Search Results

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

  • Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) x
  • All content x
Clear All
Matthew E. Jeglum, Sebastian W. Hoch, Derek D. Jensen, Reneta Dimitrova, and Zachariah Silver

terrain and insight gained will aid the model verification and improvement efforts of the MATERHORN Program and others. To investigate LTFs, an automated algorithm is applied to systematically identify LTFs at over 100 automatic weather stations (AWSs). The events identified by the algorithm will be shown to occur primarily at night on slopes elevated above the main basin and with air temperature variations of up to 13°C in less than 30 min. A case study and composite (average of multiple events

Full access
Raquel Lorente-Plazas and Joshua P. Hacker

1. Introduction In statistics, the term bias is broadly used when errors are systematic instead of random (i.e., when the mean of the error distribution is not zero). Data assimilation (DA) algorithms in wide use today rely on the basic assumptions of unbiased observations and models. In those systems, observations with assumed random errors are used to correct the random errors in a model-forecast background estimate. The underlying theories allow for known biases to be corrected prior to

Full access
Robert S. Arthur, Katherine A. Lundquist, Jeffrey D. Mirocha, and Fotini K. Chow

. On east-facing slopes, the downslope flow transition has been found to follow the shadow front down the slope ( Papadopoulos and Helmis 1999 ; Lehner et al. 2015 ), while on west-facing slopes, the downslope flow transition may follow the shadow front up the slope ( Nadeau et al. 2013 ). With this in mind, it is important to capture topographic effects on radiation in atmospheric models over mountainous terrain. Perhaps the first implementation of a topographic shading algorithm in a major

Open access
Jeffrey D. Massey, W. James Steenburgh, Sebastian W. Hoch, and Derek D. Jensen

. Bilich , J. J. Braun , and V. U. Zavorotny , 2008 : Use of GPS receivers as a soil moisture network for water cycle studies . Geophys. Res. Lett. , 35 , L24405 , doi: 10.1029/2008GL036013 . 10.1029/2008GL036013 Liu , J. , and Coauthors , 2009 : Validation of Moderate Resolution Imaging Spectroradiometer (MODIS) albedo retrieval algorithm: Dependence of albedo on solar zenith angle . J. Geophys. Res. , 114 , D01106 , doi: 10.1029/2008JD009969 . Liu , Y. , and Coauthors , 2008

Full access
H. J. S. Fernando, E. R. Pardyjak, S. Di Sabatino, F. K. Chow, S. F. J. De Wekker, S. W. Hoch, J. Hacker, J. C. Pace, T. Pratt, Z. Pu, W. J. Steenburgh, C. D. Whiteman, Y. Wang, D. Zajic, B. Balsley, R. Dimitrova, G. D. Emmitt, C. W. Higgins, J. C. R. Hunt, J. C. Knievel, D. Lawrence, Y. Liu, D. F. Nadeau, E. Kit, B. W. Blomquist, P. Conry, R. S. Coppersmith, E. Creegan, M. Felton, A. Grachev, N. Gunawardena, C. Hang, C. M. Hocut, G. Huynh, M. E. Jeglum, D. Jensen, V. Kulandaivelu, M. Lehner, L. S. Leo, D. Liberzon, J. D. Massey, K. McEnerney, S. Pal, T. Price, M. Sghiatti, Z. Silver, M. Thompson, H. Zhang, and T. Zsedrovits

instrumented UAV, sensors for moisture and fog measurements, and a combined hot-film/sonic anemometer system for probing turbulence down to Kolmogorov scales. Advanced data retrieval and processing algorithms are also attempted. The parameterization component (MATERHORN-P) develops high-fidelity physics-based fundamental (quantitative) relationships for complex-terrain processes, which are implemented in mesoscale models followed by model evaluations. The Granite Mountain Atmospheric Science Testbed of the

Full access
Jeffrey D. Massey, W. James Steenburgh, Jason C. Knievel, and William Y. Y. Cheng

-surface soil moisture estimates from spaceborne microwave remote sensing platforms (e.g., Jackson et al. 2010 ; Kerr et al. 2010 ). Such platforms include the Soil Moisture and Ocean Salinity mission (SMOS; Kerr et al. 2010 ), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR–E), and the Advanced Scatterometer (ASCAT). Although satellite soil moisture retrieval algorithms have improved in recent years, their coarse spatial resolution (>10–30 km) and large discrepancies with in situ

Full access
Hailing Zhang, Zhaoxia Pu, and Xuebo Zhang

temperature and 10-m wind speed and direction. According to Horel et al. (2002) , quality control algorithms and data monitoring programs are performed for all available data. The quality-controlled data are then made available hourly with quality flags. In this study, only those observations with a quality flag of “OK” (the highest quality) are used for verification. Since there is case-by-case variation in near-surface atmospheric conditions due to various synoptic systems and terrain, verification of

Full access
Manuela Lehner, C. David Whiteman, Sebastian W. Hoch, Derek Jensen, Eric R. Pardyjak, Laura S. Leo, Silvana Di Sabatino, and Harindra J. S. Fernando

in Fig. 8b . It shows the gradual propagation of surface cooling down the slope from northwest to southeast, in agreement with the shadow propagation on the slope ( Fig. 8a ). Fig . 8. Map of time (MST) of (a) local sunset, (b) cooling onset, and (c) downslope-flow onset. Local sunset in (a) is determined from a shadow algorithm on a 10-m-resolution digital elevation model with a temporal resolution of 5 min, the cooling onset in (b) is defined as the time for which the 2-m temperature (1 m for

Full access
Sean M. Wile, Joshua P. Hacker, and Kenneth H. Chilcoat

.1175/1520-0493(2001)129<2884:AEAKFF>2.0.CO;2 . Anderson, J. L. , 2003 : A local least squares framework for ensemble filtering . Mon. Wea. Rev. , 131 , 634 – 642 , doi: 10.1175/1520-0493(2003)131<0634:ALLSFF>2.0.CO;2 . Anderson, J. L. , 2007 : An adaptive covariance inflation error correction algorithm for ensemble filters . Tellus , 59A , 210 – 224 , doi: 10.1111/j.1600-0870.2006.00216.x . Anderson, J. L. , Hoar T. , Raeder K. , Liu H. , Collins N. , Torn R. , and Avellano A. , 2009 : The Data

Full access