GTS COARE Land Station Quality Control Report Christopher Harvey and Shawn Smith Tropical Ocean Global Atmosphere (TOGA) Coupled Ocean Atmosphere Response Experiment (COARE) Surface Meteorological Data Processing Center Center for Ocean Atmospheric Prediction Studies The Florida State University June 27, 1995 Report COAREMET 95-2 Version 1.0 Introduction: The data referenced in this report were collected from the Global Telecommunications System (GTS) data set (data acquired from National Center for Atmospheric Research) for TOGA COARE during the Intensive Observing Period (IOP). All data were converted to a standard format and were then preprocessed using an automated data quality checking program. The data were then visually inspected by a data quality analyst who reviewed, modified, and added appropriate quality control (QC) flags to the data. This report summarizes the flags for the GTS data sets, including both flags added by the preprocessor and the analyst. Statistical Information: The data from the GTS during the IOP were expected to include observations every three hours (eight times per day) from 0000 UTC on November 1, 1992 to 2400 UTC on February 28, 1993 (120 days) resulting in at most 960 data values for each variable at each station. Time (TIME), latitude (LAT), longitude (LON), wind direction (DIR), wind speed (SPD), atmospheric pressure (P), temperature (T), and dew point temperature (TD) were quality controlled for forty stations in the Large-scale Soundings Array (LSA) and 39 stations outside the LSA. A listing of the stations, Table 1, indicates the availability of data and the percentage of the data flagged. There were 44,686 records total for these 79 stations and up to eight variables for each record resulting in 357,488 values that were reviewed and checked. Table 2 details the distribution of flags and includes the percentages flagged for each variable sorted by flag type. Table 1: Availability of Data Total Number WMO ID Number of of Data Percent Station Name Number Records Values Flagged Port Blair 43333 300 2400 0 King's Park 45004 931 7448 0 Naha/Kagamizu 47936 931 7448 0.013 Chichijima Island 47971 921 7368 0.027 Minamitorishima 47991 481 3848 0.026 Bangkok 48455 923 7384 0.027 Singapore 48698 888 7104 0.014 Xisha Island 59981 929 7432 0.040 Guam 91217 301 2408 0 Pagan 91222 917 7336 0 Wake Island Airfield 91245 436 3488 0.057 Eniwetok 91251 923 7384 0.027 Woleai Atoll 91317 290 2320 0.129 Puluwat Atoll 91324 321 2568 0.156 Truk/Moen Flight Strip 91334 446 3568 0.140 Lukunor Atoll 91339 330 2640 0.303 Oroluk Island 91343 923 7384 0.027 Ponape Island 91348 420 3360 0.298 Pingelap Atoll 91353 250 2000 0 Kusaie/Kosrae East 91356 213 1704 0.059 Kwajalein/Bucholz 91366 467 3736 0 Ailinglapalap Atoll 91367 291 2328 0.172 Jaluit Atoll/Jabor 91369 229 1832 0.164 Wotje Atoll 91371 284 2272 0.088 Majuro/Marshall Island 91376 423 3384 0.118 Mili/Marshall Island 91377 922 7376 0 Mili Atoll/Marshall Isl.91378 235 1880 0.106 Koror/Palau Island 91408 415 3320 0.060 Yap Island 91413 435 3480 0.029 Nukuoro Atoll 91425 209 1672 0.120 Kapingamarangi Atoll 91434 141 1128 0.354 Taro Island 91502 606 4848 0.062 Munda/New Georgia 91503 738 5904 0.034 Auki/Malaita Island 91507 608 4864 0.062 Honiara 91517 571 4568 0.109 Honiara/Henderson 91520 887 7096 0.042 Nauru Island 91530 6 48 6.250 Santa Cruz/Graciosa 91541 641 5128 0.020 Bauerfield/Efate Island 91557 907 7256 0.014 Noumea/Caledonie 91592 921 7368 0.014 Butaritari Atoll 91601 339 2712 0.037 Tarawa/Bonriki Intl 91610 812 6496 0.031 Beru Island 91623 183 1464 0 Arorae Island 91629 122 976 0 Nanumea Island 91631 436 3488 0.172 Nui Atoll 91636 389 3112 0 Funafuti Intl Airport 91643 804 6432 0.202 Nandi/Nadi Intl 91680 915 7320 0.082 Canton Island 91701 173 1384 0 Pago Pago (Tutuila) 91765 449 3592 0.223 Wewak/Boram 94004 400 3200 0.188 Madang Airport 94014 594 4752 0.063 Lae M.O. 94027 9 72 9.722 Momote/Manus Island 94044 628 5024 0.239 Rabaul/New Britain 94085 438 3504 0.057 Misima/Loaga 94087 743 5944 0.084 Darwin Airport 94120 926 7408 0 Gove Airport 94150 917 7336 0.068 Thursday Island M.O 94175 659 5272 0.057 Broome Airport 94203 744 5952 0 Townsville/Garbutt 94294 928 7424 0.013 Willis Island M.O. 94299 924 7392 0.041 Padang/Tabing 96163 596 4768 0.147 Kuching-In-Sarawak 96413 900 7200 0.028 Kota-Kinabalu 96471 902 7216 0.069 Soekarno-Hatta Intl 96749 522 4176 0.096 Cocos Island M.O. 96996 502 4016 0.050 Menado/Sam Ratulang 97014 526 4208 0.095 Ujungpandang 97180 474 3792 0.105 Kupang/Penfui 97372 438 3504 0 Biak/Mokmer 97560 472 3776 0.053 Sentani 97690 406 3248 0.031 Jayapura/Irian Jaya 97698 282 2256 0.044 Tanah Merah 97876 183 1464 0 Merauke/Mopah 97980 342 2736 0.073 Laoag Intl(Ph-Army) 98223 903 7224 0.083 Legazpi/Luzon Island 98444 902 7216 0.014 Mactan Intl(Civ/Af) 98646 899 7192 0.097 Davao/Francisco Ban 98753 895 7160 0.028 Total 44,686 357,488 0.064 Table 2: Frequency of Flags Assigned for each Variable and Flag Type Not Within Interest- Percent of Realistic ing Suspect Spike in Total Number Variable Records Variable Range Feature Value Data of Flags Flagged TIME 0 0 LAT 0 0 LON 0 0 DIR 3 3 0.007 SPD 3 33 36 0.081 P 14 1 54 69 0.154 T 2 1 68 71 0.159 TD 8 39 47 0.105 Total 10 17 2 197 226 Percent of Total Data Flagged 0.003 0.005 0.001 0.055 0.064 Summary: As can be seen from the statistical information, few data values were flagged. However, several problems appeared throughout the data. The most common were missing data, a spike in all, or most of, the variables at the same date and time, and possible typographical errors. Missing data were rather sporadic and only on a few occasions did it occur for more than several consecutive times. Arorae (91629) had no atmospheric pressure data, and Nauru (91530) and Lae (94027) had less than ten total values for each variable. Spikes in all, or most of, the variables at the same date and time occurred at several stations. Large spikes, usually toward extremely high values, were probably caused by a power surge at the time of observation. These spikes were flagged accordingly. Possible typographical errors were the largest occurring problem. In many cases, it seems that the person who entered the data made a simple key stroke error. For example, several pressures were reported as 2000 mb. where a pressure of 1020 mb. would have made more sense, or, in a three to six hour period, the wind speed might have gone from five meters per second to fifty meters per second and back to five meters per second with no other evidence for the severe increase in speed. Another good example is of a temperature record that goes from 24°C to 14°C and back to 24°C in a three to six hour period at a near-equatorial station. Temperature seemed to have the largest number of possible typographical errors. Many large spikes in the data appeared to simply be the result of a coding error. These values were flagged as spikes, but no attempt to correct the data was made. Final Notes: Overall the data appeared to be quite good and the analyst does not foresee any problems in using the data. There were fifteen stations that had no flags added. Several interesting features were noticed in some of the 79 stations. Most notably were the tropical cyclones Joni, Kina, Nina, Oli, and Oliver, and the supertyphoon, Gay. All of these systems produced dramatic wind speed increases and pressure drops.