nm0881: the point we got to [0.3] last time [0.5] was that [0.2] we we'd shown 
that using these observations of [0.5] atmospheric water vapour transport [3.0] 
we could deduce the [0.3] net evaporation or net precipitation at the surface 
so [0.5] again those of you who've now done [0.2] done problem sheet one [0.7] 
should should be well familiar with this that if we [1.0] if we [0.2] know the 
atmospheric transports of water vapour we can deduce [0.4] E-minus-P as a 
function of latitude [1.2] and so we talked about [0.5] doing this for a 
particul-, er pa-, [0.3] particular latitude bands [0.5] and what i said at the 
end of last lecture is that we can [0.4] we can carry on this procedure to 
consider [0.5] a particular latitude [0.6] longitude box [0.6] so there's no 
reason why this technique should be restricted to particular latitudes [0.4] 
just latitudes [0.7] so [1.1] the principle's exactly the same if we know [0.3] 
the divergence of water vapour coming into the box [0.6] er we can deduce the 
evaporation minus precipitation so there's er [0.5] exactly the same technique 
[1.4] so we can derive [2.9] er E-minus-P [2.6] er on a [1.8] on a 
latitude times longitude grid [4.7] and [1.0] the one example that I've got 
here then is from [1.7] again from these assimilated data sets [3.5] so [0.3] 
these two plots here are the annual mean [0.6] er [0.3] E-minus-P in 
millimetres per day [0.6] er [0.8] so that these are from two two assimilated 
data sets [7.0] and that these are [0.6] one of them just happens to be 
European centre up the road and the other is the [0.4] U-S [0.2] er [0.5] 
National Meteorological Centre [0.4] and [1.5] again these are giving us [0.8] 
firstly giving us some of the [0.2] patterns that we would expect to see [0.7] 
we can see [0.3] that there's a [0.4] E-minus-P [1.9] er is negative [3.2] and 
over the I-T-C-Z where we would [0.3] again there's nothing [0.7] suprising 
about that we've got this band [0.9] very narrow band it's striking even in the 
annual mean how narrow this band is [0.4] across the Pacific and across the 
Atlantic where [0.5] the precipitation is exceeding the evaporation [0.8] and 
there's other features that we're not going to talk about much for example this 
[0.4] this one going [1.1] er [0.4] south south-east from the [0.2] Indonesia 
the South Pacific 
convergence zone [0.6] which is a feature i don't terribly well understand in 
the atmosphere [0.4] we can see that [0.4] er [0.9] both marked in these plots 
[0.5] and we can also see [0.6] the positive regions [0.5] er [3.3] and again 
we'd expect these to me [0.3] be most positive where there's [0.4] loads of 
sunlight but loads of water [0.4] so [0.4] to evaporate so particularly the the 
subtropical anticyclones over the oceans [0.5] we expect to see [0.5] large 
quantities and they're they're in [2.9] they're in both of the plots [16.6] 
assuming there's abundant energy available over the desert regions but of 
course there's no water availability [0.4] so we don't see these strong peaks 
over [0.5] over the land regions [10.3] and i won't write it down but again 
what we expect to see is E-minus-P becoming positive [2.2] er [0.4] sorry 
negative [0.3] as we go into the storm tracks in the northern hemisphere so we 
can see [1.5] we can see those there too so [0.5] they're in general 
qualitative agreement but there's [0.5] er [0.6] there's some interesting [0.8] 
interesting differences [0.2] if we think about the headwaters of a big river 
[0.2] 
say the Amazon [0.4] then what sign would we expect E-minus-P to be [0.7] over 
the headwaters of the Amazon [4.2] if you've got a great big river flowing out 
of it what sign would you expect E-minus-P to be [3.8] yeah so we'd expect [0.
3] strongly negative and if we look at the [0.3] European centre one [1.9] then 
[0.8] we can f-, we find that E-minus-P is indeed negative we'd expect the 
precipitation to exceed rainfall where you've got a great big river flowing out 
of [0.5] but interestingly over this region in the N-M-C analyses [0.6] it's 
not negative so it's indicating that there's some [0.5] er some perplexing 
differences [5.9] and i've just picked out one example here [3.6] over the 
headwaters of the Amazon [1.1] where we think we know the answer because we've 
[0.7] we can measure the river flow coming out of the region [1.7] i don't [0.
3] i ha-, i haven't done that to try and say E-C-M-W-F is better than N-M-C 
i've just picked out one i'm sure we could pick out other regions of the world 
where [0.5] er [0.3] E-C-M-W-F would be worse [0.5] than than N-M-C so [0.7] er 
[1.6] it'd be 
nice to [0.2] having said that it would be nice to know how [0.3] how accurate 
are [0.9] ho-, [0.6] how accurate is the [3.9] er is the E-minus-P data [10.9] 
what what we're going to do just to finish off this section is just look at a 
[0.5] rather nice [1.7] analyses [2.4] that i've taken from a [1.8] so it's at 
the bottom of this sheet again the [0.8] quite a lot of the [2.3] quite a lot 
of the papers i'm going to refer to were from the Bulletin of the American 
Meteorological Society which we have in the library in the main library [0.5] 
and they're often [0.2] quite readable articles and this is [0.5] one where the 
instead of looking over the Amazon [0.3] headwaters [0.4] where we haven't got 
much data there's not many radiosonde the sense over [0.5] that part of the 
world [0.7] what they've done is to look [0.4] in two regions where [1.5] er [1.
1] where there are [0.2] good instrumental records [1.2] in in the United 
States so good [0.6] you'd expect a lot of radiosonde offence in these regions 
[0.5] and they've taken two [0.2] two basins [0.5] so this this again is just 
very much an example but er [0.6] quite an illustrative one [1.7] is that we'll 
look over [3.4] er to [1.9] er U-S river basins [5.1] so the Ohio Tennessee and 
the upper Mississippi [0.5] and for both these we've got er good [3.1] 
radiosonde coverage [3.8] and so the [0.5] the data going into our assimilated 
data sets should be [0.6] should be pretty good [0.6] and we've also got er 
stream flow measurements [11.2] so the situation here [0.2] what do w-, got 
here is if this is the [0.4] if this is the catchment of the river and this is 
this is a river flowing out without with all its [0.7] tributaries instead of 
[0.4] calculating the E-minus-P on a nice square box what we're doing is 
calculating the [0.7] the convergence of water vapour into this [0.5] er [0.5] 
so this is the [0.8] the boundary of the catchment [4.2] we ca-, we calculate 
[1.8] and the [0.3] divergence or its convergence is written on these slides 
but doesn't matter which [4.9] calculate the divergence of the water vapour 
transport [0.5] and [1.2] we also then measure the stream flow [8.4] the stream 
flow leaving the catchment [26.9] so if our system is perfect [0.2] the amount 
of rainfall [0.7] the the amount of [1.5] the amount of water 
leaving the catchment assuming this is the only way that water can get out [0.
5] ought to be the same as the amount being [0.5] the convergence into the 
catchment [1.0] so we can ask how [0.4] how how good it is and these are [1.5] 
two diagrams which [0.8] er [1.6] illustrate that so [0.4] if we just for a 
moment concentrate on the upper Mississippi [0.8] and the this is the [0.5] 
variation of the function of time of year from January [0.2] back through to 
January [0.5] and this dashed line is a measured stream flow [1.1] and this 
solid line is how much [0.6] how much water is essentially being [0.6] 
deposited into the [1.5] into the catchment by [0.2] by convergence [2.4] and 
[2.3] and this is for the [0.5] Ohio Tennessee and i've just put in the annual 
averages and what we can see is that [0.5] er [0.9] is that these numbers don't 
agree wonderfully well i mean these are [0.3] errors of maybe thirty per cent 
between the [0.6] er [0.3] convergence and the stream flow [1.4] so even in one 
of these [0.3] well instrumented areas [0.8] where we think we've got good data 
[0.4] er the the difference between [4.1] and the deduced [1.4] er convergence 
of water 
vapour by the atmosphere [6.3] and stream flow is [0.7] is only around thirty 
per cent [0.8] it turns out that the sign differs between this in one case [0.
5] one's getting more [0.7] more convergence and stream flow [0.4] so where's 
the water going [0.6] and in the other case [0.6] er it's the opposite way 
round [16.4] now [0.2] of course there's [0.2] when you've got two sets of 
measurement there's [0.3] two sets of measurements could be an error so is [0.
3] is this telling us that the stream flow measurement is wrong [0.5] or is it 
that the convergence measurement were wrong or is there some other way that 
water can [0.4] get out this catchment the [0.4] the authors i'm not a [0.4] 
obviously not an expert in [0.4] in measuring stream flow the authors conclude 
[1.5] er that most of the error [3.4] er [1.0] is in the E-minus-P [1.2] so [1.
0] we reckon we can measure stream flow with [0.4] reasonable accuracy [0.2] so 
we know how much water was leaving the catchment [0.7] but we can't measure the 
[1.6] and that we c-, the implication is that er [0.4] even our best systems [0.
5] say from [0.2] the European centre [1.9] aren't getting this [0.4] er [4.3] 
aren't allowing us 
to deduce this convergence of water vapour and hence the E-minus-P with an 
accuracy of better than thirty per cent [0.4] so this is kind of a limit of how 
well we can do [0.5] with these techniques [4.7] okay so [0.6] er [2.5] that [0.
2] then concludes this first section where we've looked at [0.5] atmospheric 
water vapour and its transport and what we can deduce from it [0.8] so we've 
deduced we've shown that one of the most [0.3] powerful if if somewhat flawed 
[1.2] outputs is that we can actually work out what the net [0.3] surface water 
balance is which is very powerful [0.6] but obviously we need to know how much 
precipitation's [0.5] going on so [1.1] now let's go to the next big section [5.
7] this is section [1.2] section four [6.7] 
precipitation [0.9] and i hope a section like this i don't need to motivate why 
we're [0.4] why we're doing it [1.2] but what we're going to be concerned with 
is [0.4] er [2.0] is essentially how how is rainfall measured [0.6] which again 
you'll have touched on in first year courses [0.7] the problems in making those 
measurements [0.5] and [1.1] one of the problems we're going to come across 
which is a major one is the sampling [0.4] if you've got one little rain gauge 
here trying to represent a huge area around it [0.5] er [0.3] how how reliable 
is that [0.2] tiny little sample [0.7] and then we'll go on to talk about [0.4] 
observed distributions of rainfall [0.7] so let's [0.2] er [0.9] spend the 
first [1.1] first section [0.2] thinking about techniques [1.2] for measuring 
precipitation [6.0] and of course there's many [1.0] many different techniques 
we're going to touch on we're going to touch on [0.4] obviously rain gauges [0.
8] radars satellites [0.8] 
but let's start [0.2] with the [1.2] in many ways the simplest which is [3.3] 
rain gauges [3.4] and so this [0.8] this hopefully will build on what you 
learned in Dr Pedder's course [1.1] er measuring the atmosphere [0.5] in the 
first year [4.7] now we're going to as i said we're going to look at [0.2] 
loads of different techniques for measuring rainfall [1.0] but there's one 
distinguishing feature about [0.4] rain gauges [0.5] compared to say satellite 
systems and radar [0.6] does anyone know [0.4] what it is [6.5] i mean you 
might not you might think that radars measure rainfall [0.5] but they don't 
rain gauges are the only technique that actually measure [0.4] how much water 
is reaching the surface [0.4] so we're going to look at lots of other 
techniques [0.5] where people talk about [0.3] measuring rainfall but they're 
not actually measuring rainfall they're deducing it [0.4] indirectly so these 
are the [0.7] the only technique [6.8] that actually measures the rainfall 
reaching the surface [7.1] and [1.0] don't be tricked into thinking otherwise 
when you read [0.4] read about some other techniques [0.4] in in books so it's 
er [1.9] and the other thing that we'll find is that every other technique 
radars and satellite techniques they are absolutely rely [0.2] on rain gauges 
[0.4] so er [0.4] so that's the other important point [0.9] no other techniques 
[4.2] can rely on them [3.6] so we can go to some fancy high tech solutions 
with radars and satellites but at the end of the day [0.7] er [1.3] they can't 
do without [1.5] er [0.6] our old Victorian [0.6] technology [12.5] er [0.2] 
types again a lot of this you'll [0.2] hopefully know [1.1] know very [2.6] 
very well [0.2] the [0.4] the main type of rain gauge are storage gauges [1.6] 
where [0.3] these are generally read [1.0] these are s-, [0.2] simple [2.5] er 
collectors [0.3] of rainfall [1.2] and they're normally just read [0.9] er once 
per day [7.3] matters up to even at operational [0.5] weather sites [1.0] 
sm0882: sorry i 
nm0881: that that you that you measure only once per day from a rain gauge [0.
4] i mean certainly on a site like ours [0.2] they're only read once a day [0.
5] 
sm0882: yeah you you [0.2] you then for the standard five inch gauges but the 
nm0881: mm 
sm0882: there are [0.9] automatic loggers which actually do what the 
nm0881: yeah well i understand you [0.4] so these these are what so so at some 
sites they would be measured twice a day but say on our [0.3] our 
climatological web [0.6] climatological site [0.4] 
we'll only use them once a day [0.5] so [0.9] and then obviously the [0.4] the 
second type of gauge [0.6] which i'm not going to [0.2] talk about much in this 
[0.8] these lecture courses the [2.2] the automatic gauge [0.2] gauges [1.4] 
for example the [0.5] there's various different models but the [1.6] the c-, 
whoop [0.3] let's get it right the tilting syphon [4.0] er gauge that we have 
on our [2.2] on our met site [0.6] which i hope you've all [0.6] all seen [2.5] 
and the these of course give [0.8] give the amount [2.2] er plus the timing [1.
7] of the rainfall [0.7] so they give us [0.2] extra information [7.6] as i say 
i'm not going to talk too much about these these have real advantages also in t-
, [0.2] in terms of [0.4] and when we get to talk about radars is that these 
can be set up so they can actually [0.3] transmit the data they're recording so 
they'll [0.4] you'll get data in real time coming back for a [0.5] from an 
automatic rain gauge if they're [0.3] properly set up [1.1] but the other thing 
about them is that they're rather complex pieces of equipment there's lo-, [0.
5] many more things that can go wrong with a [0.4] an automatic rain gauge 
than a [0.2] than a storage gauge so they're [0.6] less robust in many ways [0.
2] but we'll going to [2.0] over the world as a whole [0.5] it's these these 
kind of rain gauges [0.4] that are dominant and the ones that are used most in 
[0.5] in trying to understand the hydrological cycle [2.9] so let's just [0.4] 
sit back and think about rain gauges [0.6] a little bit [35.5] sorry did i [0.
8] failed to count properly [0.2] sorry [7.8] so [0.9] so the first point is 
that rain gauges are [0.2] the storage gauges [4.9] er are the most common [3.
1] i think Strangeways in his book estimates something like two-hundred-
thousand of them [0.5] across the world [0.5] but there's [0.3] there's a [0.4] 
lot of problems we have to be aware about with rain gauges and again some you 
will have touched on the first is that there's a [1.7] there's a whole [0.2] 
zoo of different rain gauges which are routinely [0.5] used [1.2] and [1.1] so 
[0.5] so this is potentially [1.8] problems is that there are about fifty [1.6] 
in routine use [2.2] er around the world [9.9] and [0.3] the these [0.3] what 
i've [0.3] reproduced here is just a [0.4] a subset of [0.7] er [0.2] nine of 
these [0.4] nine of these different ones and i'm not going 
to [1.1] look at them [0.4] i-, in any great detail [0.5] and the [0.3] 
[sneeze] [0.3] the U-K one happens to be this one [0.6] and [0.7] and these are 
ones used in [0.2] in d-, [0.2] b-, various other countries as er [1.3] is 
indicated there [0.4] and they all differ in [0.2] in in characteristics they 
differ in [2.4] er [2.3] in size [1.4] they differ in [1.0] they can differ in 
[0.3] in the shape of the [0.5] collector [1.8] things that also [0.4] matter 
er [0.3] er [0.7] is the material they're made out of and that can have an 
impact on [1.0] whether the [1.1] surface tension forces cause little droplets 
just to sit in the gauge or run down into the [0.4] collecting bottle [0.4] and 
so some of those things are are indicated on this diagram [0.7] er [2.7] i 
should say one i don't believe this figure if it one of the [0.2] figures it [0.
4] it tells us that the first number [0.4] indicates the code [1.1] gives the 
orifice of the [0.2] gauge area and i don't think it's correct for this [0.3] s-
, one so i'm not sure quite what the units are [0.5] but nevertheless the main 
point about this is that we've got this whole [0.6] zoo of [0.2] of different 
gauges [2.3] and so [0.4] er [1.0] th-, [0.2] the reason why this is a 
problem is that is that they're [0.2] they're not not all [1.5] er easily 
compared if you're getting rainfall measured by one gauge [0.4] you can't 
immediately [0.2] compare that to [1.0] measurements from another gauge [2.1] 
another problem can come if you're looking at trends in rainfall [0.5] is if [0.
2] there's a slow changeover from one of these gauge types to another [0.7] er 
you have to be [0.2] damn sure you know that if you're going to not [0.4] if 
the trends you see are are real trends in rainfall rather than [0.5] a a trend 
[0.3] in use from one type to another [1.1] so that's [0.2] er [0.8] big [0.6] 
big potential problem [3.1] and the second problem about rain gauges i said 
that they're [0.2] they're the only technique that actually measure rainfall 
but they're [0.4] they're they're imperfect collectors of rainfall [19.3] and 
[0.6] what this second diagram [0.2] does is just sort of [0.4] shows some [2.
1] some of the different things that we have to [0.5] worry about [0.8] er [3.
2] when when we're thinking about rain getting into a rain gauge so one of the 
things that can happen [0.4] is that rain falls into the [0.6] into the mouth 
of the gauge [0.2] forms a little [0.3] droplet and [0.4] during the [0.3] 
during the day that water is evaporated up into the [0.6] atmosphere and that 
obviously depends on the input of the sun and the wind [0.6] rather than going 
into the gauge [0.4] we've got other things if we're going to [0.3] accurately 
know how much rainfall [0.6] has gone on we need to know what size [0.6] our 
gauge is [0.4] now if someone [0.7] if someone when they're mowing the lawn on 
the ga-, on the [0.3] on the [0.4] on the site manages to bash their rain gauge 
with a [0.6] er [0.2] lawnmower and i gather that's not er uncommon [0.5] then 
you you end up with your [laugh] [0.4] with your rain gauge being something 
less than [0.5] less than circular [0.5] so there's there's [0.2] there's 
various different er [1.4] different [0.8] er [0.7] sources of error [6.2] 
and let's just er [2.1] note note some of them [1.8] potential errors [1.0] 
include things like precision of manufacture [6.3] do we really know accurately 
what the area is [0.3] course that's c-, if you've got a a bottle full of water 
[0.4] and we need to convert that to rainfall we need to know [0.5] precisely 
how big the [0.6] the collecting [0.4] er orifice is [2.4] we've got [0.2] er 
[1.3] evaporation [3.3] from the gauge and again this isn't [0.2] insignificant 
it's about [0.6] er [1.4] in some gauge it [0.2] the er it's reckoned at about 
point- [0.2] two millimetres per [0.5] rainfall event [0.2] there's a kind of a 
rough [0.4] figure is lost just through [0.2] evaporation [5.8] another other 
ones that can be important depending on the gauge type is water [0.2] either 
falling into the gauge [0.4] and splashing out again or the opposite falling 
out of the gauge and splashing [0.5] splashing in so those 
are [0.8] referred to as outsplash [3.5] and insplash [9.8] and [1.8] well all 
these [0.2] and [0.8] various ones i've listed there are [0.4] er [0.2] all [2.
4] of of order [0.3] cause an error of order of about one per cent [0.7] and 
it's reckoned [2.5] reckoned that er the kind of random error [1.6] due to a 
the collection of all these things a random error [0.8] er [4.4] to all all 
these things is about point [1.0] about point-six to one millimetres [0.6] per 
day [0.9] so the random error in daily rainfall is what i'm trying to say [3.9] 
is around point-six to one [0.3] millimetres [1.1] so [1.8] very small rainfall 
amounts we have to be quite careful about [0.3] how big the error is [13.4] now 
the biggest error [0.6] in terms of measuring rainfall is [0.4] is is windspeed 
[0.2] biggest by far [1.1] so the biggest error source [6.6] is wind [1.4] and 
so we're going to spend a few minutes just [0.6] er [0.2] thinking about this 
[2.4] and i've got to have a [2.4] er and the kind of error that we're talking 
about so that s-, the U-K rain gauge [1.2] the standard Met Office one has a [0.
4] has a has it's top at [1.5] er [0.2] three-hundred millimetres [1.3] again 
as you [0.4] all very familiar with [0.6] and the 
kind of error we have [0.7] ha-, [0.3] have [0.3] for this one [0.5] is [1.3] 
is about ten per cent at [1.6] at four metres [0.2] per second and is er [0.7] 
and the error [0.3] sorry the error is [1.3] and that this error increasingly 
linearly with [1.6] with wind speed [3.1] so generally it's a [1.1] unless 
someone has clouted their rain gauge with a [1.6] with a lawnmower it's 
generally [0.7] larger than [0.2] than these [0.3] error sources here [5.0] and 
[1.5] this this is kind of for a typical lowland site in [0.3] in mountainous 
regions [0.6] of course you've got more [0.2] er [0.4] wind [1.6] but but more 
particularly 'cause in mountainous areas a lot of the rainfall is from [0.4] is 
from drizzle [0.6] which is [0.5] small raindrops we can find errors [0.6] er 
[2.4] of about fifty per cent [9.1] and so why [0.7] where do these errors [0.
2] come about from [2.7] second handout [23.2] ooh sorry [27.5] so again as [0.
2] many of you will be familiar that the reason why this error comes about is 
that the [0.8] gauge itself [1.1] provides a [2.7] a block on the flow [0.6] 
and the [0.9] the air which is blocked by the [0.3] the er [0.4] rain gauge has 
to go somewhere and so [0.4] in general there'll be an acceleration of of of 
the air [0.4] 
both around the gauge and [0.2] for our purposes most importantly is [0.4] over 
the gauge so [0.5] what this means is that droplets [0.3] drops raindrops that 
would otherwise [0.4] be falling into the gauge [0.4] are swept [0.3] swept 
from it [0.6] and the [0.2] situation is worse in mountainous areas because 
there's [0.4] they if [0.2] if you've got a large droplet with a not lot of 
inertia it doesn't care too much about the wind speed [0.5] but if you've got a 
small droplet with [0.5] er [0.7] with not much i-, inertia so a drizzle 
droplet will tend to be more [0.3] susceptible to the effects of this 
acceleration [0.6] so that's the [0.3] the physical cause then is the [1.2] er 
[0.3] the acceleration [2.8] of the flow [1.3] er [0.3] due to the [2.7] er [1.
2] due to the effect of the gauge itself [5.5] so this is a classic example [0.
9] in physics of the measurement actually perturbing what we want to measure [0.
5] so the presence of a rain gauge is [0.4] is disrupting the measurement [10.
7] so so what are the [4.4] possible solutions to this [0.7] er [0.4] well 
there are [0.2] there are various ones er [0.9] one is to derive is simply [1.
0] do lots of [0.3] measurements and derive 
correction factors [5.2] so [0.9] if you know the wind speed at your 
meteorological site and the rainfall you can use the wind speed to [0.4] er [0.
4] to make a correction so that's actually [0.4] done [1.7] er [0.3] quite 
routinely in the big [0.4] big analyses of global rainfall [0.5] i-, in some 
but not all of them [5.5] the other technique is to put some kind of [0.4] 
shield [0.4] around the rain gauge which is [0.6] indicated by [0.5] er [1.7] 
by some of the gauges [0.4] here [0.5] and so the idea of the gauge [0.6] oh 
sorry the idea of the shield [3.8] is [0.7] is that it er [0.2] doesn't cause 
so much distortion of the air flow [1.2] over the [6.2] over the gauge [10.6] 
another one that's sometimes used but you need [0.5] loads of space is 
something called a [0.3] a turf wall so wall so what [0.2] this is [0.6] er [0.
2] kind of a cross section through the turf wall what you do is have a standard 
rain gauge [0.7] er [0.2] still th-, [0.8] three-hundred millimetres above 
ground level but you surround it by a [0.4] a turf wall some distance away from 
it and again [0.3] that's supposed to [0.5] reduce the editi-, er ed-, [0.3] th-
, the [0.8] eddying and the acceleration of the [1.2] air over the gauges 
reduced 
because er [0.9] it it's sheltered so that's one [0.5] one other technique [18.
2] but all [0.2] all these [0.2] gauge types have the problem in that they're 
trying to measure rainfall [0.5] from [0.5] from a gauge which is stuck [0.2] 
typically thirty [0.4] thirty centimetres above the ground so it's not 
measuring at ground level and you've got [0.4] an acceleration of the flow [0.
9] so probably the best [1.8] er solution [3.9] is the one that again [0.4] we 
can see on our own [0.7] met site [1.0] outside [0.6] is the [0.4] er [0.8] is 
to put the gauge at ground level [0.7] or the gauge opening [5.1] 
at ground level [0.6] so flush with the surface [0.5] and surround it by a [0.
5] a pit with a grating on [18.8] so [0.2] let's just think about this design 
for a second [0.3] the [0.9] obviously putting it at ground level [0.7] is is a 
solution but if we [0.4] if we just put it at ground level on normal [0.4] 
normal ground then you'd have [0.2] terrible trouble with [0.2] water splashing 
and running into the gauge so you want to have [0.6] an area around the gauge 
where [0.9] er where the rain can't bounce off so you you sink [0.4] you you 
put it in surrounded by a pit [0.4] but if you just left that pit open [0.6] 
then [0.5] er [0.2] you'd have all kinds of eddying [0.3] due to the sudden 
change in surface from the [0.2] from the grass [0.4] to a [0.8] er to a deep 
pit [0.3] so the the idea of the grating is to [0.4] er not really [0.2] give 
much [1.0] er [0.2] insplash but it [0.2] gives you a a more smooth aerodynamic 
surface so you don't get too much eddying [0.6] so this is generally regarded 
as the best solution it's not always [0.3] a practical solution 
particularly if you're [0.5] er in a rocky area and need to [laugh] [0.4] dig a 
dig a deep pit to do this [1.8] and it also has to be looked after [2.5] you 
have to er make sure this pit is kept [0.2] kept clear and weed free [1.1] and 
if you want to which i do encourage you to do [0.2] read a little more about 
this i i refer to [0.6] this book b-, er [0.2] a book by Ian Strangeways 
earlier in the course he's written a few [0.4] nice little articles for Weather 
so these are [0.4] just a few pages long [0.4] so this one's [0.2] er [0.4] 
just a few years old now so i'd encourage you to go and [0.4] read that and [0.
3] er he also talks about [0.5] er his experiments with rather more [0.7] 
bizarre [0.3] types of gauge which might be [0.6] er sort of gauges of the 
future [10.6] so how how much [0.2] difference do these [0.3] these make [0.4] 
well it it's [0.3] typically [0.2] so er er [0.6] one of these [1.5] er [0.7] 
these pit gauges [3.1] they typically measure [4.1] er for a for a U-K site 
they'll typically measure something like [1.4] three to six per cent more than 
a standard gauge [10.1] and again in mountainous areas where we tend to have 
stronger winds and [0.4] often smaller raindrops it 
can be [0.6] er [0.9] can be as much as twenty per cent [8.8] so they're much 
more [0.4] much much more efficient collectors of rainfall [12.0] but i should 
stress that this kind of rain gauge is much [0.2] much less common than the [0.
4] the standard [0.6] the more standard type that we're used to seeing [6.9] 
now there's two other kinds of precipito-, well there's a two two other [0.4] 
things that we have to worry about with measuring rainfall it's very easy to 
put a rain gauge out on the [0.5] on on the land but how [0.4] any ideas how 
you'd measure r-, rain [0.2] in the o-, [0.3] on the ocean [1.9] so [0.3] two-
thirds of the planet is covered by ocean [0.5] and we need to know the rainfall 
there [1.7] 
sm0883: buoys maybe [0.8] 
nm0881: yeah do you think that would work very well [0.2] 'cause the [0.8] one 
of the problems these things are rocky you need to keep keep your gauge [0.6] 
level and you've got a lot of [1.3] a lot of [0.2] waves splashing in and 
things like that so [0.4] they don't tend to work terribly well [1.1] any other 
ideas [1.9] measuring rain in [0.2] the ocean [1.7] 
sm0884: put them on ships [0.2] 
nm0881: pardon [0.2] 
sm0884: put them on ships 
nm0881: well you can but you've got real 
problem there is keeping the ship [0.4] steady and er [0.2] it [0.2] it tends 
to be many metres above the surface so it's not [0.2] really regarded as very 
reliable [0.9] i mean there's two things that tend to be done [0.4] er one is 
just to use [0.9] stations in island re-, er island stations and hope that 
they're somehow representative of the surrounding region which is a [0.5] a [0.
2] a big assumption [0.7] a-, another thing that's being thought about is 
actually just measuring [0.2] which is amazing is is measuring the noise [0.2] 
due to the raindrops hitting the surface [0.4] so there are now people trying 
to develop acoustic techniques [0.4] of actually having little microphones 
under the ocean [0.4] literally listening to the pitter-patter of the rainfall 
[0.4] so they're very much at the [0.2] at the research level [0.5] er and [0.
3] er [0.6] they can be interfered with by [0.2] by all kinds of things [0.3] 
so that that's a problem th-, th-, the other problem i'm just going to [0.3] 
touch on [0.5] er [0.8] briefly is [0.2] is of course [0.8] measuring snow [0.
5] snowfall [1.1] which in certain parts of the world is a a large part of 
the [0.8] rainfall again we're not well large part of the precipitation [1.1] 
is [0.3] is that gauges are of [0.3] of of limited use [5.9] and [0.2] of 
course one of the most severe problems in these situations is [0.4] is drifting 
where all you're doing is redistributing snow that's already fallen [0.7] which 
ends up in your gauge and you don't know whether it's [0.4] it's just due to 
drifting or whether it's due to er [2.1] er [3.0] whe-, [0.6] whether it's real 
precipitation or whether it's due to drifting [0.3] and also it doesn't take 
that much snowfall in some some areas to overtop [0.4] top the gauge [0.2] 
'cause obviously snow's a lot less dense so it doesn't take so much snow to 
actually [0.4] fill up your [0.7] fill up the top of your [0.8] er rain gauge 
so [0.4] those are some problems there's [0.4] er [1.9] so there's various 
other techniques that er [0.2] try to be used [0.4] one is to try and [1.3] er 
[4.6] one is that you simply forget the gauge [0.4] and you just measure the 
depth [0.3] of snow [7.7] and and assume the volume [0.9] oh sorry assume 
assume a density [0.7] but even the density of snow [0.4] depends very much on 
its form and how 
old it is [0.5] or actually [0.4] er take [2.2] take a core of the snow [3.4] 
and ju-, and just melt it [3.4] and so you measure the [0.2] and [0.8] and 
calculate the rainfall [0.2] or calculate the [0.9] the [0.3] the precipitation 
[6.4] there are more subtle techniques being [0.4] being [0.4] being used in 
some areas and one one of these is er [0.9] is that we know that the earth is a 
natural source of radioactivity [0.5] and there's [0.4] for example gamma rays 
being emitted [0.3] just by natural radioactivity in the earth and [0.6] and [0.
7] snow is quite a good absorber of those [0.4] er [0.6] o-, of gamma rays [1.
7] and so [0.2] i-, if you if you measure how much attenuation you've got of 
the normal gamma rays you'd expect [0.4] say measured by an aircraft you get 
can get some idea of the volume of of snow [0.4] so [0.4] that's a kind of a [0.
7] a very [1.5] modern technique [10.6] and [0.3] you you probably wouldn't use 
that just for a [0.2] a little area but for getting some kind of aerial average 
picture you can get some idea of the [0.5] w-, the er [0.2] snow water content 
[0.2] there [0.9] and i'm not going to [0.3] to do any more and talk about this 
if you're interested in them 
then both [0.3] er [0.7] two of the books that i i've referred to [0.2] Ward 
and Robinson [2.0] and Strangeways [2.0] er go into quite a lot of detail about 
snow measuring techniques it's really quite an interesting area [0.7] and of 
course if in some [0.5] continelt-, ar-, continental areas [0.4] it's an 
important contribution to the er [2.2] to the whole hydrological cycle [6.3] 
okay now what we're not going to touch on here [0.2] which is a [1.2] which is 
a serious issue [1.7] is [0.6] is as i said before a rain gauge only [0.5] only 
measures a a very small [0.9] fraction of the total area [0.4] and if say we 
want to know the rainfall over the U-K [0.3] how many rain gauges do we need [0.
5] is it one [0.2] ten a hundred a thousand [0.5] and what we're going to do 
have to do later is to c-, try and come up with some quantative way of saying 
[0.4] how [0.7] how densely do we need to pack our rain gauges to get a 
reasonable [0.5] er indication of the [0.5] of the total rainfall and of course 
that will be [0.8] er dependent on whether [1.4] er on on the particular 
weather we have [0.3] for example whether it's er frontal [0.3] or [0.6] or 
convective [0.4] so 
we'll come back to that because that's and that's a very important part of [0.
3] hydro-meteorology is [0.5] how you [0.3] reliably average [1.0] the [0.2] 
the next technique we're going to touch on [0.3] er [1.1] for measuring 
rainfall is one that we can see [0.9] on the telly every night of the week 
these days [1.5] is radar [1.5] and [0.3] i'm not going to [0.3] labour the 
technical side of radar [0.4] the [0.9] Met students will get it i think in 
their third year from [0.4] Dr namex [1.6] what i'm going to just going to do 
is is put it in the context of [0.4] er [1.8] as a hydrological cycle [0.7] so 
[0.7] er [0.9] the real routes of of the radar growth of c-, of course radars 
grew out of the Second World War but it's only been since i guess the [0.5] er 
mid-nineteen-seventies [3.2] er we've seen a [1.4] a massive [1.4] growth 
in the use of radars for rainfall growth in [1.3] rainfall radars [2.7] and 
particularly in developed countries [0.5] and the U-K now is is pretty well 
covered by [0.5] by by radars [1.8] and [0.9] er [0.5] what we're going to do 
is look at [3.1] look at some of the prob-, some of the advantages and 
disadvantages of radars one of the big problems we're going to find is that 
they don't actually measure rainfall [0.5] they're measuring the water while 
it's still up in the atmosphere [0.5] which isn't telling you about [0.5] how 
much is actually hitting the ground and we have to go through a lot of 
assumptions to [0.4] to deduce that so [0.4] and that's a convenient place to 
leave it [0.7] leave it for now [1.3] and [0.4] see you nine o'clock tomorrow 
morning