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• 21. [Article] Projected temperature and precipitation changes for Corvallis and Los Angeles for the 2030-2059 period using the Hadley Center's regional climate model (HadRM3P).

  Average monthly temperatures (maximum and minimum) and precipitation patterns are expected to change as a direct consequence of anthropogenic climate change. Temperatures are expected to be warmer in the ...

  Citation × Citation Citation Abstract Copy Title: Projected temperature and precipitation changes for Corvallis and Los Angeles for the 2030-2059 period using the Hadley Center's regional climate model (HadRM3P). Author: Cheema, Karandeep Singh Average monthly temperatures (maximum and minimum) and precipitation patterns are expected to change as a direct consequence of anthropogenic climate change. Temperatures are expected to be warmer in the future but precise estimates vary depending on factors like number of ensembles and emission scenario. For this study, we used 100 ensembles to simulate a recent historical period (Dec. 1985-Nov 2014) and a future climate scenario (Dec. 2030-Nov. 2059) for two cities: Corvallis, OR and Los Angeles, CA. Atmospheric forcings followed the RCP 4.5 scenario. We used results from the simulations to compare temperature and precipitation changes between the two periods for both cities. Average monthly temperatures (maximum and minimum) increased for both cities. Both cities would experience an increase in number of days above 90 °F (14 for Corvallis and 18 more days for Los Angeles). For Corvallis, average annual temperature increased from 12.8 ± 0.3°? to 14.4 ± 0.3 °?. Average annual precipitation increased from 942.0 mm to 994.0 mm (p-value: 10−23). Likewise, for Los Angeles, average annual temperature increased from 18.1 ± 0.3°? to 19.5 ± 0.3 °? and average annual precipitation changed from 265.0 mm to 260.0 mm (p-value: 0.32). We further analyzed changes in precipitation in terms of changes in frequency and intensity. Frequency and intensity of precipitation increased in winter months for Corvallis while non-uniform patterns were seen for Los Angeles. Summer precipitation decreased in terms of frequency and intensity of precipitation events for both cities. Title: Projected temperature and precipitation changes for Corvallis and Los Angeles for the 2030-2059 period using the Hadley Center's regional climate model (HadRM3P). Author: Cheema, Karandeep Singh Average monthly temperatures (maximum and minimum) and precipitation patterns are expected to change as a direct consequence of anthropogenic climate change. Temperatures are expected to be warmer in the future but precise estimates vary depending on factors like number of ensembles and emission scenario. For this study, we used 100 ensembles to simulate a recent historical period (Dec. 1985-Nov 2014) and a future climate scenario (Dec. 2030-Nov. 2059) for two cities: Corvallis, OR and Los Angeles, CA. Atmospheric forcings followed the RCP 4.5 scenario. We used results from the simulations to compare temperature and precipitation changes between the two periods for both cities. Average monthly temperatures (maximum and minimum) increased for both cities. Both cities would experience an increase in number of days above 90 °F (14 for Corvallis and 18 more days for Los Angeles). For Corvallis, average annual temperature increased from 12.8 ± 0.3°? to 14.4 ± 0.3 °?. Average annual precipitation increased from 942.0 mm to 994.0 mm (p-value: 10−23). Likewise, for Los Angeles, average annual temperature increased from 18.1 ± 0.3°? to 19.5 ± 0.3 °? and average annual precipitation changed from 265.0 mm to 260.0 mm (p-value: 0.32). We further analyzed changes in precipitation in terms of changes in frequency and intensity. Frequency and intensity of precipitation increased in winter months for Corvallis while non-uniform patterns were seen for Los Angeles. Summer precipitation decreased in terms of frequency and intensity of precipitation events for both cities. Close

• 22. [Article] Statistical relationships between the mesoscale organization of convection, precipitation and the large-scale wind fields during the GATE

  Data from the GARP Atlantic Tropical Experiment (GATE) was analysed in an exploratory manner to discover the characteristics of mesoscale organization of convection and it's relationship to large-scale ...

  Citation × Citation Citation Abstract Copy Title: Statistical relationships between the mesoscale organization of convection, precipitation and the large-scale wind fields during the GATE Author: De Silva, Sirilath J. Data from the GARP Atlantic Tropical Experiment (GATE) was analysed in an exploratory manner to discover the characteristics of mesoscale organization of convection and it's relationship to large-scale wind profiles. Automated methods were developed to identify the convective cells and their linear organization. These automated methods use a median high-pass filter to identify enhanced cells and a simple pattern recognition technique to ascertain the linear organization between them. Due to the simplified nature of the algorithm, the whole data set of the 21 day period from the phase 3 of GATE was processed in an economical manner obtaining a large data base which was used in the investigation of clusters and other associated phenomena. The mesoscale organization of convective cells and the widespread areas of lighter precipitation associated with them showed expected characteristics and compared satisfactorily with previous results. A large fraction of the rainfall (64%) fell from the widespread area. The total precipitation had a correlation of 0.94 with the fractional area of the widespread and a correlation of 0.89 with the fractional area of the clusters. The widespread precipitation had a correlation index of 0.97 with it's fractional area and the cluster precipitation had a strong linear relationship to it's area with a correlation of 0.99. These factors argue well for the parameterization of rainfall rate in tropical regions to a high accuracy by the area covered by organized convective cells and widespread areas. It was also seen that there was a good correlation with the number of clusters and number of cores with the total precipitation rate in a given area. These factors create a strong argument for identifying mesoscale systems consisting of convective cells and widespread precipitation as basic units of precipitation in tropical regions, having a characteristic life cycle of their own. The widespread and total precipitation showed very good correlation with upper-level vertical motion. Clusters tended to align parallel with the horizontal low-level wind shear and the degree of alignment appears to depend on the strength of the wind shear. Title: Statistical relationships between the mesoscale organization of convection, precipitation and the large-scale wind fields during the GATE Author: De Silva, Sirilath J. Data from the GARP Atlantic Tropical Experiment (GATE) was analysed in an exploratory manner to discover the characteristics of mesoscale organization of convection and it's relationship to large-scale wind profiles. Automated methods were developed to identify the convective cells and their linear organization. These automated methods use a median high-pass filter to identify enhanced cells and a simple pattern recognition technique to ascertain the linear organization between them. Due to the simplified nature of the algorithm, the whole data set of the 21 day period from the phase 3 of GATE was processed in an economical manner obtaining a large data base which was used in the investigation of clusters and other associated phenomena. The mesoscale organization of convective cells and the widespread areas of lighter precipitation associated with them showed expected characteristics and compared satisfactorily with previous results. A large fraction of the rainfall (64%) fell from the widespread area. The total precipitation had a correlation of 0.94 with the fractional area of the widespread and a correlation of 0.89 with the fractional area of the clusters. The widespread precipitation had a correlation index of 0.97 with it's fractional area and the cluster precipitation had a strong linear relationship to it's area with a correlation of 0.99. These factors argue well for the parameterization of rainfall rate in tropical regions to a high accuracy by the area covered by organized convective cells and widespread areas. It was also seen that there was a good correlation with the number of clusters and number of cores with the total precipitation rate in a given area. These factors create a strong argument for identifying mesoscale systems consisting of convective cells and widespread precipitation as basic units of precipitation in tropical regions, having a characteristic life cycle of their own. The widespread and total precipitation showed very good correlation with upper-level vertical motion. Clusters tended to align parallel with the horizontal low-level wind shear and the degree of alignment appears to depend on the strength of the wind shear. Close

• 23. [Article] Long-term effects of changes in vegetation condition, precipitation and watershed parameters on summer low-flows in the semi-arid Pacific Northwest

  Summer low-flow behavior in the semi-arid areas of the Pacific Northwest was studied. Long-term data from thirty-eight streams/rivers and thirty-six precipitation stations was exploited. The study area ...

  Citation × Citation Citation Abstract Copy Title: Long-term effects of changes in vegetation condition, precipitation and watershed parameters on summer low-flows in the semi-arid Pacific Northwest Author: Zeb, Aurang Summer low-flow behavior in the semi-arid areas of the Pacific Northwest was studied. Long-term data from thirty-eight streams/rivers and thirty-six precipitation stations was exploited. The study area was divided into five zones based on annual average precipitation. Trends and patterns in summer low-flows and precipitation were identified. Different zones showed different trends and patterns in precipitation over the period of record but significant similarities within each zone. Most of the summer low-flow and precipitation records showed that the 1930's and the late 1980's to early 1990's experienced major droughts. A possible return interval of 50-60 years appeared reasonable for similar major droughts in the study area. Spring, summer and fall precipitation, on average, were found insignificantly related to the summer low-flows, except for northern Idaho and southeastern Oregon where summer precipitation was significant in explaining the summer low-flow trends. Winter and annual precipitation were found significantly related to summer low-flows. But the zonal equations constructed to predict summer low-flows using precipitation alone were considered unsuitable for practical use. Zonal and regional recession models to forecast summer stream flows with significant accuracies were constructed successfully. Extreme summer low-flows were not significantly related to different watershed cover types in eastern Oregon. However, percentage of rangelands appeared to be more related to the extreme summer low-flow than other cover types. An extreme summer low-flow prediction model was constructed using several watershed and precipitation variables. Many of these variables were found to be significantly related to extreme summer low-flow. Watershed average width and annual minimum precipitation explained 71% of the variations in the extreme summer low-flow. The model finally selected, with the inclusion of watershed end point elevation, was able to explain 79% of the variability in the extreme summer low-flow. Stream and precipitation gauges need to be carefully maintained during dry periods. Also, generalization of climatic trends based on a few observations in a large region can be misleading. Title: Long-term effects of changes in vegetation condition, precipitation and watershed parameters on summer low-flows in the semi-arid Pacific Northwest Author: Zeb, Aurang Summer low-flow behavior in the semi-arid areas of the Pacific Northwest was studied. Long-term data from thirty-eight streams/rivers and thirty-six precipitation stations was exploited. The study area was divided into five zones based on annual average precipitation. Trends and patterns in summer low-flows and precipitation were identified. Different zones showed different trends and patterns in precipitation over the period of record but significant similarities within each zone. Most of the summer low-flow and precipitation records showed that the 1930's and the late 1980's to early 1990's experienced major droughts. A possible return interval of 50-60 years appeared reasonable for similar major droughts in the study area. Spring, summer and fall precipitation, on average, were found insignificantly related to the summer low-flows, except for northern Idaho and southeastern Oregon where summer precipitation was significant in explaining the summer low-flow trends. Winter and annual precipitation were found significantly related to summer low-flows. But the zonal equations constructed to predict summer low-flows using precipitation alone were considered unsuitable for practical use. Zonal and regional recession models to forecast summer stream flows with significant accuracies were constructed successfully. Extreme summer low-flows were not significantly related to different watershed cover types in eastern Oregon. However, percentage of rangelands appeared to be more related to the extreme summer low-flow than other cover types. An extreme summer low-flow prediction model was constructed using several watershed and precipitation variables. Many of these variables were found to be significantly related to extreme summer low-flow. Watershed average width and annual minimum precipitation explained 71% of the variations in the extreme summer low-flow. The model finally selected, with the inclusion of watershed end point elevation, was able to explain 79% of the variability in the extreme summer low-flow. Stream and precipitation gauges need to be carefully maintained during dry periods. Also, generalization of climatic trends based on a few observations in a large region can be misleading. Close

• 24. [Article] The effect of precipitation variation on soil moisture, soil nitrogen, nitrogen response and winter wheat yields in eastern Oregon

  The semi-arid regions of the Pacific Northwest are characterized by a high degree of annual temperature and precipitation variation. As a result of this climatic variation, dryland nitrogen fertilizer ...

  Citation × Citation Citation Abstract Copy Title: The effect of precipitation variation on soil moisture, soil nitrogen, nitrogen response and winter wheat yields in eastern Oregon Author: Glenn, D. M. (David Michael) The semi-arid regions of the Pacific Northwest are characterized by a high degree of annual temperature and precipitation variation. As a result of this climatic variation, dryland nitrogen fertilizer trials on fallow- ,wheat rotations typically demonstrate a variable response. Wheat growers in the area must not only cope with this climatic variation and its sundry effects upon their livelihood, they must also make decisions regarding the future level of anticipated climatic variation. The specific objectives were to: 1) develop a climatically responsive yield potential prediction model for soft white winter wheat from historical data at the Sherman Branch Experiment Station (Moro, OR); 2) modify this model for use on commercial fields; 3) field simulate five fallow-crop precipitation patterns characteristic of the variation found in the Sherman county area of eastern Oregon in order to test the yield potential model: 4) examine the effects of precipitation variation on nitrogen fertilizer responses, moisture storage and depletion and nitrogen mineralization; and 5) establish a quantitative relationship between precipitation/ soil moisture and nitrate accumulation in both the fallow and crop seasons. Two interacting regression models were developed to estimate grain yield levels in the 250-350 mm precipitation zone of eastern Oregon. The first model estimates yield potential from monthly precipitation and temperature values. The second model estimates the percent grain reduction due to delayed crop emergence. The grain yield model was adapted to commercial fields using a Productivity Index factor (PI). The PI is a measure of the productivity of other locations in relation to the Sherman Branch Experiment Station, using water-use-efficiency (WUE) as the basis of comparison. The field simulation of five fallow-crop precipitation patterns demonstrated that the maximum grain yield response occurred at 40 kg N (soil + fertilizer)/metric ton. The grain yield model demonstrated a 15% level of accuracy on a commercial field basis in both field trials and a survey of past production levels (1972-1980). It was hypothesized that the distribution of precipitation in the fallow and crop periods had an effect on both the amount and distribution of stored soil moisture. The field simulation demonstrated that more soil moisture was stored at the 90-240 cm depths by the patterns with more fallow season precipitation when measured in March of the crop year. Soil moisture storage and storage efficiencies fluctuated throughout the fallow and crop periods. At the cessation of the winter precipitation season in both the fallow and crop periods (March), the storage efficiency was highest when low levels of precipitation occurred. At this point in time, the mean crop period storage efficiency was 10% below the mean fallow period storage efficiency (34 and 44%, respectively) in both simulation studies. Soil moisture, temperature and immobilization requirements of crop residues interact to affect the net amount of nitrogen mineralization. The mineralization model proposed by Stanford and Smith (1972) was tested under field conditions. When the nitrogen immobilization requirement of the crop residues was included, the actual and predicted values were in agreement at the close of the 1978 fallow period. A nitrogen deficit was predicted at the 0-30 cm depth at the close of the 1980 fallow; however, the actual levels indicated a net accumulation of nitrate-nitrogen. Crop season mineralization, inferred from Mitscherlick and a-value extrapolations, in 1979 demonstrated that there was a decreasing amount of net mineralization during the crop season with increasing amounts of both fallow and crop season precipitation. Crop season mineralization in 1980 indicated that there was no net accumulation of nitrogen, rather a tie-up of 14 kg N/ha. This result reflects both the unsatisfied immobilization requirement predicted for the 1979 fallow season and crop season denitrification. Title: The effect of precipitation variation on soil moisture, soil nitrogen, nitrogen response and winter wheat yields in eastern Oregon Author: Glenn, D. M. (David Michael) The semi-arid regions of the Pacific Northwest are characterized by a high degree of annual temperature and precipitation variation. As a result of this climatic variation, dryland nitrogen fertilizer trials on fallow- ,wheat rotations typically demonstrate a variable response. Wheat growers in the area must not only cope with this climatic variation and its sundry effects upon their livelihood, they must also make decisions regarding the future level of anticipated climatic variation. The specific objectives were to: 1) develop a climatically responsive yield potential prediction model for soft white winter wheat from historical data at the Sherman Branch Experiment Station (Moro, OR); 2) modify this model for use on commercial fields; 3) field simulate five fallow-crop precipitation patterns characteristic of the variation found in the Sherman county area of eastern Oregon in order to test the yield potential model: 4) examine the effects of precipitation variation on nitrogen fertilizer responses, moisture storage and depletion and nitrogen mineralization; and 5) establish a quantitative relationship between precipitation/ soil moisture and nitrate accumulation in both the fallow and crop seasons. Two interacting regression models were developed to estimate grain yield levels in the 250-350 mm precipitation zone of eastern Oregon. The first model estimates yield potential from monthly precipitation and temperature values. The second model estimates the percent grain reduction due to delayed crop emergence. The grain yield model was adapted to commercial fields using a Productivity Index factor (PI). The PI is a measure of the productivity of other locations in relation to the Sherman Branch Experiment Station, using water-use-efficiency (WUE) as the basis of comparison. The field simulation of five fallow-crop precipitation patterns demonstrated that the maximum grain yield response occurred at 40 kg N (soil + fertilizer)/metric ton. The grain yield model demonstrated a 15% level of accuracy on a commercial field basis in both field trials and a survey of past production levels (1972-1980). It was hypothesized that the distribution of precipitation in the fallow and crop periods had an effect on both the amount and distribution of stored soil moisture. The field simulation demonstrated that more soil moisture was stored at the 90-240 cm depths by the patterns with more fallow season precipitation when measured in March of the crop year. Soil moisture storage and storage efficiencies fluctuated throughout the fallow and crop periods. At the cessation of the winter precipitation season in both the fallow and crop periods (March), the storage efficiency was highest when low levels of precipitation occurred. At this point in time, the mean crop period storage efficiency was 10% below the mean fallow period storage efficiency (34 and 44%, respectively) in both simulation studies. Soil moisture, temperature and immobilization requirements of crop residues interact to affect the net amount of nitrogen mineralization. The mineralization model proposed by Stanford and Smith (1972) was tested under field conditions. When the nitrogen immobilization requirement of the crop residues was included, the actual and predicted values were in agreement at the close of the 1978 fallow period. A nitrogen deficit was predicted at the 0-30 cm depth at the close of the 1980 fallow; however, the actual levels indicated a net accumulation of nitrate-nitrogen. Crop season mineralization, inferred from Mitscherlick and a-value extrapolations, in 1979 demonstrated that there was a decreasing amount of net mineralization during the crop season with increasing amounts of both fallow and crop season precipitation. Crop season mineralization in 1980 indicated that there was no net accumulation of nitrogen, rather a tie-up of 14 kg N/ha. This result reflects both the unsatisfied immobilization requirement predicted for the 1979 fallow season and crop season denitrification. Close

• 25. [Article] The Relation of Precipitation and Annual Tree-Ring Growth of Douglas-Fir in Stands of Different Ages in the Western Oregon Cascade Range

  33 p. A THESIS Presented to the Department of Environmental Studies of the University of Oregon in partial fulfillment of the requirements for the degree of Bachelor of Science with Honors in Environmental ...

  Citation × Citation Citation Abstract Copy Title: The Relation of Precipitation and Annual Tree-Ring Growth of Douglas-Fir in Stands of Different Ages in the Western Oregon Cascade Range Author: Argo, Kathryn L., 1985- Year: 2007 33 p. A THESIS Presented to the Department of Environmental Studies of the University of Oregon in partial fulfillment of the requirements for the degree of Bachelor of Science with Honors in Environmental Science, Spring 2007. Title: The Relation of Precipitation and Annual Tree-Ring Growth of Douglas-Fir in Stands of Different Ages in the Western Oregon Cascade Range Author: Argo, Kathryn L., 1985- Year: 2007 33 p. A THESIS Presented to the Department of Environmental Studies of the University of Oregon in partial fulfillment of the requirements for the degree of Bachelor of Science with Honors in Environmental Science, Spring 2007. Close

• 26. [Article] A study of the relation between radar and raingage indicated rainfall over northern California

  The WSR-57 weather radar operated by the National Weather Service at Sacramento, California, plus a network of precipitation gages provided data for this comparison of radar reflectivity with precipitation ...

  Citation × Citation Citation Abstract Copy Title: A study of the relation between radar and raingage indicated rainfall over northern California Author: Strem, Eric Thomas The WSR-57 weather radar operated by the National Weather Service at Sacramento, California, plus a network of precipitation gages provided data for this comparison of radar reflectivity with precipitation rates. Located in a valley with mountains within range of the radar on three sides, this radar has varying sensitivity for precipitation rates as a result of the terrain effects. Variation in the terrain surrounding the radar has led to a very wide scatter in precipitation rates associated with any particular radar reflectivity. The radar failed to detect precipitation up to 77% of the time over the Coast Range at ranges greater than 100 nm. Linear regression analyses revealed very poor correlation between the raingage indicated precipitation rate and the radar reflectivity. These analyses resulted in values of (R²), the coefficient of determination, ranging from zero as a minimum to only 0.502 as a maximum. Such results are generally much poorer than results obtained by others. The poor correlations and both overestimation and underestimation of rainfall resulted from factors such as range, terrain blocking, windward or leeward exposure, freezing level height, beam height and width, and the distribution of water vapor in the vertical. Title: A study of the relation between radar and raingage indicated rainfall over northern California Author: Strem, Eric Thomas The WSR-57 weather radar operated by the National Weather Service at Sacramento, California, plus a network of precipitation gages provided data for this comparison of radar reflectivity with precipitation rates. Located in a valley with mountains within range of the radar on three sides, this radar has varying sensitivity for precipitation rates as a result of the terrain effects. Variation in the terrain surrounding the radar has led to a very wide scatter in precipitation rates associated with any particular radar reflectivity. The radar failed to detect precipitation up to 77% of the time over the Coast Range at ranges greater than 100 nm. Linear regression analyses revealed very poor correlation between the raingage indicated precipitation rate and the radar reflectivity. These analyses resulted in values of (R²), the coefficient of determination, ranging from zero as a minimum to only 0.502 as a maximum. Such results are generally much poorer than results obtained by others. The poor correlations and both overestimation and underestimation of rainfall resulted from factors such as range, terrain blocking, windward or leeward exposure, freezing level height, beam height and width, and the distribution of water vapor in the vertical. Close

• 27. [Article] Precipitation-snowmelt timing and snowmelt augmentation of large peak flow events, western Cascades, Oregon

  Despite advances in the understanding of rain-on-snow storms and their resulting peak flows, little is understood about the response of snowmelt to precipitation and the relative timing of the two at multiple ...

  Citation × Citation Citation Abstract Copy Title: Precipitation-snowmelt timing and snowmelt augmentation of large peak flow events, western Cascades, Oregon Author: Jennings, Keith S. Despite advances in the understanding of rain-on-snow storms and their resulting peak flows, little is understood about the response of snowmelt to precipitation and the relative timing of the two at multiple temporal scales within such events. To address this issue, climate, snowmelt, and streamflow data were analyzed for 26 large storms in the H.J. Andrews Experimental Forest in the western Cascades of Oregon. Cumulative net snowmelt was plotted against precipitation for each storm to identify net snowmelt response categories, which were then used to summarize climatic and streamflow data, while the timing of precipitation and net snowmelt was assessed at multiple temporal scales and time ranges with wavelet coherence. Five precipitation-net snowmelt response categories were identified: flat; persistent melt; persistent accumulation; late melt; and late accumulation. Persistent melt events, which were characterized by concomitantly increasing cumulative net snowmelt and precipitation, had the highest mean peak flow and water available for runoff values of the response categories. Large, contiguous regions of significant wavelet coherence at multiple temporal scales were observed in both the persistent melt and persistent accumulation categories, but the phase difference distributions indicated differing snowpack dynamics with pulses of precipitation leading pulses of snowmelt in the former and precipitation being absorbed by the snowpack in the latter. High water available for runoff totals and peak flows were observed in each of the five response categories, but a dewpoint temperature consistently above 0.5°C, elevated wind speeds, and a high fraction of precipitation falling as rain in the persistent melt category facilitated rapid snowmelt rates which were often synchronized with precipitation. Wavelet coherence showed this synchronization to be significant across all temporal scales and time periods for the two largest peak flows in the study, indicating that tightly coupled rainfall-synchrony is essential in generating an extreme rain-on-snow flood. By quantifying the amount and timing of net snowmelt, the categorization scheme provides a means of distinguishing among rain-on-snow events and predicting peak discharge magnitude. Title: Precipitation-snowmelt timing and snowmelt augmentation of large peak flow events, western Cascades, Oregon Author: Jennings, Keith S. Despite advances in the understanding of rain-on-snow storms and their resulting peak flows, little is understood about the response of snowmelt to precipitation and the relative timing of the two at multiple temporal scales within such events. To address this issue, climate, snowmelt, and streamflow data were analyzed for 26 large storms in the H.J. Andrews Experimental Forest in the western Cascades of Oregon. Cumulative net snowmelt was plotted against precipitation for each storm to identify net snowmelt response categories, which were then used to summarize climatic and streamflow data, while the timing of precipitation and net snowmelt was assessed at multiple temporal scales and time ranges with wavelet coherence. Five precipitation-net snowmelt response categories were identified: flat; persistent melt; persistent accumulation; late melt; and late accumulation. Persistent melt events, which were characterized by concomitantly increasing cumulative net snowmelt and precipitation, had the highest mean peak flow and water available for runoff values of the response categories. Large, contiguous regions of significant wavelet coherence at multiple temporal scales were observed in both the persistent melt and persistent accumulation categories, but the phase difference distributions indicated differing snowpack dynamics with pulses of precipitation leading pulses of snowmelt in the former and precipitation being absorbed by the snowpack in the latter. High water available for runoff totals and peak flows were observed in each of the five response categories, but a dewpoint temperature consistently above 0.5°C, elevated wind speeds, and a high fraction of precipitation falling as rain in the persistent melt category facilitated rapid snowmelt rates which were often synchronized with precipitation. Wavelet coherence showed this synchronization to be significant across all temporal scales and time periods for the two largest peak flows in the study, indicating that tightly coupled rainfall-synchrony is essential in generating an extreme rain-on-snow flood. By quantifying the amount and timing of net snowmelt, the categorization scheme provides a means of distinguishing among rain-on-snow events and predicting peak discharge magnitude. Close

• 28. [Article] Detecting Change in Rainstorm Properties from 1977-2016 and Associated Future Flood Risks in Portland, Oregon

  In response to increased greenhouse gases and global temperatures, changes to the hydrologic cycle are projected to occur and new precipitation characteristics are expected to emerge. The study of these ...

  Citation × Citation Citation Abstract Copy Title: Detecting Change in Rainstorm Properties from 1977-2016 and Associated Future Flood Risks in Portland, Oregon Author: Cooley, Alexis Kirsten Year: 2017 In response to increased greenhouse gases and global temperatures, changes to the hydrologic cycle are projected to occur and new precipitation characteristics are expected to emerge. The study of these characteristics is facilitated by common indices to measure precipitation and temperature developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). These indices can be used to describe the likely consequences of climate change such as increased daily precipitation intensity (SDII) and heavier rainfall events (R95p). This study calculates a subset of these indices from observed and modelled precipitation data in Portland, Oregon. Five rainfall gages from a high resolution rain gage network and projections from three downscaled global climate models including CanESM2, CESM1, CNRM-CM5 are used to calculate precipitation indices. Mann-Kendall's tau is used to detect monotonic trends in indices. The observational record is compared with models for the historic period (1977-2005) and these past trends are compared with projected future trends (2006-2100). The influence of study unit on trend detection is analyzed by computing trends at the annual and monthly scale. Study unit is show to be important for trend detection. When the annual study unit is used, projected future trends towards increased precipitation intensity and event volumes are not observed in the historic data. However, when analyzed with a monthly study unit, trends towards increased precipitation intensity and event volumes are observed in the historic data. These trends are shown to be important for Portland area flooding, as precipitation indices are shown to significantly correlate with 40 maximum peak flow events that occurred during the period of study. Title: Detecting Change in Rainstorm Properties from 1977-2016 and Associated Future Flood Risks in Portland, Oregon Author: Cooley, Alexis Kirsten Year: 2017 In response to increased greenhouse gases and global temperatures, changes to the hydrologic cycle are projected to occur and new precipitation characteristics are expected to emerge. The study of these characteristics is facilitated by common indices to measure precipitation and temperature developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). These indices can be used to describe the likely consequences of climate change such as increased daily precipitation intensity (SDII) and heavier rainfall events (R95p). This study calculates a subset of these indices from observed and modelled precipitation data in Portland, Oregon. Five rainfall gages from a high resolution rain gage network and projections from three downscaled global climate models including CanESM2, CESM1, CNRM-CM5 are used to calculate precipitation indices. Mann-Kendall's tau is used to detect monotonic trends in indices. The observational record is compared with models for the historic period (1977-2005) and these past trends are compared with projected future trends (2006-2100). The influence of study unit on trend detection is analyzed by computing trends at the annual and monthly scale. Study unit is show to be important for trend detection. When the annual study unit is used, projected future trends towards increased precipitation intensity and event volumes are not observed in the historic data. However, when analyzed with a monthly study unit, trends towards increased precipitation intensity and event volumes are observed in the historic data. These trends are shown to be important for Portland area flooding, as precipitation indices are shown to significantly correlate with 40 maximum peak flow events that occurred during the period of study. Close

• 29. [Article] Uncertainty Quantification of Satellite Precipitation Estimation and Monte Carlo Assessment of the Error Propagation into Hydrologic Response

  The aim of this paper is to foster the development of an end-to-end uncertainty analysis framework that can quantify satellite-based precipitation estimation error characteristics and to assess the influence ...

  Citation × Citation Citation Abstract Copy Title: Uncertainty Quantification of Satellite Precipitation Estimation and Monte Carlo Assessment of the Error Propagation into Hydrologic Response Author: Moradkhani, Hamid, Hong, Yang, Sorooshian, Soroosh Year: 2006 The aim of this paper is to foster the development of an end-to-end uncertainty analysis framework that can quantify satellite-based precipitation estimation error characteristics and to assess the influence of the error propagation into hydrological simulation. First, the error associated with the satellite-based precipitation estimates is assumed as a nonlinear function of rainfall space-time integration scale, rain intensity, and sampling frequency. Parameters of this function are determined by using high-resolution satellite-based precipitation estimates and gauge-corrected radar rainfall data over the southwestern United States. Parameter sensitivity analysis at 16 selected 5ø ? 5ø latitude-longitude grids shows about 12?16% of variance of each parameter with respect to its mean value. Afterward, the influence of precipitation estimation error on the uncertainty of hydrological response is further examined with Monte Carlo simulation. By this approach, 100 ensemble members of precipitation data are generated, as forcing input to a conceptual rainfall-runoff hydrologic model, and the resulting uncertainty in the streamflow prediction is quantified. Case studies are demonstrated over the Leaf River basin in Mississippi. Compared with conventional procedure, i.e., precipitation estimation error as fixed ratio of rain rates, the proposed framework provides more realistic quantification of precipitation estimation error and offers improved uncertainty assessment of the error propagation into hydrologic simulation. Further study shows that the radar rainfall-generated streamflow sequences are consistently contained by the uncertainty bound of satellite rainfall generated streamflow at the 95% confidence interval. Title: Uncertainty Quantification of Satellite Precipitation Estimation and Monte Carlo Assessment of the Error Propagation into Hydrologic Response Author: Moradkhani, Hamid, Hong, Yang, Sorooshian, Soroosh Year: 2006 The aim of this paper is to foster the development of an end-to-end uncertainty analysis framework that can quantify satellite-based precipitation estimation error characteristics and to assess the influence of the error propagation into hydrological simulation. First, the error associated with the satellite-based precipitation estimates is assumed as a nonlinear function of rainfall space-time integration scale, rain intensity, and sampling frequency. Parameters of this function are determined by using high-resolution satellite-based precipitation estimates and gauge-corrected radar rainfall data over the southwestern United States. Parameter sensitivity analysis at 16 selected 5ø ? 5ø latitude-longitude grids shows about 12?16% of variance of each parameter with respect to its mean value. Afterward, the influence of precipitation estimation error on the uncertainty of hydrological response is further examined with Monte Carlo simulation. By this approach, 100 ensemble members of precipitation data are generated, as forcing input to a conceptual rainfall-runoff hydrologic model, and the resulting uncertainty in the streamflow prediction is quantified. Case studies are demonstrated over the Leaf River basin in Mississippi. Compared with conventional procedure, i.e., precipitation estimation error as fixed ratio of rain rates, the proposed framework provides more realistic quantification of precipitation estimation error and offers improved uncertainty assessment of the error propagation into hydrologic simulation. Further study shows that the radar rainfall-generated streamflow sequences are consistently contained by the uncertainty bound of satellite rainfall generated streamflow at the 95% confidence interval. Close

• 30. [Article] Assessing the Impact of CMIP5 Climate Multi-Modeling on Estimating the Precipitation Seasonality and Timing

  This paper investigates the effect of a Bayesian Model Averaging (BMA) method on simulated precipitation over the Columbia River Basin using two statistically downscaled climate datasets, i.e., Bias-Correction ...

  Citation × Citation Citation Abstract Copy Title: Assessing the Impact of CMIP5 Climate Multi-Modeling on Estimating the Precipitation Seasonality and Timing Author: Demirel, Mehmet, Moradkhani, Hamid Year: 2015 This paper investigates the effect of a Bayesian Model Averaging (BMA) method on simulated precipitation over the Columbia River Basin using two statistically downscaled climate datasets, i.e., Bias-Correction Spatial Disaggregation (BCSD) and Multivariate Adaptive Constructed Analogs (MACA). To this end daily observed and simulated precipitation are used to calculate different indices focusing solely on seasonality, event-timing, and variability in timing (persistence) of the precipitation. The climate model weights are estimated for each cell (6 × 6 km) of the Columbia River Basin using daily time series for the historical period 1970–1999 from the ten Global Climate Models (GCMs) participating to the Coupled Model Intercomparison Project platform, Phase 5. The results show that BMA results in more than 15 % improvement/reduction in mean absolute error as compared to the individual GCMs. The improvement is, in general, higher for the MACA models than for the BCSD models. The results of variability in precipitation timing show that extreme precipitation events are mostly not persistent (i.e., occurring in different periods throughout the year), i.e., more than 75 % of the grid cells with an elevation above 900 m indicate persistence values less than 0.2 whereas nearly 70 % of the high elevation cells indicate such low persistence. Further we find that the variability in persistence is higher in high elevation cells than those with low elevation. The picture is different for MACA ensembles as the simulated persistence of extreme precipitation events is higher than that for the observed and BCSD datasets. Title: Assessing the Impact of CMIP5 Climate Multi-Modeling on Estimating the Precipitation Seasonality and Timing Author: Demirel, Mehmet, Moradkhani, Hamid Year: 2015 This paper investigates the effect of a Bayesian Model Averaging (BMA) method on simulated precipitation over the Columbia River Basin using two statistically downscaled climate datasets, i.e., Bias-Correction Spatial Disaggregation (BCSD) and Multivariate Adaptive Constructed Analogs (MACA). To this end daily observed and simulated precipitation are used to calculate different indices focusing solely on seasonality, event-timing, and variability in timing (persistence) of the precipitation. The climate model weights are estimated for each cell (6 × 6 km) of the Columbia River Basin using daily time series for the historical period 1970–1999 from the ten Global Climate Models (GCMs) participating to the Coupled Model Intercomparison Project platform, Phase 5. The results show that BMA results in more than 15 % improvement/reduction in mean absolute error as compared to the individual GCMs. The improvement is, in general, higher for the MACA models than for the BCSD models. The results of variability in precipitation timing show that extreme precipitation events are mostly not persistent (i.e., occurring in different periods throughout the year), i.e., more than 75 % of the grid cells with an elevation above 900 m indicate persistence values less than 0.2 whereas nearly 70 % of the high elevation cells indicate such low persistence. Further we find that the variability in persistence is higher in high elevation cells than those with low elevation. The picture is different for MACA ensembles as the simulated persistence of extreme precipitation events is higher than that for the observed and BCSD datasets. Close