Search Results

You are looking at 1 - 9 of 9 items for :

  • The Olympic Mountains Experiment (OLYMPEX) x
  • All content x
Clear All
Zeinab Takbiri, Ardeshir Ebtehaj, Efi Foufoula-Georgiou, Pierre-Emmanuel Kirstetter, and F. Joseph Turk

Johnson 2011 ). These characteristics are difficult to accurately parameterize as of today. Second, the already weak snowfall scattering signal tends to be masked by the increased atmospheric emissivity and liquid water content in precipitating conditions ( Liu and Seo 2013 ; Wang et al. 2013 ; Panegrossi et al. 2017 ). Third, changes in surface emissivity due to snow accumulation on the ground can significantly alter the snowfall microwave signal. Dry snow cover scatters the upwelling surface

Full access
Robert A. Houze Jr., Lynn A. McMurdie, Walter A. Petersen, Mathew R. Schwaller, William Baccus, Jessica D. Lundquist, Clifford F. Mass, Bart Nijssen, Steven A. Rutledge, David R. Hudak, Simone Tanelli, Gerald G. Mace, Michael R. Poellot, Dennis P. Lettenmaier, Joseph P. Zagrodnik, Angela K. Rowe, Jennifer C. DeHart, Luke E. Madaus, Hannah C. Barnes, and V. Chandrasekar

. With its onboard Dual-Frequency Precipitation Radar (DPR) and 13-channel GPM Microwave Imager (GMI), the GPM satellite extends into future decades the global surveillance of precipitation provided until 2014 by the Tropical Rainfall Measuring Mission (TRMM) satellite and broadens coverage to higher latitudes, where many of Earth’s snow-covered mountain ranges are located. GPM also serves as a reference for other satellites carrying a variety of microwave imaging or sounding radiometers [see Hou et

Open access
William Ryan Currier, Theodore Thorson, and Jessica D. Lundquist

precipitation on the Olympic Peninsula . J. Hydrometeor. , 8 , 1068 – 1081 , doi: 10.1175/JHM610.1 . 10.1175/JHM610.1 Anderson , E. A. , 1976 : A point energy and mass balance model of a snow cover. NOAA Tech. Rep. NWS 19, 150 pp., http://amazon.nws.noaa.gov/articles/HRL_Pubs_PDF_May12_2009/HRL_PUBS_51-100/81_A_POINT_ENERGY_AND_MASS.pdf . Bohn , T. J. , B. Livneh , J. W. Oyler , S. W. Running , B. Nijssen , and D. P. Lettenmaier , 2013 : Global evaluation of MTCLIM and related algorithms for

Full access
Qian Cao, Thomas H. Painter, William Ryan Currier, Jessica D. Lundquist, and Dennis P. Lettenmaier

jets. Over the last decade, several studies have been performed that use remotely sensed snow data to help infer the spatial distribution of precipitation. Durand et al. (2008) and Girotto et al. (2014a , b ) used satellite-derived snow covered area (SCA) data, after converting to SWE using a snow depletion curve, to update the precipitation disaggregation weights in a land surface model via smoothing methods. Livneh et al. (2014) used the seasonal peak value of SWE via reconstructions based

Full access
Minda Le and V. Chandrasekar

. The solid black line is the left boundary of the DPR outer swath. Black dashed lines are the boundaries of the DPR inner swath. In Fig. 4b , hydrometeor type from ground radar shows most of the scan is covered by crystal and dry snow, with a small area of scattered rain identified to the west of the radar. DPR reflectivity at 2-km height is in Fig. 4c and the corresponding snow flag is illustrated in Fig. 4d . The region between KCLE 100-km range (big circle) and the DPR inner swath is pretty

Full access
Andrew Heymsfield, Aaron Bansemer, Norman B. Wood, Guosheng Liu, Simone Tanelli, Ousmane O. Sy, Michael Poellot, and Chuntao Liu

snowfall-rate–radar reflectivity relationships, referred to as the mass-flux (MF) method, is designed to cover a wide range of reflectivities, cloud types, and geographical locations. Consider a precipitating cloud layer with a melting layer (ML). From the top to the bottom of the ML—a thickness of 200–500 m ( Fabry and Zawadzki 1995 )—there is approximately conservation of water mass flux. Snow, with a reflectivity of Z t (reflectivity at the top of the ML) and precipitation rate S , is falling

Full access
Mircea Grecu, Lin Tian, Gerald M. Heymsfield, Ali Tokay, William S. Olson, Andrew J. Heymsfield, and Aaron Bansemer

potential time difference between the two types of estimates of up to 6 min, and in an Eulerian framework PSDs may change significantly in a 6-min interval. At the same time, especially given complex processes such as ice splintering and aggregation, it is possible that the ice particles and the associated backscattering properties considered in this study do not cover the entire spectrum encountered in nature, which may occasionally result in significantly larger errors than expected from the

Open access
Bin Pei and Firat Y. Testik

the following estimator given in Eq. (5) to estimate the mixed and cold-season precipitation (e.g., hail, snow, graupel): where is the signum function that indicates the sign (positive or negative) of the value. The details of the WSR-88D QPE algorithm can be found in Giangrande and Ryzhkov (2008) and Berkowitz et al. (2013) . In these publications the HCA was reported to be capable of identifying 10 different types of meteorological and nonmeteorological classifications, including light

Open access
Stephanie M. Wingo, Walter A. Petersen, Patrick N. Gatlin, Charanjit S. Pabla, David A. Marks, and David B. Wolff

, when a GPM Core Observatory overpass and exceptionally well-coordinated airborne observations sampled an evolving baroclinic system over the domain covered by ground-based instruments. Figures 4 and 5 give an overview of this case and illustrate the extensive network of field sites, including operational and research ground-based scanning radars, profiling Doppler radars, sounding launch locations, and various rain gauge and disdrometer installations. Fortuitously, the geometry of this

Full access