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Jadwiga R. Ziolkowska, Christopher A. Fiebrich, J. D. Carlson, Andrea D. Melvin, Albert J. Sutherland, Kevin A. Kloesel, Gary D. McManus, Bradley G. Illston, James E. Hocker, and Reuben Reyes

impacting economic growth and human well-being. Over the past decades, the need for accurate and timely information has become increasingly important and is anticipated to increase even more in the future, especially in times of extreme weather events. In response to the growing demand for reliable weather observations, the first automated weather monitoring technologies were developed as early as the 1970s ( Brock and Govind 1977 ; Brock et al. 1986 ) and set the stage for the establishment of

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Markus Enenkel, Daniel Osgood, Martha Anderson, Bristol Powell, Jessica McCarty, Christopher Neigh, Mark Carroll, Margaret Wooten, Greg Husak, Christopher Hain, and Molly Brown

. C. Anderson , and T. Holmes , 2011 : An intercomparison of available soil moisture estimates from thermal infrared and passive microwave remote sensing and land surface modeling . J. Geophys. Res. , 116 , D15107 , . 10.1029/2011JD015633 Hain , C. R. , W. T. Crow , M. C. Anderson , and J. R. Mecikalski , 2012 : An ensemble Kalman filter dual assimilation of thermal infrared and microwave satellite observations of soil moisture into the Noah land

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Johannes Schmetz and W. Paul Menzel

beyond the currently established coordination of meteorological satellite measurements. We freely admit that it would be a paradigm shift in many ways and therefore present significant challenges; however, it would make observations, especially the operational, to-be-sustained part of the satellite observing system, more affordable. We also emphasize that there should always be enough room for innovation and free thinking; this is currently well captured in the principal investigator (PI

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Jason A. Otkin, Tonya Haigh, Anthony Mucia, Martha C. Anderson, and Christopher Hain

the routine monitoring of various biophysical and biological indicators of vegetation health, such as plant vigor, leaf area index, gross primary productivity, ET, and solar-induced chlorophyll fluorescence (e.g., Tucker 1979 ; Liu and Kogan 1996 ; Huete et al. 2002 ; Myneni et al. 2002 ; Heinsch et al. 2003 ; Anderson et al. 2007a ; Mu et al. 2011 ; Guanter et al. 2014 ). In addition, observations from microwave sensors onboard polar-orbiting satellites such as the Soil Moisture Ocean

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A. Bonazzi, A. L. Dobbin, J. K. Turner, P. S. Wilson, C. Mitas, and E. Bellone

choice is to refer to the longest available time series of hurricane data and build risk models that integrate over the climate variability of the period for which observations are available. In present conditions, the implied assumption of climate as stationary that underlies this choice might lead to a substantial underestimation of risk as the Atlantic is in a period of heightened activity ( Elsner et al. 2000 , 2004 ). A more appealing—but admittedly more difficult—alternative would be to

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Chengcheng Xu, Chen Wang, and Pan Liu

Bayesian logistic regression model for real-time crash risk assessment at expressway weaving segments. The traffic flow data collected from the microwave vehicle detection system were used for model development. Basso et al. (2018) developed a real-time crash risk model using traffic flow data measured by the Automatic Vehicle Identification system. Yuan et al. (2018) used conditional logistic regression to link the crash likelihood with real-time traffic conditions and adaptive signal phasing on

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Berill Blair, Malte Müller, Cyril Palerme, Rayne Blair, David Crookall, Maaike Knol-Kauffman, and Machiel Lamers

forecasts and a climatological reference (defined as the 10 years preceding the forecast start date) were evaluated using passive microwave observations of sea ice concentration and a metric called the spatial probability score ( Goessling and Jung 2018 ). Then, the duration during which the S2S forecasts significantly outperform the climatological reference was assessed using weekly means of the spatial probability score for each forecast during the period 1999–2014. The distribution of these durations

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J. Sander, J. F. Eichner, E. Faust, and M. Steuer

time, because of changes in the observing system during the reanalysis period (1948 up to the present). This was caused by the use of satellite data from the 1970s onward, increasing numbers of observations from aircraft, ocean buoys and other surface platforms, and a changing number of soundings since the late 1980s. Reanalysis data are a merger of model forecasts and observational data, wherein spatial homogeneity is achieved by interpolating results from observation-rich to observation

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Maqsooda Mahomed, Alistair D. Clulow, Sheldon Strydom, Tafadzwanashe Mabhaudhi, and Michael J. Savage

implications of combined aircraft storm electric current measurements and satellite-based diurnal lightning statistics . J. Geophys. Res. , 116 , D05201 , . Madhulatha , A. , M. Rajeevan , M. Venkat Ratnam , J. Bhate , and C. Naidu , 2013 : Nowcasting severe convective activity over southeast India using ground-based microwave radiometer observations . J. Geophys. Res. Atmos. , 118 ( 1 ), 1 – 13 , . 10

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Zoe Schroder and James B. Elsner

.1175/1520-0493(1977)105<0477:SCAOTO>2.0.CO;2 . 10.1175/1520-0493(1977)105<0477:SCAOTO>2.0.CO;2 Gensini , V. A. , and W. Ashley , 2011 : Climatology of potentially severe convective environments from the North American Regional Reanalysis . Electron. J. Severe Storms Meteor. , 6 ( 8 ), . Gensini , V. A. , T. L. Mote , and H. E. Brooks , 2014 : Severe-thunderstorm reanalysis environments and collocated radiosonde observations . J. Appl. Meteor

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