1. Automated Weather Observations from Ships and Buoys: A Future Resource for Climatologists Shawn R. Smith Center for Ocean-Atmospheric Prediction Studies Florida State University Tallahassee, FL USA

2. Overview  The need for in-situ climate data is not limited to land stations  Knowledge of air-sea fluxes (e.g., heat, water, carbon) is essential for understanding global climate processes  NOAA is spearheading the U. S. effort to expand and improve the network of in-situ observations from the global oceans Image from NOAA OGP

3. Example: ENSO Monitoring u Prior to the 1982/83 El Niño, in-situ observations of the tropical Pacific were limited to merchant ships and island stations.  Along came TAO/TRITON – PMEL began installing and maintaining a continuous network of moored buoys – Data from these buoys improved analyses (e.g., FSU winds) used to force models – Provided a data resource to better understand ENSO as part of the climate u Recently this array is transitioning from a research mode to become part of an operational observing system Photo credit: NOAA/PMEL/TAO Project Office

4. Needed Observations  Ideally in-situ measurements near the ocean surface should provide all parameters needed to resolve air-sea fluxes – Meteorology: Winds, air temperature, humidity, pressure, precipitation, radiation (multiple components) – Sea surface: Temperature, salinity, sea state, ice cover – Precise platform navigation (location, orientation, earth-relative motion)  High data accuracy and sampling rates are desired  Detailed metadata are also essential (instrument heights, exposures, etc.)  Must go beyond the tropics, into harsh operational environments (e.g., Southern Ocean, North Pacific) Photo credit: USCG

5.  For the last century, the primary source of weather data over the ocean was observations made by merchant vessel operators  Data primarily collected manually and submitted upon arrival in suitable port  GTS provided for real- time data transmission  Limitations: –Low sampling rates (3- 6 hr) –Minimal navigation information –Incomplete metadata Ships: The early days

6.  More recently advancements in computer technology has led to the deployment of automated weather systems (AWS)  First deployed on research vessels and buoys  In the past 5 years, new initiatives have deployed sensors on volunteer observing ships (merchant ships, yachts, cruise ships)  Initial development underway for moored platforms in extreme environments Ships: Automation Photo credit: WHOI Photo credit: NOAA

7. Typical AWS  High-resolution marine AWS – Sampling rates 1-60 minutes – Continuous recording – Typically bow or mast mounted on R/V Photo credit: WHOI – Data rarely available in real-time (good for independent validation)

8. Automation: future  Standard meteorological package – Fluxes are determined using a bulk modeling approach  Experimental system – Directly measure fluxes – Example: Southampton Oceanography Center AutoFlux – Hourly fluxes sent in real time Photo credit: Southampton Oceanography CentrePhoto Credit: WHOI

9. AWS Application  Quality processed AWS data are ideal for evaluation of global reanalysis fluxes (e.g., Smith et al., 2001, J. Climate)  Sampling rates allow accurate estimation of 6 hourly integrated fluxes

10. AWS Application  R/V-AWS observations have also been used for validating satellite wind sensors (e.g., Bourassa et al., 2003, J. Geophys. Res.) Wind DirectionWind Speed SeaWinds on Midori

11. Final Thoughts  A new initiative is underway to ensure routine delivery of calibrated, quality assured, surface meteorological data collected using AWS on research vessels, volunteer observing ships, and new moored platforms.  User input is essential – Marine AWS data are a new resource for climatologists – Climatologists are asked to provide input to network design  Sampling rates, platform locations, parameters desired  Second workshop on role of marine AWS in a sustained ocean observing system is planned for 17-18 April 2004 (Silver Spring, MD) – Plan to open discussions with user community (modelers, satellite programs, etc.) – Discussion will focus on implementation plans, data user needs, and coordination between R/V, VOS, and buoy programs – Interested participants should contact (smith@coaps.fsu.edu)