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Eun-Kyoung Seo, Sung-Dae Yang, Mircea Grecu, Geun-Hyeok Ryu, Guosheng Liu, Svetla Hristova-Veleva, Yoo-Jeong Noh, Ziad Haddad, and Jinho Shin

sensors. The model was also analyzed relative to a two-stream Eddington model. Results showed that it is more accurate than the Eddington model, especially for ice cloud conditions ( Liu 1998 ). 3. Retrievals of geophysical variables in clear sky To correctly quantify the relationship between observed TBs and precipitation over oceans, information regarding other geophysical variables, such as the sea surface temperature (SST), the surface wind, and the total precipitable water (TPW), is necessary

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S. Joseph Munchak, Robert Meneghini, Mircea Grecu, and William S. Olson

surface emissivity. The relative importance of these mechanisms depends on the relative sensitivity of the Tb and to changes in the rain column and surface wind. Figure 10 shows the change in near-surface precipitation rate retrieved by the GPM combined algorithm over ocean surfaces equatorward of 55° latitude (to eliminate possible sea ice) when the SRT PIA (single frequency for NS retrievals in the top panels; DSRT in the MS retrieval shown in the bottom panels) is replaced with the observed

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

for the standard products, and from ERA-Interim for the final quality-controlled climatology products. Fig . 4. Surface classes defined by GPROF 2014 for a single day. High latitudes occasionally experience colder temperatures than are seen by the NMQ network. Databases for large sections of Siberia as well as sea ice and sea ice edges cannot be populated using NMQ data. These regions were populated using a combination of satellite and model data. CloudSat data was collocated with AMSR-E and

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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

(midlatitude cyclones, tropical convection, etc.). Cloud ice is currently not represented in the combined algorithm, and therefore it is neither included in nor prescribed otherwise. Surface emissivity is modeled as a function of surface wind and temperature over oceans ( Meissner and Wentz 2012 ; Munchak et al. 2016 ) and is prescribed based on the Tool to Estimate Land Surface Emissivities at Microwave Frequencies (TELSEM) database ( Aires et al. 2011 ) over land. The sea surface wind is therefore

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

. , 2015 : Exploiting over-land OceanSat-2 scatterometer observations to capture short-period time-integrated precipitation . J. Hydrometeor. , 16 , 2519 – 2535 doi: 10.1175/JHM-D-15-0046.1 . Wilks, D. S. , 2006 : Discrimination and classification . Statistical Methods in the Atmospheric Sciences , International Geophysics Series, Vol. 91, Academic Press, 529–548 . Willmes, S. , Nicolaus M. , and Haas C. , 2014 : The microwave emissivity variability of snow covered first-year sea ice

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Takuji Kubota, Toshio Iguchi, Masahiro Kojima, Liang Liao, Takeshi Masaki, Hiroshi Hanado, Robert Meneghini, and Riko Oki

might not reflect its true or appropriate value. This characteristic is referred to as “saturation,” and it occurs in the strong surface echo at the near-nadir angles over a calm sea, sea ice, or ice-covered land. Therefore, the linear relationship between NRCS and sidelobe clutter is not suitable for the strong NRCS because of the saturation issue. One way to solve the problem of deviations from a linear relationship is to employ a higher-degree equation. The lowest-degree equation of a monotonic

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Olivier Hautecoeur and Régis Borde

on 19 October 2006) and MetOp-B (launched on 17 September 2012) are in the same polar orbit at 0930 local solar time, equator crossing time, and descending node, and at an altitude of 817 km. The last satellite of the EPS program— MetOp-C —is due to be launched in 2018. The AVHRR/3 on board MetOp is an imager used for global monitoring of various meteorological quantities like sea surface temperature, cloud cover, ice, snow, and vegetation cover characteristics. The AVHRR/3 instrument is

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

). While an attenuation due to cloud ice is negligibly small for Ku and Ka bands, attenuation by the CLWC is larger in the Ka band than in the Ku band, as known in previous works (e.g., Meneghini and Kozu 1990 ). Therefore, estimating precipitation intensity with high accuracy from KaPR observations can require developing a method to estimate the attenuation due to CLWC and incorporate it into the algorithm. CLWC assumptions are common to spaceborne radar precipitation retrievals and regional

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Tomoaki Mega and Shoichi Shige

(see review in Indu and Kumar 2014 ). For an ocean-only footprint which is radiometrically cold and homogeneous, an emission signature from raindrops across the lower-frequency spectrum is essentially used. For a land-only footprint, a scattering signature from ice crystals over the higher-frequency spectrum is used because a radiometrically warm background tends to obscure emissions from raindrops. Coastal regions include radiative contributions from both ocean and land. Because the ratio of

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Atsushi Hamada and Yukari N. Takayabu

increments exhibit a zonally uniform increase with slight asymmetry, possibly related to storm-track activity ( Hoskins and Hodges 2005 ). In the Northern Hemisphere, a significant increment can be observed over the Bering Sea. Relatively lower increments in the Northern Hemisphere are possibly due to the analysis period, when extratropical cyclones in the Northern Hemisphere are generally less active in summer. b. Two kinds of increments in newly detected precipitation profiles Figure 4 shows the 12-dB

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