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• 11. [Article] The Effect of Multi-Model Averaging of Climate Model Outputs on the Seasonality of Rainfall Over the Columbia River Basin

  The rainfall seasonality index is the measure of precipitation distribution throughout the seasonal cycle. The aim of this study is to compare the effect of different multi-model averaging methods on the ...

  Citation × Citation Citation Abstract Copy Title: The Effect of Multi-Model Averaging of Climate Model Outputs on the Seasonality of Rainfall Over the Columbia River Basin Author: Demirel, Mehmet, Rana, Arun, Moradkhani, Hamid Year: 2014 The rainfall seasonality index is the measure of precipitation distribution throughout the seasonal cycle. The aim of this study is to compare the effect of different multi-model averaging methods on the rainfall seasonality index at each 1/16 latitude-longitude cells covering the Columbia River Basin. In accordance with the same, ten different climate model outputs are selected from 45 available climate models from CMIP5 dataset. The reanalysis precipitation data is used to estimate the errors in rainfall seasonality for the climate model outputs. The inverse variance method and statistical multi criteria analysis (SMCA) method were used to estimate the weights for each climate model output. The precipitation amounts from the climate model outputs were then averaged using these model weights. The rainfall seasonality index was estimated from: (1) observed reanalysis data; (2) averaged precipitation amount from ten combinations of CMIP5 outputs for the current climate (1979–2005) using inverse variance method; (3) averaged precipitation amount from the ten combinations of CMIP5 outputs for the current climate using SMCA. The results showed the large differences in rainfall seasonality index for each climate model averaging. Moreover, the multi-modelling of climate models resulted in relative improvements in the performance of the rainfall seasonality over the Columbia River Basin. The estimated model weights for the current climate can be useful to combine the model outputs for the future climate. Title: The Effect of Multi-Model Averaging of Climate Model Outputs on the Seasonality of Rainfall Over the Columbia River Basin Author: Demirel, Mehmet, Rana, Arun, Moradkhani, Hamid Year: 2014 The rainfall seasonality index is the measure of precipitation distribution throughout the seasonal cycle. The aim of this study is to compare the effect of different multi-model averaging methods on the rainfall seasonality index at each 1/16 latitude-longitude cells covering the Columbia River Basin. In accordance with the same, ten different climate model outputs are selected from 45 available climate models from CMIP5 dataset. The reanalysis precipitation data is used to estimate the errors in rainfall seasonality for the climate model outputs. The inverse variance method and statistical multi criteria analysis (SMCA) method were used to estimate the weights for each climate model output. The precipitation amounts from the climate model outputs were then averaged using these model weights. The rainfall seasonality index was estimated from: (1) observed reanalysis data; (2) averaged precipitation amount from ten combinations of CMIP5 outputs for the current climate (1979–2005) using inverse variance method; (3) averaged precipitation amount from the ten combinations of CMIP5 outputs for the current climate using SMCA. The results showed the large differences in rainfall seasonality index for each climate model averaging. Moreover, the multi-modelling of climate models resulted in relative improvements in the performance of the rainfall seasonality over the Columbia River Basin. The estimated model weights for the current climate can be useful to combine the model outputs for the future climate. Close

• 12. [Article] The Role of Atmospheric Circulation Patterns in Agroclimate Variability in Finland, 1961-2011

  This study evaluates interannual variations and trends in growing season daily temperature sum and daily precipitation sum in Finland during 1961–2011, and their connections to well known atmospheric circulation ...

  Citation × Citation Citation Abstract Copy Title: The Role of Atmospheric Circulation Patterns in Agroclimate Variability in Finland, 1961-2011 Author: Irannezhad, Masoud, Chen, Deliang, Kløve, Bjørn Year: 2016 This study evaluates interannual variations and trends in growing season daily temperature sum and daily precipitation sum in Finland during 1961–2011, and their connections to well known atmospheric circulation patterns. Changes in summer (June–August) climate partially explain changes in growing season daily temperature sum and daily precipitation sum over Finland, which naturally decreased from south to north. On a national scale, growing season warmed and became wetter during 1961–2011, as growing season daily temperature sum and daily precipitation sum significantly (p < 0.05) increased by 5.01 ± 3.17°C year–1 and 1.39 ± 0.91 mm year–1, respectively. The East Atlantic pattern was the most influential atmospheric circulation pattern for variations in growing season daily temperature sum (rho = 0.40) across Finland and the East Atlantic/West Russia pattern was most influential for growing season daily precipitation sum variability (rho = –0.54). There were significant (p < 0.05) increasing trends in growing season daily temperature sum and daily precipitation sum throughout Finland during 1961–2011. Increased growing season daily temperature sum was mainly observed in northern, central, western, eastern and coastal areas of south-western Finland. This warming was positively associated with the East Atlantic pattern in the north, centre and south, but negatively associated with the East Atlantic/West Russia pattern in eastern Finland. Increased GSP mostly occurred in southern, eastern, western, central, northern and north-western Finland. These wetting trends were positively correlated with the East Atlantic pattern in the north and negatively correlated with the Polar pattern in the south and the East Atlantic/West Russia pattern in the east, west, centre and north-east of Finland. The overall agroclimatic year-to-year variability in Finland between 1961 and 2011 was mostly linked to variations in the East Atlantic and East Atlantic/West Russia patterns. Title: The Role of Atmospheric Circulation Patterns in Agroclimate Variability in Finland, 1961-2011 Author: Irannezhad, Masoud, Chen, Deliang, Kløve, Bjørn Year: 2016 This study evaluates interannual variations and trends in growing season daily temperature sum and daily precipitation sum in Finland during 1961–2011, and their connections to well known atmospheric circulation patterns. Changes in summer (June–August) climate partially explain changes in growing season daily temperature sum and daily precipitation sum over Finland, which naturally decreased from south to north. On a national scale, growing season warmed and became wetter during 1961–2011, as growing season daily temperature sum and daily precipitation sum significantly (p < 0.05) increased by 5.01 ± 3.17°C year–1 and 1.39 ± 0.91 mm year–1, respectively. The East Atlantic pattern was the most influential atmospheric circulation pattern for variations in growing season daily temperature sum (rho = 0.40) across Finland and the East Atlantic/West Russia pattern was most influential for growing season daily precipitation sum variability (rho = –0.54). There were significant (p < 0.05) increasing trends in growing season daily temperature sum and daily precipitation sum throughout Finland during 1961–2011. Increased growing season daily temperature sum was mainly observed in northern, central, western, eastern and coastal areas of south-western Finland. This warming was positively associated with the East Atlantic pattern in the north, centre and south, but negatively associated with the East Atlantic/West Russia pattern in eastern Finland. Increased GSP mostly occurred in southern, eastern, western, central, northern and north-western Finland. These wetting trends were positively correlated with the East Atlantic pattern in the north and negatively correlated with the Polar pattern in the south and the East Atlantic/West Russia pattern in the east, west, centre and north-east of Finland. The overall agroclimatic year-to-year variability in Finland between 1961 and 2011 was mostly linked to variations in the East Atlantic and East Atlantic/West Russia patterns. Close

• 13. [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

• 14. [Article] Characterizing Large-Scale Meteorological Patterns and Associated Temperature and Precipitation Extremes over the Northwestern United States Using Self-Organizing Maps

  The self-organizing maps (SOMs) approach is demonstrated as a way to identify a range of archetypal large-scale meteorological patterns (LSMPs) over the northwestern United States and connect these patterns ...

  Citation × Citation Citation Abstract Copy Title: Characterizing Large-Scale Meteorological Patterns and Associated Temperature and Precipitation Extremes over the Northwestern United States Using Self-Organizing Maps Author: Loikith, Paul C., Lintner, Benjamin R., Sweeney, Alex Year: 2017 The self-organizing maps (SOMs) approach is demonstrated as a way to identify a range of archetypal large-scale meteorological patterns (LSMPs) over the northwestern United States and connect these patterns with local-scale temperature and precipitation extremes. SOMs are used to construct a set of 12 characteristic LSMPs (nodes) based on daily reanalysis circulation fields spanning the range of observed synoptic-scale variability for the summer and winter seasons for the period 1979–2013. Composites of surface variables are constructed for subsets of days assigned to each node to explore relationships between temperature, precipitation, and the node patterns. The SOMs approach also captures interannual variability in daily weather regime frequency related to El Niño–Southern Oscillation. Temperature and precipitation extremes in high-resolution gridded observations and in situ station data show robust relationships with particular nodes in many cases, supporting the approach as a way to identify LSMPs associated with local extremes. Assigning days from the extreme warm summer of 2015 and wet winter of 2016 to nodes illustrates how SOMs may be used to assess future changes in extremes. These results point to the applicability of SOMs to climate model evaluation and assessment of future projections of local-scale extremes without requiring simulations to reliably resolve extremes at high spatial scales. Title: Characterizing Large-Scale Meteorological Patterns and Associated Temperature and Precipitation Extremes over the Northwestern United States Using Self-Organizing Maps Author: Loikith, Paul C., Lintner, Benjamin R., Sweeney, Alex Year: 2017 The self-organizing maps (SOMs) approach is demonstrated as a way to identify a range of archetypal large-scale meteorological patterns (LSMPs) over the northwestern United States and connect these patterns with local-scale temperature and precipitation extremes. SOMs are used to construct a set of 12 characteristic LSMPs (nodes) based on daily reanalysis circulation fields spanning the range of observed synoptic-scale variability for the summer and winter seasons for the period 1979–2013. Composites of surface variables are constructed for subsets of days assigned to each node to explore relationships between temperature, precipitation, and the node patterns. The SOMs approach also captures interannual variability in daily weather regime frequency related to El Niño–Southern Oscillation. Temperature and precipitation extremes in high-resolution gridded observations and in situ station data show robust relationships with particular nodes in many cases, supporting the approach as a way to identify LSMPs associated with local extremes. Assigning days from the extreme warm summer of 2015 and wet winter of 2016 to nodes illustrates how SOMs may be used to assess future changes in extremes. These results point to the applicability of SOMs to climate model evaluation and assessment of future projections of local-scale extremes without requiring simulations to reliably resolve extremes at high spatial scales. Close

• 15. [Article] Stable Isotope Variations (δ18O and δD) in Modern Waters Across the Andean Plateau

  Environmental parameters that influence the isotopic composition of meteoric water (δ18O and δD) are well characterized up the windward side of mountains, where orographic precipitation results in a predictable ...

  Citation × Citation Citation Abstract Copy Title: Stable Isotope Variations (δ18O and δD) in Modern Waters Across the Andean Plateau Author: Bershaw, John, Saylor, Joel E., Garzione, Carmala N., Leier, Andrew Year: 2016 Environmental parameters that influence the isotopic composition of meteoric water (δ18O and δD) are well characterized up the windward side of mountains, where orographic precipitation results in a predictable relationship between the isotopic composition of precipitation and elevation. The topographic and climatic evolution of the Andean Plateau and surrounding regions has been studied extensively by exploiting this relationship through the use of paleowater proxies. However, interpretation on the plateau itself is challenged by a poor understanding of processes that fractionate isotopes during vapor transport and rainout, and by the relative contribution of unique moisture sources. Here, we present an extensive dataset of modern surface water samples for the northern Andean Plateau and surrounding regions to elucidate patterns and causes of isotope fractionation in this continental environment. These data show a progressive increase in δ18O of stream water west of the Eastern Cordillera (∼1‰/70 km), almost identical to the rate observed across the Tibetan Plateau, attributed to a larger fraction of recycled water in precipitation and/or increased evaporative enrichment downwind. This may lead to underestimates of paleoelevation, particularly for sites deep into the rainshadow of the Eastern Cordilleran crest. That said, elevation is a primary control on the isotopic composition of surface waters across the entire Andean Plateau and its flanks when considering the most negative δ18O values, highlighting the need for sufficiently large datasets to distinguish minimally evaporated samples. There is a general increase in δ18O on the plateau from north to south, concomitant with an increase in aridity and decrease in convective moistening (amount effect). Lastly, stable isotope and seasonal precipitation patterns suggest easterlies provide the vast majority of moisture that falls as precipitation across the Andean Plateau and Western Cordillera, from Peru to northern Bolivia (−13° to −20° latitude), with Pacific-derived moisture contributing a minor amount at low elevations near the coast. Title: Stable Isotope Variations (δ18O and δD) in Modern Waters Across the Andean Plateau Author: Bershaw, John, Saylor, Joel E., Garzione, Carmala N., Leier, Andrew Year: 2016 Environmental parameters that influence the isotopic composition of meteoric water (δ18O and δD) are well characterized up the windward side of mountains, where orographic precipitation results in a predictable relationship between the isotopic composition of precipitation and elevation. The topographic and climatic evolution of the Andean Plateau and surrounding regions has been studied extensively by exploiting this relationship through the use of paleowater proxies. However, interpretation on the plateau itself is challenged by a poor understanding of processes that fractionate isotopes during vapor transport and rainout, and by the relative contribution of unique moisture sources. Here, we present an extensive dataset of modern surface water samples for the northern Andean Plateau and surrounding regions to elucidate patterns and causes of isotope fractionation in this continental environment. These data show a progressive increase in δ18O of stream water west of the Eastern Cordillera (∼1‰/70 km), almost identical to the rate observed across the Tibetan Plateau, attributed to a larger fraction of recycled water in precipitation and/or increased evaporative enrichment downwind. This may lead to underestimates of paleoelevation, particularly for sites deep into the rainshadow of the Eastern Cordilleran crest. That said, elevation is a primary control on the isotopic composition of surface waters across the entire Andean Plateau and its flanks when considering the most negative δ18O values, highlighting the need for sufficiently large datasets to distinguish minimally evaporated samples. There is a general increase in δ18O on the plateau from north to south, concomitant with an increase in aridity and decrease in convective moistening (amount effect). Lastly, stable isotope and seasonal precipitation patterns suggest easterlies provide the vast majority of moisture that falls as precipitation across the Andean Plateau and Western Cordillera, from Peru to northern Bolivia (−13° to −20° latitude), with Pacific-derived moisture contributing a minor amount at low elevations near the coast. Close

• 16. [Article] A Multivariate Modeling Approach for Generating Ensemble Climatology Forcing for Hydrologic Applications

  Reliability and accuracy of the forcing data plays a vital role in the Hydrological Streamflow Prediction. Reliability of the forcing data leads to accurate predictions and ultimately reduction of uncertainty. ...

  Citation × Citation Citation Abstract Copy Title: A Multivariate Modeling Approach for Generating Ensemble Climatology Forcing for Hydrologic Applications Author: Khajehei, Sepideh Year: 2015 Reliability and accuracy of the forcing data plays a vital role in the Hydrological Streamflow Prediction. Reliability of the forcing data leads to accurate predictions and ultimately reduction of uncertainty. Currently, Numerical Weather Prediction (NWP) models are developing ensemble forecasts for various temporal and spatial scales. However, it is proven that the raw products of the NWP models may be biased at the basin scale; unlike model grid scale, depending on the size of the catchment. Due to the large space-time variability of precipitation, bias-correcting the ensemble forecasts has proven to be a challenging task. In recent years, Ensemble Pre-Processing (EPP), a statistical approach, has proven to be helpful in reduction of bias and generation of reliable forecast. The procedure is based on the bivariate probability distribution between observation and single-value precipitation forecasts. In the current work, we have applied and evaluated a Bayesian approach, based on the Copula density functions, to develop an ensemble precipitation forecasts from the conditional distribution of the single-value precipitation. Copula functions are the multivariate joint distribution of univariate marginal distributions and are capable of modeling the joint distribution of two variables with any level of correlation and dependency. The advantage of using Copulas, amongst others, includes its capability of modeling the joint distribution independent of the type of marginal distribution. In the present study, we have evaluated the capability of copula-based functions in EPP and comparison is made against an existing and commonly used procedure for same i.e. meta-Gaussian distribution. Monthly precipitation forecast from Climate Forecast System (CFS) and gridded observation from Parameter-elevation Relationships on Independent Slopes Model (PRISM) have been utilized to create ensemble pre-processed precipitation over three sub-basins in the western USA at 0.5-degree spatial resolution. The comparison has been made using both deterministic and probabilistic frameworks of evaluation. Across all the sub-basins and evaluation techniques, copula-based technique shows more reliability and robustness as compared to the meta-Gaussian approach. Title: A Multivariate Modeling Approach for Generating Ensemble Climatology Forcing for Hydrologic Applications Author: Khajehei, Sepideh Year: 2015 Reliability and accuracy of the forcing data plays a vital role in the Hydrological Streamflow Prediction. Reliability of the forcing data leads to accurate predictions and ultimately reduction of uncertainty. Currently, Numerical Weather Prediction (NWP) models are developing ensemble forecasts for various temporal and spatial scales. However, it is proven that the raw products of the NWP models may be biased at the basin scale; unlike model grid scale, depending on the size of the catchment. Due to the large space-time variability of precipitation, bias-correcting the ensemble forecasts has proven to be a challenging task. In recent years, Ensemble Pre-Processing (EPP), a statistical approach, has proven to be helpful in reduction of bias and generation of reliable forecast. The procedure is based on the bivariate probability distribution between observation and single-value precipitation forecasts. In the current work, we have applied and evaluated a Bayesian approach, based on the Copula density functions, to develop an ensemble precipitation forecasts from the conditional distribution of the single-value precipitation. Copula functions are the multivariate joint distribution of univariate marginal distributions and are capable of modeling the joint distribution of two variables with any level of correlation and dependency. The advantage of using Copulas, amongst others, includes its capability of modeling the joint distribution independent of the type of marginal distribution. In the present study, we have evaluated the capability of copula-based functions in EPP and comparison is made against an existing and commonly used procedure for same i.e. meta-Gaussian distribution. Monthly precipitation forecast from Climate Forecast System (CFS) and gridded observation from Parameter-elevation Relationships on Independent Slopes Model (PRISM) have been utilized to create ensemble pre-processed precipitation over three sub-basins in the western USA at 0.5-degree spatial resolution. The comparison has been made using both deterministic and probabilistic frameworks of evaluation. Across all the sub-basins and evaluation techniques, copula-based technique shows more reliability and robustness as compared to the meta-Gaussian approach. Close

• 17. [Article] Centennial Drought Outlook Over the CONUS Using NASA-NEX Downscaled Climate Ensemble

  Drought is a natural hazard developing slowly and affecting large areas which may have severe consequences on society and economy. Due to the effects of climate change, drought is expected to exacerbate ...

  Citation × Citation Citation Abstract Copy Title: Centennial Drought Outlook Over the CONUS Using NASA-NEX Downscaled Climate Ensemble Author: Ahmadalipour, Ali, Moradkhani, Hamid, Svoboda, Mark Year: 2017 Drought is a natural hazard developing slowly and affecting large areas which may have severe consequences on society and economy. Due to the effects of climate change, drought is expected to exacerbate in various regions in future. In this study, the impact of climate change on drought characteristics is assessed, and statistical methods are employed to analyse the significance of projections. This is the first study utilizing 21 recently available downscaled global climate models generated by NASA (NEX-GDDP) to evaluate drought projections over various regions across the United States. Drought is investigated through a multi-model dual-index dual-scenario approach to probabilistically analyse drought attributes while characterizing the uncertainty in future drought projections. Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index values at the seasonal scale (3 months) are used to project and analyse meteorological drought conditions from 1950 to 2099 at 0.25° spatial resolution. Two future concentration pathways of RCP4.5 and RCP8.5 are considered for this analysis. Accounting for the combined effects of precipitation and temperature variations reveals a considerable aggravation in severity and extent of future drought in the western United States and a tendency toward more frequent and intense summer droughts across the Contiguous United States. Title: Centennial Drought Outlook Over the CONUS Using NASA-NEX Downscaled Climate Ensemble Author: Ahmadalipour, Ali, Moradkhani, Hamid, Svoboda, Mark Year: 2017 Drought is a natural hazard developing slowly and affecting large areas which may have severe consequences on society and economy. Due to the effects of climate change, drought is expected to exacerbate in various regions in future. In this study, the impact of climate change on drought characteristics is assessed, and statistical methods are employed to analyse the significance of projections. This is the first study utilizing 21 recently available downscaled global climate models generated by NASA (NEX-GDDP) to evaluate drought projections over various regions across the United States. Drought is investigated through a multi-model dual-index dual-scenario approach to probabilistically analyse drought attributes while characterizing the uncertainty in future drought projections. Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index values at the seasonal scale (3 months) are used to project and analyse meteorological drought conditions from 1950 to 2099 at 0.25° spatial resolution. Two future concentration pathways of RCP4.5 and RCP8.5 are considered for this analysis. Accounting for the combined effects of precipitation and temperature variations reveals a considerable aggravation in severity and extent of future drought in the western United States and a tendency toward more frequent and intense summer droughts across the Contiguous United States. Close

• 18. [Article] The Geography of Glaciers and Perennial Snowfields in the American West

  A comprehensive mid-20th century inventory of glaciers and perennial snowfields (G&PS) was compiled for the American West, west of the 100° meridian. The inventory was derived from U.S. Geological Survey ...

  Citation × Citation Citation Abstract Copy Title: The Geography of Glaciers and Perennial Snowfields in the American West Author: Fountain, Andrew G., Glenn, Bryce, Basagic, Hassan J. Year: 2017 A comprehensive mid-20th century inventory of glaciers and perennial snowfields (G&PS) was compiled for the American West, west of the 100° meridian. The inventory was derived from U.S. Geological Survey 1:24,000 topographic maps based on aerial photographs acquired during 35 years, 1955–1990, of which the first 20 years or more was a cool period with little glacier change. The mapped features were filtered for those greater than 0.01 km2. Results show that 5036 G&PS (672 km2, 14 km3) populate eight states, of which about 1276 (554 km2, 12 km3) are glaciers. Uncertainty is estimated at ±9% for area and ±20% for volume. Two populations of G&PS were identified based on air temperature and precipitation. The larger is found in a maritime climate of the Pacific Northwest, characterized by warm winter air temperatures and high winter precipitation (~2100 mm). The other population is continental in climate, characterized by cold winter air temperatures, relatively low winter precipitation (~880 mm), and located at higher elevations elsewhere. The G&PS in the Pacific Northwest, especially in the Olympic Mountains, are particularly vulnerable to warming winter air temperatures that will change the phase of winter precipitation from snow to rain, further accelerating glacier shrinkage in the future. Comparison with a recent inventory suggests that the total G&PS area in the American West may have decreased by as much as 39% since the mid-20th century. Title: The Geography of Glaciers and Perennial Snowfields in the American West Author: Fountain, Andrew G., Glenn, Bryce, Basagic, Hassan J. Year: 2017 A comprehensive mid-20th century inventory of glaciers and perennial snowfields (G&PS) was compiled for the American West, west of the 100° meridian. The inventory was derived from U.S. Geological Survey 1:24,000 topographic maps based on aerial photographs acquired during 35 years, 1955–1990, of which the first 20 years or more was a cool period with little glacier change. The mapped features were filtered for those greater than 0.01 km2. Results show that 5036 G&PS (672 km2, 14 km3) populate eight states, of which about 1276 (554 km2, 12 km3) are glaciers. Uncertainty is estimated at ±9% for area and ±20% for volume. Two populations of G&PS were identified based on air temperature and precipitation. The larger is found in a maritime climate of the Pacific Northwest, characterized by warm winter air temperatures and high winter precipitation (~2100 mm). The other population is continental in climate, characterized by cold winter air temperatures, relatively low winter precipitation (~880 mm), and located at higher elevations elsewhere. The G&PS in the Pacific Northwest, especially in the Olympic Mountains, are particularly vulnerable to warming winter air temperatures that will change the phase of winter precipitation from snow to rain, further accelerating glacier shrinkage in the future. Comparison with a recent inventory suggests that the total G&PS area in the American West may have decreased by as much as 39% since the mid-20th century. Close

• 19. [Article] Spatial, Temporal and Frequency Based Climate change Assessment in Columbia River Basin Using Multi Downscaled-Scenarios

  Uncertainties in climate modelling are well documented in literature. Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional scale. In the present work, we have ...

  Citation × Citation Citation Abstract Copy Title: Spatial, Temporal and Frequency Based Climate change Assessment in Columbia River Basin Using Multi Downscaled-Scenarios Author: Rana, Arun, Moradkhani, Hamid Year: 2016 Uncertainties in climate modelling are well documented in literature. Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional scale. In the present work, we have analyzed the changes in precipitation and temperature for future scenario period of 2070–2099 with respect to historical period of 1970–2000 from statistically downscaled GCM projections in Columbia River Basin (CRB). Analysis is performed using two different statistically downscaled climate projections (with ten GCMs downscaled products each, for RCP 4.5 and RCP 8.5, from CMIP5 dataset) namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. The two datasets for BCSD and MACA are downscaled from observed data for both scenarios projections i.e. RCP4.5 and RCP8.5. Analysis is performed using spatial change (yearly scale), temporal change (monthly scale), percentile change (seasonal scale), quantile change (yearly scale), and wavelet analysis (yearly scale) in the future period from the historical period, respectively, at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice versa for temperature. Most of the models have indicated considerate positive change in quantiles and percentiles for both precipitation and temperature. Wavelet analysis provided insights into possible explanation to changes in precipitation. Title: Spatial, Temporal and Frequency Based Climate change Assessment in Columbia River Basin Using Multi Downscaled-Scenarios Author: Rana, Arun, Moradkhani, Hamid Year: 2016 Uncertainties in climate modelling are well documented in literature. Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional scale. In the present work, we have analyzed the changes in precipitation and temperature for future scenario period of 2070–2099 with respect to historical period of 1970–2000 from statistically downscaled GCM projections in Columbia River Basin (CRB). Analysis is performed using two different statistically downscaled climate projections (with ten GCMs downscaled products each, for RCP 4.5 and RCP 8.5, from CMIP5 dataset) namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. The two datasets for BCSD and MACA are downscaled from observed data for both scenarios projections i.e. RCP4.5 and RCP8.5. Analysis is performed using spatial change (yearly scale), temporal change (monthly scale), percentile change (seasonal scale), quantile change (yearly scale), and wavelet analysis (yearly scale) in the future period from the historical period, respectively, at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice versa for temperature. Most of the models have indicated considerate positive change in quantiles and percentiles for both precipitation and temperature. Wavelet analysis provided insights into possible explanation to changes in precipitation. Close

• 20. [Article] Streamflow Modeling of Johnson Creek Subwatersheds Using the Precipitation Runoff Modeling System

  Johnson Creek, in the Portland, Oregon metropolitan region, has several pollutants on the U.S. Environmental Protection Agency’s (EPA) 303(d) list including excess heat, low dissolved oxygen, and harmful ...

  Citation × Citation Citation Abstract Copy Title: Streamflow Modeling of Johnson Creek Subwatersheds Using the Precipitation Runoff Modeling System Author: Malone, Theophilus M Year: 2014 Johnson Creek, in the Portland, Oregon metropolitan region, has several pollutants on the U.S. Environmental Protection Agency’s (EPA) 303(d) list including excess heat, low dissolved oxygen, and harmful bacteria. Understanding streamflow response to precipitation events is an important component to evaluating water quality trends and calculating the Total Maximum Daily Load (TMDL) for pollutants of concern. Investigating the streamflow-precipitation relationship on the subwatershed scale can give insight to the hydrologic response of a given watershed. However, developing rating curves for several subwatersheds can be cost and time prohibitive. The objective of this project was to develop a hydrologic model using the Precipitation Runoff Modeling System (PRMS), developed by the United States Geological Survey (USGS) to validate streamflow estimates for subwatersheds lacking a significant period of record. ESRI’s ArcMap, a geographic information system (GIS), was used to characterize the target drainage basins and extract basin-specific parameters for upper watersheds of Johnson Creek. The Johnson Creek Upper Watershed (JCUW) model was calibrated to an existing streamflow gage at Regner Road, in Gresham, Oregon. Calibrated parameters were substituted into a second PRMS model characterizing the Sunshine Creek Subwatershed, which lies within the JCUW. The Sunshine Creek model was used to validate a flow time-series derived from a pressure transducer and a rating curve. Title: Streamflow Modeling of Johnson Creek Subwatersheds Using the Precipitation Runoff Modeling System Author: Malone, Theophilus M Year: 2014 Johnson Creek, in the Portland, Oregon metropolitan region, has several pollutants on the U.S. Environmental Protection Agency’s (EPA) 303(d) list including excess heat, low dissolved oxygen, and harmful bacteria. Understanding streamflow response to precipitation events is an important component to evaluating water quality trends and calculating the Total Maximum Daily Load (TMDL) for pollutants of concern. Investigating the streamflow-precipitation relationship on the subwatershed scale can give insight to the hydrologic response of a given watershed. However, developing rating curves for several subwatersheds can be cost and time prohibitive. The objective of this project was to develop a hydrologic model using the Precipitation Runoff Modeling System (PRMS), developed by the United States Geological Survey (USGS) to validate streamflow estimates for subwatersheds lacking a significant period of record. ESRI’s ArcMap, a geographic information system (GIS), was used to characterize the target drainage basins and extract basin-specific parameters for upper watersheds of Johnson Creek. The Johnson Creek Upper Watershed (JCUW) model was calibrated to an existing streamflow gage at Regner Road, in Gresham, Oregon. Calibrated parameters were substituted into a second PRMS model characterizing the Sunshine Creek Subwatershed, which lies within the JCUW. The Sunshine Creek model was used to validate a flow time-series derived from a pressure transducer and a rating curve. Close