Search Results

You are looking at 1 - 6 of 6 items for :

  • Operational forecasting x
  • Air–Sea Interactions from the Diurnal to the Intraseasonal during the PISTON, MISOBOB, and CAMP2Ex Observational Campaigns in the Tropics x
  • All content x
Clear All
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

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

( Liebmann and Smith 1996 ) of daily OLR data from 1 June 1974 through 31 January 2017 are taken from NOAA’s Interpolated OLR product at a 2.5° gridded horizontal resolution ( https://www.esrl.noaa.gov/psd/data/gridded/data.interp_OLR.html ). Salinity was also obtained from a coupled operational analysis using the NCEP Climate Forecast System version 2 (CFSv2; Saha et al. 2013 ) to cover the period from 2012 to 2017 at 6-hourly intervals. CFSv2 has superior seasonal and subseasonal prediction capability

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

profiles of temperature T ( z ), and sometimes salinity and velocity u ( z ). Several idealizations have been proposed for use in either climate models or operational procedures like SST corrections. These include linear T and u ( Fairall et al. 1996 ), T and u ∝ z −1/3 ( Fine et al. 2015 ; Large and Caron 2015 ), and T ∝ e − z with either a wind speed–dependent depth scale ( Gentemann et al. 2009 ) or a depth-dependent phase lag ( Matthews et al. 2014 ). These latter two studies

Free access
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

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

temperature feedbacks from operational hurricane forecasts to observations . J. Adv. Model. Earth Syst. , 3 , M11002 , https://doi.org/10.1029/2011MS000075 . 10.1029/2011MS000075 Lotliker , A. A. , T. S. Kumar , V. S. Reddem , and S. Nayak , 2014 : Cyclone Phailin enhanced the productivity following its passage: Evidence from satellite data . Curr. Sci. , 106 ( 3 ), 360 – 361 . Maneesha , K. , V. Murty , M. Ravichandran , T. Lee , W. Yu , and M. McPhaden , 2012

Full access
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

Free access