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  • Air–Sea Interactions from the Diurnal to the Intraseasonal during the PISTON, MISOBOB, and CAMP2Ex Observational Campaigns in the Tropics x
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Kyle Chudler, Weixin Xu, and Steven A. Rutledge

method (VAM) to combine wind measurements from moored buoys and several microwave radiometers and scatterometers with reanalysis data from the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) database. From this, global 0.25° gridded 6-hourly wind vector estimates are produced. By combining rainfall information from TRMM and GPM with wind estimates from CCMP, a detailed picture of variability between BSISO phases can be established. An understanding of intraseasonal

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Kenneth G. Hughes, James N. Moum, and Emily L. Shroyer

fluxes at the surface. In the tropics, the atmosphere is sensitive to small SST variations ( Webster and Lukas 1992 ). Increases in SST during the day can lead to air–sea heat flux anomalies of 50 W m −2 relative to what they would be if the sea surface remained at its presunrise temperature ( Fairall et al. 1996 ). Understanding these increases can improve numerical weather forecasts (e.g., Pimentel et al. 2008 ) and inform operational procedures such as corrections to SST based on bulk

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Corinne B. Trott, Bulusu Subrahmanyam, Heather L. Roman-Stork, V. S. N. Murty, and C. Gnanaseelan

). RMM1 and RMM2 are used to trace MJO propagation in the Indian Ocean and are appropriate for use in this study. Evaporation and 10-m winds are provided from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim global atmospheric reanalysis, available daily at 1° spatial resolution from 1979 to present ( http://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/ ; Berrisford et al. 2011 ). ERA-Interim is an improvement of the previous reanalysis ERA-40 as it better

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Wei-Ting Chen, Shih-Pei Hsu, Yuan-Huai Tsai, and Chung-Hsiung Sui

and December 2013 was chosen to compute OLR climatology. The OLR for December 2016 is obtained from NOAA Climate Data Record (CDR) of OLR version 1.2 ( Lee and NOAA CDR Program 2011 ), which is estimated from High-Resolution Infrared Radiation Sounder (HIRS) radiance observations with a 2-day lag. It is given daily with 1° × 1° horizontal resolution. The European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim, hereinafter ERA-Int; Dee et al. 2011 ) is utilized for zonal

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Wei-Ting Chen, Chien-Ming Wu, and Hsi-Yen Ma

every day for the years 1998–2012, with prescribed NOAA Optimum Interpolation (OI) weekly SSTs and sea ice ( Reynolds et al. 2002 ). Initial atmospheric state variables (horizontal velocities, temperature, specific humidity, and surface pressure) are from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim, hereinafter ERA-Int; Dee et al. 2011 ). The initialization procedure is described in Ma et al. (2015) . Based on the results in Ma et al. (2013

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D. A. Cherian, E. L. Shroyer, H. W. Wijesekera, and J. N. Moum

). Furthermore, improved upper-ocean state representation in the CFSv2 operational forecast model run by the Indian Institute of Tropical Meteorology for India’s Monsoon Mission program has been shown to improve rainfall forecasts over central India ( Koul et al. 2018 ). Chowdary et al. (2016) show this model to be biased cold in the top 80 m, biased warm below 100 m, excessively saline in the top 500 m and have excessive vertical turbulent heat fluxes in the top 200 m ( annual mean ). They link the high

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Dipanjan Chaudhuri, Debasis Sengupta, Eric D’Asaro, R. Venkatesan, and M. Ravichandran

stress uncertainty of 5% for wind speeds of 0–10 m s −1 and 10% for wind speeds between 10 and 20 m s −1 . At wind speed higher than 20 m s −1 , we follow the prescription of Powell et al. (2003) . The intensity of a tropical cyclone depends strongly on its wind stress as it can limit the intensity by extracting energy and momentum from the storm. So the accuracy at higher wind speeds is essential for both forecasting and predicting the oceanic response of the tropical cyclones. Model simulations

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Michael B. Natoli and Eric D. Maloney

cycle and its variability is required in order to benefit forecast skill locally and convective parameterizations. This paper aims to add to the body of work on the variability of the diurnal cycle on intraseasonal time scales. Here, the focus is on the overlooked boreal summer season with a focus on the Philippines and South China Sea. The mean state of the MC diurnal cycle has been studied extensively, primarily focusing on the islands of Sumatra, Borneo, and New Guinea. Houze et al. (1981

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Kenneth G. Hughes, James N. Moum, and Emily L. Shroyer

numerics of the MIT GCM. Proc. ECMWF Seminar Series on Numerical Methods: Recent Developments in Numerical Methods for Atmosphere and Ocean Modelling , Reading, United Kingdom, European Centre for Medium-Range Weather Forecasts, 139–149 , https://www.ecmwf.int/node/7642 . Bellenger , H. , and J.-P. Duvel , 2009 : An analysis of tropical ocean diurnal warm layers . J. Climate , 22 , 3629 – 3646 , https://doi.org/10.1175/2008JCLI2598.1 . 10.1175/2008JCLI2598.1 Bogdanoff , A. S. , 2017

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

-Range Weather Forecasts (ECMWF) reanalysis (ERA5; Copernicus Climate Change Service 2017 ). ERA5 has 31-km horizontal resolution at a 1-hourly time scale. RAMS interpolates ERA5 to the simulation horizontal and vertical grid spacing. Lateral and top boundary nudging of the variables listed above, except for soil moisture and temperature, is applied using ERA5 with a 15-min time scale for the outermost 50 grid points for the lateral boundary nudging and the top 5 km of the model for the top boundary nudging

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