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- Author or Editor: Nolan Doesken x
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New snow density distributions are presented for six measurement sites in the mountains of Colorado and Wyoming. Densities were computed from daily measurements of new snow depth and water equivalent from snow board cores. All data were measured once daily in wind-protected forest sites. Observed densities of freshly fallen snow ranged from 10 to 257 kg m−3. Average densities at each site based on four year's of daily observations ranged from 72 to 103 kgm−3. Seventy-two percent of all daily densities fell between 50 and 100 kg m−3. Approximately 5% of all daily snows had densities below 40 kg m−3. The highest frequency of low densities occurred at Steamboat Springs and Dry Lake. The relationship between air temperature and new snow density exhibited a decline of density with temperature with a correlation coefficient of 0.52. No obvious reversal toward higher densities occurred at cold temperatures, as some previous studies have reported. No clear relationship was found between snow density and the depth of new snowfalls. Correlations of daily densities between measurement sites decreased rapidly with increasing distance between sites. New snow densities are strongly influenced by orography, which contributes to density differences over short distances.
New snow density distributions are presented for six measurement sites in the mountains of Colorado and Wyoming. Densities were computed from daily measurements of new snow depth and water equivalent from snow board cores. All data were measured once daily in wind-protected forest sites. Observed densities of freshly fallen snow ranged from 10 to 257 kg m−3. Average densities at each site based on four year's of daily observations ranged from 72 to 103 kgm−3. Seventy-two percent of all daily densities fell between 50 and 100 kg m−3. Approximately 5% of all daily snows had densities below 40 kg m−3. The highest frequency of low densities occurred at Steamboat Springs and Dry Lake. The relationship between air temperature and new snow density exhibited a decline of density with temperature with a correlation coefficient of 0.52. No obvious reversal toward higher densities occurred at cold temperatures, as some previous studies have reported. No clear relationship was found between snow density and the depth of new snowfalls. Correlations of daily densities between measurement sites decreased rapidly with increasing distance between sites. New snow densities are strongly influenced by orography, which contributes to density differences over short distances.
Abstract
The Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) is a large and growing community of volunteers measuring and reporting precipitation and is making this information broadly available for the research and operational community. CoCoRaHS has evolved through several phases since its beginnings in 1998, first starting as a flood-motivated local Colorado Front Range project, then through a 5-yr nationwide expansion period (2005–09), followed by five years (2010–14) of internal growth and capacity building.
As of mid-2015, CoCoRaHS volunteers have submitted over 31 million daily precipitation reports and tens of thousands of reports of hail, heavy rain, and snow, representing over 1.5 million volunteer hours. During the past 10 years, there has been wide demand for and use of CoCoRaHS data by professional and scientific users with an interest in its applicability to their different areas of focus. These range from hydrological applications and weather forecasting to agriculture, entomology, remote sensing validation, city snow removal contracting, and recreational activities, just to name a few. The high demand for CoCoRaHS data by many entities is an effective motivator for volunteer observers, who want to be assured that their efforts are needed and appreciated.
Going forward, CoCoRaHS hopes to continue to play a leading role in the evolution and growth of citizen science while contributing to research and operational meteorology and hydrology.
Abstract
The Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) is a large and growing community of volunteers measuring and reporting precipitation and is making this information broadly available for the research and operational community. CoCoRaHS has evolved through several phases since its beginnings in 1998, first starting as a flood-motivated local Colorado Front Range project, then through a 5-yr nationwide expansion period (2005–09), followed by five years (2010–14) of internal growth and capacity building.
As of mid-2015, CoCoRaHS volunteers have submitted over 31 million daily precipitation reports and tens of thousands of reports of hail, heavy rain, and snow, representing over 1.5 million volunteer hours. During the past 10 years, there has been wide demand for and use of CoCoRaHS data by professional and scientific users with an interest in its applicability to their different areas of focus. These range from hydrological applications and weather forecasting to agriculture, entomology, remote sensing validation, city snow removal contracting, and recreational activities, just to name a few. The high demand for CoCoRaHS data by many entities is an effective motivator for volunteer observers, who want to be assured that their efforts are needed and appreciated.
Going forward, CoCoRaHS hopes to continue to play a leading role in the evolution and growth of citizen science while contributing to research and operational meteorology and hydrology.
Abstract
Every day, thousands of volunteers across the United States report the amount of precipitation they have received in the past 24 hours. This study focuses on the largest of these volunteer-submitted reports for each day, using precipitation measurements from the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) from January 2010 to December 2017 as well as observations from the U.S. Cooperative Observer Program (COOP) network from January 1981 through December 2017. Results provide clarity on spatial variability, temporal variability, and seasonal cycle of contiguous U.S daily precipitation extremes (DPEs). During 2010–17, the DPEs ranged from 11 mm on 28 March 2013 in Oregon to 635 mm on 27 August 2017 in Texas during Hurricane Harvey. Coastal states are most prone to high daily precipitation totals, especially those bordering the Gulf of Mexico or Atlantic Gulf Stream. The average DPE value varies with season; it is greater than 175 mm in late August and less than 100 mm through meteorological winter. These observations also show that location of the DPE varies with season as well. For example, 28.5% of February extremes fall in Pacific states, whereas all August extremes occur east of that region. Perhaps most importantly, these findings demonstrate strength in numbers. The large daily sample size of CoCoRaHS and COOP networks forms a basis for monitoring, mapping, and categorizing DPEs, and other aspects of extreme precipitation, with considerable spatial detail.
Abstract
Every day, thousands of volunteers across the United States report the amount of precipitation they have received in the past 24 hours. This study focuses on the largest of these volunteer-submitted reports for each day, using precipitation measurements from the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) from January 2010 to December 2017 as well as observations from the U.S. Cooperative Observer Program (COOP) network from January 1981 through December 2017. Results provide clarity on spatial variability, temporal variability, and seasonal cycle of contiguous U.S daily precipitation extremes (DPEs). During 2010–17, the DPEs ranged from 11 mm on 28 March 2013 in Oregon to 635 mm on 27 August 2017 in Texas during Hurricane Harvey. Coastal states are most prone to high daily precipitation totals, especially those bordering the Gulf of Mexico or Atlantic Gulf Stream. The average DPE value varies with season; it is greater than 175 mm in late August and less than 100 mm through meteorological winter. These observations also show that location of the DPE varies with season as well. For example, 28.5% of February extremes fall in Pacific states, whereas all August extremes occur east of that region. Perhaps most importantly, these findings demonstrate strength in numbers. The large daily sample size of CoCoRaHS and COOP networks forms a basis for monitoring, mapping, and categorizing DPEs, and other aspects of extreme precipitation, with considerable spatial detail.
Abstract
This article introduces two new tools developed to enhance drought impacts monitoring by citizen scientists. In collaboration with the National Integrated Drought Information System (NIDIS), the National Drought Mitigation Center (NDMC), and the Community Collaborative Rain, Hail and Snow (CoCoRaHS) network, the Carolinas Integrated Sciences and Assessments (CISA) developed an experimental method of drought monitoring and reporting by citizen scientists. Since 2013, CISA has recruited CoCoRaHS observers in the Carolinas to participate in “condition monitoring,” the regular reporting of local conditions. In contrast to intermittent drought impact reports, condition monitoring creates a baseline for comparison of change through time and improves understanding of the onset, intensification, and recovery of drought.
A project evaluation demonstrated the usefulness of the qualitative reports, while also identifying a need for improved accessibility to the information and a quantitative metric to more quickly assess changing conditions. Evaluation findings informed the development of 1) a condition monitoring scale bar for inclusion on the national CoCoRaHS reporting form and 2) a web map to spatially display the condition monitoring reports. CoCoRaHS observers use the scale bar to record their assessment of local conditions, ranging from severely wet to severely dry. Their qualitative reports provide more in-depth information about their selection, noting the effects of weather and climate on the environment and communities in their area. The web map provides an easily accessible format for users such as the State Climate Offices to view the reports, facilitating the incorporation of CoCoRaHS observations into drought monitoring processes.
Abstract
This article introduces two new tools developed to enhance drought impacts monitoring by citizen scientists. In collaboration with the National Integrated Drought Information System (NIDIS), the National Drought Mitigation Center (NDMC), and the Community Collaborative Rain, Hail and Snow (CoCoRaHS) network, the Carolinas Integrated Sciences and Assessments (CISA) developed an experimental method of drought monitoring and reporting by citizen scientists. Since 2013, CISA has recruited CoCoRaHS observers in the Carolinas to participate in “condition monitoring,” the regular reporting of local conditions. In contrast to intermittent drought impact reports, condition monitoring creates a baseline for comparison of change through time and improves understanding of the onset, intensification, and recovery of drought.
A project evaluation demonstrated the usefulness of the qualitative reports, while also identifying a need for improved accessibility to the information and a quantitative metric to more quickly assess changing conditions. Evaluation findings informed the development of 1) a condition monitoring scale bar for inclusion on the national CoCoRaHS reporting form and 2) a web map to spatially display the condition monitoring reports. CoCoRaHS observers use the scale bar to record their assessment of local conditions, ranging from severely wet to severely dry. Their qualitative reports provide more in-depth information about their selection, noting the effects of weather and climate on the environment and communities in their area. The web map provides an easily accessible format for users such as the State Climate Offices to view the reports, facilitating the incorporation of CoCoRaHS observations into drought monitoring processes.
Abstract
In recent years, hail accumulations from thunderstorms have occurred frequently enough to catch the attention of the National Weather Service, the general public, and news agencies. Despite the extreme nature of these thunderstorms, no mechanism is currently in place to obtain adequate reports, measurements, or forecasts of accumulated hail depth. To better identify and forecast hail accumulations, the Colorado Hail Accumulation from Thunderstorms (CHAT) project was initiated in 2016 with the goals of collecting improved and more frequent hail depth reports on the ground as well as studying characteristics of storms that produce hail accumulations in Colorado. A desired outcome of this research is to identify predictors for hail-producing thunderstorms typically occurring along the Colorado Front Range that might be used as operational nowcast products in the future. During the 2016 convective season, we asked amateur meteorologists to send general information, photos, and videos on hail depth using social media. They submitted over 58 reports in Colorado with information on location, time, depth, and areal coverage of hail accumulations. We have analyzed dual-polarization radar and lightning mapping array data from 32 thunderstorms in Colorado, which produced between 0.5 and 50 cm of hail accumulation on the ground, to identify characteristics unique to storms with hail accumulations. This preliminary analysis shows how enhanced in-cloud hail presence and surface accumulation can be tracked throughout the lifetime of a thunderstorm using dual-polarization radar and lightning data, and how hail accumulation events are associated with large in-cloud ice water content, long hailfall duration, or a combination of these.
Abstract
In recent years, hail accumulations from thunderstorms have occurred frequently enough to catch the attention of the National Weather Service, the general public, and news agencies. Despite the extreme nature of these thunderstorms, no mechanism is currently in place to obtain adequate reports, measurements, or forecasts of accumulated hail depth. To better identify and forecast hail accumulations, the Colorado Hail Accumulation from Thunderstorms (CHAT) project was initiated in 2016 with the goals of collecting improved and more frequent hail depth reports on the ground as well as studying characteristics of storms that produce hail accumulations in Colorado. A desired outcome of this research is to identify predictors for hail-producing thunderstorms typically occurring along the Colorado Front Range that might be used as operational nowcast products in the future. During the 2016 convective season, we asked amateur meteorologists to send general information, photos, and videos on hail depth using social media. They submitted over 58 reports in Colorado with information on location, time, depth, and areal coverage of hail accumulations. We have analyzed dual-polarization radar and lightning mapping array data from 32 thunderstorms in Colorado, which produced between 0.5 and 50 cm of hail accumulation on the ground, to identify characteristics unique to storms with hail accumulations. This preliminary analysis shows how enhanced in-cloud hail presence and surface accumulation can be tracked throughout the lifetime of a thunderstorm using dual-polarization radar and lightning data, and how hail accumulation events are associated with large in-cloud ice water content, long hailfall duration, or a combination of these.
The objective of this research is to determine whether poorly sited long-term surface temperature monitoring sites have been adjusted in order to provide spatially representative independent data for use in regional and global surface temperature analyses. We present detailed analyses that demonstrate the lack of independence of the poorly sited data when they are adjusted using the homogenization procedures employed in past studies, as well as discuss the uncertainties associated with undocumented station moves. We use simulation and mathematics to determine the effect of trend on station adjustments and the associated effect of trend in the reference series on the trend of the adjusted station. We also compare data before and after adjustment to the reanalysis data, and we discuss the effect of land use changes on the uncertainty of measurement.
A major conclusion of our analysis is that there are large uncertainties associated with the surface temperature trends from the poorly sited stations. Moreover, rather than providing additional independent information, the use of the data from poorly sited stations provides a false sense of confidence in the robustness of the surface temperature trend assessments.
The objective of this research is to determine whether poorly sited long-term surface temperature monitoring sites have been adjusted in order to provide spatially representative independent data for use in regional and global surface temperature analyses. We present detailed analyses that demonstrate the lack of independence of the poorly sited data when they are adjusted using the homogenization procedures employed in past studies, as well as discuss the uncertainties associated with undocumented station moves. We use simulation and mathematics to determine the effect of trend on station adjustments and the associated effect of trend in the reference series on the trend of the adjusted station. We also compare data before and after adjustment to the reanalysis data, and we discuss the effect of land use changes on the uncertainty of measurement.
A major conclusion of our analysis is that there are large uncertainties associated with the surface temperature trends from the poorly sited stations. Moreover, rather than providing additional independent information, the use of the data from poorly sited stations provides a false sense of confidence in the robustness of the surface temperature trend assessments.
On the evening of 28 July 1997 the city of Fort Collins, Colorado, experienced a devastating flash flood that caused five fatalities and over 200 million dollars in damage. Maximum accumulations of rainfall in the western part of the city exceeded 10 in. in a 6-h period. This study presents a multiscale meteorological overview of the event utilizing a wide variety of instrument platforms and data including rain gauge, CSU–CHILL multiparameter radar, Next Generation Radar, National Lightning Detection Network, surface and Aircraft Communication Addressing and Reporting System observations, satellite observations, and synoptic analyses.
Many of the meteorological features associated with the Fort Collins flash flood typify those of similar events in the western United States. Prominent features in the Fort Collins case included the presence of a 500-hPa ridge axis over northeastern Colorado; a weak shortwave trough on the western side of the ridge; postfrontal easterly upslope flow at low levels; weak to moderate southwesterly flow aloft; a deep, moist warm layer in the sounding; and the occurrence of a quasi-stationary rainfall system. In contrast to previous events such as the Rapid City or Big Thompson floods, the thermodynamic environment of the Fort Collins storm exhibited only modest instability, consistent with low lightning flash rates and an absence of hail and other severe storm signatures.
Radar, rain gauge, and lightning observations provided a detailed view of the cloud and precipitation morphology. Polarimetric radar observations suggest that a coupling between warm-rain collision coalescence processes and ice processes played an important role in the rainfall production. Dual-Doppler radar and mesoscale wind analyses revealed that the low-level flow field associated with a bow echo located 60 km to the southeast of Fort Collins may have been responsible for a brief easterly acceleration in the low-level winds during the last 1.5 h of the event. The enhanced flow interacted with both topography and the convection located over Fort Collins, resulting in a quasi-stationary convective system and the heaviest rainfall of the evening.
On the evening of 28 July 1997 the city of Fort Collins, Colorado, experienced a devastating flash flood that caused five fatalities and over 200 million dollars in damage. Maximum accumulations of rainfall in the western part of the city exceeded 10 in. in a 6-h period. This study presents a multiscale meteorological overview of the event utilizing a wide variety of instrument platforms and data including rain gauge, CSU–CHILL multiparameter radar, Next Generation Radar, National Lightning Detection Network, surface and Aircraft Communication Addressing and Reporting System observations, satellite observations, and synoptic analyses.
Many of the meteorological features associated with the Fort Collins flash flood typify those of similar events in the western United States. Prominent features in the Fort Collins case included the presence of a 500-hPa ridge axis over northeastern Colorado; a weak shortwave trough on the western side of the ridge; postfrontal easterly upslope flow at low levels; weak to moderate southwesterly flow aloft; a deep, moist warm layer in the sounding; and the occurrence of a quasi-stationary rainfall system. In contrast to previous events such as the Rapid City or Big Thompson floods, the thermodynamic environment of the Fort Collins storm exhibited only modest instability, consistent with low lightning flash rates and an absence of hail and other severe storm signatures.
Radar, rain gauge, and lightning observations provided a detailed view of the cloud and precipitation morphology. Polarimetric radar observations suggest that a coupling between warm-rain collision coalescence processes and ice processes played an important role in the rainfall production. Dual-Doppler radar and mesoscale wind analyses revealed that the low-level flow field associated with a bow echo located 60 km to the southeast of Fort Collins may have been responsible for a brief easterly acceleration in the low-level winds during the last 1.5 h of the event. The enhanced flow interacted with both topography and the convection located over Fort Collins, resulting in a quasi-stationary convective system and the heaviest rainfall of the evening.
