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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] Short-tailed temperature distributions over North America and Implications for Future Changes in Extremes

  Some regions of North America exhibit nonnormal temperature distributions. Shorter-than-Gaussian warm tails are a special subset of these cases, with potentially meaningful implications for future changes ...

  Citation × Citation Citation Abstract Copy Title: Short-tailed temperature distributions over North America and Implications for Future Changes in Extremes Author: Loikith, Paul C., Neelin, J. David Year: 2015 Some regions of North America exhibit nonnormal temperature distributions. Shorter-than-Gaussian warm tails are a special subset of these cases, with potentially meaningful implications for future changes in extreme warm temperatures under anthropogenic global warming. Locations exhibiting shorter-than-Gaussian warm tails would experience a greater increase in extreme warm temperature exceedances than a location with a Gaussian or long warm-side tail under a simple uniform warm shift in the distribution. Here we identify regions exhibiting such behavior over North America and demonstrate the effect of a simple warm shift on changes in extreme warm temperature exceedances. Some locations exceed the 95th percentile of the original distribution by greater than 40% of the time after this uniform shift. While the manner in which distributions change under global warming may be more complex than a simple shift, these results provide an observational baseline for climate model evaluation. Title: Short-tailed temperature distributions over North America and Implications for Future Changes in Extremes Author: Loikith, Paul C., Neelin, J. David Year: 2015 Some regions of North America exhibit nonnormal temperature distributions. Shorter-than-Gaussian warm tails are a special subset of these cases, with potentially meaningful implications for future changes in extreme warm temperatures under anthropogenic global warming. Locations exhibiting shorter-than-Gaussian warm tails would experience a greater increase in extreme warm temperature exceedances than a location with a Gaussian or long warm-side tail under a simple uniform warm shift in the distribution. Here we identify regions exhibiting such behavior over North America and demonstrate the effect of a simple warm shift on changes in extreme warm temperature exceedances. Some locations exceed the 95th percentile of the original distribution by greater than 40% of the time after this uniform shift. While the manner in which distributions change under global warming may be more complex than a simple shift, these results provide an observational baseline for climate model evaluation. Close

• 3. [Article] Surface Temperature Probability Distributions in the NARCCAP Hindcast Experiment: Evaluation Methodology, Metrics, and Results

  Methodology is developed and applied to evaluate the characteristics of daily surface temperature distributions in a six-member regional climate model (RCM) hindcast experiment conducted as part of the ...

  Citation × Citation Citation Abstract Copy Title: Surface Temperature Probability Distributions in the NARCCAP Hindcast Experiment: Evaluation Methodology, Metrics, and Results Author: Loikith, Paul C., Waliser, Duane E., Lee, Huikyo, Kim, Jinwon, Neelin, J. David, Lintner, Benjamin R., McGinnis, Seth, Mattmann, Chris A., Mears, Linda O. Year: 2015 Methodology is developed and applied to evaluate the characteristics of daily surface temperature distributions in a six-member regional climate model (RCM) hindcast experiment conducted as part of the North American Regional Climate Change Assessment Program (NARCCAP). A surface temperature dataset combining gridded station observations and reanalysis is employed as the primary reference. Temperature biases are documented across the distribution, focusing on the median and tails. Temperature variance is generally higher in the RCMs than reference, while skewness is reasonably simulated in winter over the entire domain and over the western United States and Canada in summer. Substantial differences in skewness exist over the southern and eastern portions of the domain in summer. Four examples with observed long-tailed probability distribution functions (PDFs) are selected for model comparison. Long cold tails in the winter are simulated with high fidelity for Seattle, Washington, and Chicago, Illinois. In summer, theRCMs are unable to capture the distribution width and long warm tails for the coastal location of Los Angeles, California, while long cold tails are poorly realized for Houston, Texas. The evaluation results are repeated using two additional reanalysis products adjusted by station observations and two standard reanalysis products to assess the impact of observational uncertainty. Results are robust when compared with those obtained using the adjusted reanalysis products as reference, while larger uncertainties are introduced when standard reanalysis is employed as reference. Model biases identified in this work will allow for further investigation into associated mechanisms and implications for future simulations of temperature extremes. Title: Surface Temperature Probability Distributions in the NARCCAP Hindcast Experiment: Evaluation Methodology, Metrics, and Results Author: Loikith, Paul C., Waliser, Duane E., Lee, Huikyo, Kim, Jinwon, Neelin, J. David, Lintner, Benjamin R., McGinnis, Seth, Mattmann, Chris A., Mears, Linda O. Year: 2015 Methodology is developed and applied to evaluate the characteristics of daily surface temperature distributions in a six-member regional climate model (RCM) hindcast experiment conducted as part of the North American Regional Climate Change Assessment Program (NARCCAP). A surface temperature dataset combining gridded station observations and reanalysis is employed as the primary reference. Temperature biases are documented across the distribution, focusing on the median and tails. Temperature variance is generally higher in the RCMs than reference, while skewness is reasonably simulated in winter over the entire domain and over the western United States and Canada in summer. Substantial differences in skewness exist over the southern and eastern portions of the domain in summer. Four examples with observed long-tailed probability distribution functions (PDFs) are selected for model comparison. Long cold tails in the winter are simulated with high fidelity for Seattle, Washington, and Chicago, Illinois. In summer, theRCMs are unable to capture the distribution width and long warm tails for the coastal location of Los Angeles, California, while long cold tails are poorly realized for Houston, Texas. The evaluation results are repeated using two additional reanalysis products adjusted by station observations and two standard reanalysis products to assess the impact of observational uncertainty. Results are robust when compared with those obtained using the adjusted reanalysis products as reference, while larger uncertainties are introduced when standard reanalysis is employed as reference. Model biases identified in this work will allow for further investigation into associated mechanisms and implications for future simulations of temperature extremes. Close

• 4. [Article] Evaluation of Large‑Scale Meteorological Patterns Associated with Temperature Extremes in the NARCCAP Regional Climate Model Simulations

  Large-scale meteorological patterns (LSMPs) associated with temperature extremes are evaluated in a suite of regional climate model (RCM) simulations contributing to the North American Regional Climate ...

  Citation × Citation Citation Abstract Copy Title: Evaluation of Large‑Scale Meteorological Patterns Associated with Temperature Extremes in the NARCCAP Regional Climate Model Simulations Author: Loikith, Paul C., Waliser, Duane E., Lee, Huikyo, Neelin, J. David, Lintner, Benjamin, McGinnis, Seth, Mears, Linda, Kim, Jinwon Year: 2015 Large-scale meteorological patterns (LSMPs) associated with temperature extremes are evaluated in a suite of regional climate model (RCM) simulations contributing to the North American Regional Climate Change Assessment Program. LSMPs are characterized through composites of surface air temperature, sea level pressure, and 500 hPa geopotential height anomalies concurrent with extreme temperature days. Six of the seventeen RCM simulations are driven by boundary conditions from reanalysis while the other eleven are driven by one of four global climate models (GCMs). Four illustrative case studies are analyzed in detail. Model fidelity in LSMP spatial representation is high for cold winter extremes near Chicago. Winter warm extremes are captured by most RCMs in northern California, with some notable exceptions. Model fidelity is lower for cool summer days near Houston and extreme summer heat events in the Ohio Valley. Physical interpretation of these patterns and identification of wellsimulated cases, such as for Chicago, boosts confidence in the ability of these models to simulate days in the tails of the temperature distribution. Results appear consistent with the expectation that the ability of an RCM to reproduce a realistically shaped frequency distribution for temperature, especially at the tails, is related to its fidelity in simulating LMSPs. Each ensemble member is ranked for its ability to reproduce LSMPs associated with observed warm and cold extremes, identifying systematically high performing RCMs and the GCMs that provide superior boundary forcing. The methodology developed here provides a framework for identifying regions where further process-based evaluation would improve the understanding of simulation error and help guide future model improvement and downscaling efforts. Title: Evaluation of Large‑Scale Meteorological Patterns Associated with Temperature Extremes in the NARCCAP Regional Climate Model Simulations Author: Loikith, Paul C., Waliser, Duane E., Lee, Huikyo, Neelin, J. David, Lintner, Benjamin, McGinnis, Seth, Mears, Linda, Kim, Jinwon Year: 2015 Large-scale meteorological patterns (LSMPs) associated with temperature extremes are evaluated in a suite of regional climate model (RCM) simulations contributing to the North American Regional Climate Change Assessment Program. LSMPs are characterized through composites of surface air temperature, sea level pressure, and 500 hPa geopotential height anomalies concurrent with extreme temperature days. Six of the seventeen RCM simulations are driven by boundary conditions from reanalysis while the other eleven are driven by one of four global climate models (GCMs). Four illustrative case studies are analyzed in detail. Model fidelity in LSMP spatial representation is high for cold winter extremes near Chicago. Winter warm extremes are captured by most RCMs in northern California, with some notable exceptions. Model fidelity is lower for cool summer days near Houston and extreme summer heat events in the Ohio Valley. Physical interpretation of these patterns and identification of wellsimulated cases, such as for Chicago, boosts confidence in the ability of these models to simulate days in the tails of the temperature distribution. Results appear consistent with the expectation that the ability of an RCM to reproduce a realistically shaped frequency distribution for temperature, especially at the tails, is related to its fidelity in simulating LMSPs. Each ensemble member is ranked for its ability to reproduce LSMPs associated with observed warm and cold extremes, identifying systematically high performing RCMs and the GCMs that provide superior boundary forcing. The methodology developed here provides a framework for identifying regions where further process-based evaluation would improve the understanding of simulation error and help guide future model improvement and downscaling efforts. Close

• 5. [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

• 6. [Article] Comparison between Observed and Model-Simulated Atmospheric CirculationPatterns Associated with Extreme Temperature Days over North AmericaUsing CMIP5 Historical Simulations

  Circulation patterns associated with extreme temperature days over North America, as simulated by a suite of climate models, are compared with those obtained from observations. The authors analyze 17 coupled ...

  Citation × Citation Citation Abstract Copy Title: Comparison between Observed and Model-Simulated Atmospheric CirculationPatterns Associated with Extreme Temperature Days over North AmericaUsing CMIP5 Historical Simulations Author: Loikith, Paul C., Broccoli, Anthony J. Year: 2015 Circulation patterns associated with extreme temperature days over North America, as simulated by a suite of climate models, are compared with those obtained from observations. The authors analyze 17 coupled atmosphere–ocean general circulation models contributing to the fifth phase of the Coupled Model Intercomparison Project. Circulation patterns are defined as composites of anomalies in sea level pressure and 500-hPa geopotential height concurrent with days in the tails of temperature distribution. Several metrics used to systematically describe circulation patterns associated with extreme temperature days are applied to both the observed and model-simulated data. Additionally, self-organizing maps are employed as a means of comparing observed and model-simulated circulation patterns across the North American domain. In general, the multimodel ensemble resembles the observed patterns well, especially in areas removed from complex geographic features (e.g., mountains and coastlines). Individual model results vary; however, the majority of models capture the major features observed. The multimodel ensemble captures several key features, including regional variations in the strength and orientation of atmospheric circulation patterns associated with extreme temperatures, both near the surface and aloft, as well as variations with latitude and season. The results from this work suggest that these models can be used to comprehensively examine the role that changes in atmospheric circulation will play in projected changes in temperature extremes because of future anthropogenic climate warming. Title: Comparison between Observed and Model-Simulated Atmospheric CirculationPatterns Associated with Extreme Temperature Days over North AmericaUsing CMIP5 Historical Simulations Author: Loikith, Paul C., Broccoli, Anthony J. Year: 2015 Circulation patterns associated with extreme temperature days over North America, as simulated by a suite of climate models, are compared with those obtained from observations. The authors analyze 17 coupled atmosphere–ocean general circulation models contributing to the fifth phase of the Coupled Model Intercomparison Project. Circulation patterns are defined as composites of anomalies in sea level pressure and 500-hPa geopotential height concurrent with days in the tails of temperature distribution. Several metrics used to systematically describe circulation patterns associated with extreme temperature days are applied to both the observed and model-simulated data. Additionally, self-organizing maps are employed as a means of comparing observed and model-simulated circulation patterns across the North American domain. In general, the multimodel ensemble resembles the observed patterns well, especially in areas removed from complex geographic features (e.g., mountains and coastlines). Individual model results vary; however, the majority of models capture the major features observed. The multimodel ensemble captures several key features, including regional variations in the strength and orientation of atmospheric circulation patterns associated with extreme temperatures, both near the surface and aloft, as well as variations with latitude and season. The results from this work suggest that these models can be used to comprehensively examine the role that changes in atmospheric circulation will play in projected changes in temperature extremes because of future anthropogenic climate warming. Close

• 7. [Article] Understanding the Joint Behavior of Temperature and Precipitation for Climate Change Impact Studies

  The multiple downscaled-scenario products allow us to assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Probabilistic assessments of both climatic ...

  Citation × Citation Citation Abstract Copy Title: Understanding the Joint Behavior of Temperature and Precipitation for Climate Change Impact Studies Author: Rana, Arun, Moradkhani, Hamid, Qin, Yueyue Year: 2016 The multiple downscaled-scenario products allow us to assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Probabilistic assessments of both climatic variables help better understand the interdependence of the two, and thus in-turn help in assessing the future with confidence. In the present study, we use ensemble of statistically downscaled precipitation and temperature from various models. 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 of both precipitation and temperature is evaluated for dry and wet periods for 10 sub-basins across Columbia River Basin (CRB). Thereafter, Copula is applied to establish the joint distribution of two variables on multi-model ensemble data. 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 varies, but certainly positive, for dry and wet periods in sub-basins of CRB. Dry season, generally, is indicating a higher positive change in precipitation than temperature (as compared to historical) across sub-basins with wet season inferring otherwise. Probabilities of changes in future, as estimated from the joint distribution indicate varied degrees and forms during dry season whereas the wet season is rather constant across all the sub-basins. Title: Understanding the Joint Behavior of Temperature and Precipitation for Climate Change Impact Studies Author: Rana, Arun, Moradkhani, Hamid, Qin, Yueyue Year: 2016 The multiple downscaled-scenario products allow us to assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Probabilistic assessments of both climatic variables help better understand the interdependence of the two, and thus in-turn help in assessing the future with confidence. In the present study, we use ensemble of statistically downscaled precipitation and temperature from various models. 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 of both precipitation and temperature is evaluated for dry and wet periods for 10 sub-basins across Columbia River Basin (CRB). Thereafter, Copula is applied to establish the joint distribution of two variables on multi-model ensemble data. 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 varies, but certainly positive, for dry and wet periods in sub-basins of CRB. Dry season, generally, is indicating a higher positive change in precipitation than temperature (as compared to historical) across sub-basins with wet season inferring otherwise. Probabilities of changes in future, as estimated from the joint distribution indicate varied degrees and forms during dry season whereas the wet season is rather constant across all the sub-basins. Close

• 8. [Article] Utilizing Humidity and Temperature Data to Advance Monitoring and Prediction of Meteorological Drought

  The fraction of land area over the Continental United States experiencing extreme hot and dry conditions has been increasing over the past several decades, consistent with expectation from anthropogenic ...

  Citation × Citation Citation Abstract Copy Title: Utilizing Humidity and Temperature Data to Advance Monitoring and Prediction of Meteorological Drought Author: Behrangi, Ali, Loikith, Paul C., Fetzer, Eric J., Nguyen, Hai M., Granger, Stephanie L. Year: 2015 The fraction of land area over the Continental United States experiencing extreme hot and dry conditions has been increasing over the past several decades, consistent with expectation from anthropogenic climate change. A clear concurrent change in precipitation, however, has not been confirmed. Vapor pressure deficit (VPD), combining temperature and humidity, is utilized here as an indicator of the background atmospheric conditions associated with meteorological drought. Furthermore, atmospheric conditions associated with warm season drought events are assessed by partitioning associated VPD anomalies into the temperature and humidity components. This approach suggests that the concurrence of anomalously high temperature and low humidity was an important driver of the rapid development and evolution of the exceptionally severe 2011 Texas and the 2012 Great Plains droughts. By classification of a decade of extreme drought events and tracking them back in time, it was found that near surface atmospheric temperature and humidity add essential information to the commonly used precipitation-based drought indicators and can advance efforts to determine the timing of drought onset and its severity. Title: Utilizing Humidity and Temperature Data to Advance Monitoring and Prediction of Meteorological Drought Author: Behrangi, Ali, Loikith, Paul C., Fetzer, Eric J., Nguyen, Hai M., Granger, Stephanie L. Year: 2015 The fraction of land area over the Continental United States experiencing extreme hot and dry conditions has been increasing over the past several decades, consistent with expectation from anthropogenic climate change. A clear concurrent change in precipitation, however, has not been confirmed. Vapor pressure deficit (VPD), combining temperature and humidity, is utilized here as an indicator of the background atmospheric conditions associated with meteorological drought. Furthermore, atmospheric conditions associated with warm season drought events are assessed by partitioning associated VPD anomalies into the temperature and humidity components. This approach suggests that the concurrence of anomalously high temperature and low humidity was an important driver of the rapid development and evolution of the exceptionally severe 2011 Texas and the 2012 Great Plains droughts. By classification of a decade of extreme drought events and tracking them back in time, it was found that near surface atmospheric temperature and humidity add essential information to the commonly used precipitation-based drought indicators and can advance efforts to determine the timing of drought onset and its severity. Close

• 9. [Article] Measuring the Effects of Parking Lots and Tree Shading on Microscale Urban Heat Islands

  55 pages. A thesis presented to the Department of Planning, Public Policy, and Management and the Clark Honors College of the University of Oregon in partial fulfillment of the requirements for degree ...

  Citation × Citation Citation Abstract Copy Title: Measuring the Effects of Parking Lots and Tree Shading on Microscale Urban Heat Islands Author: Goodrich, Elliot Year: 2016 55 pages. A thesis presented to the Department of Planning, Public Policy, and Management and the Clark Honors College of the University of Oregon in partial fulfillment of the requirements for degree of Bachelor of Arts, Winter 2016. Title: Measuring the Effects of Parking Lots and Tree Shading on Microscale Urban Heat Islands Author: Goodrich, Elliot Year: 2016 55 pages. A thesis presented to the Department of Planning, Public Policy, and Management and the Clark Honors College of the University of Oregon in partial fulfillment of the requirements for degree of Bachelor of Arts, Winter 2016. Close

• 10. [Article] Assessing Mechanisms of Climate Change Impact on the Upland Forest Water Balance of the Willamette River Basin, Oregon

  Projected changes in air temperature, precipitation, and vapor pressure for the Willamette River Basin (Oregon, USA) over the next century will have significant impacts on the river basin water balance, ...

  Citation × Citation Citation Abstract Copy Title: Assessing Mechanisms of Climate Change Impact on the Upland Forest Water Balance of the Willamette River Basin, Oregon Author: Turner, David P., Conklin, David R., Vache, Kellie B., Schwartz, Cynthia, Nolin, Anne, Chang, Heejun, Watson, Eric, Bolte, John P. Year: 2016 Projected changes in air temperature, precipitation, and vapor pressure for the Willamette River Basin (Oregon, USA) over the next century will have significant impacts on the river basin water balance, notably on the amount of evapotranspiration (ET). Mechanisms of impact on ET will be both direct and indirect, but there is limited understanding of their absolute and relative magnitudes. Here, we developed a spatially explicit, daily time-step, modeling infrastructure to simulate the basin-wide water balance that accounts for meteorological influences, as well as effects mediated by changing vegetation cover type, leaf area, and ecophysiology. Three CMIP5 climate scenarios (Lowclim, Reference, and HighClim) were run for the 2010–2100 period. Besides warmer temperatures, the climate scenarios were characterized by wetter winters and increasing vapor pressure deficits. In the mid-range Reference scenario, our landscape simulation model (Envision) projected a continuation of forest cover on the uplands but a threefold increase in area burned per year. A decline (12–30%) in basin-wide mean leaf area index (LAI) in forests was projected in all scenarios. The lower LAIs drove a corresponding decline in ET. In a sensitivity test, the effect of increasing CO2 on stomatal conductance induced a further substantial decrease (11–18%) in basin-wide mean ET. The net effect of decreases in ET and increases in winter precipitation was an increase in annual streamflow. These results support the inclusion of changes in land cover, land use, LAI, and ecophysiology in efforts to anticipate impacts of climate change on basin-scale water balances. Title: Assessing Mechanisms of Climate Change Impact on the Upland Forest Water Balance of the Willamette River Basin, Oregon Author: Turner, David P., Conklin, David R., Vache, Kellie B., Schwartz, Cynthia, Nolin, Anne, Chang, Heejun, Watson, Eric, Bolte, John P. Year: 2016 Projected changes in air temperature, precipitation, and vapor pressure for the Willamette River Basin (Oregon, USA) over the next century will have significant impacts on the river basin water balance, notably on the amount of evapotranspiration (ET). Mechanisms of impact on ET will be both direct and indirect, but there is limited understanding of their absolute and relative magnitudes. Here, we developed a spatially explicit, daily time-step, modeling infrastructure to simulate the basin-wide water balance that accounts for meteorological influences, as well as effects mediated by changing vegetation cover type, leaf area, and ecophysiology. Three CMIP5 climate scenarios (Lowclim, Reference, and HighClim) were run for the 2010–2100 period. Besides warmer temperatures, the climate scenarios were characterized by wetter winters and increasing vapor pressure deficits. In the mid-range Reference scenario, our landscape simulation model (Envision) projected a continuation of forest cover on the uplands but a threefold increase in area burned per year. A decline (12–30%) in basin-wide mean leaf area index (LAI) in forests was projected in all scenarios. The lower LAIs drove a corresponding decline in ET. In a sensitivity test, the effect of increasing CO2 on stomatal conductance induced a further substantial decrease (11–18%) in basin-wide mean ET. The net effect of decreases in ET and increases in winter precipitation was an increase in annual streamflow. These results support the inclusion of changes in land cover, land use, LAI, and ecophysiology in efforts to anticipate impacts of climate change on basin-scale water balances. Close