Most-Logged Stations in CQ WW SSB

As I mentioned in my last post, I thought that it might be interesting to use the public CQ WW logs to see which calls are logged most often in CQ WW, and how that changes from year to year. In this post I'll tabulate the SSB results.

As before, the first column is the callsign. The second column is the total number of times that the call appears in logs. That is, if a station worked HC8N on six bands, that will increment the value in the second column of the HC8N row by six. The third column is the percentage of logs that contain the callsign at least once.

CQ WW 2005:

Callsign	Appearances	% logs
CT3YA	6510	73
LZ9W	5616	66
V26B	5601	61
6Y2Z	5481	57
DF0CG	5359	65
RW2F	5259	63
OT5A	5251	65
MD4K	5007	60
9A7A	4999	62
DQ0Q	4994	62

CQ WW 2006:

Callsign	Appearances	% logs
DR1A	6414	71
DF0HQ	5905	67
MD4K	5707	60
CT3YA	5676	66
OT6A	5548	64
V26B	5539	59
EA8AH	5515	65
3V6T	5397	61
9A7A	5356	63
CT9L	5287	63

CQ WW 2007:

Callsign	Appearances	% logs
DR1A	6813	66
AO8A	6582	65
DF0HQ	6488	63
V26B	6426	57
CQ9K	6325	65
TS6A	6257	60
OT5A	6020	61
HC8N	5917	55
C50C	5866	57
LZ9W	5851	59

CQ WW 2008:

Callsign	Appearances	% logs
AO8A	6008	63
DF0HQ	5722	62
OT5A	5357	60
LZ9W	5205	57
P33W	4940	56
D4C	4898	54
CT9L	4714	54
6Y1V	4692	48
IR4X	4631	55
CN3A	4513	54

CQ WW 2009:

Callsign	Appearances	% logs
DR1A	7995	68
DF0HQ	7402	63
9A1P	7324	64
LZ9W	7089	60
YT9X	6976	61
AO8A	6769	60
OT5A	6361	59
OH0Z	6334	56
OL7R	6226	58
EE2W	6039	59

CQ WW 2010:

Callsign	Appearances	% logs
DR1A	7986	66
CR3A	7893	62
EF8R	7875	62
CN3A	7778	63
DF0HQ	7158	60
LZ9W	7036	59
A73A	6690	53
CR2X	6120	53
PJ2T	5973	45
OT5A	5894	55

CQ WW 2011:

Callsign	Appearances	% logs
DR1A	10118	66
C5A	9450	65
9A1P	9314	61
C37N	8705	56
CR3L	8323	59
OT5A	8211	58
LZ9W	8156	56
K3LR	8040	55
A73A	7487	53
DF0HQ	7291	52

CQ WW 2012:

Callsign	Appearances	% logs
DR1A	10734	65
HK1NA	10171	62
C5A	10060	63
LZ9W	9798	60
9A1A	9779	61
DF0HQ	9328	59
OT5A	9279	58
CN3A	9029	60
V26B	8704	55
PJ4X	8703	56

CQ WW 2013:

Callsign	Appearances	% logs
ES9C	12863	70
D4C	12274	69
DR1A	11230	66
HK1NA	10631	61
II9P	10559	63
IG9Y	9991	59
PJ2T	9896	59
K3LR	9452	57
LZ9W	9445	57
CN3A	9142	60

CQ WW 2014:

Callsign	Appearances	% logs
II9P	11128	66
HK1NA	10676	62
LZ9W	10366	60
CN3A	9526	62
DF0HQ	9393	57
CN2AA	8648	58
OT5A	8607	55
K3LR	8409	54
P33W	8250	55
P40L	8246	54

CQ WW 2015:

Callsign	Appearances	% logs
CN2AA	15100	78
CN2R	10017	63
9A1A	9872	61
CN3A	9693	61
DF0HQ	9237	59
LZ9W	9045	56
HK1NA	8936	54
PJ2T	8456	51
K3LR	8310	54
EF8R	8254	57

We can also look at ten-year spans:

CQ WW 2005 to 2014:

Callsign	Appearances	% logs
LZ9W	68565	55
DF0HQ	66790	55
DR1A	65618	52
OT5A	64050	54
K3LR	61458	52
CN3A	59763	53
PJ2T	59700	47
LY7A	56378	50
V26B	54656	46
P33W	50855	45

CQ WW 2006 to 2015:

Callsign	Appearances	% logs
DF0HQ	76024	59
LZ9W	71994	54
CN3A	69456	58
OT5A	66397	53
K3LR	65974	52
DR1A	65622	49
PJ2T	63768	47
LY7A	58901	49
P33W	58520	49
V26B	56197	45

Most-Logged Stations in CQ WW CW

I thought that it might be interesting to use the public CQ WW logs to see which calls are logged most often in CQ WW, and how that changes from year to year.

Looking at CW first (SSB will be a separate post):

CQ WW 2005:

Callsign	Appearances	% logs
HC8N	7302	73
PJ2T	6405	66
LZ9W	6329	75
IH9P	5881	69
TZ5A	5378	67
RW2F	5293	69
DQ0Q	5169	69
DF0CG	5106	66
EA6IB	5074	66
UU7J	5062	65

The first column is the callsign. The second column is the total number of times that the call appears in logs. That is, if a station worked HC8N on six bands, that will increment the value in the second column of the HC8N row by six. The third column is the percentage of logs that contain the callsign at least once.

CQ WW 2006:

Callsign	Appearances	% logs
HC8N	8170	73
IH9P	8167	75
5A7A	7715	74
EA8EW	7405	64
TZ5A	7111	70
Z38N	7105	73
CT9L	6753	73
EA6IB	6590	70
DF0HQ	6311	70
DR1A	6160	69

CQ WW 2007:

Callsign	Appearances	% logs
LZ9W	7797	73
EF8M	7443	72
3X5A	7395	66
EA6IB	6721	68
HC8N	6705	60
D4C	6522	63
HI3A	6274	58
PJ4A	6181	62
DF0HQ	6172	65
P3F	6138	64

CQ WW 2008:

Callsign	Appearances	% logs
D4C	7710	71
HC8N	7515	64
CT9L	7193	71
3X5A	6870	63
LZ9W	6691	70
DF0HQ	6351	67
EE2W	6160	54
KP2M	6009	58
P3F	5982	64
PJ2T	5888	57

CQ WW 2009:

Callsign	Appearances	% logs
HC8GR	8066	61
LX7I	7693	68
DR1A	7300	67
CR3L	7208	67
EE2W	6917	64
LZ9W	6776	64
DF0HQ	6736	63
6Y1V	6408	56
EA8URL	6268	60
UU7J	6119	58

CQ WW 2010:

Callsign	Appearances	% logs
C5A	9102	68
EA2EA	8940	71
LZ9W	8790	70
9A1A	8286	69
CR3L	8157	68
DF0HQ	8025	67
PJ2T	7748	55
YT2W	7634	67
KC1XX	7141	57
LX7I	7119	62

CQ WW 2011:

Callsign	Appearances	% logs
C5A	11477	73
DR1A	10731	70
9A1A	10399	70
LZ9W	9739	67
CR3L	9509	68
PJ2T	9474	62
SK3W	9354	65
DF0HQ	9221	65
TK4W	8555	61
C6AAW	8534	57

CQ WW 2012:

Callsign	Appearances	% logs
D4C	14304	79
C5A	12357	73
HK1NA	11133	67
Z38N	10900	67
CR3L	10696	68
9A1A	10420	69
DR1A	10122	65
LZ9W	10090	67
PJ4A	8995	59
PJ2T	8773	57

CQ WW 2013:

Callsign	Appearances	% logs
D4C	15607	83
ES9C	12575	74
9A1A	11606	73
ED6A	11477	69
HK1NA	11264	68
PJ2T	11058	66
DR1A	10666	66
LZ9W	10250	67
CR3L	10103	67
IR9Y	9471	63

CQ WW 2014:

Callsign	Appearances	% logs
CN2AA	16754	83
9A1A	12234	73
LZ9W	11784	70
HK1NA	11660	68
9K2HN	11499	70
PJ2T	10433	63
EA5KA	10412	66
DR1A	10151	64
DF0HQ	10093	65
K3LR	9911	61

CQ WW 2015:

Callsign	Appearances	% logs
D4C	11129	68
9A1A	11047	72
LZ9W	10375	68
PJ2T	9498	58
CR3L	9456	63
CN2AA	8934	59
LX7I	8933	62
YT5A	8827	62
P33W	8764	60
DF0HQ	8537	61

We can also look at ten-year spans:


CQ WW 2005 to 2014:

Callsign	Appearances	% logs
LZ9W	81702	68
PJ2T	75453	59
DF0HQ	70559	60
DR1A	66706	55
K3LR	64391	54
W3LPL	63800	53
9A1A	62050	53
LX7I	61869	56
LY7A	61258	57
PJ4A	60797	52

CQ WW 2006 to 2015:

Callsign	Appearances	% logs
LZ9W	85748	67
DF0HQ	79095	64
PJ2T	78546	58
9A1A	73092	58
PJ4A	68977	56
W3LPL	68458	54
K3LR	68360	55
LX7I	67527	57
D4C	67448	48
DR1A	66737	52

Online Files Now Hosted By Adrive

I have been using copy.com to host the files I make available online. Unfortunately, that service is going to close in a few weeks' time.

So I have copied the files over to the Adrive hosting service.

The relevant files are to be found at the following new locations:

• RBN data: https://www.adrive.com/public/cQwkEB/rbn
• CQ WW logs: https://www.adrive.com/public/Ws5CQw/cq-ww
• CQ WPX logs: https://www.adrive.com/public/BaAVjK/cq-wpx

I am sorry for any inconvenience caused by this change.

The files will continue to be available at their original locations on copy.com until that service is closed.

"Nowhere to Run" available in electronic formats

My Christian action novel (for want of a better description), Nowhere to Run, is now available in several electronic formats:

• Amazon for the Kindle ($3.50);
• Smashwords in several formats ($3.50);
• Barnes and Noble for the NOOK ($3.50);
• iTunes store for Apple devices ($3.99).

Don't ask me why Apple charges more than the price I set. They seem to do this with all my books.

Most of the above links also allow you to read a sample, typically 10 to 15 percent of the book.

This book was inspired by events in the life of a fellow member of the Rotary Club of Boulder (Colorado) and his wife.

You can, of course, still purchase a print version of the book.

Plots from CQ WW logs

The availability of the CQ WW public logs covering the period 2005 to 2015 allows us to look at various trends over that period.

The number of logs shows that for both CW and SSB the total number of entrants has been more or less stable for the most recent years, following a period of increase:

Breaking it down between unassisted and assisted, we see:

The number of assisted entrants shows a remarkably constant increase from year to year, whereas the unassisted numbers are close to constant. It will be interesting to see whether the assisted lines cross the unassisted lines next year.

The geographical distribution of entrants on CW has changed little over the period:

As I have noted before, on SSB the percentage of logs from western EU has decreased somewhat, and the percentage from JA/HL and zone 28 has slightly increased.

Of more interest (well, I think so, anyway) than the numbers of logs is the number of QSOs in the logs:

This shows the perhaps not-unexpected reality that as the number of assisted logs has increased, the number of QSOs in the top 10 percent of logs (as determined by number of QSOs in the log) has steadily declined. The median number of QSOs (represented by the coloured near-horizontal lines) has varied little, with only SSB Assisted showing a clear change in recent years, although both CW and SSB Assisted show a more or less gentle trend downwards in the median number of QSOs in the logs.

One unexpected fact emerges: the median log in CQ WW CW has consistently contained about a hundred more QSOs than has the median CQ WW SSB log.  I'm not sure why this should be, but it is a robust result.

Now, how about whether the CQ WW contest is actually gaining in popularity, as is often claimed (without any supporting evidence for the declaration, as far as I know). How many people are actually getting on the air and making QSOs in the contest?

Different people may set the bar as to how many times a call has to appear in the logs of other stations at different values. For example, if a call appears only once, it might well be a bust rather than a real participant. Even if a call appears, say, twenty times, that might merely reflect a busted spot that was logged by twenty people who did not check the call.

So we can produce a series of nearly-parallel lines, setting the required number of appearances at different values.

On CW, it makes no substantive difference which definition of participation one chooses: the number of participants is essentially unchanged from year to year. Any increase in recent years is marginal at best.

On SSB, there is indication of a slight decline in recent years.

Finally, it's of some interest to plot the year-by-year number of distinct QSOs made on each band. By "distinct" I mean that a QSO both sides of which are logged by entrants counts just once.

For CW:

And for SSB:

In both cases, one can see the importance of 10m in determining the total number of distinct QSOs. However, while 10m is the most dominant band on SSB in years of good propagation, that is not true on CW: on CW, in years of good propagation, 10m, 15m, 20m and 40m provide essentially identical contributions to the total.

We also see that on CW, 20m and 40m provide nearly identical numbers throughout the cycle; on SSB, 20m and 15m have this characteristic.

The relative lack of dominance of 10m on CW is likely due to the timing of the two contests (indeed, I wish that both CQ WPX and CQ WW would swap the SSB and CW events each year; with the current calendar, CW suffers in both types of contest). By the end of November, the number of hours of common daylight between EU and NA are simply too few for 10m to be dominant.

"Nowhere to Run" available on Kindle

My book Nowhere to Run is now available for the Kindle. You may read a sample (from the hardcopy version).

Obtaining Magnetometer Data

The Problem  

 

Until a few days ago, it was possible to obtain near-real-time ("NRT") magnetometer data files from directories housed below http://magweb.cr.usgs.gov/data/magnetometer/. Attempts to reach that location, and the subordinate files that held the actual NRT data, now return:

The requested service is temporarily unavailable. Please try later.

After waiting for several days for something more useful to be returned, I finally realised that temporarily here seems to be government-speak for permanently.

There is still a way to obtain NRT magnetometer data, but it's vastly more complicated than simply downloading data from a URL. I do not know why the sites that make the data available do not hide all the complexity from users and simply provide a URL as an interface, but the fact is that, at least for now, they do not, and we now have to go through a rather tortuous process to obtain data that was, until a few days ago, essentially trivial to obtain.

Obtaining the data in the absence of a URL

These are the steps that I had to take on debian stable; other Linux distributions and other operating systems will likely differ in details, but the basic idea should be the same.

First, one needs to install python, since the data are accessed via a python script. Debian, like most  Linux distributions installs python by default.
Next, install the packages python-numpy, python-scipy and python-flake8 from the distribution repositories.

Now, install obspy by following the instructions at: https://github.com/obspy/obspy/wiki/Installation-on-Linux-via-Apt-Repository. If using a different distribution or operating system, follow the pertinent instructions at https://github.com/obspy/obspy/wiki.

Now that python and the necessary libraries are available, we need to download the actual software package that does the work; we get this from: https://github.com/usgs/geomag-algorithms.

I note that the installation instructions on the site read, in their entirety:
First time install. Walk through dependencies and other considerations.

If one looks inside the downloaded package, there is no sign of the standard INSTALL file. Neither is there a README or README.FIRST file. There is a README.md file, but its contents merely repeat the above "instructions" from the site. So I simply unpacked the package in a reasonable location and used it as-is. I am sure that that is not what one is supposed to do, but in the absence of explicit, detailed installation instructions, it will have to do.

After unpacking that software somewhere suitable, we have access to the script we need, which is geomag.py in the .../bin directory.

The documentation is... well, the politest word I can think of is "sparse". As unfortunately seems to be so often the case when trying to use government data, it is hard to escape the conclusion that they don't really want it to be used. They certainly don't seem to go to any effort to explain the details of the package in a way that is useful to users. So we're pretty much on our own. 

The command geomag.py -h offers a lot of output, most of it incomprehensible without further documentation. However, the following command (typed on one line) produces output in a format very similar to that stored at the URL that in the past provided one-minute Boulder magnetometer data for a particular day:

geomag.py --inchannels H D Z F --observatory BOU --starttime 2016-01-23T00:00:00Z --endtime 2016-01-23T23:59:00Z --input-edge cwbpub.cr.usgs.gov --output-iaga-file output-file-name

From this point one can process the file output-file-name appropriately, in a way similar to the manner in which the old URL-based data could be processed. For example, I have a widget on my desktop that displays the last couple of hours of data from the Boulder magnetometer, using the above method to obtain data every five minutes: