Cummings
James A.
Cummings
James A.
No Thumbnail Available
Search Results
Now showing
1 - 3 of 3
-
ArticleTargeted ocean sampling guidance for tropical cyclones(John Wiley & Sons, 2017-05-13) Chen, Sue ; Cummings, James A. ; Schmidt, Jerome M. ; Sanabia, Elizabeth ; Jayne, Steven R.A 3-D variational ocean data assimilation adjoint approach is used to examine the impact of ocean observations on coupled tropical cyclone (TC) model forecast error for three recent hurricanes: Isaac (2012), Hilda (2015), and Matthew (2016). In addition, this methodology is applied to develop an innovative ocean observation targeting tool validated using TC model simulations that assimilate ocean temperature observed by Airborne eXpendable Bathy Thermographs and Air-Launched Autonomous Micro-Observer floats. Comparison between the simulated targeted and real observation data assimilation impacts reveals a positive maximum mean linear correlation of 0.53 at 400–500 m, which implies some skill in the targeting application. Targeted ocean observation regions from these three hurricanes, however, show that the largest positive impacts in reducing the TC model forecast errors are sensitive to the initial prestorm ocean conditions such as the location and magnitude of preexisting ocean eddies, storm-induced ocean cold wake, and model track errors.
-
ArticleEstimating infrared radiometric satellite sea surface temperature retrieval cold biases in the tropics due to unscreened optically thin cirrus clouds(American Meteorological Society, 2017-02-06) Marquis, Jared W. ; Bogdanoff, Alec S. ; Campbell, James R. ; Cummings, James A. ; Westphal, Douglas L. ; Smith, Nathaniel J. ; Zhang, JianglongPassive longwave infrared radiometric satellite–based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically thin cirrus (OTC) clouds [cloud optical depth (COD) ≤ 0.3]. Level 2 nonlinear SST (NLSST) retrievals over tropical oceans (30°S–30°N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. OTC clouds are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level 2 data, representing over 99% of all contaminating cirrus found. Cold-biased NLSST (MODIS, AVHRR, and VIIRS) and triple-window (AVHRR and VIIRS only) SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5-km-thick OTC cloud placed incrementally from 10.0 to 18.0 km above mean sea level for cloud optical depths between 0.0 and 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud-top height and COD (assuming they are consistent across each platform) integrated within each corresponding modeled cold bias matrix. NLSST relative OTC cold biases, for any single observation, range from 0.33° to 0.55°C for the three sensors, with an absolute (bulk mean) bias between 0.09° and 0.14°C. Triple-window retrievals are more resilient, ranging from 0.08° to 0.14°C relative and from 0.02° to 0.04°C absolute. Cold biases are constant across the Pacific and Indian Oceans. Absolute bias is lower over the Atlantic but relative bias is higher, indicating that this issue persists globally.
-
ArticleOceanGliders: A component of the integrated GOOS(Frontiers Media, 2019-10-02) Testor, Pierre ; de Young, Brad ; Rudnick, Daniel L. ; Glenn, Scott ; Hayes, Daniel J. ; Lee, Craig M. ; Pattiaratchi, Charitha ; Hill, Katherine Louise ; Heslop, Emma ; Turpin, Victor ; Alenius, Pekka ; Barrera, Carlos ; Barth, John A. ; Beaird, Nicholas ; Bécu, Guislain ; Bosse, Anthony ; Bourrin, François ; Brearley, J. Alexander ; Chao, Yi ; Chen, Sue ; Chiggiato, Jacopo ; Coppola, Laurent ; Crout, Richard ; Cummings, James A. ; Curry, Beth ; Curry, Ruth G. ; Davis, Richard F. ; Desai, Kruti ; DiMarco, Steven F. ; Edwards, Catherine ; Fielding, Sophie ; Fer, Ilker ; Frajka-Williams, Eleanor ; Gildor, Hezi ; Goni, Gustavo J. ; Gutierrez, Dimitri ; Haugan, Peter M. ; Hebert, David ; Heiderich, Joleen ; Henson, Stephanie A. ; Heywood, Karen J. ; Hogan, Patrick ; Houpert, Loïc ; Huh, Sik ; Inall, Mark E. ; Ishii, Masao ; Ito, Shin-ichi ; Itoh, Sachihiko ; Jan, Sen ; Kaiser, Jan ; Karstensen, Johannes ; Kirkpatrick, Barbara ; Klymak, Jody M. ; Kohut, Josh ; Krahmann, Gerd ; Krug, Marjolaine ; McClatchie, Sam ; Marin, Frédéric ; Mauri, Elena ; Mehra, Avichal ; Meredith, Michael P. ; Meunier, Thomas ; Miles, Travis ; Morell, Julio M. ; Mortier, Laurent ; Nicholson, Sarah ; O'Callaghan, Joanne ; O'Conchubhair, Diarmuid ; Oke, Peter ; Pallás-Sanz, Enric ; Palmer, Matthew D. ; Park, Jong Jin ; Perivoliotis, Leonidas ; Poulain, Pierre Marie ; Perry, Ruth ; Queste, Bastien ; Rainville, Luc ; Rehm, Eric ; Roughan, Moninya ; Rome, Nicholas ; Ross, Tetjana ; Ruiz, Simon ; Saba, Grace ; Schaeffer, Amandine ; Schönau, Martha ; Schroeder, Katrin ; Shimizu, Yugo ; Sloyan, Bernadette M. ; Smeed, David A. ; Snowden, Derrick ; Song, Yumi ; Swart, Sebastiaan ; Tenreiro, Miguel ; Thompson, Andrew ; Tintore, Joaquin ; Todd, Robert E. ; Toro, Cesar ; Venables, Hugh J. ; Wagawa, Taku ; Waterman, Stephanie N. ; Watlington, Roy A. ; Wilson, DougThe OceanGliders program started in 2016 to support active coordination and enhancement of global glider activity. OceanGliders contributes to the international efforts of the Global Ocean Observation System (GOOS) for Climate, Ocean Health, and Operational Services. It brings together marine scientists and engineers operating gliders around the world: (1) to observe the long-term physical, biogeochemical, and biological ocean processes and phenomena that are relevant for societal applications; and, (2) to contribute to the GOOS through real-time and delayed mode data dissemination. The OceanGliders program is distributed across national and regional observing systems and significantly contributes to integrated, multi-scale and multi-platform sampling strategies. OceanGliders shares best practices, requirements, and scientific knowledge needed for glider operations, data collection and analysis. It also monitors global glider activity and supports the dissemination of glider data through regional and global databases, in real-time and delayed modes, facilitating data access to the wider community. OceanGliders currently supports national, regional and global initiatives to maintain and expand the capabilities and application of gliders to meet key global challenges such as improved measurement of ocean boundary currents, water transformation and storm forecast.