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• 1. [Article] The Influence of Recurrent Modes of Climate Variability on the Occurrence of Winter and Summer Extreme Temperatures over North America

  The influence of the Pacific–North American (PNA) pattern, the northern annular mode (NAM), and the El Ni~no–Southern Oscillation (ENSO) on extreme temperature days and months over North America is examined. ...

  Citation × Citation Citation Abstract Copy Title: The Influence of Recurrent Modes of Climate Variability on the Occurrence of Winter and Summer Extreme Temperatures over North America Author: Loikith, Paul C., Broccoli, Anthony J. Year: 2014 The influence of the Pacific–North American (PNA) pattern, the northern annular mode (NAM), and the El Ni~no–Southern Oscillation (ENSO) on extreme temperature days and months over North America is examined. Associations between extreme temperature days and months are strongest with the PNA and NAM andweaker for ENSO. In general, the associationwith extremes tends to be stronger onmonthly than daily time scales and for winter as compared to summer. Extreme temperatures are associated with the PNAandNAMin the vicinity of the centers of action of these circulation patterns; however, many extremes also occur on days when the amplitude and polarity of these patterns do not favor their occurrence. In winter, synoptic-scale, transient weather disturbances are important drivers of extreme temperature days; however, many of these smaller-scale events are concurrent with amplified PNA or NAMpatterns. Associations are weaker in summer when other physicalmechanisms affecting the surface energy balance, such as anomalous soilmoisture content, also influence the occurrence of extreme temperatures. Title: The Influence of Recurrent Modes of Climate Variability on the Occurrence of Winter and Summer Extreme Temperatures over North America Author: Loikith, Paul C., Broccoli, Anthony J. Year: 2014 The influence of the Pacific–North American (PNA) pattern, the northern annular mode (NAM), and the El Ni~no–Southern Oscillation (ENSO) on extreme temperature days and months over North America is examined. Associations between extreme temperature days and months are strongest with the PNA and NAM andweaker for ENSO. In general, the associationwith extremes tends to be stronger onmonthly than daily time scales and for winter as compared to summer. Extreme temperatures are associated with the PNAandNAMin the vicinity of the centers of action of these circulation patterns; however, many extremes also occur on days when the amplitude and polarity of these patterns do not favor their occurrence. In winter, synoptic-scale, transient weather disturbances are important drivers of extreme temperature days; however, many of these smaller-scale events are concurrent with amplified PNA or NAMpatterns. Associations are weaker in summer when other physicalmechanisms affecting the surface energy balance, such as anomalous soilmoisture content, also influence the occurrence of extreme temperatures. Close

• 2. [Article] Climate Change Effects and Water Vulnerability in the Molalla Pudding River Basin, Oregon, USA

  Water management plans are typically developed using historical data records and historical return periods for extreme events, such as floods or droughts. Since these analyses of return periods typically ...

  Citation × Citation Citation Abstract Copy Title: Climate Change Effects and Water Vulnerability in the Molalla Pudding River Basin, Oregon, USA Author: Wherry, Susan Amelia Year: 2012 Water management plans are typically developed using historical data records and historical return periods for extreme events, such as floods or droughts. Since these analyses of return periods typically assume a certain degree of stationarity (constant mean, standard deviation, distribution) in hydrologic variables, the potential future impacts of climate change are excluded. In developing water management plans, predicted changes to climate variables should be considered to evaluate the degree of non-stationarity that may exist in the future. In this way, regions most sensitive to climate change can be identified and managed appropriately. This study performed such a task by using predicted climate data that were downscaled from general circulation models (GCM) by regional climate models (RCM) to compare climate variables in the historical period of 1971-1998 to the future period of 2041-2068. The study evaluated the precipitation and minimum/maximum temperature data from five different GCM/RCM combinations: 1) CCSM/CRCM; 2) CCSM/WRFG; 3) CGCM3/CRCM; 4) CGCM3/WRFG; and 5) HadCM3/HRM3. The five datasets were then used to calculate drought indices and drive a calibrated PRMS model of the Molalla Pudding river basin in order to evaluate changes in droughts and streamflow. The predicted changes in droughts and streamflow were then evaluated with social/economic factors for twelve cities in the Molalla Pudding river basin by two different water vulnerability indices. The index values were used to determine a rank for each city that indicated its relative vulnerability to water scarcity as compared to the other cities. In this study, three out of the five datasets predicted increased precipitation (+97-115 mm/year) over the Molalla Pudding basin and the two datasets using the CCSM GCM data predicted either no change or slightly decreased precipitation (-60 mm/year) over the Molalla Pudding basin in 2041-2068. All datasets predicted increased minimum and maximum average temperature of +1.5°C and +1.4°C respectively, and all datasets displayed increasing trends in temperature. The drought indices predicted fewer drought events (-2.4 events) over 2041-2068 with no change in duration, and no change to the number of serious drought events over 2041-2068 but with increased durations (+1.9 months). Results from the hydrologic modeling predicted increased streamflow (+4-249 cfs) in four out of the five future datasets. Using the predicted changes in hydrologic variables and social/economic census data from 2000, two types of water vulnerability indices were calculated for the twelve cities of interest. The results suggested that cities in the western portion of the basin would be more susceptible to current and future water vulnerability due to high irrigation demands for water and high social vulnerability as determined by minority populations and higher poverty, while the small cities with less dependence on agriculture would be less vulnerable. Title: Climate Change Effects and Water Vulnerability in the Molalla Pudding River Basin, Oregon, USA Author: Wherry, Susan Amelia Year: 2012 Water management plans are typically developed using historical data records and historical return periods for extreme events, such as floods or droughts. Since these analyses of return periods typically assume a certain degree of stationarity (constant mean, standard deviation, distribution) in hydrologic variables, the potential future impacts of climate change are excluded. In developing water management plans, predicted changes to climate variables should be considered to evaluate the degree of non-stationarity that may exist in the future. In this way, regions most sensitive to climate change can be identified and managed appropriately. This study performed such a task by using predicted climate data that were downscaled from general circulation models (GCM) by regional climate models (RCM) to compare climate variables in the historical period of 1971-1998 to the future period of 2041-2068. The study evaluated the precipitation and minimum/maximum temperature data from five different GCM/RCM combinations: 1) CCSM/CRCM; 2) CCSM/WRFG; 3) CGCM3/CRCM; 4) CGCM3/WRFG; and 5) HadCM3/HRM3. The five datasets were then used to calculate drought indices and drive a calibrated PRMS model of the Molalla Pudding river basin in order to evaluate changes in droughts and streamflow. The predicted changes in droughts and streamflow were then evaluated with social/economic factors for twelve cities in the Molalla Pudding river basin by two different water vulnerability indices. The index values were used to determine a rank for each city that indicated its relative vulnerability to water scarcity as compared to the other cities. In this study, three out of the five datasets predicted increased precipitation (+97-115 mm/year) over the Molalla Pudding basin and the two datasets using the CCSM GCM data predicted either no change or slightly decreased precipitation (-60 mm/year) over the Molalla Pudding basin in 2041-2068. All datasets predicted increased minimum and maximum average temperature of +1.5°C and +1.4°C respectively, and all datasets displayed increasing trends in temperature. The drought indices predicted fewer drought events (-2.4 events) over 2041-2068 with no change in duration, and no change to the number of serious drought events over 2041-2068 but with increased durations (+1.9 months). Results from the hydrologic modeling predicted increased streamflow (+4-249 cfs) in four out of the five future datasets. Using the predicted changes in hydrologic variables and social/economic census data from 2000, two types of water vulnerability indices were calculated for the twelve cities of interest. The results suggested that cities in the western portion of the basin would be more susceptible to current and future water vulnerability due to high irrigation demands for water and high social vulnerability as determined by minority populations and higher poverty, while the small cities with less dependence on agriculture would be less vulnerable. Close

• 3. [Article] Glacier Change in the North Cascades, Washington: 1900-2009

  Glaciers respond to local climate changes making them important indicators of regional climate change. The North Cascades region of Washington is the most glaciated region in the lower-48 states with approximately ...

  Citation × Citation Citation Abstract Copy Title: Glacier Change in the North Cascades, Washington: 1900-2009 Author: Dick, Kristina Amanda Year: 2013 Glaciers respond to local climate changes making them important indicators of regional climate change. The North Cascades region of Washington is the most glaciated region in the lower-48 states with approximately 25% of all glaciers and 40% of the total ice-covered area. While there are many on-going investigations of specific glaciers, little research has addressed the entire glacier cover of the region. A reference inventory of glaciers was derived from a comparison of two different inventories dating to about 1958. The different inventories agree within 93% of total number of glaciers and 94% of total ice-covered area. To quantify glacier change over the past century aerial photographs, topographic maps, and geologic maps were used. In ~1900 total area was about 533.89 ± 22.77 km2 and by 2009 the area was reduced by -56% ± 3% to 236.20 ± 12.60 km2. Most of that change occurred in the first half of the 20th century, between 1900 and 1958, -245.59 ± 25.97 km2 (-46% ± 5%) was lost, followed by a period of stability/growth in mid-century (-1% ± 3% from 1958-1990) then decline since the 1990s (-9% ± 3% from 1990-2009). The century-scale loss is associated with increasing regional temperatures warming in winter and summer; precipitation shows no trend. On a decadal time scale winter precipitation and winter and summer temperatures are important factors correlated with area loss. Topographically, smaller glaciers at lower elevations with steeper slopes and higher mean insolation exhibited greater loss than higher, gentler more shaded glaciers. Title: Glacier Change in the North Cascades, Washington: 1900-2009 Author: Dick, Kristina Amanda Year: 2013 Glaciers respond to local climate changes making them important indicators of regional climate change. The North Cascades region of Washington is the most glaciated region in the lower-48 states with approximately 25% of all glaciers and 40% of the total ice-covered area. While there are many on-going investigations of specific glaciers, little research has addressed the entire glacier cover of the region. A reference inventory of glaciers was derived from a comparison of two different inventories dating to about 1958. The different inventories agree within 93% of total number of glaciers and 94% of total ice-covered area. To quantify glacier change over the past century aerial photographs, topographic maps, and geologic maps were used. In ~1900 total area was about 533.89 ± 22.77 km2 and by 2009 the area was reduced by -56% ± 3% to 236.20 ± 12.60 km2. Most of that change occurred in the first half of the 20th century, between 1900 and 1958, -245.59 ± 25.97 km2 (-46% ± 5%) was lost, followed by a period of stability/growth in mid-century (-1% ± 3% from 1958-1990) then decline since the 1990s (-9% ± 3% from 1990-2009). The century-scale loss is associated with increasing regional temperatures warming in winter and summer; precipitation shows no trend. On a decadal time scale winter precipitation and winter and summer temperatures are important factors correlated with area loss. Topographically, smaller glaciers at lower elevations with steeper slopes and higher mean insolation exhibited greater loss than higher, gentler more shaded glaciers. Close

• 4. [Article] Late Pleistocene and Holocene Aged Glacial and Climatic Reconstructions in the Goat Rocks Wilderness, Washington, United States

  Eight glaciers, covering an area of 1.63 km2, reside on the northern and northeastern slopes of the Goat Rocks tallest peaks in the Cascades of central Washington. At least three glacial stands occurred ...

  Citation × Citation Citation Abstract Copy Title: Late Pleistocene and Holocene Aged Glacial and Climatic Reconstructions in the Goat Rocks Wilderness, Washington, United States Author: Heard, Joshua Andrews Year: 2012 Eight glaciers, covering an area of 1.63 km2, reside on the northern and northeastern slopes of the Goat Rocks tallest peaks in the Cascades of central Washington. At least three glacial stands occurred downstream from these glaciers. Closest to modern glacier termini are Little Ice Age (LIA) moraines that were deposited between 1870 and 1899 AD, according to the lichenometric analysis. They are characterized by sharp, minimally eroded crests, little to no soil cover, and minimal vegetation cover. Glacier reconstructions indicate that LIA glaciers covered 8.29 km2, 76% more area than modern ice coverage. The average LIA equilibrium line altitude (ELA) of 1995 ± 70 m is ~150 m below the average modern ELA of 2149 ± 76 m. To satisfy climate conditions at the LIA ELA, the winter snow accumulation must have been 8 to 43 cm greater and mean summer temperatures 0.2 to 1.3 ºC cooler than they are now. Late Pleistocene to early Holocene (LPEH) aged moraines are located between 100 and 400 m below the LIA deposits. They have degraded moraine crests, few surface boulders, and considerable vegetation and soil cover. Volcanic ashes indicate LPEH moraines were deposited before 1480 AD while morphometric data suggest deposition during the late Pleistocene or early Holocene. The average LPEH ELA of 1904 ± 110 m is ~ 240 m and ~90 m below the modern and LIA ELAs, respectively. The climate change necessary to maintain a glacier with an ELA at that elevation for LPEH conditions requires the winter accumulation to increase by 47 to 48 cm weq and the mean summer temperature to cool by 1.4 to 1.5 ºC. Last glacial maximum (LGM) moraines are located more than 30 km downstream from modern glacial termini. They are characterized by hummocky topography, rounded moraine crests, complete vegetation cover, and well developed soil cover. Moraine morphometry, soil characteristics, and distance from modern glacial termini indicate that deposition occurred at least 15 ka BP during an expansive cooling event, the last being the LGM. The LGM ELA of 1230 m is ~920 m below the modern ELA. The climate change necessary to maintain a glacier with an ELA at that elevation for LGM conditions requires the mean summer temperature to cool by 5.6 ºC with no change in precipitation. Title: Late Pleistocene and Holocene Aged Glacial and Climatic Reconstructions in the Goat Rocks Wilderness, Washington, United States Author: Heard, Joshua Andrews Year: 2012 Eight glaciers, covering an area of 1.63 km2, reside on the northern and northeastern slopes of the Goat Rocks tallest peaks in the Cascades of central Washington. At least three glacial stands occurred downstream from these glaciers. Closest to modern glacier termini are Little Ice Age (LIA) moraines that were deposited between 1870 and 1899 AD, according to the lichenometric analysis. They are characterized by sharp, minimally eroded crests, little to no soil cover, and minimal vegetation cover. Glacier reconstructions indicate that LIA glaciers covered 8.29 km2, 76% more area than modern ice coverage. The average LIA equilibrium line altitude (ELA) of 1995 ± 70 m is ~150 m below the average modern ELA of 2149 ± 76 m. To satisfy climate conditions at the LIA ELA, the winter snow accumulation must have been 8 to 43 cm greater and mean summer temperatures 0.2 to 1.3 ºC cooler than they are now. Late Pleistocene to early Holocene (LPEH) aged moraines are located between 100 and 400 m below the LIA deposits. They have degraded moraine crests, few surface boulders, and considerable vegetation and soil cover. Volcanic ashes indicate LPEH moraines were deposited before 1480 AD while morphometric data suggest deposition during the late Pleistocene or early Holocene. The average LPEH ELA of 1904 ± 110 m is ~ 240 m and ~90 m below the modern and LIA ELAs, respectively. The climate change necessary to maintain a glacier with an ELA at that elevation for LPEH conditions requires the winter accumulation to increase by 47 to 48 cm weq and the mean summer temperature to cool by 1.4 to 1.5 ºC. Last glacial maximum (LGM) moraines are located more than 30 km downstream from modern glacial termini. They are characterized by hummocky topography, rounded moraine crests, complete vegetation cover, and well developed soil cover. Moraine morphometry, soil characteristics, and distance from modern glacial termini indicate that deposition occurred at least 15 ka BP during an expansive cooling event, the last being the LGM. The LGM ELA of 1230 m is ~920 m below the modern ELA. The climate change necessary to maintain a glacier with an ELA at that elevation for LGM conditions requires the mean summer temperature to cool by 5.6 ºC with no change in precipitation. Close

• 5. [Article] Where Is the Rain-on-Snow Zone in the West-Central Washington Cascades?: Monte Carlo Simulation of Large Storms in the Northwest

  Rain-on-snow (ROS) occurs when warm, wet air moves into latitudes and/or elevations having vulnerable snowpacks, where it can alter water inputs to infiltration, runoff and erosion. The Pacific Northwest ...

  Citation × Citation Citation Abstract Copy Title: Where Is the Rain-on-Snow Zone in the West-Central Washington Cascades?: Monte Carlo Simulation of Large Storms in the Northwest Author: Brunengo, Matthew John Year: 2012 Rain-on-snow (ROS) occurs when warm, wet air moves into latitudes and/or elevations having vulnerable snowpacks, where it can alter water inputs to infiltration, runoff and erosion. The Pacific Northwest is particularly susceptible: winter storms off the Pacific cause locally heavy rain plus snowmelt almost annually, and disastrous flooding and landsliding intermittently. In maritime mountainous terrain, the effects seem more likely and hydrologically important where warm rains and seasonal snowpacks are liable to coincide, in middle elevations. Several questions arise: (1) In the PNW, does ROS affect the long-term frequency and magnitude of water delivery to the ground, versus total precipitation (liquid and solid), during big storms? Where and how much? (2) If so, can we determine which elevations experience maximum hydrologic effects, the peak ROS zone? Probabilistic characteristics of ROS are difficult to establish because of geographic variability and sporadic occurrence: scattered stations and short observational records make quantitative frequency analysis difficult. These problems dictate a modeling approach, combining semi-random selection of storm properties with physical rules governing snow and water behavior during events. I created a simple computer program to perform Monte Carlo simulation of large storms over 1000 "years", generating realizations of snowpack and storm-weather conditions; in each event precipitation falls, snow accumulates and/or melts, and water moves to the ground. Frequency distributions are based on data from the Washington Cascades, and the model can be applied to specific sites or generalized elevations. Many of the data sets were based on observations at Stampede Pass, where high-quality measurements of weather and snow at the Cascade crest have been made since the 1940s. These data were used to inform the model, and to test its reliability with respect to the governing data distributions. In addition, data from ROS events at Stampede, and at research sites in southwest Oregon, were used to confirm that the model's deterministic calculations of snow accumulation, snowmelt, and percolation (yielding water available for runoff) adequately simulate conditions observed in the field. The Monte Carlo model was run for elevations ranging from 200 to 1500 m, each over a hypothetical millennium. Results indicate that the presence of snow in some storms reduces the amount of water reaching the ground. This occurred more often in highlands but also at middle and lower elevations, affecting the long-term frequency-magnitude relations across the landscape. In these conditions, the rain-gauges overestimate the amount of liquid water actually reaching the ground. For many storms, however, ROS enhances water reaching the ground, most significantly at elevations between ~500-1100 m. At lower and higher elevations, the water available for runoff exceeds precipitation in ~2% of events, but this proportion rises to ~20-30% at ~800 m. Other metrics (e.g., series statistics, exponential regression coefficients, frequency-magnitude factors) also indicate that this middle-elevation band (around ~800 m) experiences ROS most often and with greatest water available for runoff. Of the west-central Washington Cascades study region, about one-third to one-half the landscape is susceptible to significant ROS influence. These results indicate areas where ROS currently has the greatest hydrologic consequence on ecosystems and human works, and possibly the greatest sensitivity to changes in land-use and climate. Title: Where Is the Rain-on-Snow Zone in the West-Central Washington Cascades?: Monte Carlo Simulation of Large Storms in the Northwest Author: Brunengo, Matthew John Year: 2012 Rain-on-snow (ROS) occurs when warm, wet air moves into latitudes and/or elevations having vulnerable snowpacks, where it can alter water inputs to infiltration, runoff and erosion. The Pacific Northwest is particularly susceptible: winter storms off the Pacific cause locally heavy rain plus snowmelt almost annually, and disastrous flooding and landsliding intermittently. In maritime mountainous terrain, the effects seem more likely and hydrologically important where warm rains and seasonal snowpacks are liable to coincide, in middle elevations. Several questions arise: (1) In the PNW, does ROS affect the long-term frequency and magnitude of water delivery to the ground, versus total precipitation (liquid and solid), during big storms? Where and how much? (2) If so, can we determine which elevations experience maximum hydrologic effects, the peak ROS zone? Probabilistic characteristics of ROS are difficult to establish because of geographic variability and sporadic occurrence: scattered stations and short observational records make quantitative frequency analysis difficult. These problems dictate a modeling approach, combining semi-random selection of storm properties with physical rules governing snow and water behavior during events. I created a simple computer program to perform Monte Carlo simulation of large storms over 1000 "years", generating realizations of snowpack and storm-weather conditions; in each event precipitation falls, snow accumulates and/or melts, and water moves to the ground. Frequency distributions are based on data from the Washington Cascades, and the model can be applied to specific sites or generalized elevations. Many of the data sets were based on observations at Stampede Pass, where high-quality measurements of weather and snow at the Cascade crest have been made since the 1940s. These data were used to inform the model, and to test its reliability with respect to the governing data distributions. In addition, data from ROS events at Stampede, and at research sites in southwest Oregon, were used to confirm that the model's deterministic calculations of snow accumulation, snowmelt, and percolation (yielding water available for runoff) adequately simulate conditions observed in the field. The Monte Carlo model was run for elevations ranging from 200 to 1500 m, each over a hypothetical millennium. Results indicate that the presence of snow in some storms reduces the amount of water reaching the ground. This occurred more often in highlands but also at middle and lower elevations, affecting the long-term frequency-magnitude relations across the landscape. In these conditions, the rain-gauges overestimate the amount of liquid water actually reaching the ground. For many storms, however, ROS enhances water reaching the ground, most significantly at elevations between ~500-1100 m. At lower and higher elevations, the water available for runoff exceeds precipitation in ~2% of events, but this proportion rises to ~20-30% at ~800 m. Other metrics (e.g., series statistics, exponential regression coefficients, frequency-magnitude factors) also indicate that this middle-elevation band (around ~800 m) experiences ROS most often and with greatest water available for runoff. Of the west-central Washington Cascades study region, about one-third to one-half the landscape is susceptible to significant ROS influence. These results indicate areas where ROS currently has the greatest hydrologic consequence on ecosystems and human works, and possibly the greatest sensitivity to changes in land-use and climate. Close

• 6. [Article] Climate Change Impact on the Spatio-Temporal Variability of Hydro-Climate Extremes

  The rising temperature of the earth due to climate change has shown to alter the variations of hydro-climate variables, including their intensities, frequencies and durations. Extreme events such as floods ...

  Citation × Citation Citation Abstract Copy Title: Climate Change Impact on the Spatio-Temporal Variability of Hydro-Climate Extremes Author: Najafi, Mohammad Reza Year: 2013 The rising temperature of the earth due to climate change has shown to alter the variations of hydro-climate variables, including their intensities, frequencies and durations. Extreme events such as floods are, in particular, susceptible to any disturbances in climate cycles. As such it is important to provide policymakers with sufficient knowledge about the probable impacts of climate change on hydrologic extremes and most importantly on floods, which have the highest impacts on the societies. For this reason analysis of hydro-climate extremes is commonly performed using data at each site (or grid cell), however due to the limited number of extreme events, these analyses are not robust. Current methods, such as the regional frequency analysis, which combine data from different locations are incapable of incorporating the spatial structure of the data as well as other explanatory variables, and do not explicitly, assess the uncertainties. In this thesis the spatial hierarchical Bayesian model is proposed for hydro-climate extreme analyses using data recorded at each site or grid. This method combines limited number of data from different locations, estimates the uncertainties in different stages of the hierarchy, incorporates additional explanatory variables (covariates), and can be used to estimate extreme events at un-gaged sites. The first project develops a spatial hierarchical Bayesian method to model the extreme runoffs over two spatial domains in the Columbia River Basin, U.S. The model is also employed to estimate floods with different return levels within time slices of fifteen years in order to detect possible trends in runoff extremes. Continuing on the extreme analysis, the impact of climate change on runoff extremes is investigated over the whole Pacific Northwest (PNW). This study aims to address the question of how the runoff extremes will change in the future compared to the historical time period, investigate the different behaviors of the regional climate models (RCMs) regarding the runoff extremes, and assess the seasonal variations of runoff extremes. Given the increasing number of climate model simulations the goal of the third project is to provide a multi-model ensemble average of hydro-climate extremes and characterize the inherent uncertainties. Outputs from several regional climate models provided by NARCCAP are considered for the analysis in all seasons. Three combination scenarios are defined and compared for multi-modeling of extreme runoffs. The biases of each scenario are calculated and the scenario with the least bias is selected for projecting seasonal runoff extremes. The aim of the fourth project is to quantify and compare the uncertainties regarding global climate models to the ones from the hydrologic model structures in climate change impact studies. Various methods have been proposed to downscale the coarse resolution General Circulation Model (GCM) climatological variables to the fine scale regional variables; however fewer studies have been focused on the selection of GCM predictors. Additionally, the results obtained from one downscaling technique may not be robust and the uncertainties related to the downscaling scheme are not realized. To address these issues, in the fifth study we employed Independent Component Analysis (ICA) for predictor selection which determines spatially independent GCM variables (as discussed in Appendix A). Cross validation of the independent components is employed to find the predictor combination that describes the regional precipitation over the upper Willamette basin with minimum error. These climate variables along with the observed precipitation are used to calibrate three downscaling models: Multi Linear Regression (MLR), Support Vector Machine (SVM) and Adaptive-Network-Based Fuzzy Inference System (ANFIS). Title: Climate Change Impact on the Spatio-Temporal Variability of Hydro-Climate Extremes Author: Najafi, Mohammad Reza Year: 2013 The rising temperature of the earth due to climate change has shown to alter the variations of hydro-climate variables, including their intensities, frequencies and durations. Extreme events such as floods are, in particular, susceptible to any disturbances in climate cycles. As such it is important to provide policymakers with sufficient knowledge about the probable impacts of climate change on hydrologic extremes and most importantly on floods, which have the highest impacts on the societies. For this reason analysis of hydro-climate extremes is commonly performed using data at each site (or grid cell), however due to the limited number of extreme events, these analyses are not robust. Current methods, such as the regional frequency analysis, which combine data from different locations are incapable of incorporating the spatial structure of the data as well as other explanatory variables, and do not explicitly, assess the uncertainties. In this thesis the spatial hierarchical Bayesian model is proposed for hydro-climate extreme analyses using data recorded at each site or grid. This method combines limited number of data from different locations, estimates the uncertainties in different stages of the hierarchy, incorporates additional explanatory variables (covariates), and can be used to estimate extreme events at un-gaged sites. The first project develops a spatial hierarchical Bayesian method to model the extreme runoffs over two spatial domains in the Columbia River Basin, U.S. The model is also employed to estimate floods with different return levels within time slices of fifteen years in order to detect possible trends in runoff extremes. Continuing on the extreme analysis, the impact of climate change on runoff extremes is investigated over the whole Pacific Northwest (PNW). This study aims to address the question of how the runoff extremes will change in the future compared to the historical time period, investigate the different behaviors of the regional climate models (RCMs) regarding the runoff extremes, and assess the seasonal variations of runoff extremes. Given the increasing number of climate model simulations the goal of the third project is to provide a multi-model ensemble average of hydro-climate extremes and characterize the inherent uncertainties. Outputs from several regional climate models provided by NARCCAP are considered for the analysis in all seasons. Three combination scenarios are defined and compared for multi-modeling of extreme runoffs. The biases of each scenario are calculated and the scenario with the least bias is selected for projecting seasonal runoff extremes. The aim of the fourth project is to quantify and compare the uncertainties regarding global climate models to the ones from the hydrologic model structures in climate change impact studies. Various methods have been proposed to downscale the coarse resolution General Circulation Model (GCM) climatological variables to the fine scale regional variables; however fewer studies have been focused on the selection of GCM predictors. Additionally, the results obtained from one downscaling technique may not be robust and the uncertainties related to the downscaling scheme are not realized. To address these issues, in the fifth study we employed Independent Component Analysis (ICA) for predictor selection which determines spatially independent GCM variables (as discussed in Appendix A). Cross validation of the independent components is employed to find the predictor combination that describes the regional precipitation over the upper Willamette basin with minimum error. These climate variables along with the observed precipitation are used to calibrate three downscaling models: Multi Linear Regression (MLR), Support Vector Machine (SVM) and Adaptive-Network-Based Fuzzy Inference System (ANFIS). Close

• 7. [Article] Climate Change and Freshwater Resources in Oregon

  Climate change will affect various sectors of water resources in Oregon in the 21st century. The observed trends in streamflow show significant declines in September flow and, although not significant, ...

  Citation × Citation Citation Abstract Copy Title: Climate Change and Freshwater Resources in Oregon Author: Chang, Heejun, Jones, Julie Year: 2010 Climate change will affect various sectors of water resources in Oregon in the 21st century. The observed trends in streamflow show significant declines in September flow and, although not significant, increases in March flow in many transient rain-snow basins. These streamflow trends are associated with rising temperature and coincident declines in snowpack in spring in the latter half of the 20th century. While there are no distinct trends in high precipitation events, such events are associated with climate variability such as ENSO and PDO. Effects of ENSO and PDO are more pronounced at the beginning and end of the wet season in the Willamette River basin. The amount and seasonality of water supply is projected to shift as the distribution of precipitation changes and temperatures rise. Higher summer air temperatures accompanied by reduced precipitation are projected to increase evapotranspiration and decrease stream flow in summer. Although there are no distinct spatial patterns of changes in precipitation and temperature across the State in the 21st century (uniform increase in temperature across the region), significant regional variations do exist. The magnitude of change depends on the importance of snow in the current water budget, so projected changes are greater for mountainous regions than for low-elevation areas. Transient rain-snow basins, such as those in the Western Cascade basins, are projected to be more sensitive to these changes in precipitation and temperature. The high Cascade basins that are primarily fed by deep groundwater systems could sustain low flow during summer months. Basins in the east of the Cascades are projected to have low summer flow in a distant future as groundwater recharge declines over time. April 1 snow water equivalent (SWE) will decline and the center timing of runoff will become earlier in transient rain-snow basins as snowpack is projected to decline consistently in the 21st century. These model projections should be viewed with caution for several reasons when considering climate change impacts on water supply in Oregon. First, this chapter shows that few consistent trends in runoff are apparent in streamflow records from Oregon; instead, the direction and magnitude of change in streamflow varies by season, by basin size, and among ecoregions in Oregon. Second, observed streamflow trends (e.g., declining flows in summer, or in September) may be explained by factors that may not be directly related to global climate change. For example, recent low-flow years are attributable to low precipitation years (especially 2001 and 2005) and perhaps to interannual variations in snowpack associated with cyclical variation in ocean temperatures, while long-term decreases in summer flows are attributable to the combination of summer precipitation decline and increasing water withdrawals for consumptive use. Third, model projections do not account for possible resilience and adaptations in natural ecosystems that may alter water use and lead to smaller than expected changes in streamflow. More work is needed on vegetation responses to climate variability, the interactions between soil water and vegetation, and the relationship between streamflow and precipitation (runoff ratios) in large basins. Title: Climate Change and Freshwater Resources in Oregon Author: Chang, Heejun, Jones, Julie Year: 2010 Climate change will affect various sectors of water resources in Oregon in the 21st century. The observed trends in streamflow show significant declines in September flow and, although not significant, increases in March flow in many transient rain-snow basins. These streamflow trends are associated with rising temperature and coincident declines in snowpack in spring in the latter half of the 20th century. While there are no distinct trends in high precipitation events, such events are associated with climate variability such as ENSO and PDO. Effects of ENSO and PDO are more pronounced at the beginning and end of the wet season in the Willamette River basin. The amount and seasonality of water supply is projected to shift as the distribution of precipitation changes and temperatures rise. Higher summer air temperatures accompanied by reduced precipitation are projected to increase evapotranspiration and decrease stream flow in summer. Although there are no distinct spatial patterns of changes in precipitation and temperature across the State in the 21st century (uniform increase in temperature across the region), significant regional variations do exist. The magnitude of change depends on the importance of snow in the current water budget, so projected changes are greater for mountainous regions than for low-elevation areas. Transient rain-snow basins, such as those in the Western Cascade basins, are projected to be more sensitive to these changes in precipitation and temperature. The high Cascade basins that are primarily fed by deep groundwater systems could sustain low flow during summer months. Basins in the east of the Cascades are projected to have low summer flow in a distant future as groundwater recharge declines over time. April 1 snow water equivalent (SWE) will decline and the center timing of runoff will become earlier in transient rain-snow basins as snowpack is projected to decline consistently in the 21st century. These model projections should be viewed with caution for several reasons when considering climate change impacts on water supply in Oregon. First, this chapter shows that few consistent trends in runoff are apparent in streamflow records from Oregon; instead, the direction and magnitude of change in streamflow varies by season, by basin size, and among ecoregions in Oregon. Second, observed streamflow trends (e.g., declining flows in summer, or in September) may be explained by factors that may not be directly related to global climate change. For example, recent low-flow years are attributable to low precipitation years (especially 2001 and 2005) and perhaps to interannual variations in snowpack associated with cyclical variation in ocean temperatures, while long-term decreases in summer flows are attributable to the combination of summer precipitation decline and increasing water withdrawals for consumptive use. Third, model projections do not account for possible resilience and adaptations in natural ecosystems that may alter water use and lead to smaller than expected changes in streamflow. More work is needed on vegetation responses to climate variability, the interactions between soil water and vegetation, and the relationship between streamflow and precipitation (runoff ratios) in large basins. Close

• 8. [Article] North America. Climate Change 2007: Impacts, Adaptation and Vulnerability

  The United States (U.S.) and Canada will experience climate changes through direct effects of local changes (e.g., temperature, precipitation and extreme weather events), as well as through indirect effects, ...

  Citation × Citation Citation Abstract Copy Title: North America. Climate Change 2007: Impacts, Adaptation and Vulnerability Author: Fields, Christopher B., Mortsch, Linda D., Brklacich, Michael, Forbes, Donald L., Kovacs, Paul, Patz, Jonathan A., Running, Steven W., Scott, Michael J., Andrey, Jean, Cayan, Dan, Demuth, Mike, Hamlet, Alan, Jones, Gregory, Mills, Evan, Mills, Scott, Minns, Charles K., Sailor, David J., Saunders, Mark, Scott, Daniel, Solecki, William Year: 2007 The United States (U.S.) and Canada will experience climate changes through direct effects of local changes (e.g., temperature, precipitation and extreme weather events), as well as through indirect effects, transmitted among regions by interconnected economies and migrations of humans and other species. Variations in wealth and geography, however, lead to an uneven distribution of likely impacts, vulnerabilities and capacities to adapt. This chapter reviews and synthesises the state of knowledge on direct and indirect impacts, vulnerability and adaptations for North America (comprising Canada and the U.S). Hawaii and other U.S. protectorates are discussed in Chapter 16 on Small Islands, and Mexico and Central America are treated in Chapter 13 on Latin America. Chapter 15, Polar Regions, covers high-latitude issues and peoples. Title: North America. Climate Change 2007: Impacts, Adaptation and Vulnerability Author: Fields, Christopher B., Mortsch, Linda D., Brklacich, Michael, Forbes, Donald L., Kovacs, Paul, Patz, Jonathan A., Running, Steven W., Scott, Michael J., Andrey, Jean, Cayan, Dan, Demuth, Mike, Hamlet, Alan, Jones, Gregory, Mills, Evan, Mills, Scott, Minns, Charles K., Sailor, David J., Saunders, Mark, Scott, Daniel, Solecki, William Year: 2007 The United States (U.S.) and Canada will experience climate changes through direct effects of local changes (e.g., temperature, precipitation and extreme weather events), as well as through indirect effects, transmitted among regions by interconnected economies and migrations of humans and other species. Variations in wealth and geography, however, lead to an uneven distribution of likely impacts, vulnerabilities and capacities to adapt. This chapter reviews and synthesises the state of knowledge on direct and indirect impacts, vulnerability and adaptations for North America (comprising Canada and the U.S). Hawaii and other U.S. protectorates are discussed in Chapter 16 on Small Islands, and Mexico and Central America are treated in Chapter 13 on Latin America. Chapter 15, Polar Regions, covers high-latitude issues and peoples. Close

• 9. [Article] Application of Tree-Structured Regression for Regional Precipitation Prediction Using General Circulation Model Output

  This study presents a tree-structured regression (TSR) method to relate daily precipitation with a variety of free-atmosphere variables. Historical data were used to identify distinct weather patterns ...

  Citation × Citation Citation Abstract Copy Title: Application of Tree-Structured Regression for Regional Precipitation Prediction Using General Circulation Model Output Author: Li, Xiangshang, Sailor, David J. Year: 2000 This study presents a tree-structured regression (TSR) method to relate daily precipitation with a variety of free-atmosphere variables. Historical data were used to identify distinct weather patterns associated with differing types of precipitation events. Models were developed using 67% of the data for training and the remaining data for model validation. Seasonal models were built for each of 2 US sites: San Francisco, California, and San Antonio, Texas. The average correlation between observed and simulated daily precipitation data series is 0.75 for the training set and 0.68 for the validation set. Relative humidity was found to be the dominant variable in these TSR models. Output from an NCAR CSM (climate system model) transient simulation of climate change were then used to drive the TSR models in the prediction of precipitation characteristics under climate change. A preliminary screening of the GCM output variables for current climate, however, revealed significant problems for the San Antonio site. Specifically, the CSM missed the annual trends in humidity for the grid cell containing this site. CSM output for the San Francisco site was found to be much more reliable. Therefore, we present future precipitation estimates only for the San Francisco site. Title: Application of Tree-Structured Regression for Regional Precipitation Prediction Using General Circulation Model Output Author: Li, Xiangshang, Sailor, David J. Year: 2000 This study presents a tree-structured regression (TSR) method to relate daily precipitation with a variety of free-atmosphere variables. Historical data were used to identify distinct weather patterns associated with differing types of precipitation events. Models were developed using 67% of the data for training and the remaining data for model validation. Seasonal models were built for each of 2 US sites: San Francisco, California, and San Antonio, Texas. The average correlation between observed and simulated daily precipitation data series is 0.75 for the training set and 0.68 for the validation set. Relative humidity was found to be the dominant variable in these TSR models. Output from an NCAR CSM (climate system model) transient simulation of climate change were then used to drive the TSR models in the prediction of precipitation characteristics under climate change. A preliminary screening of the GCM output variables for current climate, however, revealed significant problems for the San Antonio site. Specifically, the CSM missed the annual trends in humidity for the grid cell containing this site. CSM output for the San Francisco site was found to be much more reliable. Therefore, we present future precipitation estimates only for the San Francisco site. Close

• 10. [Article] Climate Change Assessment in Columbia River Basin (CRB) Using Copula Based on Coupling of Temperature and Precipitation

  The multi downscaled-scenario products allow us to better assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions ...

  Citation × Citation Citation Abstract Copy Title: Climate Change Assessment in Columbia River Basin (CRB) Using Copula Based on Coupling of Temperature and Precipitation Author: Qin, Yueyue Year: 2015 The multi downscaled-scenario products allow us to better assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions (PDFs), of both the climatic variables, might help better understand the interdependence of the two, and thus in-turn help in accessing the future with confidence. In the present study, we have used multi-modelled statistically downscaled ensemble of precipitation and temperature variables. The dataset used is multi-model ensemble of 10 Global Climate Models (GCMs) downscaled product from CMIP5 daily dataset, using the Bias Correction and Spatial Downscaling (BCSD) technique, generated at Portland State University. The multi-model ensemble PDFs of both precipitation and temperature is evaluated for summer (dry) and winter (wet) periods for 10 sub-basins across Columbia River Basin (CRB). Eventually, Copula is applied to establish the joint distribution of two variables on multi-model ensemble data. Results have indicated that the probabilistic distribution helps remove the limitations on marginal distributions of variables in question and helps in better prediction. The joint distribution is then used to estimate the change in trends of said variables in future, along with estimation of the probabilities of the given change. The joint distribution trends are varied, but certainly positive, for summer and winter time scales based on sub-basins. Dry season, generally, is indicating towards higher positive changes in precipitation than temperature (as compared to historical) across sub-basins with wet season inferring otherwise. Probabilities of changes in future, as estimated by the joint precipitation and temperature, also indicates varied degree and forms during dry season whereas the wet season is rather constant across all the sub-basins. Title: Climate Change Assessment in Columbia River Basin (CRB) Using Copula Based on Coupling of Temperature and Precipitation Author: Qin, Yueyue Year: 2015 The multi downscaled-scenario products allow us to better assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions (PDFs), of both the climatic variables, might help better understand the interdependence of the two, and thus in-turn help in accessing the future with confidence. In the present study, we have used multi-modelled statistically downscaled ensemble of precipitation and temperature variables. The dataset used is multi-model ensemble of 10 Global Climate Models (GCMs) downscaled product from CMIP5 daily dataset, using the Bias Correction and Spatial Downscaling (BCSD) technique, generated at Portland State University. The multi-model ensemble PDFs of both precipitation and temperature is evaluated for summer (dry) and winter (wet) periods for 10 sub-basins across Columbia River Basin (CRB). Eventually, Copula is applied to establish the joint distribution of two variables on multi-model ensemble data. Results have indicated that the probabilistic distribution helps remove the limitations on marginal distributions of variables in question and helps in better prediction. The joint distribution is then used to estimate the change in trends of said variables in future, along with estimation of the probabilities of the given change. The joint distribution trends are varied, but certainly positive, for summer and winter time scales based on sub-basins. Dry season, generally, is indicating towards higher positive changes in precipitation than temperature (as compared to historical) across sub-basins with wet season inferring otherwise. Probabilities of changes in future, as estimated by the joint precipitation and temperature, also indicates varied degree and forms during dry season whereas the wet season is rather constant across all the sub-basins. Close