Understanding and Improving Marine Air Temperatures David I. Berry and Elizabeth C. Kent National Oceanography Centre, Southampton David I. Berry and Elizabeth C. Kent National Oceanography Centre, Southampton MARCDAT II, Exeter, 17th - 20th October 2005

Outline  Introduction  Why Marine Air Temperature (MAT)  Sources and current status  Recent developments  Individual observations  Gridded dataset  Results  Summary and future work  Introduction  Why Marine Air Temperature (MAT)  Sources and current status  Recent developments  Individual observations  Gridded dataset  Results  Summary and future work

Intro - Why marine air temperature ?  MAT observations give an independent indicator of climate change and can be used to confirm the trends seen in SST  We also need observation of the MAT to understand air - sea interaction and to calculate the turbulent heat fluxes  We rely on in-situ data for observations of the MAT  MAT observations give an independent indicator of climate change and can be used to confirm the trends seen in SST  We also need observation of the MAT to understand air - sea interaction and to calculate the turbulent heat fluxes  We rely on in-situ data for observations of the MAT

Intro - Sources of in-situ MAT observations  Three different observing platforms  Moored buoys  Drifting buoys  Voluntary Observing Ships  Problems with all platform types  Limited geographic coverage for moored buoys  Uncertain reliability and error characteristic of drifting buoys  Inhomogeneous distribution in time and space  Heating errors, biasing observations by up to 2 °C  Three different observing platforms  Moored buoys  Drifting buoys  Voluntary Observing Ships  Problems with all platform types  Limited geographic coverage for moored buoys  Uncertain reliability and error characteristic of drifting buoys  Inhomogeneous distribution in time and space  Heating errors, biasing observations by up to 2 °C

Intro - Gridded products - current status  Despite these problems the in-situ sources are the only source of air temperature information over the oceans  Hence they need to be handled with care  This has been done in a number of recent datasets, e.g. HadMAT  Night only analysis, excludes observations with daytime heating errors  Bulk height correction  Uncertainty estimates  However there is still room for improvement  Despite these problems the in-situ sources are the only source of air temperature information over the oceans  Hence they need to be handled with care  This has been done in a number of recent datasets, e.g. HadMAT  Night only analysis, excludes observations with daytime heating errors  Bulk height correction  Uncertainty estimates  However there is still room for improvement

Recent developments - Individual ship observations  Platform heights from merged WMO Pub. 47 / ICOADS dataset (Kent et al., 2005)  Allows height correction to standard height (10m)  Without height correction artificial trend introduced  Uncertainty estimates for individual VOS observations (Kent and Berry, 2005, CLIMAR-II IJC special issue)  Allows uncertainty estimates to be made for gridded products  Correction for heating errors in VOS observations (Berry et al., 2004, Presented at CLIMAR-II)  Allows use of day time MAT observations  Platform heights from merged WMO Pub. 47 / ICOADS dataset (Kent et al., 2005)  Allows height correction to standard height (10m)  Without height correction artificial trend introduced  Uncertainty estimates for individual VOS observations (Kent and Berry, 2005, CLIMAR-II IJC special issue)  Allows uncertainty estimates to be made for gridded products  Correction for heating errors in VOS observations (Berry et al., 2004, Presented at CLIMAR-II)  Allows use of day time MAT observations

Berry et al. (2004) - Summary  Heat budget solved analytically to give correction  Heating errors estimated as day - night or ship - model difference  Correction fitted to small subset of estimated errors  Heat budget solved analytically to give correction  Heating errors estimated as day - night or ship - model difference  Correction fitted to small subset of estimated errors Berry, D. I., E. C. Kent and P. K. Taylor, 2004: An analytical model of heating errors in marine air temperatures in ships. Journal of Atmos. Oceanic Technol., 21(8),

Recent developments – Gridded fields  These developments have been combined in OI scheme to give daily 1˚ MAT fields (see poster by Kent and Berry for further details on scheme)  Only VOS observations used (no buoy observations)  Daily analysis (heating error and sampling error estimates)  Individual corrections (height and heating errors)  Uncertainty estimates (natural variability, random errors and sampling)  OI scheme still under development but promising initial results  These developments have been combined in OI scheme to give daily 1˚ MAT fields (see poster by Kent and Berry for further details on scheme)  Only VOS observations used (no buoy observations)  Daily analysis (heating error and sampling error estimates)  Individual corrections (height and heating errors)  Uncertainty estimates (natural variability, random errors and sampling)  OI scheme still under development but promising initial results

Results - Overview  Mean fields  Realistic monthly mean fields and variability  Reasonable uncertainty estimates  Ship - buoy comparisons  Good agreement between daily MATs from buoys and OI  Monthly mean MAT values from OI and buoy observations within a few tenths °C  Air temperature correction  Effect of using uncorrected MAT observations  Mean fields  Realistic monthly mean fields and variability  Reasonable uncertainty estimates  Ship - buoy comparisons  Good agreement between daily MATs from buoys and OI  Monthly mean MAT values from OI and buoy observations within a few tenths °C  Air temperature correction  Effect of using uncorrected MAT observations

Results – Average daily MAT during June 1991 (°C)

Results – Variability (MAT standard deviation , °C)

Results – Uncertainty in daily MAT field averaged over June 1991 (˚C)

Results – Comparison buoys – Subduction array (07/91 – 03/93) Data from Woods Hole Upper Ocean Mooring Data Archive at

Results – Good agreement in daily MAT between OI (red) and observations from NW buoy (black)

Results – Monthly means from buoy (black) and OI (red) within a few tenths ˚C

Results – Similar results at all 4 buoys Black = buoy, Red = Ship OI

Results – Comparison of daily MAT observations from NW buoy (black) with daily OI MAT using uncorrected (green) and corrected (red) ship observations

Summary and Further work  Improved MAT product under development at NOC  Daytime observations recovered with removal of heating errors  Trends due to changing platform heights removed  Uncertainty estimates  Initial comparison to buoy observations promising but further validation needed  Improvements to OI scheme possible  Refinement of spatial scales  Improved estimates of natural variability  Improved observational error estimates (random errors and bias)  Improved MAT product under development at NOC  Daytime observations recovered with removal of heating errors  Trends due to changing platform heights removed  Uncertainty estimates  Initial comparison to buoy observations promising but further validation needed  Improvements to OI scheme possible  Refinement of spatial scales  Improved estimates of natural variability  Improved observational error estimates (random errors and bias)

References  Berry, D. I., E. C. Kent and P. K. Taylor, 2004: An analytical model of heating errors in marine air temperatures in ships. Journal of Atmos. Oceanic Technol., 21(8),  Kent, E. C. and D. I. Berry, 2005: Quantifying random measurement errors in Voluntary Observing Ships’ meteorological observations. Int. J. Climatol., 25,  Kent, E. C., Woodruff, S. D., and D. I. Berry, 2005: WMO Publication No. 47 metadata and an assessment of observation heights in ICOADS. Submitted to Journal of Atmos. Oceanic Technol.  Berry, D. I., E. C. Kent and P. K. Taylor, 2004: An analytical model of heating errors in marine air temperatures in ships. Journal of Atmos. Oceanic Technol., 21(8),  Kent, E. C. and D. I. Berry, 2005: Quantifying random measurement errors in Voluntary Observing Ships’ meteorological observations. Int. J. Climatol., 25,  Kent, E. C., Woodruff, S. D., and D. I. Berry, 2005: WMO Publication No. 47 metadata and an assessment of observation heights in ICOADS. Submitted to Journal of Atmos. Oceanic Technol. Acknowledgements  This work has been funded under NOC core funding CSP1 and MoD/NERC Joint Grant Funding Scheme  ICOADS data has been provided by Steve Worley  The plots shown in this presentation have been created using Ferret available from NOAA’s Pacific Marine Environmental Laboratory  Original OI code used to develop scheme supplied by Dick Reynolds and Diane Stokes  This work has been funded under NOC core funding CSP1 and MoD/NERC Joint Grant Funding Scheme  ICOADS data has been provided by Steve Worley  The plots shown in this presentation have been created using Ferret available from NOAA’s Pacific Marine Environmental Laboratory  Original OI code used to develop scheme supplied by Dick Reynolds and Diane Stokes