Publications

Total Number Records: 1125
Page 1 of 113

Search for Pub Year = 9999, to display preprints.

Pub Id Pub Year Author(s) Title
View 1175 2025 Bingham, F., and Bayler, E. Intensifying Seasonality of the Global Water Cycle as Indicated by Sea Surface Salinity
View 1174 2025 Wei, Y., Xu, Q., Yin, X., Li, Y., and Fan, K. A Deep Neural Network Framework for Estimating Coastal Salinity from SMAP Brightness Temperature Data
View 1173 2025 Gawarkiewicz, G., Taenzer, L., Silver, A., Ryan, S., Green, E., Gangopadhyay, A., Musgrave, R., Bahr, F., Kukulya, A., and Yoder, N. Mapping of a Mid-Depth Salinity Maximum Intrusion South of New England in June 2021 and Implications for Cross-Shelf Exchange
View 1172 9999 Guo, S., Zhu, M., Xu, W., Zheng, S., Liu, S., Wu, Y., Du, J., Zhao, C., and Sun, X. Distribution and Fluxes of Marine Particles in the South China Sea Continental Slope: Implications for Carbon Export
View 1171 2025 Koosha, M., and Mastronarde, N. Sensing Outage Probability of Space-Borne Passive Radiometry in Coexistence with an Active Terrestrial Network
View 1170 2025 Grodsky, S., Vandemark, D., and Levin, J. An Eastern Gulf of Maine Salinity Index for Monitoring Winter Scotian Shelf Inflow and Its Relation to Coastal and Interior Pathways
View 1169 2025 Hackert, E., Akella, S., Ruiz-Xomchuk, V., Nakada, K., Jacob, M., Drushka, K., Ren, L., and Molod, A. Impact of Rain-Adjusted Satellite Sea Surface Salinity on ENSO Predictions From the GMAO S2S Forecast System
View 1168 2025 Gopalakrishnan, G., Trott, C., Cruz, E., and Subrahmanyam, B. Understanding Ocean Surface Response to Hurricane Idalia Using SWOT Altimetry in the Gulf of Mexico
View 1167 2025 Thangaprakash, V., Girishkumar, M., Sureshkumar, N., Ravichandran, M., V. Naidu, C., Ramakrishna, S., and Sahoo, A. Mixed Layer Salinity Budget in the Northern Bay of Bengal using the Data from a Mooring Array in 2015
View 1166 2025 Guan, Z., Ren, K., Bao, S., Yan, H., Wang, H., Zhao, Y., and Liu, J. Mixed Layer Depth Estimation From Multisource Remote Sensing Data Using Clustering-Machine Learning Method