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Dataset Title:  "Profile - R1.x138.079.0015 - CTD_06042013_C3_downcast - 30.17N, 86.67W - 2013-
06-04"
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Institution:  Florida of West University   (Dataset ID: R1_x138_079_0015_CTD_06042013_C3_downcast)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 69)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    depth ?  =  m   35 options
    pressure ?  =  db   35 options
    temperature ?  =  deg C   62 options
    cond ?  =  S/m   68 options
    sal ?  =  PSU   61 options
    oxy1 ?  =  mg/l   69 options
    oxy_s ?  =  percent saturation   69 options
    oxy2 ?  =  mg/l   63 options
    flECO ?  =  mg/m^3   21 options
    wetCDOM ?  =  mg/m^3   29 options
    tur ?  =  NTU   20 options

View:      Map of All Related Data ?      Distinct Data Counts ?     Distinct Data ?      Related Data Counts ?     Related Data ?

 
Map of All Related Data ?   (Refine the map and/or download the image)

To view the map, check View : Map of All Related Data above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.
 


Distinct Data Counts ?

To view the counts of distinct combinations of the variables listed above,
check View : Distinct Data Counts above and select a value for one of the variables above.

 


Distinct Data ?   (Metadata)    (Refine the data subset and/or download the data)  

depth pressure temperature cond sal oxy1 oxy_s oxy2 flECO wetCDOM tur
m db deg C S/m PSU mg/l percent saturation mg/l mg/m^3 mg/m^3 NTU
1.188 1.197 26.827 5.078545 32.0084 4.44621 95.15021 4.66052 0.3556 6.1862 0.3754
1.361 1.37 26.8225 5.077751 32.0058 4.46741 95.59539 4.66093 0.3679 7.296 0.406
1.361 1.37 26.8234 5.077894 32.0062 4.47023 95.65725 4.66085 0.3679 5.0763 0.4121
1.361 1.37 26.8245 5.077609 32.0034 4.46576 95.56184 4.66084 0.3434 5.5696 0.3938
1.361 1.37 26.8248 5.078163 32.0071 4.45806 95.39956 4.66072 0.3556 5.6929 0.3754
1.361 1.37 26.8248 5.078298 32.0081 4.49211 96.12875 4.6607 0.3556 4.9529 0.3693
1.361 1.37 26.8253 5.078276 32.0076 4.47493 95.76164 4.66067 0.3556 6.9261 0.4304
1.361 1.37 26.8254 5.078396 32.0084 4.48271 95.92881 4.66064 0.3556 4.8296 0.3999
1.361 1.37 26.8255 5.077849 32.0044 4.47701 95.80481 4.66074 0.3679 5.4462 0.4853
1.361 1.37 26.827 5.078253 32.0063 4.46282 95.50447 4.66057 0.3556 5.0763 0.3754
1.361 1.37 26.8276 5.078373 32.0067 4.45076 95.24755 4.66051 0.3556 5.0763 0.3938
1.533 1.544 26.8205 5.077414 32.0047 4.44186 95.04489 4.66112 0.3556 5.0763 0.4243
1.533 1.544 26.8249 5.077661 32.0035 4.44513 95.12104 4.66081 0.3556 5.6929 0.4426
1.533 1.544 26.8253 5.078103 32.0063 4.44857 95.19697 4.6607 0.3801 3.8431 0.3877
1.533 1.544 26.8253 5.078388 32.0083 4.4828 95.93057 4.66065 0.3556 5.3229 0.4304
1.533 1.544 26.8255 5.078351 32.0079 4.47635 95.7925 4.66065 0.3679 6.0628 0.3999
1.533 1.544 26.8255 5.078381 32.0081 4.4612 95.46844 4.66064 0.3679 6.3095 0.3754
1.533 1.544 26.8268 5.078448 32.0077 4.47113 95.68291 4.66055 0.3556 6.6794 0.4182
1.533 1.544 26.8269 5.078088 32.0051 4.46541 95.55916 4.66061 0.3679 5.6929 0.4731
1.533 1.544 26.8274 5.078133 32.0051 4.46694 95.59266 4.66057 0.3923 5.3229 0.5464
1.533 1.544 26.8274 5.078553 32.008 4.42656 94.73021 4.66049 0.3679 3.2265 0.3754
1.706 1.717 26.8238 5.077811 32.0052 4.4564 95.3614 4.66085 0.3801 6.1862 0.4609
1.706 1.717 26.825 5.078381 32.0085 4.47601 95.78472 4.66067 0.3434 5.0763 0.3938
1.706 1.717 26.8263 5.078403 32.0077 4.4312 94.82743 4.66059 0.3434 7.5427 0.3754
1.706 1.717 26.8267 5.078456 32.0078 4.46924 95.64212 4.66056 0.3679 4.9529 0.4121
1.706 1.717 26.8275 5.078321 32.0063 4.45519 95.34202 4.66053 0.3556 5.9395 0.3938
1.706 1.717 26.8294 5.078531 32.0065 4.43479 94.90863 4.66038 0.3679 5.5696 0.4121
1.878 1.891 26.8302 5.078793 32.0077 4.41119 94.40534 4.66029 0.3312 6.6794 0.3693
2.223 2.238 26.8329 5.079153 32.0083 4.43762 94.97573 4.66005 0.3434 4.9529 0.3693
3.085 3.106 26.831 5.079161 32.0094 4.44466 95.12387 4.66018 0.3679 6.5561 0.3693
4.119 4.147 26.7602 5.077012 32.0427 4.42912 94.69707 4.66483 0.3556 6.4328 0.3571
4.981 5.015 26.3053 5.072795 32.3291 4.48409 95.29725 4.69306 0.3556 5.4462 0.3816
5.843 5.883 25.9023 5.090071 32.7383 4.52972 95.8369 4.71424 0.3801 6.3095 0.3816
6.705 6.751 25.6696 5.118311 33.11 4.5339 95.75026 4.72293 0.3801 6.1862 0.3693
7.567 7.619 25.4599 5.135619 33.3887 4.57819 96.49522 4.73232 0.4045 5.0763 0.3754
8.429 8.487 25.3744 5.15991 33.629 4.58548 96.64067 4.73276 0.4045 6.3095 0.3693
9.118 9.181 25.3435 5.177372 33.7796 4.5704 96.35505 4.7312 0.4045 4.4597 0.3571
10.153 10.223 25.3245 5.184461 33.8454 4.58303 96.62619 4.73097 0.3923 5.8162 0.3571
11.187 11.264 25.3164 5.203813 33.9931 4.58578 96.75221 4.72765 0.3801 4.8296 0.3571
11.876 11.958 25.3218 5.209568 34.0311 4.57624 96.58068 4.7262 0.3923 5.0763 0.3632
12.738 12.826 25.3212 5.20972 34.0324 4.5834 96.73164 4.72621 0.3801 4.7063 0.3693
13.6 13.694 25.3408 5.223718 34.1202 4.58742 96.89705 4.72227 0.3923 3.7197 0.3571
14.462 14.562 25.3454 5.243138 34.2591 4.5928 97.09497 4.71819 0.3923 3.9664 0.3571
15.324 15.43 25.3765 5.256862 34.3361 4.58927 97.11427 4.71362 0.3801 4.4597 0.351
16.186 16.298 25.3969 5.267161 34.396 4.6032 97.47597 4.71038 0.4167 4.0897 0.3571
17.048 17.165 25.3874 5.271774 34.4369 4.59874 97.38825 4.71006 0.3923 5.9395 0.351
17.91 18.033 25.4066 5.281834 34.4959 4.57956 97.04637 4.70694 0.4045 4.3363 0.3449
18.427 18.554 25.3978 5.285987 34.5329 4.56938 96.83653 4.70665 0.3679 4.9529 0.351
19.289 19.422 25.3886 5.293459 34.5946 4.56002 96.65703 4.70574 0.3923 5.3229 0.3571
20.495 20.637 25.3122 5.30231 34.7177 4.52719 95.90408 4.70857 0.4289 4.583 0.3693
21.357 21.505 25.187 5.289682 34.7201 4.51871 95.52269 4.71855 0.4167 4.4597 0.3571
22.046 22.199 25.1233 5.282946 34.719 4.54017 95.87208 4.72371 0.4167 4.583 0.351
22.736 22.893 24.8955 5.264563 34.7578 4.55359 95.80452 4.7411 0.4289 2.9798 0.3571
23.598 23.761 24.5791 5.239944 34.8186 4.5792 95.85745 4.76525 0.4533 5.3229 0.3693
24.632 24.803 24.1466 5.21683 34.9819 4.61998 96.08564 4.79646 0.4777 4.9529 0.3693
25.494 25.67 23.2186 5.140944 35.1379 4.72294 96.74705 4.8703 0.5998 6.0628 0.406
25.666 25.844 23.0957 5.132212 35.1688 4.71647 96.42479 4.87996 0.6487 5.3229 0.406
25.666 25.844 23.1368 5.139876 35.195 4.75453 97.28731 4.8757 0.6243 4.9529 0.3938
25.666 25.844 23.2299 5.14401 35.1524 4.73314 96.98324 4.86893 0.5998 5.8162 0.3999
25.666 25.844 23.3122 5.156476 35.1824 4.7692 97.87931 4.86106 0.5754 5.6929 0.3938
25.666 25.844 23.357 5.163431 35.2 4.67144 95.95747 4.85676 0.5144 3.9664 0.3693
25.666 25.844 23.8675 5.184705 34.9578 4.63736 95.97059 4.8204 0.551 6.3095 0.3877
25.666 25.844 23.924 5.196388 35.0019 4.72899 97.98733 4.81445 0.551 5.3229 0.3877
25.666 25.844 23.9986 5.196796 34.9464 4.71841 97.86277 4.80976 0.5632 4.3363 0.3999
25.666 25.844 24.1165 5.20649 34.9272 4.67304 97.1083 4.80047 0.5632 5.4462 0.3938
25.838 26.018 23.0444 5.130911 35.1998 4.73976 96.83136 4.88349 0.6365 5.1996 0.3999
25.838 26.018 23.045 5.12921 35.1863 4.71653 96.35021 4.88382 0.6487 4.583 0.406
25.838 26.018 23.9721 5.197387 34.9716 4.72508 97.97058 4.81127 0.5388 5.9395 0.3877
25.838 26.018 23.9932 5.199006 34.9672 4.70902 97.67062 4.80963 0.5266 6.3095 0.3754

In total, there are 69 rows of distinct combinations of the variables listed above. All of the rows are shown above.
To change the maximum number of rows displayed, change View : Distinct Data above.
 


Related Data Counts ?

To view the related data counts,
check View : Related Data Counts above and select a value for one of the variables above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.
 


Related Data ?   (Metadata)    (Refine the data subset and/or download the data)

To view the related data, change View : Related Data above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.


 
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