Preprints
https://doi.org/10.5194/gmd-2021-409
https://doi.org/10.5194/gmd-2021-409
Submitted as: model experiment description paper
08 Feb 2022
Submitted as: model experiment description paper | 08 Feb 2022
Status: this preprint is currently under review for the journal GMD.

Inland lake temperature initialization via cycling with atmospheric data assimilation

Stanley G. Benjamin1, Tatiana G. Smirnova2,1, Eric P. James2,1, Eric J. Anderson3, Ayumi Fujisaki-Manome4,5, John G. W. Kelley6, Greg E. Mann7, Andrew D. Gronewold5, Philip Chu8, and Sean G. T. Kelley9 Stanley G. Benjamin et al.
  • 1NOAA Global Systems Laboratory, Boulder, CO 80305 USA
  • 2Cooperative Institute for Research in Environmental Science (CIRES), University of Colorado, Boulder, CO 80303 USA
  • 3Civil and Engineering Department, Colorado School of Mines, Golden, CO USA
  • 4Cooperative Institute for Great Lakes Research (CIGLR), University of Michigan, Ann Arbor, MI USA
  • 5University of Michigan, Ann Arbor, MI USA
  • 6NOAA National Ocean Service, Coast Survey Development Laboratory, Durham, NH 03824 USA
  • 7NOAA National Weather Service, White Lake, MI, USA
  • 8NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, MI, USA
  • 9University of Massachusetts, Department of Mathematics and Statistics, Amherst, MA, USA

Abstract. Application of lake models coupled within earth-system prediction models, especially for short-term predictions from days to weeks, requires accurate initialization of lake temperatures. Here, we describe a lake initialization method by cycling within an hourly updated weather prediction model to constrain lake temperature evolution. We compare these simulated lake temperature values with other estimates from satellite and in situ and interpolated-SST data sets for a multi-month period in 2021. The lake cycling initialization, now applied to two operational US NOAA weather models, was found to decrease errors in lake temperature from as much as 5–10 K (using interpolated-SST data) to about 1–2 K (comparing with available in situ and satellite observations.

Stanley G. Benjamin et al.

Status: open (until 20 May 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'General and editorial comments on gmd-2021-409 thru Page 13', Jack Settelmaier, 06 May 2022 reply
    • CC2: 'Completing my 'General and editorial comments on gmd-2021-409'', Jack Settelmaier, 11 May 2022 reply
  • AC1: 'Comment on gmd-2021-409', Stan Benjamin, 13 May 2022 reply
  • RC1: 'Comment on gmd-2021-409', Anonymous Referee #1, 16 May 2022 reply
    • AC2: 'Reply on RC1', Stan Benjamin, 19 May 2022 reply

Stanley G. Benjamin et al.

Stanley G. Benjamin et al.

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Short summary
Application of 1-d lake models coupled within earth-system prediction models will improve accuracy but requires accurate initialization of lake temperatures. Here, we describe a lake initialization method by cycling within a weather prediction model to constrain lake temperature evolution. We compare these lake temperature values with other estimates and found much reduced errors (down to 1–2 K). The lake cycling initialization is now applied to two operational US NOAA weather models.