Tien Shan

Summary

Introduction

What is the Tien Shan Network?

The Tien Shan network is composed of the KNET, Kaznet and GHENGIS digital broadband stations and together they contribute to the Central Asia Bulletin.

The Tien Shan network records earthquakes both locally as well as globally. These data are useful in a number of geophysical problems. For example, local recordings of teleseisms can be used in teleseismic tomography studies and to address seismotectonic problems.

Summary of activities

Major findings over the project duration

Third year (2001-01-01 to 2001-12-31)

Comparison of earthquake locations from different network bulletins

In general, for local earthquakes, the Tien Shan catalog contains an order of magnitude more events than the global network catalogs, and the magnitude of completeness of the Tien Shan catalog is ~2.5, which greatly exceeds the completeness level of 3.5 of the global catalogs for local earthquakes in this region.

We compare the location (latitude, longitude and depth) of earthquakes determined from the Tien Shan network with data from global (e.g., PDE, REB & QED) and local (e.g., KIS) networks. We can only compare the larger magnitude events (M>3.5) because the global catalogs lack earthquakes of lower magnitude. The difference in latitude and longitude range between 0.2-0.8 and the median difference in depth ranges is 30km. The difference in depth is highly dependent on the 33 km depth that the PDE catalog assigns when the depth of an earthquake is unknown.

Assessing the depth range of the brittle faulting throughout the region

From ~93,000 earthquakes recorded by the Tien Shan network we see that the seismicity in Northern region of Tien Shan is shallower than that in the Southern regions. Although this depth variation is hinted at in other catalogs, the Tien Shan catalog shows this transition in more detail.

Recognition of seismicity migration

Seismicity patterns found in the Tien Shan catalog, in regions even on the edge of our network, are substantially more detailed than in other catalogs. For example, in the Xinjiang province of China, ~2000 earthquakes were recorded by the Tien Shan network during 1997-1999 that exhibit a clear spatial progression of seismicity. This progression, which is confined to a 50 km diameter region, is undetectable in other data catalogs, both global (e.g., REB, PDE, CMT) and local (KIS). The two largest earthquakes in this sequence were the M6.1 August 2, 1998, and the M6.2 August 27, 1998, earthquakes.

Seismic waveform Cross-correlation techniques

A problem-free seismic network with excellent azimutal coverage of the seismic area of interest and an acceptable model of the velocity structure does not guarantee precise earthquake locations can be determined. This is because location errors can result not only from uncertainties in the velocity model but also from uncertainties in the time of the seismic wave's arrival or misidentification of the seismic phases. New algorithms, based on seismic waveform cross-correlation, can account for uncertainties in arrival times and in some cases correct for misidentified phases. These methods make use of the fact that earthquakes from the same region (< 3 km) whose seismic waves travel the same path from source-to-station have similar waveforms. By correlating these similar waveforms sub-sample accuracy of seismic wave arrival times can often be attained. This, in turn, can reduce the relative errors in earthquake locations to tens or hundreds of meters, values that are often an order of magnitude smaller than the errors in the original catalogs.

We demonstrate the power of relocation methods that are based on waveform cross-correlations, with a simple example. Here, we begin by segmenting the data into 10 second windows which include the P-wave arrival time. We align all of the segmented data on the P-wave arrival time and produce a color-coded map of the waveform amplitudes and the resulting waveform stack. The jitter in the waveform stack, and randomness of the color-map, indicates the waveforms are not optimally aligned. We next repeat the process after correlating all waveforms with a master event. The waveform alignments have been greatly improved as indicated in the fringe pattern in the color map and reduction of noise in the stack. Further refinement is obtained by restricting the data to only event pairs that have a high correlation coefficients (>0.6).

For each station in the Tien Shan network, using all available data, we produced figures similar to Figure 7 to determine if the seismic waveforms are similar enough for cross-correlation analyses to be successful. We also test different frequency band filters with the aim to identify one that will eliminate most of the noise while not destroying important aspects of the signal. We find a bandpass filter of 1-8 Hz is optimal. Of the ~15 stations investigated, all are suitable for use in waveform cross-correlation studies.

The optimal alignment of two waveforms is not always indicated by the maximum correlation coefficient that results from a moving window comparison of the data pair. This problem is often due to cycle skips that occur when the seismic waveforms of interest have approximately constant amplitude for multiple cycles and are dominated by a single frequency. For a pair of seismic waveforms with these characteristics, results from a moving window cross-correlation test will have, at each cycle, a peak in the correlation coefficients. These multiple peaks will have approximately the same amplitude, and the maximum peak will not necessarily correspond to the best alignment. One way to avoid cycle skips is to correlate only very short segments of the waveforms. However, if the true P-wave arrival is not in the windowed segment again the method will still fail. This can happen if the automated P-wave arrival time is in error by more than the duration of a few cycles. The most robust way to avoid the cycle-skip problem is to assure the P-wave arrival is in the window of interest by using data that was processed by a seismic analyst. Because each earthquake (~13,800) in the Tien Shan catalog has been analyst reviewed, this data set is ideal for relocation analyses.

Even with the best data, waveform correlation techniques fail when there truly is minimal similarly in the waveforms. Reason for the minimal similarity include rupture on faults with distinctly different orientations, differences in the earthquake source processes (e.g., directivity variations) or near source velocity field variations. These properties may be controlled by the tectonic setting, the mainshock fault orientation and direction of fault slip, the orientation of pre-existing faults in the region, or the magnitude of the background stress field. A byproduct of our work that examines earthquakes with similar waveforms is the identification of those events with dissimilar waveforms. These data will be the focus of a future study.

Aftershock focal mechanism heterogeneity

Aftershock sequences are prime candidates for relocation analysis because of the large number of earthquakes that occur close together in both space and time. We examine the heterogeneity of two aftershock sequences in the Tien Shan region: the 2 August 1998 M6.1 earthquake and the 27 August 1998 M6.2 earthquake. One aim of this study is to determine if it is reasonable to assume a single aftershock fault orientation and slip direction for all aftershocks; an assumption that is often made to simplify computer calculations. We align and stack seismic waveforms based on the analyst picked P-wave arrivals. For better alignment we cross-correlate the waveforms with a master event. Before cross-correlation the fringe pattern, which represents similar seismic waveforms, is undetectable, but after cross-correlation sharpness of the stacks indicates that many of the waveforms are similar.

Correlation of Static Coulomb failure stress change and the spatial distribution of aftershocks

The spatial distribution of aftershocks can sometimes be used to estimate mainshock focal mechanisms. Aftershocks that distribute in a single widely- distributed cloud about the mainshock fault are often an indication of a primarily dipping fault in the region. Aftershocks that locate primarily in the hanging wall are often an indication that the mainshock was a thrust event instead of a normal event. Whereas, aftershocks that primarily distribute beyond the tip zones of the mainshock fault and distribute in two-to-four tear-drop cells are often an indication that the mainshock was a strike-slip event that ruptured a vertical faults. These teardrop shaped distributions typically span the entire depth of the mainshock fault plane. The spatial distributions of aftershocks we describe here can be predicted with theoretical models of static Coulomb failure stress change (CFS).

Static Coulomb failure stress change (CFS) analysis is routinely used to determine if one earthquake triggered another. A correlation between regions of mainshock induced stress increases and aftershock locations is often interpreted as evidence that the CFS model is viable; yet, uncertainties as small as ±30° in the mainshock/aftershock parameters (strike, dip, or rake) can introduce different outcomes. Thus, the most significant result is when a correlation is not attainable.

Maps of CFS are dependant on both the mainshock fault orientation and the aftershock fault orientation.

We applied Coulomb stress analysis to the two ~M6 earthquakes in the Xinjiang province of China. According to the Harvard moment tensor solutions, both events ruptured faults that trend parallel to the geologic structures in the region (~N55W). However, the August 27 event was a vertical strike slip event while the August 2 event ruptured a dipping fault and had a normal component of slip. These slip directions are counter to what we expect for this fold-and-thrust-belt that typically has earthquakes with thrust mechanisms.

We compute CFS models for a number of viable mainshock models of the August 2 event and find that there is minimal correlation between regions of DCFS increase and the aftershock locations. Instead, if we assume the mainshock earthquake was a thrust event, rather than a normal event, we find a strong correlation between regions of CFS increases and the aftershock locations. One explanation for the anti-correlation when normal slip is assumed is that uncertainties in the mainshock and aftershock fault planes are so large that accurate estimates of CFS are unattainable.

Second and first years

Data processing and data delivery to the IRIS Data Management Center.

Station Map

Station map

Station List

(plain text version)

sta ondate offdate lat lon elev staname statype refsta dnorth deast
AAK 1992240 1993239 42.6333 74.4944 1.68 – ss – – –
AAK 1993305 1994241 42.6333 74.4944 1.68 – ss – – –
AAK 1996092 – 42.6333 74.4944 1.68 – ss – – –
AAK 1991244 1992239 42.6333 74.4944 1.68 – ss – – –
AAK 1993240 1993304 42.6333 74.4944 1.68 – ss – – –
AAK 1994242 1996091 42.6333 74.4944 1.68 – ss – – –
AHQI 1999163 2001365 40.9347 78.4578 1.959 – ss – – –
AKSU 1999163 2001365 41.1441 80.1098 1.109 – ss – – –
AKT 1994274 – 50.4348 58.0167 0.36 Aktyubinsk, Kazakstan ss – – –
AKTK 1999267 – 50.4348 58.0167 0.36 Aktyubinsk, Kazakstan ss – – –
AML 1993305 1994241 42.1311 73.6941 3.4 – ss – -55.434 -65.88
AML 1994242 1996091 42.1311 73.6941 3.4 – ss – -55.434 -65.88
AML 1996092 – 42.1311 73.6941 3.4 – ss – -55.434 -65.88
AML 1991244 1992239 42.1311 73.6941 3.4 – ss – -55.434 -65.88
AML 1993240 1993304 42.1311 73.6941 3.4 – ss – -55.434 -65.88
AML 1992240 1993239 42.1311 73.6941 3.4 – ss – -55.434 -65.88
ANA 1997271 2001365 42.7844 77.657 1.813 – ss – – –
ARA 1999174 2001365 41.8491 74.3292 1.484 – ss – – –
ATUS 1997271 2001365 39.716 76.1572 1.225 – ss – – –
BAY 1997190 – 50.8264 75.5537 0.442 Bayanaul, Kazakstan ss – – –
BCHU 1997271 2001365 39.7933 78.7825 1.14 – ss – – –
BGK2 1992240 1993239 42.6451 74.2274 1.64 – ss – 1.344 -21.8
BGK2 1991244 1992239 42.6451 74.2274 1.64 – ss – 1.344 -21.8
BGK2 1993240 1993253 42.6451 74.2274 1.64 – ss – 1.344 -21.8
BRVK 1994244 – 53.0581 70.2828 0.33 Borovoye, Kazakhstan – – – –
CHAT 1999195 2001365 40.918 76.5209 3.031 – ss – – –
CHK 1994204 – 53.6762 70.6152 0.24 Chkalovo, Kazakstan ss – – –
CHKZ 1996015 – 53.6762 70.6152 0.12 Chkalovo, Kazakstan ss – – –
CHM 1993240 1993304 42.9986 74.7513 0.655 – ss – 40.58 20.856
CHM 1993305 1994241 42.9986 74.7513 0.655 – ss – 40.58 20.856
CHM 1994242 1996091 42.9986 74.7513 0.655 – ss – 40.58 20.856
CHM 1991244 1992239 42.9986 74.7513 0.655 – ss – 40.58 20.856
CHM 1992240 1993239 42.9986 74.7513 0.655 – ss – 40.58 20.856
CHM 1996092 – 42.9986 74.7513 0.655 – ss – 40.58 20.856
DGE 1998249 2001365 40.9869 74.469 2.941 – ss – – –
EKS2 1993305 1994241 42.6615 73.7772 1.36 – ss – 3.378 -58.542
EKS2 1991244 1992239 42.6615 73.7772 1.36 – ss – 3.378 -58.542
EKS2 1993240 1993304 42.6615 73.7772 1.36 – ss – 3.378 -58.542
EKS2 1994242 1996091 42.6615 73.7772 1.36 – ss – 3.378 -58.542
EKS2 1996092 – 42.6615 73.7772 1.36 – ss – 3.378 -58.542
EKS2 1992240 1993239 42.6615 73.7772 1.36 – ss – 3.378 -58.542
ERPT 1999220 2000165 42.6011 76.0735 3.79 – ss – – –
HARA 1999174 2001365 40.1742 76.8367 1.585 – ss – – –
HLQI 1999163 2001365 40.8415 77.9643 2.241 – ss – – –
KAI 1998249 2001365 41.5681 75.0134 2.016 – ss – – –
KAR 1997271 2001365 42.4734 78.4003 1.778 – ss – – –
KARL 1999218 2001365 41.4733 77.3093 3.021 – ss – – –
KASH 1997271 2001365 39.5165 75.9243 1.31 – ss – – –
KAZ 1997271 2001365 41.3849 73.9437 1.404 – ss – – –
KBK 1992240 1993239 42.6564 74.9478 1.76 – ss – 2.663 37.012
KBK 1996092 – 42.6564 74.9478 1.76 – ss – 2.663 37.012
KBK 1991244 1992239 42.6564 74.9478 1.76 – ss – 2.663 37.012
KBK 1994242 1996091 42.6564 74.9478 1.76 – ss – 2.663 37.012
KBK 1993305 1994073 42.6564 74.9478 1.76 – ss – 2.663 37.012
KBK 1993240 1993304 42.6564 74.9478 1.76 – ss – 2.663 37.012
KDJ 1997271 2001365 42.1326 77.1856 1.783 – ss – – –
KENS 1999218 2001365 42.3201 79.2362 2.805 – ss – – –
KHA 1997271 2001365 44.2081 73.9973 1.014 – ss – – –
KKL 1997190 – 49.3387 75.3823 0.925 Karkalarinsk, Kazakstan ss – – –
KOPG 1999163 2001365 40.504 79.036 1.114 – ss – – –
KSA 1997271 2001365 41.5425 77.9257 3.398 – ss – – –
KUR 1994206 – 50.7149 78.6208 0.24 Kurchatov, Kazakstan ss – – –
KURK 1996330 – 50.7149 78.6208 0.24 Kurchatov, Kazakstan ss – – –
KZA 1996092 – 42.0778 75.2496 3.52 – ss – -61.384 62.22
KZA 1994242 1996091 42.0778 75.2496 3.52 – ss – -61.384 62.22
KZA 1993240 1993263 42.0778 75.2496 3.52 – ss – -61.384 62.22
KZA 1991244 1992239 42.0778 75.2496 3.52 – ss – -61.384 62.22
KZA 1992240 1993239 42.0778 75.2496 3.52 – ss – -61.384 62.22
MAK 1994207 – 46.8075 81.9774 0.6 Makanchi, Kazakstan – – – –
MAKZ 1996258 – 46.808 81.977 0.6 Makanchi, Kazakstan – – – –
NRN 1997271 2001365 41.423 75.9792 2.019 – ss – – –
PDG 1997271 2001365 43.3275 79.4876 1.286 – ss – – –
PIQG 1999171 2001365 40.3204 77.627 1.736 – ss – – –
POGR 1999195 2001365 41.0183 75.5502 2.357 – ss – – –
TERE 1999195 2001365 40.4757 75.7718 3.684 – ss – – –
TGMT 1999170 2001365 39.9956 76.139 1.823 – ss – – –
TKM 1993305 1994241 42.8601 75.3184 0.96 – ss – 25.502 67.044
TKM 1993240 1993304 42.8601 75.3184 0.96 – ss – 25.502 67.044
TKM 1991244 1992239 42.8601 75.3184 0.96 – ss – 25.502 67.044
TKM 1992240 1993239 42.8601 75.3184 0.96 – ss – 25.502 67.044
TKM2 1994257 1996091 42.9208 75.5966 2.02 – ss – 32.497 89.59
TKM2 1996092 – 42.9208 75.5966 2.02 – ss – 32.497 89.59
TLG 1994208 – 43.233 77.225 1.12 Talgar, Kazakstan – – – –
UCH 1993240 1993304 42.2275 74.5134 3.85 – ss – -45.044 1.562
UCH 1996092 – 42.2275 74.5134 3.85 – ss – -45.044 1.562
UCH 1993305 1994241 42.2275 74.5134 3.85 – ss – -45.044 1.562
UCH 1994242 1996091 42.2275 74.5134 3.85 – ss – -45.044 1.562
UCH 1992240 1993239 42.2275 74.5134 3.85 – ss – -45.044 1.562
UCH 1991244 1992239 42.2275 74.5134 3.85 – ss – -45.044 1.562
ULHL 1996092 – 42.2456 76.2417 2.04 – ss – -41.556 143.567
ULHL 1994252 1996091 42.2456 76.2417 2.04 – ss – -41.556 143.567
USP 1992240 1993239 43.2669 74.4997 0.74 – ss – 70.33 0.428
USP 1991244 1992239 43.2669 74.4997 0.74 – ss – 70.33 0.428
USP 1996092 – 43.2669 74.4997 0.74 – ss – 70.33 0.428
USP 1993305 1994241 43.2669 74.4997 0.74 – ss – 70.33 0.428
USP 1993240 1993304 43.2669 74.4997 0.74 – ss – 70.33 0.428
USP 1994242 1996091 43.2669 74.4997 0.74 – ss – 70.33 0.428
VOS 1994205 – 52.7232 70.9797 0.45 Vostochnoye, Kazakstan ss – – –
WQIA 1997271 2001365 39.7267 75.2473 2.17 – ss – – –
WUS 1988305 – 41.199 79.218 1.457 Wushi, Xinjiang Uygur, China – – – –
XIKR 1999163 2001365 39.8178 77.3666 1.134 – ss – – –
ZRN 1994203 – 52.951 69.0043 0.42 Zerenda, Kazakstan ss – – –
ZRNK 1995143 – 52.951 69.0043 0.38 Zerenda, Kazakstan ss – – –

Total: 103

Channel List

(plain text version)

sta chan ondate chanid offdate ctype edepth hang vang descrip
AAK BHE 1996092 705 – n -0 90 90 –
AAK BHE 1991244 444 1992239 n -0 90 90 –
AAK BHE 1993240 564 1993304 n -0 90 90 –
AAK BHE 1993305 612 1994241 n -0 90 90 –
AAK BHE 1992240 477 1992261 n -0 90 90 –
AAK BHE 1994242 660 1996091 n -0 90 90 –
AAK BHN 1993240 563 1993304 n -0 0 90 –
AAK BHN 1993305 611 1994241 n -0 0 90 –
AAK BHN 1994242 659 1996091 n -0 0 90 –
AAK BHN 1991244 443 1992239 n -0 0 90 –
AAK BHN 1996092 704 – n -0 0 90 –
AAK BHN 1992240 476 1992261 n -0 0 90 –
AAK BHZ 1994242 658 1996091 n -0 0 0 –
AAK BHZ 1996092 703 – n -0 0 0 –
AAK BHZ 1992240 475 1992261 n -0 0 0 –
AAK BHZ 1991244 442 1992239 n -0 0 0 –
AAK BHZ 1993305 610 1994241 n -0 0 0 –
AAK BHZ 1993240 562 1993304 n -0 0 0 –
AAK BLE 1994242 663 1995005 n -0 90 90 –
AAK BLE 1993240 567 1993304 n -0 90 90 –
AAK BLE 1992261 507 1993239 n -0 90 90 –
AAK BLE 1993305 615 1994241 n -0 90 90 –
AAK BLN 1993240 566 1993304 n -0 0 90 –
AAK BLN 1992261 506 1993239 n -0 0 90 –
AAK BLN 1993305 614 1994241 n -0 0 90 –
AAK BLN 1994242 662 1995005 n -0 0 90 –
AAK BLZ 1992261 505 1993239 n -0 0 0 –
AAK BLZ 1993240 565 1993304 n -0 0 0 –
AAK BLZ 1994242 661 1995005 n -0 0 0 –
AAK BLZ 1993305 613 1994241 n -0 0 0 –
AAK HHE 1996092 414 – n -0 90 90 –
AAK HHE 1992240 216 1993239 n -0 90 90 –
AAK HHE 1994242 369 1996091 n -0 90 90 –
AAK HHE 1993240 273 1993304 n -0 90 90 –
AAK HHE 1991244 147 1992239 n -0 90 90 –
AAK HHE 1993305 321 1994241 n -0 90 90 –
AAK HHN 1991244 146 1992239 n -0 0 90 –
AAK HHN 1994242 368 1996091 n -0 0 90 –
AAK HHN 1993305 320 1994241 n -0 0 90 –
AAK HHN 1993240 272 1993304 n -0 0 90 –
AAK HHN 1996092 413 – n -0 0 90 –
AAK HHN 1992240 215 1993239 n -0 0 90 –
AAK HHZ 1993305 319 1994241 n -0 0 0 –
AAK HHZ 1993240 271 1993304 n -0 0 0 –
AAK HHZ 1996092 412 – n -0 0 0 –
AAK HHZ 1991244 145 1992239 n -0 0 0 –
AAK HHZ 1992240 214 1993239 n -0 0 0 –
AAK HHZ 1994242 367 1996091 n -0 0 0 –
AAK HLE 1993240 276 1993304 n -0 90 90 –
AAK HLE 1992240 213 1993239 n -0 90 90 –
AAK HLE 1991244 150 1992239 n -0 90 90 –
AAK HLE 1993305 324 1994241 n -0 90 90 –
AAK HLE 1994242 372 1995006 n -0 90 90 –
AAK HLN 1993240 275 1993304 n -0 0 90 –
AAK HLN 1992240 212 1993239 n -0 0 90 –
AAK HLN 1994242 371 1995006 n -0 0 90 –
AAK HLN 1991244 149 1992239 n -0 0 90 –
AAK HLN 1993305 323 1994241 n -0 0 90 –
AAK HLZ 1992240 211 1993239 n -0 0 0 –
AAK HLZ 1991244 148 1992239 n -0 0 0 –
AAK HLZ 1993240 274 1993304 n -0 0 0 –
AAK HLZ 1994242 370 1995006 n -0 0 0 –
AAK HLZ 1993305 322 1994241 n -0 0 0 –
AAK LHE 1998160 738 – n -0 90 90 –
AAK LHN 1998160 737 – n -0 0 90 –
AAK LHZ 1998160 736 – n -0 0 0 –
AHQI BHE 1999163 51 2001365 n -0 90 90 –
AHQI BHN 1999163 50 2001365 n -0 0 90 –
AHQI BHZ 1999163 49 2001365 n -0 0 0 –
AKSU BHE 1999163 48 2001365 n -0 90 90 –
AKSU BHN 1999163 47 2001365 n -0 0 90 –
AKSU BHZ 1999163 46 2001365 n -0 0 0 –
AKT BHE 1994274 742 – n 0 90 90 –
AKT BHN 1994274 743 – n 0 0 90 –
AKT BHZ 1994274 744 – n 0 0 0 –
AKT HHE 1994274 775 – n 0 90 90 –
AKT HHN 1994274 776 – n 0 0 90 –
AKT HHZ 1994274 777 – n 0 0 0 –
AKTK BHE 1999267 787 – n 0 90 90 –
AKTK BHN 1999267 788 – n 0 0 90 –
AKTK BHZ 1999267 789 – n 0 0 0 –
AKTK HHE 1999267 790 1999268 n 0 90 90 –
AKTK HHE 1999268 808 – n 0 90 90 –
AKTK HHN 1999267 791 1999268 n 0 0 90 –
AKTK HHN 1999268 809 – n 0 0 90 –
AKTK HHZ 1999267 792 1999268 n 0 0 0 –
AKTK HHZ 1999268 810 – n 0 0 0 –
AML BHE 1993305 594 1994241 n -0 90 90 –
AML BHE 1993240 540 1993304 n -0 90 90 –
AML BHE 1992240 465 1992261 n -0 90 90 –
AML BHE 1991244 432 1992239 n -0 90 90 –
AML BHE 1996092 693 – n -0 90 90 –
AML BHE 1994242 642 1996091 n -0 90 90 –
AML BHN 1992240 464 1992261 n -0 0 90 –
AML BHN 1993240 539 1993304 n -0 0 90 –
AML BHN 1993305 593 1994241 n -0 0 90 –
AML BHN 1994242 641 1996091 n -0 0 90 –
AML BHN 1996092 692 – n -0 0 90 –
AML BHN 1991244 431 1992239 n -0 0 90 –
AML BHZ 1993305 592 1994241 n -0 0 0 –
AML BHZ 1991244 430 1992239 n -0 0 0 –
AML BHZ 1994242 640 1996091 n -0 0 0 –
AML BHZ 1992240 463 1992261 n -0 0 0 –
AML BHZ 1996092 691 – n -0 0 0 –
AML BHZ 1993240 538 1993304 n -0 0 0 –
AML BLE 1994242 645 1995005 n -0 90 90 –
AML BLE 1992261 495 1993239 n -0 90 90 –
AML BLE 1993305 597 1994241 n -0 90 90 –
AML BLE 1993240 543 1993304 n -0 90 90 –
AML BLN 1992261 494 1993239 n -0 0 90 –
AML BLN 1994242 644 1995005 n -0 0 90 –
AML BLN 1993305 596 1994241 n -0 0 90 –
AML BLN 1993240 542 1993304 n -0 0 90 –
AML BLZ 1994242 643 1995005 n -0 0 0 –
AML BLZ 1993240 541 1993304 n -0 0 0 –
AML BLZ 1993305 595 1994241 n -0 0 0 –
AML BLZ 1992261 493 1993239 n -0 0 0 –
AML HHE 1994242 351 1996091 n -0 90 90 –
AML HHE 1996092 402 – n -0 90 90 –
AML HHE 1992240 192 1993239 n -0 90 90 –
AML HHE 1993240 249 1993304 n -0 90 90 –
AML HHE 1993305 303 1994241 n -0 90 90 –
AML HHE 1991244 123 1992239 n -0 90 90 –
AML HHN 1994242 350 1996091 n -0 0 90 –
AML HHN 1993305 302 1994241 n -0 0 90 –
AML HHN 1991244 122 1992239 n -0 0 90 –
AML HHN 1996092 401 – n -0 0 90 –
AML HHN 1993240 248 1993304 n -0 0 90 –
AML HHN 1992240 191 1993239 n -0 0 90 –
AML HHZ 1992240 190 1993239 n -0 0 0 –
AML HHZ 1993240 247 1993304 n -0 0 0 –
AML HHZ 1993305 301 1994241 n -0 0 0 –
AML HHZ 1994242 349 1996091 n -0 0 0 –
AML HHZ 1991244 121 1992239 n -0 0 0 –
AML HHZ 1996092 400 – n -0 0 0 –
AML HLE 1993305 306 1994241 n -0 90 90 –
AML HLE 1991244 126 1992239 n -0 90 90 –
AML HLE 1992240 189 1993239 n -0 90 90 –
AML HLE 1993240 252 1993304 n -0 90 90 –
AML HLE 1994242 354 1995006 n -0 90 90 –
AML HLN 1991244 125 1992239 n -0 0 90 –
AML HLN 1992240 188 1993239 n -0 0 90 –
AML HLN 1993240 251 1993304 n -0 0 90 –
AML HLN 1994242 353 1995006 n -0 0 90 –
AML HLN 1993305 305 1994241 n -0 0 90 –
AML HLZ 1991244 124 1992239 n -0 0 0 –
AML HLZ 1994242 352 1995006 n -0 0 0 –
AML HLZ 1992240 187 1993239 n -0 0 0 –
AML HLZ 1993240 250 1993304 n -0 0 0 –
AML HLZ 1993305 304 1994241 n -0 0 0 –
AML LHE 1998160 726 – n -0 90 90 –
AML LHN 1998160 725 – n -0 0 90 –
AML LHZ 1998160 724 – n -0 0 0 –
ANA BHE 1997271 18 2001365 n -0 90 90 –
ANA BHN 1997271 17 2001365 n -0 0 90 –
ANA BHZ 1997271 16 2001365 n -0 0 0 –
ARA BHE 1999174 69 2001365 n -0 90 90 –
ARA BHN 1999174 68 2001365 n -0 0 90 –
ARA BHZ 1999174 67 2001365 n -0 0 0 –
ATUS BHE 1997271 27 2001365 n -0 90 90 –
ATUS BHN 1997271 26 2001365 n -0 0 90 –
ATUS BHZ 1997271 25 2001365 n -0 0 0 –
BAY HHE 1998236 778 – n 0 90 90 –
BAY HHE 1997190 769 1998235 n 0 90 90 –
BAY HHN 1997190 770 1998235 n 0 0 90 –
BAY HHN 1998236 779 – n 0 0 90 –
BAY HHZ 1997190 771 1998235 n 0 0 0 –
BAY HHZ 1998236 780 – n 0 0 0 –
BCHU BHE 1997271 30 2001365 n -0 90 90 –
BCHU BHN 1997271 29 2001365 n -0 0 90 –
BCHU BHZ 1997271 28 2001365 n -0 0 0 –
BGK2 BHE 1992240 459 1992261 n -0 90 90 –
BGK2 BHE 1991244 429 1992239 n -0 90 90 –
BGK2 BHE 1993240 528 1993253 n -0 90 90 –
BGK2 BHN 1993240 527 1993253 n -0 0 90 –
BGK2 BHN 1992240 458 1992261 n -0 0 90 –
BGK2 BHN 1991244 428 1992239 n -0 0 90 –
BGK2 BHZ 1992240 457 1992261 n -0 0 0 –
BGK2 BHZ 1993240 526 1993253 n -0 0 0 –
BGK2 BHZ 1991244 427 1992239 n -0 0 0 –
BGK2 BLE 1992261 489 1993239 n -0 90 90 –
BGK2 BLE 1993240 531 1993253 n -0 90 90 –
BGK2 BLN 1992261 488 1993239 n -0 0 90 –
BGK2 BLN 1993240 530 1993253 n -0 0 90 –
BGK2 BLZ 1992261 487 1993239 n -0 0 0 –
BGK2 BLZ 1993240 529 1993253 n -0 0 0 –
BGK2 HHE 1992240 180 1993239 n -0 90 90 –
BGK2 HHE 1991244 117 1992239 n -0 90 90 –
BGK2 HHE 1993240 237 1993253 n -0 90 90 –
BGK2 HHN 1992240 179 1993239 n -0 0 90 –
BGK2 HHN 1993240 236 1993253 n -0 0 90 –
BGK2 HHN 1991244 116 1992239 n -0 0 90 –
BGK2 HHZ 1992240 178 1993239 n -0 0 0 –
BGK2 HHZ 1993240 235 1993253 n -0 0 0 –
BGK2 HHZ 1991244 115 1992239 n -0 0 0 –
BGK2 HLE 1992240 177 1993239 n -0 90 90 –
BGK2 HLE 1991244 120 1992239 n -0 90 90 –
BGK2 HLE 1993240 240 1993253 n -0 90 90 –
BGK2 HLN 1991244 119 1992239 n -0 0 90 –
BGK2 HLN 1993240 239 1993253 n -0 0 90 –
BGK2 HLN 1992240 176 1993239 n -0 0 90 –
BGK2 HLZ 1991244 118 1992239 n -0 0 0 –
BGK2 HLZ 1992240 175 1993239 n -0 0 0 –
BGK2 HLZ 1993240 238 1993253 n -0 0 0 –
BRVK BHE 1994244 811 – – 0.015 90 90 Station Maintenance. Tests may be in progress.
BRVK BHN 1994244 812 – – 0.015 0 90 Station Maintenance. Tests may be in progress.
BRVK BHZ 1994244 813 – – 0.015 0 0 Station Maintenance. Tests may be in progress.
BRVK BLE 1994244 814 – – 0.015 90 90 NRTS data inserted into field tape data gaps, time
BRVK BLN 1994244 815 – – 0.015 0 90 NRTS data inserted into field tape data gaps, time
BRVK BLZ 1994244 816 – – 0.015 0 0 NRTS data inserted into field tape data gaps, time
CHAT BHE 1999195 72 2001365 n -0 90 90 –
CHAT BHN 1999195 71 2001365 n -0 0 90 –
CHAT BHZ 1999195 70 2001365 n -0 0 0 –
CHK BHE 1994204 745 – n 0 90 90 –
CHK BHN 1994204 746 – n 0 0 90 –
CHK BHZ 1994204 747 – n 0 0 0 –
CHK HHE 1994204 748 – n 0 90 90 –
CHK HHN 1994204 749 – n 0 0 90 –
CHK HHZ 1994204 750 – n 0 0 0 –
CHKZ BHE 1996015 793 – n 0 90 90 –
CHKZ BHN 1996015 794 – n 0 0 90 –
CHKZ BHZ 1996015 795 – n 0 0 0 –
CHM BHE 1992240 450 1992261 n -0 90 90 –
CHM BHE 1994242 618 1996091 n -0 90 90 –
CHM BHE 1996092 678 – n -0 90 90 –
CHM BHE 1993240 510 1993304 n -0 90 90 –
CHM BHE 1993305 570 1994241 n -0 90 90 –
CHM BHE 1991244 420 1992239 n -0 90 90 –
CHM BHN 1994242 617 1996091 n -0 0 90 –
CHM BHN 1996092 677 – n -0 0 90 –
CHM BHN 1993305 569 1994241 n -0 0 90 –
CHM BHN 1993240 509 1993304 n -0 0 90 –
CHM BHN 1992240 449 1992261 n -0 0 90 –
CHM BHN 1991244 419 1992239 n -0 0 90 –
CHM BHZ 1994242 616 1996091 n -0 0 0 –
CHM BHZ 1993240 508 1993304 n -0 0 0 –
CHM BHZ 1993305 568 1994241 n -0 0 0 –
CHM BHZ 1996092 676 – n -0 0 0 –
CHM BHZ 1991244 418 1992239 n -0 0 0 –
CHM BHZ 1992240 448 1992261 n -0 0 0 –
CHM BLE 1993305 573 1994241 n -0 90 90 –
CHM BLE 1992261 480 1993239 n -0 90 90 –
CHM BLE 1993240 513 1993304 n -0 90 90 –
CHM BLE 1994242 621 1995005 n -0 90 90 –
CHM BLN 1993305 572 1994241 n -0 0 90 –
CHM BLN 1993240 512 1993304 n -0 0 90 –
CHM BLN 1994242 620 1995005 n