...
The impact of snow DA changes has been investigated for 49r1. Snow depth on the Tibetan Plateau and the Rocky Mountains is reduced by assimilating IMS except on complex orography. RMSE of 2m temperature is reduced by 0.5% for winter and 1% for spring in the Northern Hemisphere. In addition, computational time for the 'snow' task is reduced about 30 seconds at 0 UTC by reducing a radius for observation scanning and number of IMS input in 2D-OI.
Jira tickets
Jira server ECMWF Software Support serverId 267ffb4b-b041-3e3e-bee4-0486d22e0a7f key IFS-2463 Jira server ECMWF Software Support serverId 267ffb4b-b041-3e3e-bee4-0486d22e0a7f key IFS-2464 Jira server ECMWF Software Support serverId 267ffb4b-b041-3e3e-bee4-0486d22e0a7f key IFS-2465
Contents
Table of Contents |
---|
List of snow DA changes
current system | candidate for 49r1 | |
---|---|---|
IMS mask | based on altitude (>1500m) | based on SDFOR (>200>300) |
IMS thinning | select 1 from every 36 | select nearest IMS on a gaussian grid of 31km (TL639) |
IMS rejection on IMS mask | No | Yes |
Cap value for snow depth | 1.4m | 3.0m |
RSCALE_Z | 800m | 500m |
SCAN_RAD | 3000km | 300km |
ODB | Improve number of O-A |
...
In order to improve the biases, the condition to assimilate IMS has been changed. In the latest experiment, IMS is not assimilated if standard deviation of filtered sub-grid orography (SDFOR) is more than 200300. This is based on the idea that IMS snow cover from satellite observations could be less accurate on complex orography. The following figures show IMS masks for the current system and the latest experiment.
IMS mask based on altitude (>1500m) | IMS mask based on SDFOR (>200>300) |
---|---|
IMS thinning
In the current operational system, a simple data thinning is applied to IMS by "bufr_filter" (select 1 from every 36 raw observations). However, it leads to inhomogeneous coverage of IMS, especially in some areas. In order to improve it, new data thinning has been tested by "bufr_grid_screen_parallel" as same as other satellite observations. The thinning selects nearest observations on a reduced gaussian grid of 31km (TL639). As a result, the coverage becomes homogeneous and number of observations is reduced from 251926 to 109223.
...
ID | Type | Cycle | Resolution | Start | End | Description |
---|---|---|---|---|---|---|
hut8 | an | 48r1.0 | TCo399 | 02/12/2020 | 28/02/2021 | control |
hwcu | an | 48r1.0 | TCo399 | 02/12/2020 | 31/08/2021 | control (bit-identical to hut8 until 28th Feb) |
hybshxni | an | 48r1.0 | TCo399 | 02/12/2020 | 31/08/2021 | include snow DA changes |
hut7 | an | 48r1.0 | TCo399 | 02/06/2020 | 31/08/2020 | control |
hybuhzbc | an | 48r1.0 | TCo399 | 02/06/2020 | 31/08/2020 | include snow DA changes |
...
Links to IVER and scorecard
- Iver
- https://sites.ecmwf.int/dako/iver/Cy48r1p0_SnowDASnowDA1_12021_2020winterDJF/
- https://sites.ecmwf.int/dako/iver/Cy48r1p0_SnowDASnowDA1_12020_2020summerJJA/
- Scorecard
- filehttps:///permsites.ecmwf.int/dako/quaver/scorecard/hut8_vs_hybshxni_winter/scorecard.htmlfile
- https:///permsites.ecmwf.int/dako/quaver/scorecard/hut7_vs_hybuhzbc_summer/scorecard.html
Results for winter 2020/21 and summer 2020
The following figures show snow depth averaged in Feb 2021. Snow depth on the Tibetan Plateau and the Rocky Mountains is reduced by assimilating IMS. Snow depth on the other mountains are increased by the cap value change.
control (hut8) | test (hybshxni) | hybs hxni - hut8 |
---|---|---|
RMSE of 2m temperature is reduced by about 0.5% for winter in the Northern Hemisphere (especially in North America).
RMSE for 2m temperature against analysis in the NH | RMSE for 2m temperature against observations in the NH |
---|---|
Scorecard for winter | Scorecard for summer |
---|---|
Results of 9-month experiments from Dec 2020 to Aug 2021
Scorecard for winter | Scorecard for spring | Scorecard for summer | Scorecard for 9 months |
---|---|---|---|
Computational cost
- Computational time for the 'snow' task is reduced about 30 seconds (2:00 → 1:30) at 0 UTC by reducing radius for observation scanning and number of IMS input in 2D-OI.
- "bufr_grid_screen_parallel" for IMS thinning takes about 25 seconds, a bit longer than "bufr_filter" (15 seconds).
- Both tasks are not on the critical path, so total computational time is almost the same as before.