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• 1. [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

• 2. [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

• 3. [Article] Classifying Reanalysis Surface Temperature Probability Density Functions (PDFs) over North America with Cluster Analysis

  An important step in projecting future climate change impacts on extremes involves quantifying the underlying probability distribution functions (PDFs) of climate variables. However, doing so can prove ...

  Citation × Citation Citation Abstract Copy Title: Classifying Reanalysis Surface Temperature Probability Density Functions (PDFs) over North America with Cluster Analysis Author: Loikith, Paul C., Lintner, Benjamin R., Kim, Jinwon, Lee, Huikyo Year: 2013 An important step in projecting future climate change impacts on extremes involves quantifying the underlying probability distribution functions (PDFs) of climate variables. However, doing so can prove challenging when multiple models and large domains are considered. Here an approach to PDF quantification using k-means clustering is considered. A standard clustering algorithm (with k = 5 clusters) is applied to 33 years of daily January surface temperature from two state-of-the-art reanalysis products, the North American Regional Reanalysis and the Modern Era Retrospective Analysis for Research and Applications. The resulting cluster assignments yield spatially coherent patterns that can be broadly related to distinct climate regimes over North America, e.g., low variability over the tropical oceans or temperature advection across stronger or weaker gradients. This technique has the potential to be a useful and intuitive tool for evaluation of model-simulated PDF structure and could provide insight into projections of future changes in temperature. Title: Classifying Reanalysis Surface Temperature Probability Density Functions (PDFs) over North America with Cluster Analysis Author: Loikith, Paul C., Lintner, Benjamin R., Kim, Jinwon, Lee, Huikyo Year: 2013 An important step in projecting future climate change impacts on extremes involves quantifying the underlying probability distribution functions (PDFs) of climate variables. However, doing so can prove challenging when multiple models and large domains are considered. Here an approach to PDF quantification using k-means clustering is considered. A standard clustering algorithm (with k = 5 clusters) is applied to 33 years of daily January surface temperature from two state-of-the-art reanalysis products, the North American Regional Reanalysis and the Modern Era Retrospective Analysis for Research and Applications. The resulting cluster assignments yield spatially coherent patterns that can be broadly related to distinct climate regimes over North America, e.g., low variability over the tropical oceans or temperature advection across stronger or weaker gradients. This technique has the potential to be a useful and intuitive tool for evaluation of model-simulated PDF structure and could provide insight into projections of future changes in temperature. Close

• 4. [Article] Evaluating Hourly Rainfall Characteristics over the U.S. Great Plains in Dynamically Downscaled Climate Model Simulations using NASA-Unified WRF

  Accurate simulation of extreme precipitation events remains a challenge in climate models. This study utilizes hourly precipitation data from ground stations and satellite instruments to evaluate rainfall ...

  Citation × Citation Citation Abstract Copy Title: Evaluating Hourly Rainfall Characteristics over the U.S. Great Plains in Dynamically Downscaled Climate Model Simulations using NASA-Unified WRF Author: Lee, Huikyo, Waliser, Duane E., Ferraro, Robert, Iguchi, Takamichi, Peters-Lidard, Christa D., Tian, Baijun, Loikith, Paul C., Wright, Daniel B. Year: 2017 Accurate simulation of extreme precipitation events remains a challenge in climate models. This study utilizes hourly precipitation data from ground stations and satellite instruments to evaluate rainfall characteristics simulated by the NASA-Unified Weather Research and Forecasting (NU-WRF) regional climate model at horizontal resolutions of 4, 12, and 24 km over the Great Plains of the United States. We also examined the sensitivity of the simulated precipitation to different spectral nudging approaches and the cumulus parameterizations. The rainfall characteristics in the observations and simulations were defined as an hourly diurnal cycle of precipitation and a joint probability distribution function (JPDF) between duration and peak intensity of precipitation events over the Great Plains in summer. We calculated a JPDF for each data set and the overlapping area between observed and simulated JPDFs to measure the similarity between the two JPDFs. Comparison of the diurnal precipitation cycles between observations and simulations does not reveal the added value of high-resolution simulations. However, the performance of NU-WRF simulations measured by the JPDF metric strongly depends on horizontal resolution. The simulation with the highest resolution of 4 km shows the best agreement with the observations in simulating duration and intensity of wet spells. Spectral nudging does not affect the JPDF significantly. The effect of cumulus parameterizations on the JPDFs is considerable but smaller than that of horizontal resolution. The simulations with lower resolutions of 12 and 24 km show reasonable agreement but only with the high-resolution observational data that are aggregated into coarse resolution and spatially averaged. Title: Evaluating Hourly Rainfall Characteristics over the U.S. Great Plains in Dynamically Downscaled Climate Model Simulations using NASA-Unified WRF Author: Lee, Huikyo, Waliser, Duane E., Ferraro, Robert, Iguchi, Takamichi, Peters-Lidard, Christa D., Tian, Baijun, Loikith, Paul C., Wright, Daniel B. Year: 2017 Accurate simulation of extreme precipitation events remains a challenge in climate models. This study utilizes hourly precipitation data from ground stations and satellite instruments to evaluate rainfall characteristics simulated by the NASA-Unified Weather Research and Forecasting (NU-WRF) regional climate model at horizontal resolutions of 4, 12, and 24 km over the Great Plains of the United States. We also examined the sensitivity of the simulated precipitation to different spectral nudging approaches and the cumulus parameterizations. The rainfall characteristics in the observations and simulations were defined as an hourly diurnal cycle of precipitation and a joint probability distribution function (JPDF) between duration and peak intensity of precipitation events over the Great Plains in summer. We calculated a JPDF for each data set and the overlapping area between observed and simulated JPDFs to measure the similarity between the two JPDFs. Comparison of the diurnal precipitation cycles between observations and simulations does not reveal the added value of high-resolution simulations. However, the performance of NU-WRF simulations measured by the JPDF metric strongly depends on horizontal resolution. The simulation with the highest resolution of 4 km shows the best agreement with the observations in simulating duration and intensity of wet spells. Spectral nudging does not affect the JPDF significantly. The effect of cumulus parameterizations on the JPDFs is considerable but smaller than that of horizontal resolution. The simulations with lower resolutions of 12 and 24 km show reasonable agreement but only with the high-resolution observational data that are aggregated into coarse resolution and spatially averaged. Close

• 5. [Article] Extensive Aerosol Optical Properties and Aerosol Mass Related Measurements During TRAMP/TexAQS 2006 – Implications for PM Compliance and Planning

  Extensive aerosol optical properties, particle size distributions, and Aerodyne quadrupole aerosol mass spectrometer measurements collected during TRAMP/TexAQS 2006 were examined in light of collocated ...

  Citation × Citation Citation Abstract Copy Title: Extensive Aerosol Optical Properties and Aerosol Mass Related Measurements During TRAMP/TexAQS 2006 – Implications for PM Compliance and Planning Author: Wright, Monica Elizabeth, Atkinson, Dean B., Ziemba, Luke, Griffin, Robert, Hiranuma, Naruki, Brooks, Sarah D., Flynn, James, Perna, Ryan, Rappenglück, Bernhard, Luke, Winston, Kelley, Paul Year: 2010 Extensive aerosol optical properties, particle size distributions, and Aerodyne quadrupole aerosol mass spectrometer measurements collected during TRAMP/TexAQS 2006 were examined in light of collocated meteorological and chemical measurements. Much of the evident variability in the observed aerosol-related air quality is due to changing synoptic meteorological situations that direct emissions from various sources to the TRAMP site near the center of the Houston-Galveston-Brazoria (HGB) metropolitan area. In this study, five distinct long-term periods have been identified. During each of these periods, observed aerosol properties have implications that are of interest to environmental quality management agencies. During three of the periods, long range transport (LRT), both intra-continental and intercontinental, appears to have played an important role in producing the observed aerosol. During late August 2006, southerly winds brought super-micron Saharan dust and sea salt to the HGB area, adding mass to fine particulate matter (PM2.5) measurements, but apparently not affecting secondary particle growth or gas-phase air pollution. A second type of LRT was associated with northerly winds in early September 2006 and with increased ozone and sub-micron particulate matter in the HGB area. Later in the study, LRT of emissions from wildfires appeared to increase the abundance of absorbing aerosols (and carbon monoxide and other chemical tracers) in the HGB area. However, the greatest impacts on Houston PM2.5air quality are caused by periods with low-wind-speed sea breeze circulation or winds that directly transport pollutants from major industrial areas, i.e., the Houston Ship Channel, into the city center. Title: Extensive Aerosol Optical Properties and Aerosol Mass Related Measurements During TRAMP/TexAQS 2006 – Implications for PM Compliance and Planning Author: Wright, Monica Elizabeth, Atkinson, Dean B., Ziemba, Luke, Griffin, Robert, Hiranuma, Naruki, Brooks, Sarah D., Flynn, James, Perna, Ryan, Rappenglück, Bernhard, Luke, Winston, Kelley, Paul Year: 2010 Extensive aerosol optical properties, particle size distributions, and Aerodyne quadrupole aerosol mass spectrometer measurements collected during TRAMP/TexAQS 2006 were examined in light of collocated meteorological and chemical measurements. Much of the evident variability in the observed aerosol-related air quality is due to changing synoptic meteorological situations that direct emissions from various sources to the TRAMP site near the center of the Houston-Galveston-Brazoria (HGB) metropolitan area. In this study, five distinct long-term periods have been identified. During each of these periods, observed aerosol properties have implications that are of interest to environmental quality management agencies. During three of the periods, long range transport (LRT), both intra-continental and intercontinental, appears to have played an important role in producing the observed aerosol. During late August 2006, southerly winds brought super-micron Saharan dust and sea salt to the HGB area, adding mass to fine particulate matter (PM2.5) measurements, but apparently not affecting secondary particle growth or gas-phase air pollution. A second type of LRT was associated with northerly winds in early September 2006 and with increased ozone and sub-micron particulate matter in the HGB area. Later in the study, LRT of emissions from wildfires appeared to increase the abundance of absorbing aerosols (and carbon monoxide and other chemical tracers) in the HGB area. However, the greatest impacts on Houston PM2.5air quality are caused by periods with low-wind-speed sea breeze circulation or winds that directly transport pollutants from major industrial areas, i.e., the Houston Ship Channel, into the city center. Close

• 6. [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

• 7. [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

• 8. [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

• 9. [Article] Urban Scale Modeling of Atmospheric Carbon Dioxide and Validation of Emission Inventories

  There exists a pressing need for high resolution emissions inventories for cities. For greenhouse gases, cities and regions need a careful analysis of their carbon footprint to design effective policies ...

  Citation × Citation Citation Abstract Copy Title: Urban Scale Modeling of Atmospheric Carbon Dioxide and Validation of Emission Inventories Author: Powell, James E., Butenhoff, Christopher L., Rice, Andrew L. Year: 2015 There exists a pressing need for high resolution emissions inventories for cities. For greenhouse gases, cities and regions need a careful analysis of their carbon footprint to design effective policies to control and mitigate emissions. High resolution emissions inventories can be used in conjunction with meteorology models and atmospheric measurements to place top-down constraints on emissions. High resolution emissions inventories for criteria pollutants like NOx, CO, and O3 enable urban-scale air pollution modeling down to the neighborhood level. For example, the Vulcan project estimates CO2 using county-scale vehicle miles traveled (VMT) from the National Mobile Inventory Model (NMIM) County Database (NCD). The Hestia Project similarly allocates CO2 from Vulcan’s county-level inventory down to the building scale using eQUEST and building footprints. On-road transport is the most important sector for anthropogenic CO2, 38% in Portland, 32% nationally. Here we show a new model of CO2 emissions for the Portland, OR metropolitan region. The backbone is traffic counter recordings made by the Portland Bureau of Transportation at 9,352 sites over 21 years (1986-2006), augmented with PORTAL (The Portland Regional Transportation Archive Listing) freeway data. We constructed a regression model to fill in traffic network gaps using GIS data such as road class and population density. EPA MOVES was used to estimate transportation CO2 emissions. Our transportation emissions served as input into WRF meteorological modeling to simulate atmospheric CO2 at sites where frequent CO2 measurements are made. We show preliminary model results. Title: Urban Scale Modeling of Atmospheric Carbon Dioxide and Validation of Emission Inventories Author: Powell, James E., Butenhoff, Christopher L., Rice, Andrew L. Year: 2015 There exists a pressing need for high resolution emissions inventories for cities. For greenhouse gases, cities and regions need a careful analysis of their carbon footprint to design effective policies to control and mitigate emissions. High resolution emissions inventories can be used in conjunction with meteorology models and atmospheric measurements to place top-down constraints on emissions. High resolution emissions inventories for criteria pollutants like NOx, CO, and O3 enable urban-scale air pollution modeling down to the neighborhood level. For example, the Vulcan project estimates CO2 using county-scale vehicle miles traveled (VMT) from the National Mobile Inventory Model (NMIM) County Database (NCD). The Hestia Project similarly allocates CO2 from Vulcan’s county-level inventory down to the building scale using eQUEST and building footprints. On-road transport is the most important sector for anthropogenic CO2, 38% in Portland, 32% nationally. Here we show a new model of CO2 emissions for the Portland, OR metropolitan region. The backbone is traffic counter recordings made by the Portland Bureau of Transportation at 9,352 sites over 21 years (1986-2006), augmented with PORTAL (The Portland Regional Transportation Archive Listing) freeway data. We constructed a regression model to fill in traffic network gaps using GIS data such as road class and population density. EPA MOVES was used to estimate transportation CO2 emissions. Our transportation emissions served as input into WRF meteorological modeling to simulate atmospheric CO2 at sites where frequent CO2 measurements are made. We show preliminary model results. Close

• 10. [Article] Adsorption of Sulfur Dioxide on Douglas Fir Woodchips

  In recent years, people have raised their alertness to the hazard of air pollution. Sulfur dioxide is one of the most dangerous chemical compounds among those air pollutants. A study on removing sulfur ...

  Citation × Citation Citation Abstract Copy Title: Adsorption of Sulfur Dioxide on Douglas Fir Woodchips Author: Wang, Uen-Ping David Year: 1971 In recent years, people have raised their alertness to the hazard of air pollution. Sulfur dioxide is one of the most dangerous chemical compounds among those air pollutants. A study on removing sulfur dioxide from an air stream by adsorption using wood chips as the adsorbent is presented in this thesis. The reason for using wood as an adsorbent is that wood is a porous material and possesses a large surface of cell cavities which can hold a great amount of moisture. As sulfur dioxide gas is passed through the wood bed, it would be either condensed in the cell space of the wood by intermolecular attraction, adsorption or dissolved in the moisture held in the wood. This work was started with a review of literature. Then related references were collected and a proposal written. Douglas fir was chosen for the experiment because it is the most common kind of wood in the Pacific Northwest. After the process and proper equipment was set up, woodchips were screened and dried to prepare for further experiments. It was decided to use three different concentrations of sulfur dioxide. For each of the concentrations of sulfur dioxide, five levels of moisture (0%', 11%, 20%, 50% and saturated) were assigned to the selected woodchips. Fifteen combinations or experiments were done for the research. The results of the experiments show that dry wood (0% moisture content) had comparatively low characteristics in the adsorption of sulfur dioxide. For instance, at an influent so2 concentration of 1.12 ppm., about· 6 grams of dry woodchips adsorbed 29.37 µg. of sulfur dioxide in comparison to 2Q90.5 µg. of SO2 adsorbed in the same weight of woodchips but saturated with moisture. At an influent SO2 concentration of 1.83 ppm., the adsorption of sulfur dioxide increased from 7.73 µg. for the dry wood to 745.15µg. in the water saturated wood. For an influent SO2 concentration of 4.60ppm., dry wood adsorbed 15.26 µg. of SO2 while the moisture saturated wood adsorbed 1446.2 µg. The amount of dry woodchips used in above mentioned experiments were all about 6 grams. These data show that the moisture saturated wood adsorbed about 90 times the amount of sulfur dioxide that the dry wood adsorbed. It is clear that the wood adsorptivity increased with increasing moisture content. It was also found that wood adsorptivity and retention time were affected by the different flow rate of carrier gas. The figures show that most of the data fit a Freundlich equation. Other equations were developed to calculate the adsorptivity and retention time by obtaining the influent and effluent concentration of sulfur dioxide through the adsorbent bed. Title: Adsorption of Sulfur Dioxide on Douglas Fir Woodchips Author: Wang, Uen-Ping David Year: 1971 In recent years, people have raised their alertness to the hazard of air pollution. Sulfur dioxide is one of the most dangerous chemical compounds among those air pollutants. A study on removing sulfur dioxide from an air stream by adsorption using wood chips as the adsorbent is presented in this thesis. The reason for using wood as an adsorbent is that wood is a porous material and possesses a large surface of cell cavities which can hold a great amount of moisture. As sulfur dioxide gas is passed through the wood bed, it would be either condensed in the cell space of the wood by intermolecular attraction, adsorption or dissolved in the moisture held in the wood. This work was started with a review of literature. Then related references were collected and a proposal written. Douglas fir was chosen for the experiment because it is the most common kind of wood in the Pacific Northwest. After the process and proper equipment was set up, woodchips were screened and dried to prepare for further experiments. It was decided to use three different concentrations of sulfur dioxide. For each of the concentrations of sulfur dioxide, five levels of moisture (0%', 11%, 20%, 50% and saturated) were assigned to the selected woodchips. Fifteen combinations or experiments were done for the research. The results of the experiments show that dry wood (0% moisture content) had comparatively low characteristics in the adsorption of sulfur dioxide. For instance, at an influent so2 concentration of 1.12 ppm., about· 6 grams of dry woodchips adsorbed 29.37 µg. of sulfur dioxide in comparison to 2Q90.5 µg. of SO2 adsorbed in the same weight of woodchips but saturated with moisture. At an influent SO2 concentration of 1.83 ppm., the adsorption of sulfur dioxide increased from 7.73 µg. for the dry wood to 745.15µg. in the water saturated wood. For an influent SO2 concentration of 4.60ppm., dry wood adsorbed 15.26 µg. of SO2 while the moisture saturated wood adsorbed 1446.2 µg. The amount of dry woodchips used in above mentioned experiments were all about 6 grams. These data show that the moisture saturated wood adsorbed about 90 times the amount of sulfur dioxide that the dry wood adsorbed. It is clear that the wood adsorptivity increased with increasing moisture content. It was also found that wood adsorptivity and retention time were affected by the different flow rate of carrier gas. The figures show that most of the data fit a Freundlich equation. Other equations were developed to calculate the adsorptivity and retention time by obtaining the influent and effluent concentration of sulfur dioxide through the adsorbent bed. Close