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Christian D. Kummerow, David L. Randel, Mark Kulie, Nai-Yu Wang, Ralph Ferraro, S. Joseph Munchak, and Veljko Petkovic

overall uncertainty ( Kummerow et al. 2006 ). 2. The semiparametric algorithm The first attempt at making the algorithm more parametric was implemented with GPROF 2010 or TRMM 2A12, version 7, in the TRMM processing system. Over oceans this version abandoned the cloud-resolving model (CRM) database in favor of an observationally generated database that faithfully reproduced raining, nonraining, as well as convective and stratiform rain types over the oceans. The details are discussed in Kummerow et

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Atsushi Hamada and Yukari N. Takayabu

and/or infrared sensors ( Hou et al. 2014 ), as the TRMM PR and TRMM Microwave Imager (TMI) have done. The detectability enhancement of GPM DPR will provide a refined reference standard covering a broad spectrum, from light to heavy precipitation. Light precipitation of the order of 0.1 mm h −1 is mostly related to shallow precipitating clouds. Over eastern parts of the world’s oceans, where deep convection is typically suppressed, such shallow precipitation governs the total precipitation

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F. Joseph Turk, Z. S. Haddad, and Y. You

Global Precipitation measurement dual-frequency precipitation radar (GPM DPR) . J. Atmos. Oceanic Technol. , 33 , 653 – 667 , doi: 10.1175/JTECH-D-15-0097.1 . Harrison, K. W. , Tian Y. , Peters-Lidard C. D. , Ringerud S. , and Kumar S. V. , 2016 : Calibration to improve forward model simulation of microwave emissivity at GPM frequencies over the U.S. Southern Great Plains . IEEE Trans. Geosci. Remote Sens. , 54 , 1103 – 1117 , doi: 10.1109/TGRS.2015.2474120 . Hou, A. Y. , and

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Olivier Hautecoeur and Régis Borde

1. Introduction Atmospheric motion vectors (AMVs) are derived from satellites by tracking clouds or water vapor features in consecutive satellite images. Because they constitute the only upper-level wind observations with good global coverage for the tropics, midlatitudes, and polar areas, especially over the large oceanic areas, the AMVs are continuously assimilated into numerical weather prediction (NWP) models to improve the forecast score. AMVs are extracted routinely by a number of

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Mircea Grecu, William S. Olson, Stephen Joseph Munchak, Sarah Ringerud, Liang Liao, Ziad Haddad, Bartie L. Kelley, and Steven F. McLaughlin

, the agreement between computed and observed temperatures is good. Nevertheless, regional biases are apparent, with warm biases in the subtropical ocean regions and cold biases outside the tropics in the Southern Hemisphere. Table 1. Statistical measures quantifying the agreement between computed and observed brightness temperatures over oceans. Measures include correlation coefficient, bias, and root-mean-square error, and are derived using data from 1 Sep 2014 to 30 Nov 2014. H denotes

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Takuji Kubota, Shinta Seto, Masaki Satoh, Tomoe Nasuno, Toshio Iguchi, Takeshi Masaki, John M. Kwiatkowski, and Riko Oki

DPR and the GPM Microwave Imager (GMI) ( Grecu et al. 2016 ). In rainfall retrievals over the ocean with the CloudSat Cloud Profiling Radar (CPR), a spaceborne W-band radar, the CLWC was based on estimates of the cloud liquid water path (CLWP) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) products collocated with raining CPR pixels ( Haynes et al. 2009 ). Recently, high-resolution global atmospheric simulations have been done using a global cloud-system-resolving model

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