1 / 9

Bonn Temporal Downscaling of Heavy Precipitation

This presentation discusses a downscaling technique for temporal resolution of heavy precipitation data, focusing on two principle cases: downscaled averages and synthetic data in observation gaps.

josephsewell
Download Presentation

Bonn Temporal Downscaling of Heavy Precipitation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. TP 2.3 BonnTemporal downscaling of heavy precipitationRalf Lindau 3. Jahrestreffen LandCaRe 2020, Tharandt – 30. November 2009

  2. The task Soil erosion model within the LandCaRe „model chain“ needs rain input with a temporal resolution of 30 min. CLM output is available hourly. Downscaling technique is needed. First step: All model grid boxes with more than 20 mm daily precipitation are extracted from CLM output. 3. Jahrestreffen LandCaRe 2020, Tharandt – 30. November 2009

  3. Two cases of downscaling Two principle cases: Data consists of averages (1 h rain sum  30 min rain sum). Downscaling should produce averages of smaller scale. The variance of each scale should be increased by a certain amount. The pdf should contain more extremes. Data consists of point measurements (DWD rain stations  rain map of Germany) Downscling should produce synthetic data in observation gaps. The variance and pdf should remain constant. 3. Jahrestreffen LandCaRe 2020, Tharandt – 30. November 2009

  4. It results: The original covariance xixj plus the added variance DxDx This is valid for each scale as xi and xj have an arbitrary time lag. Principle of average downscaling Two coarse averages xiand xj are altered by a random Dx. 3. Jahrestreffen LandCaRe 2020, Tharandt – 30. November 2009

  5. Determination of the variance to be added The original (1h) data variance is 4.379 mm2/h2 Averaging over 2,4,8 hours reduces the variance. A linear fit enables us to estimate the potential variance for 0.5 h time resolution: 5.457 mm2/h2 3. Jahrestreffen LandCaRe 2020, Tharandt – 30. November 2009

  6. Effects on semi-variogram Thetotal variance (horizontal lines) is increased (as desired) from 4.379 to 5.455 (mm/h)2 This increase (as desired) is added equally to each scale (see dashed line for difference) 3. Jahrestreffen LandCaRe 2020, Tharandt – 30. November 2009

  7. Effects on pdf Problem: Additive noise creates negative rain values Original pdf Downscaled pdf 3. Jahrestreffen LandCaRe 2020, Tharandt – 30. November 2009

  8. Multiplicative noise Solution: Multiplicative noise instead of additive noise (down – org) / (down + org) Original Downscaled 3. Jahrestreffen LandCaRe 2020, Tharandt – 30. November 2009

  9. Kriging of Rain Beispiel: Regen vom 01.01.1996 bis 07.01.1996 Varianzeigenschaften DWD Original Ergebnis DWD Original Ergebnis Konstante Varianz- reduktion um den BeobFehler BeobFehler: 0.037 mm2/d2 3. Jahrestreffen LandCaRe 2020, Tharandt – 30. November 2009

More Related