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Abstract
The diurnal cycle in streamflow constitutes a significant part of the variability in many rivers in the western United States and can be used to understand some of the dominant processes affecting the water balance of a given river basin. Rivers in which water is added diurnally, as in snowmelt, and rivers in which water is removed diurnally, as in evapotranspiration and infiltration, exhibit substantial differences in the timing, relative magnitude, and shape of their diurnal flow variations. Snowmelt-dominated rivers achieve their highest sustained flow and largest diurnal fluctuations during the spring melt season. These fluctuations are characterized by sharp rises and gradual declines in discharge each day. In large snowmelt-dominated basins, at the end of the melt season, the hour of maximum discharge shifts to later in the day as the snow line retreats to higher elevations. Many evapotranspiration/infiltration-dominated rivers in the western states achieve their highest sustained flows during the winter rainy season but exhibit their strongest diurnal cycles during summer months, when discharge is low, and the diurnal fluctuations compose a large percentage of the total flow. In contrast to snowmelt-dominated rivers, the maximum discharge in evapotranspiration/infiltration-dominated rivers occurs consistently in the morning throughout the summer. In these rivers, diurnal changes are characterized by a gradual rise and sharp decline each day.
Abstract
The diurnal cycle in streamflow constitutes a significant part of the variability in many rivers in the western United States and can be used to understand some of the dominant processes affecting the water balance of a given river basin. Rivers in which water is added diurnally, as in snowmelt, and rivers in which water is removed diurnally, as in evapotranspiration and infiltration, exhibit substantial differences in the timing, relative magnitude, and shape of their diurnal flow variations. Snowmelt-dominated rivers achieve their highest sustained flow and largest diurnal fluctuations during the spring melt season. These fluctuations are characterized by sharp rises and gradual declines in discharge each day. In large snowmelt-dominated basins, at the end of the melt season, the hour of maximum discharge shifts to later in the day as the snow line retreats to higher elevations. Many evapotranspiration/infiltration-dominated rivers in the western states achieve their highest sustained flows during the winter rainy season but exhibit their strongest diurnal cycles during summer months, when discharge is low, and the diurnal fluctuations compose a large percentage of the total flow. In contrast to snowmelt-dominated rivers, the maximum discharge in evapotranspiration/infiltration-dominated rivers occurs consistently in the morning throughout the summer. In these rivers, diurnal changes are characterized by a gradual rise and sharp decline each day.
Abstract
Historic streamflow records show that the onset of snowfed streamflow in the western United States has shifted earlier over the past 50 yr, and March 2004 was one of the earliest onsets on record. Record high temperatures occurred throughout the western United States during the second week of March, and U.S. Geological Survey (USGS) stream gauges throughout the area recorded early onsets of streamflow at this time. However, a set of nested subbasins in Yosemite National Park, California, told a more complicated story. In spite of high air temperatures, many streams draining high-elevation basins did not start flowing until later in the spring. Temperatures during early March 2004 were as high as temperatures in late March 2002, when streams at all of the monitored Yosemite basins began flowing at the same time. However, the March 2004 onset occurred before the spring equinox, when the sun was lower in the sky. Thus, shading and solar radiation differences played a much more important role in 2004, leading to differences in streamflow timing. These results suggest that as temperatures warm and spring melt shifts earlier in the season, topographic effects will play an even more important role than at present in determining snowmelt timing.
Abstract
Historic streamflow records show that the onset of snowfed streamflow in the western United States has shifted earlier over the past 50 yr, and March 2004 was one of the earliest onsets on record. Record high temperatures occurred throughout the western United States during the second week of March, and U.S. Geological Survey (USGS) stream gauges throughout the area recorded early onsets of streamflow at this time. However, a set of nested subbasins in Yosemite National Park, California, told a more complicated story. In spite of high air temperatures, many streams draining high-elevation basins did not start flowing until later in the spring. Temperatures during early March 2004 were as high as temperatures in late March 2002, when streams at all of the monitored Yosemite basins began flowing at the same time. However, the March 2004 onset occurred before the spring equinox, when the sun was lower in the sky. Thus, shading and solar radiation differences played a much more important role in 2004, leading to differences in streamflow timing. These results suggest that as temperatures warm and spring melt shifts earlier in the season, topographic effects will play an even more important role than at present in determining snowmelt timing.
Abstract
Short-term climate and weather systems can have a strong influence on mountain snowmelt, sometimes overwhelming the effects of elevation and aspect. Although most years exhibit a spring onset that starts first at lowest and moves to highest elevations, in spring 2002, flow in a variety of streams within the Tuolumne and Merced River basins of the southern Sierra Nevada all rose synchronously on 29 March. Flow in streams draining small high-altitude glacial subcatchments rose at the same time as that draining much larger basins gauged at lower altitudes, and streams from north- and south-facing cirques rose and fell together. Historical analysis demonstrates that 2002 was one among only 8 yr with such synchronous flow onsets during the past 87 yr, recognized by having simultaneous onsets of snowmelt at over 70% of snow pillow sites, having discharge in over 70% of monitored streams increase simultaneously, and having temperatures increase over 12°C within a 5-day period. Synchronous springs tend to begin with a low pressure trough over California during late winter, followed by the onset of a strong ridge and unusually warm temperatures. Synchronous springs are characterized by warmer than average winters and cooler than average March temperatures in California. In the most elevation-dependent, nonsynchronous years, periods of little or no storm activity, with warmer than average March temperatures, precede the onset of spring snowmelt, allowing elevation and aspect to influence snowmelt as spring arrives gradually.
Abstract
Short-term climate and weather systems can have a strong influence on mountain snowmelt, sometimes overwhelming the effects of elevation and aspect. Although most years exhibit a spring onset that starts first at lowest and moves to highest elevations, in spring 2002, flow in a variety of streams within the Tuolumne and Merced River basins of the southern Sierra Nevada all rose synchronously on 29 March. Flow in streams draining small high-altitude glacial subcatchments rose at the same time as that draining much larger basins gauged at lower altitudes, and streams from north- and south-facing cirques rose and fell together. Historical analysis demonstrates that 2002 was one among only 8 yr with such synchronous flow onsets during the past 87 yr, recognized by having simultaneous onsets of snowmelt at over 70% of snow pillow sites, having discharge in over 70% of monitored streams increase simultaneously, and having temperatures increase over 12°C within a 5-day period. Synchronous springs tend to begin with a low pressure trough over California during late winter, followed by the onset of a strong ridge and unusually warm temperatures. Synchronous springs are characterized by warmer than average winters and cooler than average March temperatures in California. In the most elevation-dependent, nonsynchronous years, periods of little or no storm activity, with warmer than average March temperatures, precede the onset of spring snowmelt, allowing elevation and aspect to influence snowmelt as spring arrives gradually.
Abstract
Estimates of precipitation from the Weather Research and Forecasting (WRF) Model and the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) are widely used in complex terrain to obtain spatially distributed precipitation data. The authors evaluated both WRF (4/3 km) and PRISM’s (800-m annual climatology) ability to estimate frozen precipitation using the hydrologic model Structure for Unifying Multiple Modeling Alternatives (SUMMA) and a unique set of spatiotemporal snow depth and snow water equivalent (SWE) observations collected for the Olympic Mountain Experiment (OLYMPEX) ground validation campaign during water year 2016. When SUMMA was forced with WRF precipitation and used a calibrated, wet-bulb-temperature-based method for partitioning rain versus snow, its estimation of near-peak SWE was biased low by 21% on average. However, when SUMMA was allowed to partition WRF total precipitation into rain and snow based on output from WRF’s microphysical scheme (WRFMPP), simulations of snow depth and SWE were near equal to or better than simulations that used PRISM-derived precipitation with the calibrated partitioning method. Over all sites, WRFMPP and simulations that used PRISM-derived precipitation had relatively unbiased estimates of near-peak SWE, but both simulated absolute errors in near-peak SWE of 30%–60% at a few locations. Since, on average, WRFMPP had similar errors to PRISM, WRFMPP suggested a promising path forward in hydrology, as it was independent of gauge data and did not require SWE observations for calibration. Furthermore, in similar maritime environments, hydrologic modelers should pay close attention to decisions regarding rain-versus-snow partitioning, wind speed, and incoming longwave radiation.
Abstract
Estimates of precipitation from the Weather Research and Forecasting (WRF) Model and the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) are widely used in complex terrain to obtain spatially distributed precipitation data. The authors evaluated both WRF (4/3 km) and PRISM’s (800-m annual climatology) ability to estimate frozen precipitation using the hydrologic model Structure for Unifying Multiple Modeling Alternatives (SUMMA) and a unique set of spatiotemporal snow depth and snow water equivalent (SWE) observations collected for the Olympic Mountain Experiment (OLYMPEX) ground validation campaign during water year 2016. When SUMMA was forced with WRF precipitation and used a calibrated, wet-bulb-temperature-based method for partitioning rain versus snow, its estimation of near-peak SWE was biased low by 21% on average. However, when SUMMA was allowed to partition WRF total precipitation into rain and snow based on output from WRF’s microphysical scheme (WRFMPP), simulations of snow depth and SWE were near equal to or better than simulations that used PRISM-derived precipitation with the calibrated partitioning method. Over all sites, WRFMPP and simulations that used PRISM-derived precipitation had relatively unbiased estimates of near-peak SWE, but both simulated absolute errors in near-peak SWE of 30%–60% at a few locations. Since, on average, WRFMPP had similar errors to PRISM, WRFMPP suggested a promising path forward in hydrology, as it was independent of gauge data and did not require SWE observations for calibration. Furthermore, in similar maritime environments, hydrologic modelers should pay close attention to decisions regarding rain-versus-snow partitioning, wind speed, and incoming longwave radiation.
Abstract
Physically based models facilitate understanding of seasonal snow processes but require meteorological forcing data beyond air temperature and precipitation (e.g., wind, humidity, shortwave radiation, and longwave radiation) that are typically unavailable at automatic weather stations (AWSs) and instead are often represented with empirical estimates. Research is needed to understand which forcings (after temperature and precipitation) would most benefit snow modeling through expanded observation or improved estimation techniques. Here, the impact of forcing data availability on snow model output is assessed with data-withholding experiments using 3-yr datasets at well-instrumented sites in four climates. The interplay between forcing availability and model complexity is examined among the Utah Energy Balance (UEB), the Distributed Hydrology Soil Vegetation Model (DHSVM) snow submodel, and the snow thermal model (SNTHERM). Sixty-four unique forcing scenarios were evaluated, with different assumptions regarding availability of hourly meteorological observations at each site. Modeled snow water equivalent (SWE) and snow surface temperature T surf diverged most often because of availability of longwave radiation, which is the least frequently measured forcing in cold regions in the western United States. Availability of longwave radiation (i.e., observed vs empirically estimated) caused maximum SWE differences up to 234 mm (57% of peak SWE), mean differences up to 6.2°C in T surf, and up to 32 days difference in snow disappearance timing. From a model data perspective, more common observations of longwave radiation at AWSs could benefit snow model development and applications, but other aspects (e.g., costs, site access, and maintenance) need consideration.
Abstract
Physically based models facilitate understanding of seasonal snow processes but require meteorological forcing data beyond air temperature and precipitation (e.g., wind, humidity, shortwave radiation, and longwave radiation) that are typically unavailable at automatic weather stations (AWSs) and instead are often represented with empirical estimates. Research is needed to understand which forcings (after temperature and precipitation) would most benefit snow modeling through expanded observation or improved estimation techniques. Here, the impact of forcing data availability on snow model output is assessed with data-withholding experiments using 3-yr datasets at well-instrumented sites in four climates. The interplay between forcing availability and model complexity is examined among the Utah Energy Balance (UEB), the Distributed Hydrology Soil Vegetation Model (DHSVM) snow submodel, and the snow thermal model (SNTHERM). Sixty-four unique forcing scenarios were evaluated, with different assumptions regarding availability of hourly meteorological observations at each site. Modeled snow water equivalent (SWE) and snow surface temperature T surf diverged most often because of availability of longwave radiation, which is the least frequently measured forcing in cold regions in the western United States. Availability of longwave radiation (i.e., observed vs empirically estimated) caused maximum SWE differences up to 234 mm (57% of peak SWE), mean differences up to 6.2°C in T surf, and up to 32 days difference in snow disappearance timing. From a model data perspective, more common observations of longwave radiation at AWSs could benefit snow model development and applications, but other aspects (e.g., costs, site access, and maintenance) need consideration.
Abstract
Near-surface air temperature observations often have periods of missing data, and many applications using these datasets require filling in all missing periods. Multiple methods are available to fill missing data, but the comparative accuracy of these approaches has not been assessed. In this comparative study, five techniques were used to fill in missing temperature data: spatiotemporal correlations in the form of empirical orthogonal functions (EOFs), time series diurnal interpolation, and three variations of lapse rate–based filling. The method validation used sets of hourly surface temperature observations in complex terrain from five regions. The most accurate method for filling missing data depended on the number of available stations and the number of hours of missing data. Spatiotemporal correlations using EOF reconstruction were most accurate provided that at least 16 stations were available. Temporal interpolation was the most accurate method when only one or two stations were available or for 1-h gaps. Lapse rate–based filling was most accurate for intermediate numbers of stations. The accuracy of the lapse rate and EOF methods was found to be sensitive to the vertical separation of stations and the degree of correlation between them, which also explained some of the regional differences in performance. Horizontal distance was less significantly correlated with method performance. From these findings, guidelines are presented for choosing a filling method based on the duration of the missing data and the number of stations.
Abstract
Near-surface air temperature observations often have periods of missing data, and many applications using these datasets require filling in all missing periods. Multiple methods are available to fill missing data, but the comparative accuracy of these approaches has not been assessed. In this comparative study, five techniques were used to fill in missing temperature data: spatiotemporal correlations in the form of empirical orthogonal functions (EOFs), time series diurnal interpolation, and three variations of lapse rate–based filling. The method validation used sets of hourly surface temperature observations in complex terrain from five regions. The most accurate method for filling missing data depended on the number of available stations and the number of hours of missing data. Spatiotemporal correlations using EOF reconstruction were most accurate provided that at least 16 stations were available. Temporal interpolation was the most accurate method when only one or two stations were available or for 1-h gaps. Lapse rate–based filling was most accurate for intermediate numbers of stations. The accuracy of the lapse rate and EOF methods was found to be sensitive to the vertical separation of stations and the degree of correlation between them, which also explained some of the regional differences in performance. Horizontal distance was less significantly correlated with method performance. From these findings, guidelines are presented for choosing a filling method based on the duration of the missing data and the number of stations.
Abstract
The pre-cold-frontal low-level jet within oceanic extratropical cyclones represents the lower-tropospheric component of a deeper corridor of concentrated water vapor transport in the cyclone warm sector. These corridors are referred to as atmospheric rivers (ARs) because they are narrow relative to their length scale and are responsible for most of the poleward water vapor transport at midlatitudes. This paper investigates landfalling ARs along adjacent north- and south-coast regions of western North America. Special Sensor Microwave Imager (SSM/I) satellite observations of long, narrow plumes of enhanced integrated water vapor (IWV) were used to detect ARs just offshore over the eastern Pacific from 1997 to 2005. The north coast experienced 301 AR days, while the south coast had only 115. Most ARs occurred during the warm season in the north and cool season in the south, despite the fact that the cool season is climatologically wettest for both regions. Composite SSM/I IWV analyses showed landfalling wintertime ARs extending northeastward from the tropical eastern Pacific, whereas the summertime composites were zonally oriented and, thus, did not originate from this region of the tropics. Companion SSM/I composites of daily rainfall showed significant orographic enhancement during the landfall of winter (but not summer) ARs.
The NCEP–NCAR global reanalysis dataset and regional precipitation networks were used to assess composite synoptic characteristics and overland impacts of landfalling ARs. The ARs possess strong vertically integrated horizontal water vapor fluxes that, on average, impinge on the West Coast in the pre-cold-frontal environment in winter and post-cold-frontal environment in summer. Even though the IWV in the ARs is greater in summer, the vapor flux is stronger in winter due to much stronger flows associated with more intense storms. The landfall of ARs in winter and north-coast summer coincides with anomalous warmth, a trough offshore, and ridging over the Intermountain West, whereas the south-coast summer ARs coincide with relatively cold conditions and a near-coast trough. ARs have a much more profound impact on near-coast precipitation in winter than summer, because the terrain-normal vapor flux is stronger and the air more nearly saturated in winter. During winter, ARs produce roughly twice as much precipitation as all storms. In addition, wintertime ARs with the largest SSM/I IWV are tied to more intense storms with stronger flows and vapor fluxes, and more precipitation. ARs generally increase snow water equivalent (SWE) in autumn/winter and decrease SWE in spring. On average, wintertime SWE exhibits normal gains during north-coast AR storms and above-normal gains during the south-coast AR storms. The north-coast sites are mostly lower in altitude, where warmer-than-normal conditions more frequently yield rain. During those events when heavy rain from a warm AR storm falls on a preexisting snowpack, flooding is more likely to occur.
Abstract
The pre-cold-frontal low-level jet within oceanic extratropical cyclones represents the lower-tropospheric component of a deeper corridor of concentrated water vapor transport in the cyclone warm sector. These corridors are referred to as atmospheric rivers (ARs) because they are narrow relative to their length scale and are responsible for most of the poleward water vapor transport at midlatitudes. This paper investigates landfalling ARs along adjacent north- and south-coast regions of western North America. Special Sensor Microwave Imager (SSM/I) satellite observations of long, narrow plumes of enhanced integrated water vapor (IWV) were used to detect ARs just offshore over the eastern Pacific from 1997 to 2005. The north coast experienced 301 AR days, while the south coast had only 115. Most ARs occurred during the warm season in the north and cool season in the south, despite the fact that the cool season is climatologically wettest for both regions. Composite SSM/I IWV analyses showed landfalling wintertime ARs extending northeastward from the tropical eastern Pacific, whereas the summertime composites were zonally oriented and, thus, did not originate from this region of the tropics. Companion SSM/I composites of daily rainfall showed significant orographic enhancement during the landfall of winter (but not summer) ARs.
The NCEP–NCAR global reanalysis dataset and regional precipitation networks were used to assess composite synoptic characteristics and overland impacts of landfalling ARs. The ARs possess strong vertically integrated horizontal water vapor fluxes that, on average, impinge on the West Coast in the pre-cold-frontal environment in winter and post-cold-frontal environment in summer. Even though the IWV in the ARs is greater in summer, the vapor flux is stronger in winter due to much stronger flows associated with more intense storms. The landfall of ARs in winter and north-coast summer coincides with anomalous warmth, a trough offshore, and ridging over the Intermountain West, whereas the south-coast summer ARs coincide with relatively cold conditions and a near-coast trough. ARs have a much more profound impact on near-coast precipitation in winter than summer, because the terrain-normal vapor flux is stronger and the air more nearly saturated in winter. During winter, ARs produce roughly twice as much precipitation as all storms. In addition, wintertime ARs with the largest SSM/I IWV are tied to more intense storms with stronger flows and vapor fluxes, and more precipitation. ARs generally increase snow water equivalent (SWE) in autumn/winter and decrease SWE in spring. On average, wintertime SWE exhibits normal gains during north-coast AR storms and above-normal gains during the south-coast AR storms. The north-coast sites are mostly lower in altitude, where warmer-than-normal conditions more frequently yield rain. During those events when heavy rain from a warm AR storm falls on a preexisting snowpack, flooding is more likely to occur.
Abstract
The benefit of using solar and longwave surface irradiance data from NASA’s Clouds and the Earth’s Radiant Energy System (CERES) synoptic (SYN) satellite product in simulations of snowmelt has been examined. The accuracy of the SYN downwelling solar and longwave irradiances was first assessed by comparison to measurements at NOAA’s Surface Radiation Network (SURFRAD) reference stations and to remote mountain observations. Typical shortwave (longwave) biases had magnitudes less than 30 (10) W m−2, with most standard deviations below 140 (30) W m−2. The performance of a range of snow models of varying complexity when using SYN irradiances as forcing data was then evaluated. Simulated snow water equivalent and runoff from cases using SYN data fell in the range of those from simulations forced with irradiances from well-maintained surface observation sites as well as empirical methods that have been shown to perform well in mountainous terrain. The SYN irradiances are therefore judged to be suitable for use in snowmelt modeling. It is also noted that the SYN upwelling shortwave irradiances, and hence albedos derived from them, are frequently not representative of individual monitoring stations because of the high spatial variability of snow cover and other surface properties in mountainous regions. In addition, adjusting the SYN downwelling longwave irradiances to reflect the exact elevation of the point of interest relative to the mean altitude of the satellite grid box is recommended.
Abstract
The benefit of using solar and longwave surface irradiance data from NASA’s Clouds and the Earth’s Radiant Energy System (CERES) synoptic (SYN) satellite product in simulations of snowmelt has been examined. The accuracy of the SYN downwelling solar and longwave irradiances was first assessed by comparison to measurements at NOAA’s Surface Radiation Network (SURFRAD) reference stations and to remote mountain observations. Typical shortwave (longwave) biases had magnitudes less than 30 (10) W m−2, with most standard deviations below 140 (30) W m−2. The performance of a range of snow models of varying complexity when using SYN irradiances as forcing data was then evaluated. Simulated snow water equivalent and runoff from cases using SYN data fell in the range of those from simulations forced with irradiances from well-maintained surface observation sites as well as empirical methods that have been shown to perform well in mountainous terrain. The SYN irradiances are therefore judged to be suitable for use in snowmelt modeling. It is also noted that the SYN upwelling shortwave irradiances, and hence albedos derived from them, are frequently not representative of individual monitoring stations because of the high spatial variability of snow cover and other surface properties in mountainous regions. In addition, adjusting the SYN downwelling longwave irradiances to reflect the exact elevation of the point of interest relative to the mean altitude of the satellite grid box is recommended.
Abstract
The rate of precipitation increase with elevation, termed the orographic precipitation gradient (OPG), is critically important for hydrologic forecasting in mountain basins that receive both rain and snow. Here, the following are examined to see how well they are able to predict the OPG and how it changes between storms and years: 1) a linear model of orographic precipitation forced by upstream radiosonde data, 2) monthly Parameter-Elevation Regressions on Independent Slopes Model (PRISM) precipitation data, and 3) seven years of hourly wind profiler data used to identify characteristics of the Sierra barrier jet (SBJ). These are compared against 124 daily resolution (four of which also had quality controlled, hourly resolution) precipitation gauge records in the northern Sierra Nevada. All methods represent the OPG well in the mean and during a year when less than 30% of the precipitation occurred on days with SBJs. However, the linear model and PRISM do not adequately capture annual variations in the OPG during years when more than 70% of the precipitation occurred on days with SBJs. Throughout all of the years, wind profiler data indicating the height of the SBJ provided additional, and necessary, information. The OPG is negatively correlated with the height of the SBJ. The SBJ height is lower, and hence, the OPG greater when the westerly winds are stronger, with more vertical wind shear. These westerly storms result in greater increases of precipitation with elevation, which act to increase snow storage in most storms but also to increase storm runoff during warmer-than-average storms.
Abstract
The rate of precipitation increase with elevation, termed the orographic precipitation gradient (OPG), is critically important for hydrologic forecasting in mountain basins that receive both rain and snow. Here, the following are examined to see how well they are able to predict the OPG and how it changes between storms and years: 1) a linear model of orographic precipitation forced by upstream radiosonde data, 2) monthly Parameter-Elevation Regressions on Independent Slopes Model (PRISM) precipitation data, and 3) seven years of hourly wind profiler data used to identify characteristics of the Sierra barrier jet (SBJ). These are compared against 124 daily resolution (four of which also had quality controlled, hourly resolution) precipitation gauge records in the northern Sierra Nevada. All methods represent the OPG well in the mean and during a year when less than 30% of the precipitation occurred on days with SBJs. However, the linear model and PRISM do not adequately capture annual variations in the OPG during years when more than 70% of the precipitation occurred on days with SBJs. Throughout all of the years, wind profiler data indicating the height of the SBJ provided additional, and necessary, information. The OPG is negatively correlated with the height of the SBJ. The SBJ height is lower, and hence, the OPG greater when the westerly winds are stronger, with more vertical wind shear. These westerly storms result in greater increases of precipitation with elevation, which act to increase snow storage in most storms but also to increase storm runoff during warmer-than-average storms.
Abstract
To provide ground validation data for satellite precipitation products derived from the Global Precipitation Measurement (GPM) mission, such as IMERG, in cold seasons and where orographic factors exert strong controls on precipitation, the Olympic Mountain Experiment (OLYMPEX) was conducted during winter 2015/16. By utilizing multiple observational resources from OLYMPEX, estimates of daily and finer-scale precipitation are constructed at 1/32° spatial resolution over the OLYMPEX domain. The estimates are based on NOAA WSR-88D and gauge estimates as incorporated in NOAA’s National Severe Storms Laboratory (NSSL) Q3GC product, augmented with an additional 120 gauges available during OLYMPEX. Few stations are located in the interior of the Olympic Peninsula at elevations higher than about 500 m, and in this part of the domain the Variable Infiltration Capacity (VIC) hydrology model is used to invert the snow water equivalent (SWE) estimates, derived from two NASA JPL Airborne Snow Observatory (ASO) snow depth maps on 8–9 February 2016 and 29–30 March 2016, for precipitation through adjustment of the precipitation-weighting factor on a grid cell by grid cell basis. In comparison with this composite product, both IMERG (version 04A) and its Japanese counterpart GSMaP’s (version 04B) satellite-only products tend to underestimate winter precipitation, by 41% and 28%, respectively, over the entire domain from 1 October 2015 to 30 April 2016. The underestimation is more pronounced for the orographically enhanced mountainous interior of the OLYMPEX domain, by 57% and 48%, respectively. In contrast, IMERG and GSMaP storm interarrival time statistics are quite similar to those estimated from gridded observations.
Abstract
To provide ground validation data for satellite precipitation products derived from the Global Precipitation Measurement (GPM) mission, such as IMERG, in cold seasons and where orographic factors exert strong controls on precipitation, the Olympic Mountain Experiment (OLYMPEX) was conducted during winter 2015/16. By utilizing multiple observational resources from OLYMPEX, estimates of daily and finer-scale precipitation are constructed at 1/32° spatial resolution over the OLYMPEX domain. The estimates are based on NOAA WSR-88D and gauge estimates as incorporated in NOAA’s National Severe Storms Laboratory (NSSL) Q3GC product, augmented with an additional 120 gauges available during OLYMPEX. Few stations are located in the interior of the Olympic Peninsula at elevations higher than about 500 m, and in this part of the domain the Variable Infiltration Capacity (VIC) hydrology model is used to invert the snow water equivalent (SWE) estimates, derived from two NASA JPL Airborne Snow Observatory (ASO) snow depth maps on 8–9 February 2016 and 29–30 March 2016, for precipitation through adjustment of the precipitation-weighting factor on a grid cell by grid cell basis. In comparison with this composite product, both IMERG (version 04A) and its Japanese counterpart GSMaP’s (version 04B) satellite-only products tend to underestimate winter precipitation, by 41% and 28%, respectively, over the entire domain from 1 October 2015 to 30 April 2016. The underestimation is more pronounced for the orographically enhanced mountainous interior of the OLYMPEX domain, by 57% and 48%, respectively. In contrast, IMERG and GSMaP storm interarrival time statistics are quite similar to those estimated from gridded observations.
