partial listing of AMMA sounding sites stn_name WMO # STN_ID Sonde lat lon type Funchal 08522 32.63 -16.90 Murcia 08430 38.00 -1.17 Gibraltor 08495 36.15 -5.34 Praia 08596 GVNP sipp 14.92 -23.49 Bechar 60571 31.50 -2.25 Dar-El-Beida 60390 36.68 3.21 Tozeur 60760 33.90 8.10 Agadez 61024 DRZA vs80c 16.96 7.98 Niamey 61052 DRRN vs80c 13.47 2.17 Tombouctou 61223 GATB vs80c 16.72 -3.00 Bamako 61291 GABS vs80c 12.53 -7.95 Nouadhibou 61415 GQPP vs80c 20.93 -17.00 Nouakchott 61442 GQNN vs80c 18.10 -15.95 Dakar 61641 GOOY vs80c 14.72 -17.50 Tambacounda 61687 GOTT modem 13.74 -13.66 Conakry 61832 GUCY vs80c 9.57 -13.62 Bangui 64650 FEFF vs92 4.40 18.52 Ndjamena 64700 FTTJ vs80c 12.13 15.03 Ngoundere 64870 FKKN vs80c 7.36 13.56 Douala 64910 FKKD vs80c 4.00 9.73 Abuja 65125 DNAA vs92 9.25 7.00 Parakou 65330 DBBP modem 9.36 2.61 Cotonou 65344 DBBB modem 6.35 2.38 Tamale 65418 DGLE vs92 9.50 -0.85 Ouaga 65503 DFFD modem 12.53 -1.00 Abidjan 65578 DIAP vs80c 5.15 -3.97 Sal 08594 GVAC viz 16.72 -22.95 Guimar 60018 GUIM vs92 28.32 -16.3 In-Salah 60630 DAUI vs92 27.23 2.50 Tindouf 60656 DAOF vs92 27.20 -8.15 Tamanrasset 60680 DAAT vs80 22.79 5.42 Dano 99700 DANO graw 11.16 -3.07 N-Pol 99901 NPOL vs92 14.66 -17.10 file convection: upaqf - high-vertical resolution soundings interpolated to 5-hPa resolution upaqi - not visually inspected nor qc'ed dropsonde aircraft data upagt - gts resolution data upapb - pibal (wind) soundings Data has been quality-controlled and corrected for humidity biases, if possible. Nuret M. et al. 2009: Correction of humidity bias for Vaisala RS80-A sondes during AMMA 2006 observing period. J. Atmos. Ocean. Tech., 25, 2152-2158. ****************************************************************************** CSU Quality Control (QC) procedure for hi_res sonde data ****************************************************************************** 1) Data is put into a common 5 mb ASCII format. Temperature and dew point are interpolated to 5 mb level. Winds are averaged in 5 mb layers. A 1-2-1 filter is applied to the 5 mb wind data to remove unrealistic high-frequency vertical noise. 2) Time mean and standard deviation (sigma) of each field is computed at each 5 mb level. These statistics are computed a second time not using any data that are more than 4*sigma from the mean. These stats are saved to file and used in gross limit checks (see step 3). 3) Objective QC: Perform a gross limit check flagging all data as questionable that is more that 3*sigma from the mean and as bad if data is more than 6*sigma from the mean. Hydrostatic (pressure decreasing with height, height increasing with decreasing pressure) and vertical consistency checks (excessive lapse rates or vertical shears) are performed and flagged accordingly. 4) Subjective QC: Visually QC all sondes at a given site from the surface up to 100 mb. By viewing consecutive skew-Ts in time, large temporal changes in a field can be noted and flagged if suspicious looking. 5) Linearly interpolate (in log pressure) missing data in the vertical if the layer of missing data is 200 mb or less. Interpolated data is flagged accordingly. ****************************************************************************** The idea of using QC flags is to never change a data value, but rather to provide data flags to quide the user. In this approach, it is up to the data user to decide whether or not to use a given data value. QC FLAGS flag meaning 1 parameter good 2 parameter questionable 3 parameter "visually" questionable 4 parameter bad 5 parameter "visually" bad 6 parameter interpolated 7 parameter estimated 8 parameter unchecked 9 parameter missing email questions to Paul Ciesielski at: paulc@atmos.colostate.edu