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Principal Investigator (PI): Svetla Hristova-Veleva, NASA's Jet Propulsion Laboratory (JPL)

Ocean surface winds and wind stress are key components of the Earth system. They are a major driver of the ocean circulation and affect the air-sea interactions, providing fuel to the weather systems by modulating the sensible and latent heat fluxes. Understanding these interactions is critical for improving weather forecasting on a variety of spatial and temporal scales—from the isolated convective cores, to the organized mesoscale systems, to hurricanes, to the seasonal and intraseasonal phenomena such as Madden-Julian Oscillation (MJO), El Niño, and the trends and variability in the large-scale Hadley cell.

Space-borne scatterometer observations from a number of missions have been used extensively for over more than two decades to estimate the ocean surface winds. Significant effort has gone into instrument calibration, algorithm validation, and cross-evaluation. Yet, some small but important inconsistencies remain. Furthermore, while the wind estimates have been routinely produced and used in weather forecasting and ocean modeling, there has not been a systematic effort to produce the dynamically-significant derived products—the wind stress and the spatial derivatives of the wind and stress (their curl and the divergence). Yet, the atmospheric circulation is strongly affected by the wind convergence, while the oceanic circulation is driven by the curl of the stress.

To address the needs of the atmospheric and oceanic communities, we will:

  • Develop a consistent data record of the ocean surface winds as observed by the two technologically-different observing systems—the Ku-band pencil beam one (all NASA and ISRO instruments) and the C-band push-broom one (all EUMETSAT instruments).
  • Develop and produce new Level 2 (swath-based) derived products—wind stress, curl and divergence of the wind, and of the stress.
  • Develop Level 3 daily gridded products for the wind, stress, and derivatives (curl and divergence) for each of the past and current scatterometers. Level 3 products have proven very valuable in advancing the broader science goals of a mission. Their advantages include: i) a format that allows easy integration in space and time to facilitate the development of climatologies and to study variability and trends; ii) easy collocation with observations of other gridded parameters. Consistency between the wind estimates from the different scatterometers has been a long-standing goal of the International Ocean Vector Wind Science Team (IOVWST) and significant progress has been made in this direction.

To achieve our first goal, we will build upon this by adopting the IOVWST Ku-band Geophysical Model Function (GMF), developed to perform equally well across multiple incidence angles, providing consistent wind estimates from the multitude of Ku-band scatterometers (all NASA and ISRO missions). Here, we will use collocated ISRO’s Scatterometer Satellite-1 (ScatSat-1) Ku-band and EUMETSAT’s Advanced Scatterometer (ASCAT) C-band observations to modify the existing C-band GMF such that we eliminate the still remaining small differences between the estimates. We will then produce winds from the entire set of ASCAT and ScatSat observations, using the JPL wind retrieval system.

To achieve our second goal, we will adopt published approaches in estimating wind stress and in computing the spatial derivatives. We will evaluate and compare the different approaches and will develop criteria to select the most appropriate one, benefiting from the knowledge of our team. Using multiple algorithms will also provide a measure of the uncertainty in the derived products.

Our third goal is to produce long-term gridded products using the wind estimates and derived products from all scatterometers, starting with QuikSCAT observations in 1999 and until present. We will create daily gridded data, separately for ascending and descending orbits, to facilitate their use in model validation, data assimilation and in the understanding of the surface winds on a variety of spatial and time scales.