Surf ....

... was available today.  Photos taken by phone at Bastion Point at noon.

We also went to Quarry Beach about 1515 and I think the waves were even bigger - well over 2m,  Some of them broke right up to the vegetation which caused us to return, not wishing to get wet feet!

It's Lennie time!

One of our references is The Cloudspotters Guide by Gavin Pretor-Pinney,  He also formed the Cloud Appreciation Society so I thought it apt to link to their site!

He describes lenticular clouds as a species of alto-cumulus clouds.  They are orographic: ie formed when air is forced upwards as it goes over an obstacle such as a hill or Mountain. Apparently glider pilots refer to them as "lennies".

With the wind coming from the NW today a bunch of good lennies formed to our NW later in the day.

 The classic shape is likened to a flying saucer.  This one looks more like a cigar - or perhaps a roll-your-own!

 Mt Imlay is certainly a mountain!

As the sunsets the colours got stronger.

Sunset 25 May

Spectacular sunsets are the rule at Mallacoota, especially from our house.    Here are a set of photos I took on the 25^th.   I particularly like the textures in the clouds in the later photos.

The foggy, foggy dew.

This post does get to weather eventually.  Trust me!  (Whether what happens in that discussion is comprehensible is a separate question.)

I hate to disappoint any followers of archetypal Pom folk songs but I'm not a weaver and no young maidens will be saved in this blog post.  I will disappoint them further by not including a you-tube link to that song as everything on line seemed to either be:

• by Burl Ives or Marty Robbins - who have no connection with England - or 
• a version by Benjamin Britten which is about as folky as "Nessun dorma"  (Incidentally the answer to the question posed in that video is clearly Jussi Bjorling.).  or
• a much more modern Irish song (The Foggy Dew) about the Easter Uprising. 

To meteorological business.  In recent mornings I have noticed a heavy dew on the pavers out the front of our house.  The area concerned is approximated by the red/yellow rectangle in this image.

My weather station (WS), located at the aqua circle, produces data on the dew point as well as the actual temperature.  I was interested to see what the WS said about dew point, temperatures and humidity.  In principle I thought that to get a heavy dew the actual temperature and the dew point should be the same.  This first chart shows the hourly temperature and dew point for the first 20 days of May ( I haven't been able to work out how to get the dates in the axis ).

 Note the area boxed with dashed lines.  In that area of the chart, overnight the temperature and dew point are very close together.

The two measures never actually achieve equal values but the difference is less than 1^oC for some periods, which I suspect is equality within the accuracy of the equipment.

I also wanted to compare this with measures of relative Humidity (since dew point is a function of humidity and temperature).  When Humidity is high (ie close to 100) the difference between temperature and dew point is low which makes a messy chart, so I plotted (100 - rH ) which I am calling "inverted rH". As the two series are of different scale I have used the LH scale for difference in temperature and the RH one for inverted humidity.

With all that adjustment I am unsure how much reality is left in the information!  However it does show that the basic story of high humidity gives dew point close to the recorded temperature is supported by my data.  The two series plotted show a correlation coefficient f 0.996!

As a third way of looking at dew, Frances noted that on the morning of the 21st there was much less dew on the pavers and no condensation on the glass screens on the northern side of the house (red lines in the first image).  As with the paver area the screens are sheltered from the wind so are possibly more likely to get condensation than the more exposed WS position.

Tern and Dolphins

I know I said this blog was to be about things other than birds, but occasionally an excellent bird comes along and gets a guernsey.  Especially when there are other things to include!

I commented a few days ago about a White-fronted Tern which terned (sic) into a Little Tern.  The link there includes a couple of maps illustrating the migration of the White-fronted Tern from NZ to Australia.

Today there was an early alert about a Common Tern at Betka Beach.  However that terned out to be ....... an immature White-fronted Tern.  Amusingly one of the key field marks is that a Common Tern has more white on the front of its head  (or to put it another way, the White-fronted has more black in that area).  Here are a few photos.

This first one mainly gives an idea of the bird's size relative to Silver Gulls and a Crested Tern.

 In this one, the black scalloping on the bird's back (another strong field mark) is just hinted at,

 The scalloping is perhaps a bit more visible here.

 A nice close up.

 I ten went down to Quarry Beach.  Just as I was about to leave a pod of about 6 Bottle-nosed Dolhins appeared.  They were doing the whole athletic bit: surfing down waves and jumping completely clear of the waves.  It is pretty much impossible to tell where they were going to appear along a 200m stretch of surf so I just pointed the camera and pressed the button where I last saw them.  This snap is not too bad!

 This was my second best shot: one fin and the suggestion of a shape surfing!

 Imagine how bad the other photos were!

As a result of comments on Facebook by Dan Ashdown and Janine Duffy I now know these to be Indo-Pacific Bottlenosed Dolphins Tursiops aduncus. See this site for a field guide.

We were standing on a rock to get snaps and I thought these shells and green kelp were interesting.  They were about 1 metre above the current water level which needs a bit of thought as most of the tides are not that high.

Life form and Sunset

We went for a stroll along Bastion Point this afternoon and found another example of the life form previously identified as a shark/ray egg case.  A reaction on Facebook to these images has suggested Sea Slug (a shell-less gastropod) and that seems to be a fruitful area for exploration!  We tried to get some definitive photographs of it but it didn't hang around.

Frances has used the sea slug hint to pull out her book on the wildlife of Coffin Bay (about 1400 kms NW of Mallacoota) "Shores and Shallows of Coffin Bay" and found a very close match with Sydney Sea Hare Aplysia dactylomela.

It seemed to swim off with purpose to get away from us.  I can appreciate that egg cases have flaps but this seemed to have clear self motivation to swim off. using the flaps like fins

I am beginning to wonder it it is a hatched egg case.  However as it took off it squirted this purple liquid out the back - reminding us of coelenterate defensive techniques.  Do sharks or rays do this as well?

In attempting to ID this life form as a sea slug I feel as though I have entered a parallel universe!

1. It appears there are 400 species of sea slugs in Port Philip; 
2. There used to be an Australian Sea Slug Forum run by the Australian Museum with 23,000 posts until it closed due to lack of funding;
3. There is a Facebook group for the Sea Slug Census (an interesting adaptation of an application designed to identify hot chicks for randy frat-boys).

I am joining the third of these, so watch this space.

Back home the sunset was well up to standard.

Hear the words of Dylan

You don’t need a weatherman

To know which way the wind blows

When a link to this was posted on the Mallacoota Community Facebook group the person posting noted that "The answer is blowing in the wind."!

I started to think about this post when trying to come up with some way of comparing the readings from my weather station with the readings from the BoM site about 5 km away.  

Before getting to that I will put in a few words about quality.  Accuracy is one element of quality, indicating how close a measured data item is to the true value (where that can be detrmined).  To some extent how close you get is determined by how much effort you can put in (ie cost) and how long you want to take to do it.  So time and resources are also elements of quality.  These can be brought together though a sense of fitness for purpose: brain surgery requires a different level of accuracy to chain-sawing firewood.  For my purposes I am interested in broad level of accuracy suitable for informing general interest discussions, not launching space shuttles (nor even general aviation) so I can accept some level of rubberiness.

As I have commented in the past my weather station is not ideally situated being about 2m above the ground and rather sheltered from the East and South.  As would be hoped the BoM site is in an exposed position with the anemometer 10m above the ground.  What I was hoping was that I could find some material on the BoM site to form a standard against which my data could be assessed.  The happy (or at least less unhappy) hunting ground for this seemed to be a page of climate statistics.

Wind Run

Of the various measures of wind available I was initially attracted to the mean daily wind run.  The attraction of this comes from having just read "The Home of the Blizzard" by Mawson.  It is the story of his Antarctic adventures and he and his companions usually recorded the wind run as well as any outstandingly bad gusts.

From looking at the data from my weather station for March and April 2019 the run was approximately half the average long term value at the BoM site.  (Wind run is not in the daily or monthly climate statistics published by the BoM.)  Interestingly, the value at the BoM site for Mallacoota was approximately half that for the very exposed Gabo Island site (16 kilometres away).

The data sets are for different periods, with that for Gabo commencing in 1957  as opposed to 2003 for Mallacoota.  However I am doubtful that this would explain much of the difference.  So the difference between my site and the BoM could simply reflect a real difference in micro-climate at my site.

The mean daily wind run recorded at my site in April was 88.4% of the value recorded in March.  For the BoM long term mean, April is 89.0% of the March value.  I thus conclude that on this measure my weather station shows an expected level of change between the months.

Before leaving the subtopic I'd note that dividing the wind run by 24 gives the average wind speed across the day. Thus, for April the average speed at my station was 5.08 kph.  The chart below illustrates the pattern of winds through the day in April.

The black line is the average across all days in April  while the blue line is the day with the strongest wind (ie highest gust reading) and the red line is the day with the lowest gust.  So averaging out at ~5kph is correct.

My conclusions from this are that 

• Wind run is an appropriate measure to use as an indicator of windiness,as it includes a lot of information; and
• The information from my Weather Station is a reasonable measure of relative windiness for Mallacoota.

Recorded speeds

In the usual records for a day the BoM shows three measures of the wind:

• The highest gust in a day; and 
• the actual wind speed at 0900 and 1500.

Since BoM doesn't do daily wind run I have decided to choose one of these three measures as my indicator of current windiness.  My choice is driven by the way in which the long term monthly averages for each of them correlate with the long term mean daily wind run.  

To my surprise there is a negative correlation between maximum monthly gust and wind run (R= -0.34).  The other two series show a very significant positive correlation.  For the 0900 value R = 0.89 while for 1500 R = 0.92.  Here is a graph showing the BoM daily means of Wind Run and 1500 Wind Speed.  NOTE that the two measures are plotted on different vertical axes which emphasises the similarity in pattern across a year.

In addition to having the higher correlation the 1500 speed occurs after the day has developed a reasonable weather pattern  so I'll choose that as my standard indicator of current windiness from now on. 

My final chart shows a comparison of 1500 Hr wind speeds for the BoM Mallacoota site (BOM) and my Weather Station (WS) for the months of March and April 2019.  I have included some polynomial trend lines to filter out the random variation (aka statistical noise): as indicated by the pathetic values of R² the is a lot of noise, but I think it shows the similarity of pattern!

The chart also demonstrates that while the pattern is similar the values from WS are well below the BoM readings.

Wind Direction

Following  from the surprisingly good outcome from comparing wind speeds I thought I would take a look at wind direction.  In so doing I was not feeling very confident due to my weather station seeming to be fairly sheltered from the SW - E.  However I decided to extract the direction given by BoM for the wind readings at 0900 and 1500 for each day of April and compare them with the equivalent readings from my weather station.

I had a "duhhh" moment when initially attempting to do this since in some cases the BoM had a value of NNW (=338^o) and the WS recorded N (=0^o) or NNE (=22.5^o).  Although they are quite close compass points there is a huge difference in degrees.  Thus there was a poor level of correlation.

That was solved by manually calculating the differences as summarised in this chart.

In 44 (73%) of cases the difference was within one compass segment.  To my mind that is an astonishing level of consistency and indicates that the wind direction data from my weather station is also fit for the purpose of indicating, as Mr Zimmermann warbled, "which way the wind blows".

April 2019 Weather report

This post will be a summary of weather observed in Mallacoota in this month.  As I only have about 10 weeks of data, the longer term information will be mainly drawn from the BoM site, located off Betka Rd near the Airport.  I hope it will be clear which site the data is referring to, but they generally show a broadly similar pattern.

Overall Summary

The month of April was quite warm with average maximum and minimum temperatures both above average.  Its thus no surprise that the mean temperature was 1.04^oC above the long term average for the month.

The month was also quite dry with rainfall well below average as was Relative Humidity at both 0900 and 1500 hrs.

There was a particularly windy period at the end of the month.

Rainfall

There have been quite a few comments in the media about Adelaide and Melbourne having the lowest rainfall for the period January 1 to April since records begin (180 and 160 years ago respectively).  It wasn't that bad in Mallacoota: we have records covering most years back to 1975 and 6 of those years are below the 177 mm recorded in 2019.  

1981 looked to be a dry year but there was no rainfall observation for February so I couldn't us that year.  To get an estimate of what went on I looked at the BoM records for Gabo Island.  That series shows a good fall in February 1981 so it would not have been a low year at Mallacoota.  (As an aside, Gabo has a solid record fr rain back to 1867, so there is lots of information to be mined there!)

For the month of April BoM hs recorded 27.8 mm while my Davis WS recorded 30,8 mm.  The daily totals vary considerably between the two series.  In part this is due to the timing of recording with BoM records ending at 9am and my Davis recording on a day ending at midnight.  For this month however the major difference was a storm cell on 24 April which dropped 14.8 mm on my WS but only 2 mm at the BoM site,  (A number of other residents commented that they received falls around 15 mm from the event,)

The  following chart shows a comparison of BoM data for 2019, 2018 and the average since 1985.

 Clearly the month was well below average (but a lot damper than 2018!

I have used the daily falls - from my WS - and the average fall on that date from BoM to estimate the total annual fall.  By 30 April the projected total fall for 2019 was 720 mm.  The movement of the estimate through the year to data is illustrated in this chart.

Temperatures

The issue of timing is crucial.  The BoM approaches (note plural) to this are summarised here.  On a 'normal' day the maximum measured for a day ending at 9:am will be the "Daytime High Temperature" for the previous calendar day.  In contrast the minimum to 9am will usually have occurred early in the morning and thus match the "Overnight Low Temperature".  In situations where fronts come through (increasingly abnormal) there can be wide discrepancies!

My weather station readings are quite simple as they are based on a day ending at midnight, Australian Eastern Standard Time.  Note: I don't change the WS clock for daylight saving!

That being said the comparative averages for April 2019 are:

• Maximum: WS 21.8 BoM 21.0
• Minimum:  WS 13.4 BoM 13.3
• Average:    WS 16.9 BoM 17.1

Given the different physical situation of the two stations such similarity is remarkable.  The three values, for my WS are shown in the next graph.

Maximum Temperatures

The entries in this section are all based on the BoM site.  First a comparison of maximum temperatures for this year, last year and the average.

April 2019 was a fair amount cooler than 2018, but still above average.  The illustrate the data underlying the average this chart shows the average April maxima x year.

I have left the trend line in, but primarily so that I can comment that the value of R² shows that the trend is not significant.

Minimum temperatures

Again the entries in this section are all based on the BoM site.  First a comparison of minimum temperatures for this year, last year and the average.

 For minima 2019 was warmer than 2018 and the average.  The two year comparison probably reflects the more rain this year than last

While the longer time series looks to have an upwards trend again the value of R² shows that the trend is not significant.

Average temperatures

The BoM assesses average temperatures as the mean of daily maximum and minimum.  While not precise, I have looked at this in the past for my weather station and found it to be a very close approximation to the average of hourly values through a day.  

The following chart is rather (perhaps 'excessively' is the better word) complex but I hope illustrates a few things. An explanation of what's going on is below the graph.

The green line is the average of average temperatures temperature for that day,  There is a trend line associated with it, showing a significant downwards slope.  In simple terms the end of the month is significantly colder than the start!  While obvious, that wasn't the case in March.
The solid blue line is the average temperature month to date .  That is the average of the average temperatures from the first of the month to the date shown.  It also has a downwards slope, more significant that the green line, as the day to day variability has been averaged away.
The red line is the daily average temperatures calculated from this year's BoM extremes.  Much more variable.
The dashed mauve line is the averages from my weather station where each day has the actuall average of 24 hourly readings.  It is very similar to the red line, reinforcing the overall validity of the calculated averages.

Back to simplicity with a time series of averages calculated from the BoM data.

An important use of average temperatures is in calculating a temperature anomaly given by the difference between an average for this period and the average of all periods in the past.  In this application the anomaly is +1.04^oC.  That is the month was just over 1^oC above average.

A comment on global warming

For each month for each year I assessed whether the maximum or minimum were above the average maximum/minimum for that month.  I then counted the number of above average months for each year.

• For maxima the series of number of above average months per year, sloped upwatrds quite significantly (R²= 0.52).
• For minima the line slopes up but not significantly (R²= 0.26).
• Adding the 2 scores together shows an upwards slope with a close to significant R²= 0.49.

Although 25 years is quite a short period it does seem Mallacoota is warmer than it was.

Humidity

The BoM publishes 2 series for humidity covering the readings at 9am and 3pm.   The chart below shows the observations from my WS for those two times through April,  They show very similar patterns except for high 1500 readings on the 6th and 22 -24 which are leading up to rain.

The BoM have some average RH readings for the 2 times, but for some unknown reason they terminate at 2010. However that is good enough to give a context for current values.  For both times 2019 appears to be quite an amount drier than in the past.

Wind

This is a difficult topic as there are a number of ways of measuring wind (day-run, gusts, point of time etc) and my WS is not in an ideal situation.  The latter point is particularly important when compared with the BoM site which has the anemometer at 10m high, in an open site.

My starting point is to look at the maximum daily gust from my WS as illustrating the windy days during the month.

I have also looked at the daily windrun and the speed at 9AM (as both of these are available to some extent from BoM records).  The correlations between the 3 series from my WS are all quite good, at ~0.70. 

However when looking at point of time windspeed from the BoM site for 0900 and 1500, it can be quite different to that from my WS.  For the 0900 series the differences can be quite large (eg for one reading the WS speed is only 18% of that given by BOM).  While the correlation is again quite good at ~0.7 the differences are uncomfortable.  Further the differences vary between the 0900 and 1500 with the difference having a much lower correlation between the two series.

My conclusion from all of this is that my data is best restricted to showing when the windy periods occurred in the month using the chart above.