1. Earth Science Data Systems (ESDS) Program
  2. Competitive Programs
  3. Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program
  4. Earth System Data Records (ESDRs) of Air-Sea Variables and Fluxes Anchored on Global Moored-Buoy Observations

Earth System Data Records (ESDRs) of Air-Sea Variables and Fluxes Anchored on Global Moored-Buoy Observations

Principal Investigator (PI): Lisan Yu, Woods Hole Oceanographic Institution

The objective of this project is to produce, validate, and distribute Earth System Data Records (ESDRs) of air-sea variables and turbulent fluxes on 0.25° spatial resolution for the period from 1987 onward. The specific air-sea ESDRs include

  • Near ocean-surface wind speed (w) and components (zonal (u) and meridional (v)) merged from scatterometers and microwave radiometers;
  • Near ocean-surface air temperature (Ta) retrieved and merged from microwave scanners, microwave and infrared sounders;
  • Near ocean-surface air specific humidity (Qa) retrieved and merged from microwave scanners, microwave and infrared sounders; and
  • Air-sea turbulent momentum fluxes (zonal (τx) and meridional (τy)), latent heat flux (LH), sensible heat flux (SH), and moisture flux (evaporation (E)) that are computed from the state-of-the-art bulk flux parameterizations using the ESDRs of air-sea variables as input.

The framework of the activities leverages baseline efforts across projects supported by NASA and NOAA. We will integrate the innovative retrieval algorithms and the multi-instrument, multi-sensor fusion techniques for scalar and vector variables that have been developed in house, and further advance and mature the skills through inclusion of additional sensors, calibration, and validation with in situ measurements. Production of these air-sea ESDRs is based upon multi-instrument and multi-sensor fusions, and the calibration and validation with buoy measurements at 140+ sites are to ensure the quality and consistency of the long-term data records.

The work will have two major thrusts. The first is to improve Qa and Ta retrieve methodology through implementing a regime-dependent algorithm. The separation between warm/humid and cold/dry regimes is evident in the statistical relations between buoy-observed Qa/Ta and the brightness temperatures (Tb) from Special Sensor Microwave Imager (SSM/I), Special Sensor Microwave Imager/Sounder (SSMIS) and Advanced Microwave Sounding Unit Swath (AMSU-A) sensors. The regime separation appears to substantiate the previous observations that the physical processes governing the water valor vertical distribution in the atmosphere differ between the strong subsidence regime and active convection regime. Thus, it would be more sensible to treat the two regimes separately than fitting them into one global algorithm.

In addition to the 11 instruments that have been used in developing regime-centered, nonlinear, multivariate regression models for Qa and Ta retrievals, several additional sensors are identified to further advance and mature the algorithms. These sensors include: Atmospheric Infrared Sounder (AIRS), High Resolution Infrared Radiation Sounder (HIRS), Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and Advanced Microwave Scanning Radiometer 2 (AMSR2). The second thrust is to improve data-gap-filling skills for improved data fusion. The effort focuses particularly on the long-term vector wind (u, v, w) satellite record constructed from merging Ku- and C- band scatterometers and microwave radiometers (only wind speed retrievals provided).

Scatterometer records are discontinuous. Atmospheric reanalysis is commonly resorted upon to fill in missing gaps in scatterometer fields, but such a simple approach introduces a great degree of spatial inhomogeneity and is a source of bias in the merged products.

We propose to implement regression-based bias correction before reanalysis winds can be used. Several strategies are proposed for further development. Air-sea fluxes are the primary mechanisms for which the ocean interacts with the atmosphere. It is expected that a full suite of ESDRs for air-sea variables and fluxes will be important for improving our understanding and prediction of short-term variability and long-term trends of the weather and climate patterns.

Last Updated: Aug 29, 2019 at 11:17 AM EDT