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Andung Bayu Sekaranom and Hirohiko Masunaga

validation studies have been conducted to analyze the differences, for example, by examining with other satellite products, ground radar, and rain gauge data ( Fu and Liu 2003 ; Prakash et al. 2012 ). The above studies indicate significant improvements for the most recent TRMM algorithms, and the global rain estimations by PR and TMI show a better agreement, although the regional-scale differences remain large. It has also been suggested that the different estimations emerge because of regional

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Claire L. Vincent and Todd P. Lane

made to estimate convective and stratiform heating based on satellite-derived observations of surface precipitation, hydrometeor profiles, and other radar characteristics such as the existence of a brightband region. These methods are summarized in Tao et al. (2006) and may be grouped into methods based on lookup tables of profiles from cloud-resolving models and methods based on a more direct calculation. The SLH algorithm ( Shige et al. 2004 ) builds on the convective stratiform heating (CSH

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Benjamin A. Toms, Susan C. van den Heever, Emily M. Riley Dellaripa, Stephen M. Saleeby, and Eric D. Maloney

microphysics schemes on aerosol concentrations ( Saleeby and van den Heever 2013 ). The simulation accurately captures the evolution of the MJO event from a regional perspective based on the similarities between the simulated and observed intraseasonal structure of zonal winds and precipitation throughout the simulation period. We therefore use the CRM simulation to analyze the convective structure and mesoscale processes of the MJO event. 4. Convective tracking algorithm We utilize a convective cloud

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Casey D. Burleyson, Samson M. Hagos, Zhe Feng, Brandon W. J. Kerns, and Daehyun Kim

acceptance in the community and easy interpretability are two key reasons we selected it for this study. The amplitude of the RMM index reflects the global strength of the MJO, particularly in the upper-tropospheric zonal wind field ( Straub 2013 ). While the amplitude is not always effective for understanding individual events, averaging over multiple events spanning many years enhances the robustness of our results. Because the precipitation tracking algorithms of KC16 and ZL17 track local

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D. Argüeso, R. Romero, and V. Homar

from gauges and satellite estimates. Multiple reasons have been proposed for these problems, including scattering of the microwave signal by mountains ( Huffman et al. 2007 ), misdetection of warm clouds at the top of the mountains by infrared sensors ( Yilmaz et al. 2005 ), and underestimation of heavy rainfall events from shallow orographic systems by microwave algorithms ( Shige et al. 2013 ), among others. In the MC, satellite-derived products tend to underestimate rainfall at high elevations

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Hironari Kanamori, Tomo’omi Kumagai, Hatsuki Fujinami, Tetsuya Hiyama, and Tetsuzo Yasunari

-Julian oscillation . Geophys. Res. Lett. , 34 , L18811 , https://doi.org/10.1029/2007GL030480 . 10.1029/2007GL030480 Ichikawa , H. , and T. Yasunari , 2008 : Intraseasonal variability in diurnal rainfall over New Guinea and the surrounding oceans during austral summer . J. Climate , 21 , 2852 – 2868 , https://doi.org/10.1175/2007JCLI1784.1 . 10.1175/2007JCLI1784.1 Iguchi , T. , T. Kozu , R. Meneghini , J. Awaka , and K. Okamoto , 2000 : Rain-profiling algorithm for the TRMM precipitation radar

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Giuseppe Torri, David K. Adams, Huiqun Wang, and Zhiming Kuang

. The 3-hourly ISH meteorological variables limit the GPS PWV temporal resolution. One way to address this problem is to interpolate the surface temperature and pressure data used in the algorithm to convert ZTD to achieve a much higher resolution. However, although PWV values retrieved from ZTD are not particularly sensitive to surface temperature, they are more sensitive to surface pressure: for example, a 10-K temperature change would give a difference roughly between 0.5 and 1.5 mm in PWV, a 1

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Chu-Chun Chen, Min-Hui Lo, Eun-Soon Im, Jin-Yi Yu, Yu-Chiao Liang, Wei-Ting Chen, Iping Tang, Chia-Wei Lan, Ren-Jie Wu, and Rong-You Chien

-00122.1 . 10.1175/BAMS-D-11-00122.1 Zeng , N. , and J. D. Neelin , 1999 : A land–atmosphere interaction theory for the tropical deforestation problem . J. Climate , 12 , 857 – 872 , https://doi.org/10.1175/1520-0442(1999)012<0857:ALAITF>2.0.CO;2 . 10.1175/1520-0442(1999)012<0857:ALAITF>2.0.CO;2 Zeng , X. , M. Zhao , and R. E. Dickinson , 1998 : Comparison of bulk aerodynamic algorithms for the computation of sea surface fluxes using the TOGA COARE data . J. Climate , 11 , 2628 – 2644

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Ewan Short, Claire L. Vincent, and Todd P. Lane

sensitive to rain, and more accurate than HY2SCAT or OSCAT ( Wu and Chen 2015 ), although all of the scatterometer datasets are developed using algorithms that account for the presence of rain and adjust the wind fields accordingly. Furthermore, OSCAT exhibits zonal wind measurements in some parts of its swath that are biased relative to other parts. OceanSat-2 repeats an identical orbit every two days, so these biases do not get smoothed out by compositing ( Moroni et al. 2013 , their Fig. 4). Two

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