bias of 0.6 °C. GENMOM is demonstrated to capture ENSO dynamics similar to eight AOGCMs that were evaluated in the IPCC AR4. The Niño 3 - 4 indices have a standard deviation within 0.3 °C of the observations, indicating GENMOM is producing variability in the tropical Pacifc that is comparable to observations. GENMOM produces present-day ENSO events with an average period of 5.6 years, which is within the 2 – 7 range exhibited in the observed historical record. The mid-Holocene (6ka) and Last Glacial Maximum (LGM, 21ka) simulations are compared to the best available proxy reconstructions for sea surface temperature, precipitation and net moisture to ensure the simulations are plausible. This thesis finds that the model is in good agreement over broad spatial scales, with regional discrepancies between the model and proxy data. Coral and laminated lake sediment proxy records indicate mid-Holocene ENSO strength was reduced by 15 - 60%, offering a scenario in which ENSO-related components can be tested in climates different than present-day, thereby providing context for future changes in ENSO. The mid-Holocene simulations exhibit a 20% reduction of ENSO strength, caused by a precession forced enhancement of the Indian summer monsoon, which strengthened ENSO-related Bjerknes feedbacks. ENSO strength in the LGM is weakened by ~25%, which is not found to be caused by changes in equatorial Pacific dynamics but rather mean state cooling that weakens the tropical thermocline. The 2x and 4x simulations have strongly enhanced and more frequent ENSO events caused by disproportionate warming of the eastern Pacific relative to the western Pacific, which weakens the east-west Pacific surface temperature gradient, allowing larger anomalies, and hence ENSO events, to develop. Title: Simulating past, present, and future changes in ENSO : a model evaluation and data-model comparison Author: Alder, Jay R. This thesis presents the results of a formal evaluation of a new AOGCM, GENMOM, demonstrating its ability to simulate present-day climate and ENSO dynamics. The model is applied to simulate climate for the Last Glacial Maximum, deglacial, and Holocene time periods. The model output is evaluated against the best available proxy reconstructions in a detailed data-model comparison. ENSO strength is analyzed in seven paleo simulations and compared to coral and laminated lake sediment proxy records to provide an understanding of how ENSO related mechanisms varied in the past and how they vary under increased atmospheric CO₂ forced global warming. The GENMOM simulated present-day is found to be on par with three models used in the IPCC AR4 assessment and is comparable with reanalysis products (e.g, NCEP2). Atmospheric features such as the jet stream structure and major semipermanent sea level pressure centers are well simulated as is the mean planetary-scale wind structure that is needed to produce the correct position of stormtracks. Most ocean surface currents are reproduced except where they are not resolvable at T31 resolution. Overall, GENMOM captures the observed gradients and spatial distributions of annual surface temperature and precipitation and the simulations are on par with other AOGCMs. Deficiencies in the GENMOM present-day simulation include a warm bias in the surface temperature over the southern oceans, a split in the ITCZ and weaker-thanobserved overturning circulation. GENMOM produces a global temperature bias of 0.6 °C. GENMOM is demonstrated to capture ENSO dynamics similar to eight AOGCMs that were evaluated in the IPCC AR4. The Niño 3 - 4 indices have a standard deviation within 0.3 °C of the observations, indicating GENMOM is producing variability in the tropical Pacifc that is comparable to observations. GENMOM produces present-day ENSO events with an average period of 5.6 years, which is within the 2 – 7 range exhibited in the observed historical record. The mid-Holocene (6ka) and Last Glacial Maximum (LGM, 21ka) simulations are compared to the best available proxy reconstructions for sea surface temperature, precipitation and net moisture to ensure the simulations are plausible. This thesis finds that the model is in good agreement over broad spatial scales, with regional discrepancies between the model and proxy data. Coral and laminated lake sediment proxy records indicate mid-Holocene ENSO strength was reduced by 15 - 60%, offering a scenario in which ENSO-related components can be tested in climates different than present-day, thereby providing context for future changes in ENSO. The mid-Holocene simulations exhibit a 20% reduction of ENSO strength, caused by a precession forced enhancement of the Indian summer monsoon, which strengthened ENSO-related Bjerknes feedbacks. ENSO strength in the LGM is weakened by ~25%, which is not found to be caused by changes in equatorial Pacific dynamics but rather mean state cooling that weakens the tropical thermocline. The 2x and 4x simulations have strongly enhanced and more frequent ENSO events caused by disproportionate warming of the eastern Pacific relative to the western Pacific, which weakens the east-west Pacific surface temperature gradient, allowing larger anomalies, and hence ENSO events, to develop. Close

• 5. [Article] Regional Scale Modeling of Climate, Cryosphere, and Freshwater Discharge in Changing Coastal Mountain Environments

  The glaciated coastal mountain watersheds that drain into the Gulf of Alaska (GOA) provide a model laboratory to explore the challenges of hydrological modeling and study the impact of climate and glacier ...

  Citation × Citation Citation Abstract Copy Title: Regional Scale Modeling of Climate, Cryosphere, and Freshwater Discharge in Changing Coastal Mountain Environments Author: Beamer, Jordan P. The glaciated coastal mountain watersheds that drain into the Gulf of Alaska (GOA) provide a model laboratory to explore the challenges of hydrological modeling and study the impact of climate and glacier cover change on regional hydrology. The region is data-sparse and contains a complex assemblage of topography and land cover, including a system of mountain glaciers that are retreating at some of the highest rates on Earth. The high rates of runoff from precipitation and glacial melt delivered by coastal rivers influence ocean circulation patterns, rates of global sea level rise, and provide spawning habitat for the large salmon populations. Physically-based hydrological modeling of the major water budget components of the GOA, driven using historical reanalysis weather data and land cover, reveals that the modeled water budget components, particularly precipitation input, vary widely between commonly-used weather products. The majority of the large freshwater flux into the GOA is derived from distributed coastal streams rather than the large inland rivers. The modeled seasonal aggregated GOA hydrograph is dominated by the spring and early summer snowmelt, and supplemented by late summer glacial ice melt. Model results demonstrate good agreement with NASA Gravity Recovery and Climate Experiment (GRACE) satellite data in terms of annual amplitudes and long term losses (ice loss), and suggest that existing GRACE solutions, previously reported to represent glacier mass balance alone, are actually measuring the full water budget of land and ice surfaces. An ensemble of climate models and future emissions scenarios were paired with systematically altered land cover to test the sensitivity of the hydrologic system to changes in regional climate patterns and glacier coverage representative of late twenty first century conditions. Compared with the hindcast simulations, the model results forced with increased regional air temperatures and precipitation inputs and reduced glacier cover produce an increase in the annual GOA freshwater discharge volume. The seasonal GOA hydrograph is flattened due to increased winter runoff from more winter rainfall and less snow accumulation, and lower levels of snowmelt and glacier ice contribution. Large uncertainties exist in the direction of change in the glacier runoff component, primarily due to uncertainties that exist in predicting glacier response to climate change. Hydrological modeling with high resolution and inclusion of relevant physical processes can produce significantly improved products that are of high value to and in demand by numerous other scientific communities. However, the value and accuracy of the output from the hydrologic model is highly dependent on the weather forcing quality. Given the considerable importance of quality weather forcing for hydrologic modeling, it is imperative to assess the suitability of multiple products by evaluating local and regional performance and accounting for uncertainty. Additional efforts should be made to improve the spatial resolution of the reanalysis through downscaling and to strategically increase the number of weather stations at high elevations and incorporate that data into weather forcing datasets. Title: Regional Scale Modeling of Climate, Cryosphere, and Freshwater Discharge in Changing Coastal Mountain Environments Author: Beamer, Jordan P. The glaciated coastal mountain watersheds that drain into the Gulf of Alaska (GOA) provide a model laboratory to explore the challenges of hydrological modeling and study the impact of climate and glacier cover change on regional hydrology. The region is data-sparse and contains a complex assemblage of topography and land cover, including a system of mountain glaciers that are retreating at some of the highest rates on Earth. The high rates of runoff from precipitation and glacial melt delivered by coastal rivers influence ocean circulation patterns, rates of global sea level rise, and provide spawning habitat for the large salmon populations. Physically-based hydrological modeling of the major water budget components of the GOA, driven using historical reanalysis weather data and land cover, reveals that the modeled water budget components, particularly precipitation input, vary widely between commonly-used weather products. The majority of the large freshwater flux into the GOA is derived from distributed coastal streams rather than the large inland rivers. The modeled seasonal aggregated GOA hydrograph is dominated by the spring and early summer snowmelt, and supplemented by late summer glacial ice melt. Model results demonstrate good agreement with NASA Gravity Recovery and Climate Experiment (GRACE) satellite data in terms of annual amplitudes and long term losses (ice loss), and suggest that existing GRACE solutions, previously reported to represent glacier mass balance alone, are actually measuring the full water budget of land and ice surfaces. An ensemble of climate models and future emissions scenarios were paired with systematically altered land cover to test the sensitivity of the hydrologic system to changes in regional climate patterns and glacier coverage representative of late twenty first century conditions. Compared with the hindcast simulations, the model results forced with increased regional air temperatures and precipitation inputs and reduced glacier cover produce an increase in the annual GOA freshwater discharge volume. The seasonal GOA hydrograph is flattened due to increased winter runoff from more winter rainfall and less snow accumulation, and lower levels of snowmelt and glacier ice contribution. Large uncertainties exist in the direction of change in the glacier runoff component, primarily due to uncertainties that exist in predicting glacier response to climate change. Hydrological modeling with high resolution and inclusion of relevant physical processes can produce significantly improved products that are of high value to and in demand by numerous other scientific communities. However, the value and accuracy of the output from the hydrologic model is highly dependent on the weather forcing quality. Given the considerable importance of quality weather forcing for hydrologic modeling, it is imperative to assess the suitability of multiple products by evaluating local and regional performance and accounting for uncertainty. Additional efforts should be made to improve the spatial resolution of the reanalysis through downscaling and to strategically increase the number of weather stations at high elevations and incorporate that data into weather forcing datasets. Close