Item 4.6 - Taking into account radiosonde position in verification ET-PWFPS Beijing, China Tom Robinson Canadian Meteorological Centre March 12-16, 2018

Changes to radiosonde observations New selection scheme for TAC vs BUFR profiles Use of high-precision of temperature and humidity observations ECMWF rejection criteria for humidity Revised saturation vapor pressure formula (AERK) Revised humidity limits in the analysis 7 February 2018, 1200 UTC

Benefits of using radiosonde data in BUFR Better usage of data because of accurate time and position information for all levels More data because of more levels e.g. every 2 seconds giving ~3500 levels Higher precision of observations Temperature: 0.01 K Dew point: 0.01 K Wind direction: 1 degree Geopotential height: 1 m

Radiosonde data processing Selection process : verifies BUFR profile completeness QC of native BUFR profiles compares native drift and estimated drift based on the native time displacement and the averaged wind between 2 pressure levels. a dry energy norm of short-range forecast departures (O-B) is calculated for both TAC and BUFR profiles. BUFR profile selected only if: the number of observations in the BUFR profile is greater than in the TAC profiles less than 10% of the profile contains suspicious drift positions the dry energy norm of the BUFR profile is less than 1.3 the norm of the TAC profile GTS ~95% 42% 28% Reformatted BUFR No drift positions Native BUFR Drift positions TAC Selection scheme TAC 83% BUFR 17% Data Assimilation Systems

Radiosonde data processing Radiosonde profile Schleswig, Germany 16 December 2015 00Z after thinning Radiosonde profiles are thinned in such a way that one set of observations (temperature, wind and dewpoint) are selected per model levels (dashed green lines). The figure shows an example of data selection for the Schleswig station, which transmitted a high-resolution BUFR profile of 2468 levels and a TAC profile of 80 levels at 0000 UTC, 16 December 2015. After thinning, 68 levels were selected from the BUFR profile, corresponding to all model levels up to 8 hPa, while 29 levels for the temperature and 43 levels for the wind were selected from the TAC profile. The number of levels for temperature and wind are not the same for TAC because significant levels for temperature and wind are not the same. BURF TAC

New rejection criteria for humidity observations Currently all radiosonde humidity observations are assimilated from surface to 70 hPa

New rejection criteria for humidity observations Currently all radiosonde humidity observations are assimilated from surface to 70 hPa New rejection criteria for humidity (based on ECMWF implementation): Rejected if above 100 hPa for Vaisala 92 and 41 series Rejected if above 300 hPa for all other radiosonde types Rejected if T < -60 C for Vaisala series 92 et 41 Rejected if T < -40 C for all other radiosonde types

Change in the number of observations assimilated per day in the GDPS Average number of observations assimilated (in million) during the winter 2017 period GDPS 6.0.0 GDPS 6.1.0 Variation Radiosonde 0.165 0.178 +7.6% AMV 0.278 0.271 -2.2% Radiances 10.857 11.077 +2.0% (CSR +0.6%) Total 12.585 12.794 +1.7%

Verification Scores Verification scores against radiosondes were made for the two following period: Summer 2016: 16 June 2016 – 31 August 2016 Winter 2017: 15 December 2016 – 28 February 2017 The final cycles that use the operational GDPS components is the control (in blue) The cycles that includes all the changes is the experiment (in red)

O-A, O-B over Northern Hemisphere (Winter 2017)

Verification Scores against Radiosondes over Northern Hemisphere (Winter 2017)

Verification Scores against Radiosondes over Southern Hemisphere (Winter 2017)

Verification Scores against Radiosondes over Northern Hemisphere (Summer 2016)

Verification Scores against Radiosondes over Southern Hemisphere (Summer 2016)

Contribution of each component of Phase 1 to the GDPS forecast improvements in the troposphere Northern Hemisphere Summer 2016 Winter 2017 Short-range Medium-range 4D-EnVar RTTOV-12 o AMVs Radiosondes (TAC vs BUFR) Radiosondes (ES screening) CSR (WV channels) GB-GPS Aircraft + + + + + + + _ + + + + _ _ + + _ + + + Southern Hemisphere Summer 2016 Winter 2017 Short-range Medium-range 4D-EnVar RTTOV-12 AMVs o Radiosondes (TAC vs BUFR) Radiosondes (ES screening) CSR (WV channels) GB-GPS Aircraft + + + + + + + + + + + _ + + + +

Mean Drift Distance and Position Error The position errors are calculated by comparing the retrieved positions with the actual positions from the SPARC dataset, which are obtained from the Global Navigation Satellite System (GNSS). The mean horizontal drift distance steadily increases with height and reaches 45 km at 10 hPa for July 2008 and close to 100 km for December 2008. Overall, the mean retrieved position error for both methods is about 10% of the mean balloon drift distance.

Estimation of the Horizontal Position and Time of Radiosonde Data 1200 UTC 15 December 2008

Verification scores against radiosonde data with and without balloon drift Verification scores made with forecasts at synoptic time (0000 and 1200 UTC)

Verification scores against radiosonde data with and without balloon drift Verification scores made with forecasts at synoptic time (0000 and 1200 UTC)

Verification scores against radiosonde data with and without balloon drift Verification scores made with forecasts at synoptic time (0000 and 1200 UTC)

Verification scores against radiosonde data with and without balloon drift Verification scores made with forecasts at synoptic time (0000 and 1200 UTC)

Conclusions Radiosonde drift position has an effect on short-range forecast verification scores above 500 hPa The effects of using both time and position have not been studied The issue is not critical yet as only 30 % BUFR compliance, but needs to be addressed It is proposed that a plan of action be put in place for further study of the issue and for developing a proposal for possible implementation of radiosonde position and time in the CBS verification exchange for the next meeting of the ET-OWFPS