Search

Search Results

• 1. [Article] Sensitivity of CONUS Summer Rainfall to the Selection of Cumulus Parameterization Schemes in NU-WRF Seasonal Simulations

  This study investigates the sensitivity of daily rainfall rates in regional seasonal simulations over the contiguous United States (CONUS) to different cumulus parameterization schemes. Daily rainfall ...

  Citation × Citation Citation Abstract Copy Title: Sensitivity of CONUS Summer Rainfall to the Selection of Cumulus Parameterization Schemes in NU-WRF Seasonal Simulations Author: Iguchia, Takamichi, Tao, Wei-Kuo, Wu, Di, Peters-Lidard, Christa D., Santanello, Joseph A., Kemp, Eric, Tian, Yudong, Case, Jonathan, Wang, Weile, Ferraro, Robert, Waliser, Duane E., Kim, Jinwon, Lee, Huikyo, Guan, Bin, Tian, Baijun, Loikith, Paul C. Year: 2017 This study investigates the sensitivity of daily rainfall rates in regional seasonal simulations over the contiguous United States (CONUS) to different cumulus parameterization schemes. Daily rainfall fields were simulated at 24-km resolution using the NASA-Unified Weather Research and Forecasting (NU-WRF) Model for June–August 2000. Four cumulus parameterization schemes and two options for shallow cumulus components in a specific scheme were tested. The spread in the domain-mean rainfall rates across the parameterization schemes was generally consistent between the entire CONUS and most subregions. The selection of the shallow cumulus component in a specific scheme had more impact than that of the four cumulus parameterization schemes. Regional variability in the performance of each scheme was assessed by calculating optimally weighted ensembles that minimize full root-mean-square errors against reference datasets. The spatial pattern of the seasonally averaged rainfall was insensitive to the selection of cumulus parameterization over mountainous regions because of the topographical pattern constraint, so that the simulation errors were mostly attributed to the overall bias there. In contrast, the spatial patterns over the Great Plains regions as well as the temporal variation over most parts of the CONUS were relatively sensitive to cumulus parameterization selection. Overall, adopting a single simulation result was preferable to generating a better ensemble for the seasonally averaged daily rainfall simulation, as long as their overall biases had the same positive or negative sign. However, an ensemble of multiple simulation results was more effective in reducing errors in the case of also considering temporal variation. Title: Sensitivity of CONUS Summer Rainfall to the Selection of Cumulus Parameterization Schemes in NU-WRF Seasonal Simulations Author: Iguchia, Takamichi, Tao, Wei-Kuo, Wu, Di, Peters-Lidard, Christa D., Santanello, Joseph A., Kemp, Eric, Tian, Yudong, Case, Jonathan, Wang, Weile, Ferraro, Robert, Waliser, Duane E., Kim, Jinwon, Lee, Huikyo, Guan, Bin, Tian, Baijun, Loikith, Paul C. Year: 2017 This study investigates the sensitivity of daily rainfall rates in regional seasonal simulations over the contiguous United States (CONUS) to different cumulus parameterization schemes. Daily rainfall fields were simulated at 24-km resolution using the NASA-Unified Weather Research and Forecasting (NU-WRF) Model for June–August 2000. Four cumulus parameterization schemes and two options for shallow cumulus components in a specific scheme were tested. The spread in the domain-mean rainfall rates across the parameterization schemes was generally consistent between the entire CONUS and most subregions. The selection of the shallow cumulus component in a specific scheme had more impact than that of the four cumulus parameterization schemes. Regional variability in the performance of each scheme was assessed by calculating optimally weighted ensembles that minimize full root-mean-square errors against reference datasets. The spatial pattern of the seasonally averaged rainfall was insensitive to the selection of cumulus parameterization over mountainous regions because of the topographical pattern constraint, so that the simulation errors were mostly attributed to the overall bias there. In contrast, the spatial patterns over the Great Plains regions as well as the temporal variation over most parts of the CONUS were relatively sensitive to cumulus parameterization selection. Overall, adopting a single simulation result was preferable to generating a better ensemble for the seasonally averaged daily rainfall simulation, as long as their overall biases had the same positive or negative sign. However, an ensemble of multiple simulation results was more effective in reducing errors in the case of also considering temporal variation. Close

• 2. [Article] ENSO Controls Interannual Fire Activity in Southeast Australia

  El Niño–Southern Oscillation (ENSO) is the main mode controlling the variability in the ocean-atmosphere system in the South Pacific. While the ENSO influence on rainfall regimes in the South Pacific is ...

  Citation × Citation Citation Abstract Copy Title: ENSO Controls Interannual Fire Activity in Southeast Australia Author: Mariani, Michela, Fletcher, Michael-Shawn, Holz, Andrés, Nyman, Petter Year: 2016 El Niño–Southern Oscillation (ENSO) is the main mode controlling the variability in the ocean-atmosphere system in the South Pacific. While the ENSO influence on rainfall regimes in the South Pacific is well documented, its role in driving spatiotemporal trends in fire activity in this region has not been rigorously investigated. This is particularly the case for the highly flammable and densely populated southeast Australian sector, where ENSO is a major control over climatic variability. Here we conduct the first region-wide analysis of how ENSO controls fire activity in southeast Australia. We identify a significant relationship between ENSO and both fire frequency and area burnt. Critically, wavelet analyses reveal that despite substantial temporal variability in the ENSO system, ENSO exerts a persistent and significant influence on southeast Australian fire activity. Our analysis has direct application for developing robust predictive capacity for the increasingly important efforts at fire management. Title: ENSO Controls Interannual Fire Activity in Southeast Australia Author: Mariani, Michela, Fletcher, Michael-Shawn, Holz, Andrés, Nyman, Petter Year: 2016 El Niño–Southern Oscillation (ENSO) is the main mode controlling the variability in the ocean-atmosphere system in the South Pacific. While the ENSO influence on rainfall regimes in the South Pacific is well documented, its role in driving spatiotemporal trends in fire activity in this region has not been rigorously investigated. This is particularly the case for the highly flammable and densely populated southeast Australian sector, where ENSO is a major control over climatic variability. Here we conduct the first region-wide analysis of how ENSO controls fire activity in southeast Australia. We identify a significant relationship between ENSO and both fire frequency and area burnt. Critically, wavelet analyses reveal that despite substantial temporal variability in the ENSO system, ENSO exerts a persistent and significant influence on southeast Australian fire activity. Our analysis has direct application for developing robust predictive capacity for the increasingly important efforts at fire management. Close

• 3. [Article] High-Performance Computing for Drought Prediction

  In recent decades, there has been considerable interest in using satellite soil moisture data to examine the global water-energy cycle and manage water resources. Current satellites are limited in their ...

  Citation × Citation Citation Abstract Copy Title: High-Performance Computing for Drought Prediction Author: Cooney, Henry Year: 2016 In recent decades, there has been considerable interest in using satellite soil moisture data to examine the global water-energy cycle and manage water resources. Current satellites are limited in their sensing depth, and can only directly measure top soil layers. Using a particle filter, this data may be fused with the output of a hydrologic simulation to improve simulation results, and characterize a hydrologic system at the watershed level. However, this approach increases computational requirements dramatically, and requires rethinking to accommodate data scaling and achieve good performance. We present a detailed performance study of several alternative implementations of the hybrid approach. We combined the Precipitation Runoff Modeling System (PRMS), a widely used hydrologic model published by the U.S. Geologic Survey, with satellite data. This problem is representative of many science efforts in that it incorporates software used across the scientific domain (PRMS) with novel functionality by integrating satellite data. Title: High-Performance Computing for Drought Prediction Author: Cooney, Henry Year: 2016 In recent decades, there has been considerable interest in using satellite soil moisture data to examine the global water-energy cycle and manage water resources. Current satellites are limited in their sensing depth, and can only directly measure top soil layers. Using a particle filter, this data may be fused with the output of a hydrologic simulation to improve simulation results, and characterize a hydrologic system at the watershed level. However, this approach increases computational requirements dramatically, and requires rethinking to accommodate data scaling and achieve good performance. We present a detailed performance study of several alternative implementations of the hybrid approach. We combined the Precipitation Runoff Modeling System (PRMS), a widely used hydrologic model published by the U.S. Geologic Survey, with satellite data. This problem is representative of many science efforts in that it incorporates software used across the scientific domain (PRMS) with novel functionality by integrating satellite data. Close

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

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

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

• 5. [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

• 6. [Article] A radar and synoptic study of rain at a point

  A radar echo-contour height measurement at different gain settings of the receiver, from RHI pictures shows that heavy rain occurs at the points above which steep echo-contour gradients appear. In this ...

  Citation × Citation Citation Abstract Copy Title: A radar and synoptic study of rain at a point Author: Sarmah, Suryya Kanta A radar echo-contour height measurement at different gain settings of the receiver, from RHI pictures shows that heavy rain occurs at the points above which steep echo-contour gradients appear. In this study, radar data came from the AN/CPS-9 radar located at McCulloch peak, about five miles from the Oregon State University campus. The data for rain intensity and drop-size distribution came from filter paper rain-drop recorders exposed by observers situated at various positions beneath the radar beam at different azimuth. The occurrence of heavy rain intensity at a point with the appearance of steep echo-contour gradient showed more consistency for convective and cold front showers than with warm front showers. In the case of convective showers it appears that strong echo-contour gradients lying near the freezing level do not necessarily associate with rain. The study of drop-size distribution shows that steep echo-contour gradients also occur with the expansion of the distribution pattern towards bigger drop sizes, thus indicating the presence of up-draft with steep echo-contour gradient. Title: A radar and synoptic study of rain at a point Author: Sarmah, Suryya Kanta A radar echo-contour height measurement at different gain settings of the receiver, from RHI pictures shows that heavy rain occurs at the points above which steep echo-contour gradients appear. In this study, radar data came from the AN/CPS-9 radar located at McCulloch peak, about five miles from the Oregon State University campus. The data for rain intensity and drop-size distribution came from filter paper rain-drop recorders exposed by observers situated at various positions beneath the radar beam at different azimuth. The occurrence of heavy rain intensity at a point with the appearance of steep echo-contour gradient showed more consistency for convective and cold front showers than with warm front showers. In the case of convective showers it appears that strong echo-contour gradients lying near the freezing level do not necessarily associate with rain. The study of drop-size distribution shows that steep echo-contour gradients also occur with the expansion of the distribution pattern towards bigger drop sizes, thus indicating the presence of up-draft with steep echo-contour gradient. Close

• 7. [Article] Some characteristics of time and space patterns of fall precipitation in northwest Oregon

  Citation × Citation Citation Abstract Copy Title: Some characteristics of time and space patterns of fall precipitation in northwest Oregon Author: Velthoen, John Richard Title: Some characteristics of time and space patterns of fall precipitation in northwest Oregon Author: Velthoen, John Richard Close

• 8. [Article] Mountain waves with neutral thermodynamic stability

  Citation × Citation Citation Abstract Copy Title: Mountain waves with neutral thermodynamic stability Author: Pike, Julian McKendree Title: Mountain waves with neutral thermodynamic stability Author: Pike, Julian McKendree Close

• 9. [Article] Biases in droplet radii and optical depths of marine stratocumulus retrieved from MODIS imagery

  The 2007 Intergovernmental Panel on Climate Change assessment established that the effect of clouds on climate contributes the largest uncertainty in predicting the future climate. Satellite observations ...

  Citation × Citation Citation Abstract Copy Title: Biases in droplet radii and optical depths of marine stratocumulus retrieved from MODIS imagery Author: Boeke, Robyn C. The 2007 Intergovernmental Panel on Climate Change assessment established that the effect of clouds on climate contributes the largest uncertainty in predicting the future climate. Satellite observations provide an opportunity for learning about the behavior of clouds. This thesis seeks to assess the accuracy of cloud properties retrieved from multispectral satellite imagery and test the usefulness of satellite data in verifying conclusions based on aircraft observations that marine stratus appear to be formed through the nearly adiabatic ascent of moist air. Retrievals of cloud optical depth, a measure of cloud thickness, using 0.64-μm reflectances and droplet radii using separately 1.6, 2.1, and 3.7-μm reflectances were obtained with the MODerateresolution Imaging Spectroradiometer (MODIS). Owing to different amounts of absorption by liquid water in the near infrared, with the least at 1.6 μm and the most at 3.7 μm, the growth of droplet radius with cloud thickness should result in the largest droplet radii retrieved using the 3.7-μm reflectances and the smallest using 1.6-μm reflectances. Droplet radii retrieved using the 2.1-μm reflectances, however, are often the largest, and those retrieved using 3.7-μm reflectances are often the smallest. In addition aircraft observations indicate that the relationships between droplet radius, re, and optical depth, t, d ln r / d lnt e ,should be approximately equal to 0.2 for marine stratocumulus. While satellite observations in optically thick, overcast regions yielded d ln re/d ln t consistent with this result, retrievals for regions with broken clouds often yielded d ln r / d lnt e substantially smaller than 0.2. Clouds often exhibit large horizontal and vertical variability. In this thesis a simple radiative transfer model was used to predict reflectances at visible and near infrared wavelengths for clouds formed through the adiabatic ascent of moist air, and then a retrieval scheme based on vertically uniform clouds was used to determine if the departures from the behavior expected for adiabatic clouds might be caused by the assumption of spatial uniformity used in the retrievals. The simulations indicated that at all cloud thicknesses the progression of droplet size using 1.6, 2.1, and 3.7-μm reflectances followed that suggested by the absorptive properties of liquid water. The simulation also indicated, however, contrary to the observations, that when the clouds were optically thin, d ln r / d lnt e should be greater than 0.2, the value expected for the adiabatic ascent of moist air. The simulation was adapted to account for the effects of horizontal variations within clouds. Each 1-km pixel was given a subpixel distribution of optical depths based on a gamma distribution with mean taken from MODIS pixel-scale optical depths and variance given by Kato et al. (2006), obtained from Large Eddy Simulations of marine stratocumulus. Each subpixel was allowed to develop vertically following the adiabatic ascent of moist air. The average of the reflectances for the subpixels was used to retrieve the cloud properties for the pixels, and these properties were compared with the average properties of the subpixels. The retrievals obtained using 1.6-μm reflectances were most strongly affected by the addition of subpixel variations in optical depth and droplet radius. Mean droplet radius retrieved in the simulation was largest when using 1.6-μm reflectances, followed by that retrieved using 2.1 and 3.7-μm reflectances. The simulation of large droplet radii at the shorter wavelengths indicated that the large droplets observed in MODIS may result from horizontal variations within the 1-km MODIS pixel. The values of d ln r / d lnt e calculated for horizontally heterogeneous clouds were close to 0.2, but showed variations that extend both above and below this value, consistent with the MODIS observations. To illustrate the findings based on the simulations, visible optical depth and droplet radius were retrieved for MODIS 500-m pixels overcast by marine stratocumulus. The 500-m pixels were used to represent the subpixel variability within 2-km pixels constructed from the 500-m pixels. Differences between cloud properties retrieved using average radiances and averages of the subpixel properties were compared for overcast and broken-cloud regions using both MODIS and the Partly Cloudy Pixel Retrieval (PCPR) schemes for identifying the overcast 2-km pixels. In the regions overcast by optically thick marine stratocumulus, both methods of identifying overcast pixels led to small biases in the retrieved droplet radii and optical depths. Values of d ln r / d lnt e obtained in the overcast regions using the PCPR identifications were closer to the value of 0.2 expected for adiabatic clouds than those obtained using MODIS identifications. Additionally, values of d ln r / d lnt e calculated using the 500-m overcast pixels yielded better results than those calculated using the 2-km pixels. In regions containing broken clouds, the PCPR identification provided a smaller bias than the MODIS identification, however both methods showed greater biases than those calculated for regions overcast by optically thick marine stratocumulus. Values of d ln r / d lnt e for the regions containing broken clouds showed a positive value when using the PCPR scheme to identify overcast pixels, and a negative value when using the MODIS cloud mask to identify overcast pixels. Consistent with the results from the overcast regions, the d ln r / d lnt e obtained for the 500-m overcast pixels were in closer conformity with adiabatic clouds than the values obtained for the 2-km pixels using both the MODIS and PCPR identifications. Title: Biases in droplet radii and optical depths of marine stratocumulus retrieved from MODIS imagery Author: Boeke, Robyn C. The 2007 Intergovernmental Panel on Climate Change assessment established that the effect of clouds on climate contributes the largest uncertainty in predicting the future climate. Satellite observations provide an opportunity for learning about the behavior of clouds. This thesis seeks to assess the accuracy of cloud properties retrieved from multispectral satellite imagery and test the usefulness of satellite data in verifying conclusions based on aircraft observations that marine stratus appear to be formed through the nearly adiabatic ascent of moist air. Retrievals of cloud optical depth, a measure of cloud thickness, using 0.64-μm reflectances and droplet radii using separately 1.6, 2.1, and 3.7-μm reflectances were obtained with the MODerateresolution Imaging Spectroradiometer (MODIS). Owing to different amounts of absorption by liquid water in the near infrared, with the least at 1.6 μm and the most at 3.7 μm, the growth of droplet radius with cloud thickness should result in the largest droplet radii retrieved using the 3.7-μm reflectances and the smallest using 1.6-μm reflectances. Droplet radii retrieved using the 2.1-μm reflectances, however, are often the largest, and those retrieved using 3.7-μm reflectances are often the smallest. In addition aircraft observations indicate that the relationships between droplet radius, re, and optical depth, t, d ln r / d lnt e ,should be approximately equal to 0.2 for marine stratocumulus. While satellite observations in optically thick, overcast regions yielded d ln re/d ln t consistent with this result, retrievals for regions with broken clouds often yielded d ln r / d lnt e substantially smaller than 0.2. Clouds often exhibit large horizontal and vertical variability. In this thesis a simple radiative transfer model was used to predict reflectances at visible and near infrared wavelengths for clouds formed through the adiabatic ascent of moist air, and then a retrieval scheme based on vertically uniform clouds was used to determine if the departures from the behavior expected for adiabatic clouds might be caused by the assumption of spatial uniformity used in the retrievals. The simulations indicated that at all cloud thicknesses the progression of droplet size using 1.6, 2.1, and 3.7-μm reflectances followed that suggested by the absorptive properties of liquid water. The simulation also indicated, however, contrary to the observations, that when the clouds were optically thin, d ln r / d lnt e should be greater than 0.2, the value expected for the adiabatic ascent of moist air. The simulation was adapted to account for the effects of horizontal variations within clouds. Each 1-km pixel was given a subpixel distribution of optical depths based on a gamma distribution with mean taken from MODIS pixel-scale optical depths and variance given by Kato et al. (2006), obtained from Large Eddy Simulations of marine stratocumulus. Each subpixel was allowed to develop vertically following the adiabatic ascent of moist air. The average of the reflectances for the subpixels was used to retrieve the cloud properties for the pixels, and these properties were compared with the average properties of the subpixels. The retrievals obtained using 1.6-μm reflectances were most strongly affected by the addition of subpixel variations in optical depth and droplet radius. Mean droplet radius retrieved in the simulation was largest when using 1.6-μm reflectances, followed by that retrieved using 2.1 and 3.7-μm reflectances. The simulation of large droplet radii at the shorter wavelengths indicated that the large droplets observed in MODIS may result from horizontal variations within the 1-km MODIS pixel. The values of d ln r / d lnt e calculated for horizontally heterogeneous clouds were close to 0.2, but showed variations that extend both above and below this value, consistent with the MODIS observations. To illustrate the findings based on the simulations, visible optical depth and droplet radius were retrieved for MODIS 500-m pixels overcast by marine stratocumulus. The 500-m pixels were used to represent the subpixel variability within 2-km pixels constructed from the 500-m pixels. Differences between cloud properties retrieved using average radiances and averages of the subpixel properties were compared for overcast and broken-cloud regions using both MODIS and the Partly Cloudy Pixel Retrieval (PCPR) schemes for identifying the overcast 2-km pixels. In the regions overcast by optically thick marine stratocumulus, both methods of identifying overcast pixels led to small biases in the retrieved droplet radii and optical depths. Values of d ln r / d lnt e obtained in the overcast regions using the PCPR identifications were closer to the value of 0.2 expected for adiabatic clouds than those obtained using MODIS identifications. Additionally, values of d ln r / d lnt e calculated using the 500-m overcast pixels yielded better results than those calculated using the 2-km pixels. In regions containing broken clouds, the PCPR identification provided a smaller bias than the MODIS identification, however both methods showed greater biases than those calculated for regions overcast by optically thick marine stratocumulus. Values of d ln r / d lnt e for the regions containing broken clouds showed a positive value when using the PCPR scheme to identify overcast pixels, and a negative value when using the MODIS cloud mask to identify overcast pixels. Consistent with the results from the overcast regions, the d ln r / d lnt e obtained for the 500-m overcast pixels were in closer conformity with adiabatic clouds than the values obtained for the 2-km pixels using both the MODIS and PCPR identifications. Close

• 10. [Article] Use of a rainfall-runoff model for simulating effects of forest management on streamflow in the east fork Lobster Creek Basin, Oregon

  The report describes the results of model calibration and validation, and evaluates the extent to which runoff response to timber harvesting and increased road densities in East Fork Lobster Creek Basin ...

  Citation × Citation Citation Abstract Copy Title: Use of a rainfall-runoff model for simulating effects of forest management on streamflow in the east fork Lobster Creek Basin, Oregon Author: Risley, John C., United States.|bBureau of Land Management., Geological Survey (U.S.), Nakama, Lenore Y. The report describes the results of model calibration and validation, and evaluates the extent to which runoff response to timber harvesting and increased road densities in East Fork Lobster Creek Basin can be simulated, using Precipitation-Runoff Modeling System (PRMS), a deterministic, destributed-parameter-modeling system. Title: Use of a rainfall-runoff model for simulating effects of forest management on streamflow in the east fork Lobster Creek Basin, Oregon Author: Risley, John C., United States.|bBureau of Land Management., Geological Survey (U.S.), Nakama, Lenore Y. The report describes the results of model calibration and validation, and evaluates the extent to which runoff response to timber harvesting and increased road densities in East Fork Lobster Creek Basin can be simulated, using Precipitation-Runoff Modeling System (PRMS), a deterministic, destributed-parameter-modeling system. Close