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Advancements in Reanalysis: Enhancing Forecast Accuracy and Model Resolution

Explore the impact of improved guess-field-producing models on forecast quality. Compare CDAS and GDAS data from 1995 to 2001, discussing potential improvements in 1950 forecasts and model advancements in resolution and physics. Dive into atmospheric tides and soil moisture conditions, while considering innovative reanalysis methods back to 1850.

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Advancements in Reanalysis: Enhancing Forecast Accuracy and Model Resolution

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  1. Point of view: New Reanalysis makes sense when the guess-field-producing-model has improved over the model used in previous Reanalysis.Also:-) Input data may have improved some. More complete. Errors repaired.-) Known execution errors will be corrected-) Can’t wait too longSo have the forecasts improved???

  2. Has the model improved?? #1 Let’s check the scores of 6hr forecasts against radio-sondes.CDAS (1995;2001) vs GDAS (2001)

  3. How about any improvements to be expected in 1950???, I.e. in a limited data environment.Anecdotal evidence for 1953 gale.

  4. Forecasts valid for Feb, 1, 1953, 3Z • Reanalysis model T62L28 (vintage 1995)

  5. Does a newer model help???T254(2003) vs T62(1995) In addition to resolution, there are many changes in physics. In this 1953 case the analysis is the same.

  6. Other evidence of model improvement:1) Atmospheric tides have hugely improved

  7. Other topics:1) Soil moisture conditions underneath a global Reanalysis. Specify them?, Reanl2 strategy, or a new effort?Thanks to Yun Fan we have global ½ degree monthly analysis 1948-present.2) Playfull asides: Reanalysis without a model (and thus without model biases)For instance one can use EWP or CA as propagator to make the 6hr guess fields.Van den Dool&Anderson3) Reanalysis back to ‘1850’ for monthly conditions using EOT, i.e. orthogonal functions (derived from modern data) tethered to points where we have observations back to ‘1850’.This is how Smith&Reynolds have done the latest SST Reanalysis 1850-present.

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