Search Results

You are looking at 1 - 10 of 21 items for :

  • Data quality control x
  • Global Precipitation Measurement (GPM): Science and Applications x
  • All content x
Clear All
Rachael Kroodsma, Stephen Bilanow, and Darren McKague

other radiometer calibration issues, and in particular the GMI on-orbit analysis is used as a model for many of the TMI V8 updates. There are several modifications that are incorporated into TMI V8 to improve the calibration and quality of the data product. This paper discusses two of these modifications: the alignment of the instrument and feedhorns, and the along-scan temperature bias correction. Other corrections to TMI V8 include a hot load correction ( Alquaied et al. 2018a ), updated emissive

Full access
Lijing Cheng, Hao Luo, Timothy Boyer, Rebecca Cowley, John Abraham, Viktor Gouretski, Franco Reseghetti, and Jiang Zhu

available. 3) There are no unknown types in side-by-side datasets, but nearly half of the global-scale data are composed of an unknown probe type. Because of these caveats, we are not to use side-by-side data to evaluate the schemes. However, a side-by-side dataset is a scientifically quality-controlled dataset (i.e., all bad data are removed), and the comparisons are much less impacted by the ocean variability between XBT and collocated CTD profiles compared with the global-scale dataset. So, the

Open access
Dalia B. Kirschbaum, George J. Huffman, Robert F. Adler, Scott Braun, Kevin Garrett, Erin Jones, Amy McNally, Gail Skofronick-Jackson, Erich Stocker, Huan Wu, and Benjamin F. Zaitchik

government agencies, academia, the private sector, international organizations, and others. Additional feedback has been gained from presentations at scientific meetings, applications-focused workshops, and other events. Three main themes emerged from dialogues and engagement with the applications community: the need for a long and consistent precipitation data record that merges and intercalibrates TRMM with GPM data, the importance of clearly denoted data fields and easy-to-interpret quality-control

Full access
Daniel Watters, Alessandro Battaglia, Kamil Mroz, and Frédéric Tridon

every 5 min at 1-km horizontal resolution out to ~250-km range. With such range, the composite provides measurements over land, coastal, and oceanic regions. The Met Office Radarnet composite product is quality controlled and matches to within 2% of annual precipitation detected by surface rain gauges ( Fairman et al. 2015 ). The time stamp on the composite data file represents the average of the end time of all individual radar scans. Radar scans that ended within 2 min before or 3 min after the

Open access
Liao-Fan Lin, Ardeshir M. Ebtehaj, Alejandro N. Flores, Satish Bastola, and Rafael L. Bras

L. Fang , 2014 : Impact of quality control of satellite soil moisture data on their assimilation into land surface model . Geophys. Res. Lett. , 41 , 7159 – 7166 , . 10.1002/2014GL060659 Zhao , L. , Z.-L. Yang , and T. J. Hoar , 2016 : Global soil moisture estimation by assimilating AMSR-E brightness temperatures in a coupled CLM4–RTM–DART system . J. Hydrometeor. , 17 , 2431 – 2454 , . 10.1175/JHM

Full access
Zhaoxia Pu, Chaulam Yu, Vijay Tallapragada, Jianjun Jin, and Will McCarty

(2016), are used for case studies in this paper. The paper is organized as follows: section 2 gives a brief introduction to the GMI observations, HWRF Model, GSI data assimilation system, hurricane cases, and experimental setting designs. Section 3 provides details about quality control (QC) and bias correction (BC). Assimilation and forecast results and validation of the data impact are discussed in section 4 . Section 5 summarizes results and provides the conclusions. 2. GMI observations

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

radar volume to a full grid with an identical center location and horizontal and vertical grid spacing as the SIMBA column grid. Total vertical extent of the full grid is set to 15 km, and total horizontal extent is based on the maximum range of the radar. For GPM GV quality-controlled data (NPOL and NEXRAD), the discrete hydrometeor identification (ID) values (HID in Table 1 ) are set into the new grid via a nearest neighbor approach. Data fields for each ground-based scanning radar are presently

Full access
Jiaying Zhang, Liao-Fan Lin, and Rafael L. Bras

Stage IV product incorporates quality-controlled gauge measurements, and the central United States, where this study focuses on, has a dense gauge station coverage, which ensures a high quality of the Stage IV product for the central United States ( Nelson et al. 2016 ). Moreover, nine winter weather events over the eastern Rocky Mountains showed that the Stage IV product agrees closely with gauge measurements ( Cocks et al. 2016 ). Therefore, Stage IV is a trustworthy reference in this study. For

Full access
Gail Skofronick-Jackson, Walter A. Petersen, Wesley Berg, Chris Kidd, Erich F. Stocker, Dalia B. Kirschbaum, Ramesh Kakar, Scott A. Braun, George J. Huffman, Toshio Iguchi, Pierre E. Kirstetter, Christian Kummerow, Robert Meneghini, Riko Oki, William S. Olson, Yukari N. Takayabu, Kinji Furukawa, and Thomas Wilheit

version 03, and the other GPM products are version 04. Direct statistical GV of GPM rainfall-rate estimates relies primarily on existing high-resolution, quality-controlled U.S. national radar network rain-rate products such as the NOAA/National Severe Storms Laboratory–University of Oklahoma Multi-Radar/Multi-Sensor (MRMS) products (e.g., Zhang et al. 2016 , and references therein). Currently, the MRMS system ( ) incorporates data from all polarimetric WSR-88Ds (NEXRAD), a large

Full access
E. F. Stocker, F. Alquaied, S. Bilanow, Y. Ji, and L. Jones

spacecraft. The 180° yaw turns occurred every 2–4 weeks as the orbit precession moved the sun above and below the orbit plane. The onboard Attitude Control System (ACS) was required to provide attitude knowledge to within 0.2° and control to within 0.4° in each axis. These targets were generally met with occasional exceptions, discussed below. The ACS initially used Earth horizon sensors for pitch and roll control, and yaw was updated twice during each orbit using sun sensor data and propagated using Z

Full access