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1. Introduction Substantial changes in the precipitation regime, particularly in heavy precipitation, have been observed in the northeastern United States (e.g., Groisman et al. 2005 , 2004 ; Karl et al. 2009 ; Walsh et al. 2014 ; Douglas and Fairbank 2011 ; Matonse and Frei 2013 ; Frei et al. 2015 ). Particularly large increases in the magnitude of extreme precipitation events have also been observed (e.g., Groisman et al. 2005 , 2004 ; Karl et al. 2009 ). The National Climate
1. Introduction Substantial changes in the precipitation regime, particularly in heavy precipitation, have been observed in the northeastern United States (e.g., Groisman et al. 2005 , 2004 ; Karl et al. 2009 ; Walsh et al. 2014 ; Douglas and Fairbank 2011 ; Matonse and Frei 2013 ; Frei et al. 2015 ). Particularly large increases in the magnitude of extreme precipitation events have also been observed (e.g., Groisman et al. 2005 , 2004 ; Karl et al. 2009 ). The National Climate
date is less representative of the occurrence date of the extreme events. For analysis of potential shifts in flood seasonality, we divided the MOPEX data records into two time periods, 1951–79 and 1980–99, following Coopersmith et al. (2014) . The year of 1980 was chosen as the cutoff year for its better representation of the hydrologic regime shift in the MOPEX catchments under a possibly changing climate compared with two other candidate cutoff years ( Coopersmith et al. 2014 ). We also tested
date is less representative of the occurrence date of the extreme events. For analysis of potential shifts in flood seasonality, we divided the MOPEX data records into two time periods, 1951–79 and 1980–99, following Coopersmith et al. (2014) . The year of 1980 was chosen as the cutoff year for its better representation of the hydrologic regime shift in the MOPEX catchments under a possibly changing climate compared with two other candidate cutoff years ( Coopersmith et al. 2014 ). We also tested
al. 2013 ; Mishnaevsky 2019 ) and the rotation of the blades, which adds significant additional velocity for the drop impact ( Amirzadeh et al. 2017 ). Bech et al. (2018) propose to reduce the tip speed of the wind turbine blades during severe rain events to reduce leading edge erosion (LEE). Detailed quantification of the rain climate, in particular of KE and drop size distribution (DSD) as well as its interaction with wind speed in different environments is needed for improved understanding
al. 2013 ; Mishnaevsky 2019 ) and the rotation of the blades, which adds significant additional velocity for the drop impact ( Amirzadeh et al. 2017 ). Bech et al. (2018) propose to reduce the tip speed of the wind turbine blades during severe rain events to reduce leading edge erosion (LEE). Detailed quantification of the rain climate, in particular of KE and drop size distribution (DSD) as well as its interaction with wind speed in different environments is needed for improved understanding
a Changing Climate.” This work was partially supported by the Canadian Space Agency under a Government Related Initiative Program (GRIP) grant to CCRS. The authors thank Dr. Yu Zhang and Dr. Andrew Davidson for their help with editing and critical review of the manuscript at CCRS. REFERENCES Abdul Aziz, O. I. , and Burn D. H. , 2006 : Trends and variability in the hydrological regime of the Mackenzie River basin. J. Hydrol. , 319 , 282 – 294 . 10.1016/j.jhydrol.2005.06.039 Akinremi, O
a Changing Climate.” This work was partially supported by the Canadian Space Agency under a Government Related Initiative Program (GRIP) grant to CCRS. The authors thank Dr. Yu Zhang and Dr. Andrew Davidson for their help with editing and critical review of the manuscript at CCRS. REFERENCES Abdul Aziz, O. I. , and Burn D. H. , 2006 : Trends and variability in the hydrological regime of the Mackenzie River basin. J. Hydrol. , 319 , 282 – 294 . 10.1016/j.jhydrol.2005.06.039 Akinremi, O
from the CFSR dataset ( Saha et al. 2010 ). ALEXI is run each day over the contiguous United States with 4-km horizontal grid spacing using LST retrievals and insolation estimates derived from the Geostationary Operational Environmental Satellite imager. It has been shown to provide reasonable ET estimates for a variety of climate regimes and vegetation types ( Anderson et al. 2007a ). Because ALEXI uses the morning rise in LST to estimate ET, incomplete cloud screening can add noise to the ET time
from the CFSR dataset ( Saha et al. 2010 ). ALEXI is run each day over the contiguous United States with 4-km horizontal grid spacing using LST retrievals and insolation estimates derived from the Geostationary Operational Environmental Satellite imager. It has been shown to provide reasonable ET estimates for a variety of climate regimes and vegetation types ( Anderson et al. 2007a ). Because ALEXI uses the morning rise in LST to estimate ET, incomplete cloud screening can add noise to the ET time
could be captured empirically using a climate classification; Sturm and Holmgren (1998) confirmed this finding. Nonetheless, the approach is general. The alternative would be to explicitly model compaction processes, as has been done in several physically based snow models (cf. Anderson 1976 ; Koren et al. 1999 ; Liston et al. 2007 ; see Rutter et al. 2009 for an extensive list). The problem is that these physical models require high-quality daily or even hourly weather and snowfall data
could be captured empirically using a climate classification; Sturm and Holmgren (1998) confirmed this finding. Nonetheless, the approach is general. The alternative would be to explicitly model compaction processes, as has been done in several physically based snow models (cf. Anderson 1976 ; Koren et al. 1999 ; Liston et al. 2007 ; see Rutter et al. 2009 for an extensive list). The problem is that these physical models require high-quality daily or even hourly weather and snowfall data
by the TP can generate Rossby waves in the westerlies, which can propagate downstream and influence the circulation anomaly elsewhere. It is also located over the central and eastern parts of the Eurasian continent, facing the Indian Ocean to the south and the Pacific Ocean to its east. Therefore the Tibetan Plateau can exert profound thermal and dynamical influences on the circulation, energy, and water cycles of the climate system. Before the 1950s, most of the studies concerning the influence
by the TP can generate Rossby waves in the westerlies, which can propagate downstream and influence the circulation anomaly elsewhere. It is also located over the central and eastern parts of the Eurasian continent, facing the Indian Ocean to the south and the Pacific Ocean to its east. Therefore the Tibetan Plateau can exert profound thermal and dynamical influences on the circulation, energy, and water cycles of the climate system. Before the 1950s, most of the studies concerning the influence
. 2012 ; Yuan et al. 2013a , b ; Bell et al. 2013 ; Pan et al. 2013 ; Dutra et al. 2014 ; McEvoy et al. 2016 ) provide valuable information. For example, outputs from the North American Multi-Model Ensemble ( Kirtman et al. 2014 ) have been used to forecast future drought ( Yuan and Wood 2013 ; Mo and Lyon 2015 ; Thober et al. 2015 ). However, this guidance has typically been for seasonal time scales. To help address short-range forecasting needs, the Climate Prediction Center (CPC) issues a
. 2012 ; Yuan et al. 2013a , b ; Bell et al. 2013 ; Pan et al. 2013 ; Dutra et al. 2014 ; McEvoy et al. 2016 ) provide valuable information. For example, outputs from the North American Multi-Model Ensemble ( Kirtman et al. 2014 ) have been used to forecast future drought ( Yuan and Wood 2013 ; Mo and Lyon 2015 ; Thober et al. 2015 ). However, this guidance has typically been for seasonal time scales. To help address short-range forecasting needs, the Climate Prediction Center (CPC) issues a
changes would not be uniform from year to year and need to be understood in the context of the relative frequency of warmer winters. With this in mind, the goals of this investigation are to map areas of seasonal snow cover in the Pacific Northwest that are at risk of converting to a rainfall-dominated winter precipitation regime under projected climate warming, and quantify the current and projected relative frequencies of warm winters in the Pacific Northwest. The data and methodology used
changes would not be uniform from year to year and need to be understood in the context of the relative frequency of warmer winters. With this in mind, the goals of this investigation are to map areas of seasonal snow cover in the Pacific Northwest that are at risk of converting to a rainfall-dominated winter precipitation regime under projected climate warming, and quantify the current and projected relative frequencies of warm winters in the Pacific Northwest. The data and methodology used
parameters arising from climate regime dependencies can be translated into an uncertainty in retrieved rainfall rate. 2. Identifying rain types Conventional approaches to rain-type classification are generally based on a subjective separation of rainfall into two types: 1) convective precipitation characterized by strong updrafts, significant horizontal variability, and little or no evidence of a BB, and 2) stratiform precipitation characterized by horizontally homogeneous rainfall in regions of weak and
parameters arising from climate regime dependencies can be translated into an uncertainty in retrieved rainfall rate. 2. Identifying rain types Conventional approaches to rain-type classification are generally based on a subjective separation of rainfall into two types: 1) convective precipitation characterized by strong updrafts, significant horizontal variability, and little or no evidence of a BB, and 2) stratiform precipitation characterized by horizontally homogeneous rainfall in regions of weak and
