They discuss how to match weather station specifications to project requirements, how differences in instrumentation can affect data quality, and what environmental factors might make a weather station ineffective. They answer customer-submitted questions, including:

• What differences can you expect between using an in-field weather station vs. virtual weather?
• What are the risks of choosing the wrong weather station?
• What are the pros and cons of modular systems vs. all-in-one systems?
• How often should sensors be calibrated?
• Does a temperature sensor need to be shielded?
• How do canopies affect the reliability of a weather station?
• And more

Presenters

Jeff Ritter is the Product Manager for plant, canopy, and atmospheric monitoring instrumentation here at METER. He earned his master’s degree in plant physiology from Washington State University, where his research focused on leaf-level gas exchange, and the impact of plant biochemistry on the measurement of the global carbon cycle. Prior to working at METER, he held a research faculty position at Washington State University in the Department of Crop and Soil Sciences.

Chris Chambers operates as the Environment Support Manager and the Soil Moisture Sensor Product Manager at METER Group, the world leader in soil moisture measurement. He specializes in ecology and plant physiology and has over 15 years of experience helping researchers measure the soil-plant-atmosphere continuum.

Questions?

Our scientists have decades of experience helping researchers and growers measure the soil-plant-atmosphere continuum.

• Talk to an expert
• Request a quote

Follow us on LinkedIn: https://www.linkedin.com/company/meter-group

Transcript:

BRAD NEWBOLD 0:00
Hello everyone, and welcome to Office Hours with the METER Environment Team. Today’s session will focus on how to choose the right weather station for your application, and we’re shooting for about 30 to 40 minutes of Q and A with our experts, Jeff Ritter and Chris chambers, whom I’ll introduce in just a moment. But before we start, one housekeeping item, if you’re watching this video and you think of a question you’d like to ask our science experts, we encourage you to submit your question on our [email protected], and then someone from our science and support team will get back to you with an answer via email. All right, with that out of the way, let’s get started, today our panelists are application specialists Jeff Ritter and Chris chambers. Jeff Ritter is the product manager for plant canopy and atmospheric monitoring instrumentation here at METER, he earned his master’s degree in plant physiology from Washington State University, where his research focused on leaf level gas exchange and the impact of plant biochemistry on the measurement of the global carbon cycle. Prior to working at METER, he held a research faculty position at Washington State University in the Department of Crop Department of Crop and Soil Sciences. Chris Chambers operates as the environment support manager and the soil moisture sensor Product Manager at METER. He specializes in ecology and plant physiology, and has over 15 years of experience helping researchers measure the soil plant atmosphere continuum. So thanks for joining us guys.

JEFF RITTER 1:20
Happy to be here Brad, hi Jeff.

JEFF RITTER 1:22
How’s it going Chris?

CHRIS CHAMBERS 1:23
Good to see you over here.

BRAD NEWBOLD 1:24
First question here, how do you define the sweet spot on the price performance maintenance continuum for different industries, say, for instance, agriculture or aviation, etc?

JEFF RITTER 1:36
Yeah, Chris, I’m interested to get your your thoughts on that. I’ve got got some some experience with this, but I’m interested to see what you think.

CHRIS CHAMBERS 1:45
I think there’s one descriptor missing from that, price performance maintenance, and I think that’s risk, right? And the risk of having low quality data or no data at all from unreliable weather stations or missed transmissions. And you can look at it, you can kind of put it in the context of those examples, at the end of agriculture versus aviation. And so we have a whole range of use cases for weather data, everything from Is it warm enough to go water skiing this weekend, or what’s the wind speed like for planes landing, where people’s lives are at stake, to weather data for crop insurance and ensuring you’re going to Get good wheat good yields. And so I think when you add that variable, then it kind of changes the calculus just a little bit.

JEFF RITTER 2:48
I think scalability is another big one. Yeah, exactly. So if you are monitoring weather at an airport you need a station versus us, you know, your huge farm where you need micro climate data right for decision making, right, what the where you fall in terms of price versus performance and how much maintenance you need to do, it impacts it a lot. So, yeah, that sweet spot, I think the answer is that that sweet spot is going to be different depending on on where you are. Yeah, exactly, risk versus scalability.

CHRIS CHAMBERS 3:25
Exactly and you know, some weather stations have redundant systems and system checks. So if you have to have minute to minute high quality data, that’s probably what you want to go with and spend the extra money, right? Whereas, if you have high spatial variability, you’re trying to cover the weather over a county or a couple of fields, but the accuracy doesn’t need to quite be there. You might be able to get something like an all in one weather station that you can get more spatial sampling, absolutely.

BRAD NEWBOLD 4:03
All right. Next question here, what trade offs should users expect when choosing three season versus four season systems?

JEFF RITTER 4:12
Well, when we talk about a three season system, we’re almost always talking about losing one season in particular, and that’s that’s winter, that’s the cold season. Normally, that’s because of power constraints. If you have a four season station, typically it’s one that has heaters on board, right? And you’re going to blow through the power budget on some lower power data acquisition systems, if you put a heater on board.

CHRIS CHAMBERS 4:42
And the precipitation is really the limiting factor here, right? A lot of three station systems will measure relative humidity or wind speed through the winter, at least in some conditions.

JEFF RITTER 4:54
They will there’s, there’s, there are other things to consider there. Snow build up on top of the station can limit your ability to measure solar radiation.

CHRIS CHAMBERS 5:04
Icing on transducers or cup anemometers.

JEFF RITTER 5:08
Absolutely things, things can still freeze up. So losing precipitation and only being able to measure liquid precipitation is obviously the biggest risk of having a three season station, right? But there are other parameters that you’ll lose as well if conditions get bad enough.

CHRIS CHAMBERS 5:28
And in many cases, snowpack is critical, like around the Palouse region, where METER is located, we our winter precipitation is a huge part of the hydrologic balance here.

JEFF RITTER 5:42
Right so, you know, if, if you need measurements in all four seasons, you want to go with with something that has heaters on board, but just keep in mind that it has risks as well. As far as you need to make sure that if, if you’re out in a remote location without mainline power, you need big solar panels, big batteries. You know, I’ve been involved with projects where we were having to trek gas out on four wheelers or snowmobiles, you know, yeah, once a week just to keep generators running.

CHRIS CHAMBERS 6:13
Can be fun, but trying fun the first couple of times, that’s right, depends how often you have to get out there. But in many cases where you’re just interested in the growing season, plants are generally not that active in the winter, especially in agricultural systems. So if you’re looking at ET during your growing season, the three season weather station is should hit everything you need.

BRAD NEWBOLD 6:37
Next question, can you describe use cases or an example where low, medium or high grade stations are most appropriate.

JEFF RITTER 6:48
Sure, I think when we talk about, I’m not sure I love calling something a low grade station, but there’s, you know, there’s definitely stations that are more designed for hobbyists, more designed to measure weather on your back, your back, back patio. And there’s nothing wrong with that. I think it’s great to have people interested in weather. And there’s a whole range even of hobby stations where you can get ones that are $20 you know, and any, any big box store to, you know, even some hobby stations can be several $100.

CHRIS CHAMBERS 7:22
Some Wi Fi, so that you get a console inside your house. And, yeah, you know, just not rely on your local weather station.

JEFF RITTER 7:32
Yeah, even, even for some folks who get really into gardening, you can use it for some decision making applications there, I think though, once you get into research or commercial applications, is when you kind of need to make that next step up to, you know, something that’s more reliable. And I think reliability is the biggest thing that separates these different categories. So sensor specs for accuracy, yeah, so reliability of the data and reliability of the sensor, right, surviving in the elements and so that’s the question that you always need to answer is, how critical are these data that I have them coming in all the time, right?

BRAD NEWBOLD 8:15
What are the practical system limitations of all in one stations compared to more modular setups?

CHRIS CHAMBERS 8:23
Yeah, and in many cases, it kind of depends on the standards. The standards are a great example of this, right? If you look at world Meterological organization standards, the technology has gotten a bit ahead of the standards. So a lot of those standards are designed for modular stations. And I’ve heard that they’re developing new standards for, like, a new class of all in one weather station. But, you know, yeah, there’s development.

JEFF RITTER 8:53
There’s movement there towards our standards, but there is, there’s always going to be a little bit of reticence for the adoption of something a new set of standards until a lot of data has been collected. And one of the practical limitations of something like an all in one, in regard to those standards, is, you know, there are in a modular system, you can easily swap out any particular sensor that’s right, with an all in one, you are, you’re, you know, tied to what fits on that all in one station.

CHRIS CHAMBERS 9:27
And occasionally, if you have problems with the station, you can lose all of your data and an all in one, whereas a modular system, you know, your solar radiation goes out and the rest of your system will keep on going. And that is one of the biggest challenges with modular versus all in one.

JEFF RITTER 9:44
Yeah, yeah. With an all in one you you kind of it’s super easy to set up and get data, but you have what you have if a standard calls for a bigger funnel than what’s on your all in one, right? Just not a lot you can do about that.

CHRIS CHAMBERS 9:56
Or a certain distance of your anemometer away from the. Rest of your station, right? And that’s that’s really a value trade off situation.

BRAD NEWBOLD 10:08
This next question is asking, How frequently should users realistically recalibrate sensors like temperature, pressure, solar radiation to prevent drift?

JEFF RITTER 10:19
So this one, we could go through, you know, every parameter that’s being measured, but it’s really important for anybody purchasing weather station to look into the specs of what they’re measuring beforehand, to know what’s what’s going to be required.

CHRIS CHAMBERS 10:37
And it’s going to vary from from measurement to measurement. Some measurements, let’s use the ATMOS 41 for an example. Some measurements don’t require calibration. We don’t see drift in the wind speed. On the other hand, the relative humidity sensor is known to drift over time, and we recommend recalibrating or replacing that sensor every two years.

JEFF RITTER 10:59
Yeah, and that’s that tends to be what most of the sensors are pegged at that are out there. You know, they’re, they’re typically, their drift allows them to go about two to three years without recalibration when they’re in the field. That’s not for every sensor, though, and so it’s something that you’ve got to really look at for you purchase the station, what you are able to maintain and with any weather station, with any sensor, you need to make sure that you have a maintenance and recalibration schedule created exactly before you install.

BRAD NEWBOLD 11:34
This question is asking, in what field conditions might unshielded sensors outperform shielded alternatives?

CHRIS CHAMBERS 11:41
None.

JEFF RITTER 11:43
Well, this is a contentious nuance. This is nuance. So let’s assume we’re talking about shielded temperature Exactly, yep, because there definitely is an argument or a discussion that we could have about precipitation shielding. But as far as temperature shielding goes, I’d like to hear your viewpoint there.

CHRIS CHAMBERS 12:06
So the reason the ATMOS 41W or W doesn’t need a shield is because we measure all the parameters that are going to affect or bias temperature, so it’s modeled and that that generally outperforms, outperforms passive shielded sensors. So you know the type of shielding really matters here, and I’m going to amend my previous very flippant statement to to be uncompensated. Temperature measurements will will not outperform a some system that compensates for solar radiation on temperature sensors.

JEFF RITTER 12:52
Yeah, I think part of the something that we run into a lot is what we consider truth. And so in this case, the reference set that you use is an aspirated shielded temperature sensor. So if we call that our reference, there’s no way that you can ever outperform your reference in these studies.

CHRIS CHAMBERS 13:12
And it is pretty much the gold standard. It is the gold standard from the physics point of view.

JEFF RITTER 13:16
So as far as a gold standard goes, the aspirated shield temperature sensor is going to be your best bet, except in cases where one power is an issue, yep. Also, if that fan stops running in low end conditions, you actually get less air movement through that sort of a shield than a passive shield. If something plugs up those holes, an aspirated shield can actually be worse, because it allows less air flow through, but under standard conditions where the aspiration is performing, well, that’s going to be your best bet. What we’ve seen with something like an energy balance corrected temperature measurement like the ATMOS 41 it actually outperforms I haven’t tested every passive shield. I know there are reports general passive shields. They’ve been pretty well. It tests outperforms the passive shields I’ve seen it tested against, because you get these midday spikes in air temp inside of those passive shields in low end conditions.

CHRIS CHAMBERS 14:18
And this is a case where real field condition specifications are really hard to draw. A recent client conversation comes to mind where they had ATMOS fourteens that were quite different from their ATMOS 41’s, even though they’re specified fairly similarly, but the passive radiation shield wasn’t doing as good a job, and it was just a difficult conversation to have.

BRAD NEWBOLD 14:43
This one is asking, how do micro climates such as canopy versus open field conditions impact the reliability of weather station data?

JEFF RITTER 14:54
So this, this comes down to what you consider reliable. What are you trying. Trying to measure, because if you are trying to measure the micro climate, then putting it out away from that is you’re not getting reliable, reliable data. If you are relying on weather, weather data from a National Weather Service Station at the airport a couple of miles away, you’re missing out on what you’re actually looking at so it really comes down to what question are you asking.

CHRIS CHAMBERS 15:28
Exactly and the reliability of the weather station isn’t really impacted. You know, as long as it’s functioning properly, the weather, the measurements, the temperature, the wind speed, you know, they are what they are. It’s just you’re you might not be measuring the actual weather, right? And the micro climate has, you know, real conditions. That might be a more important question to you, so that, like you said, that’s the first thing to answer is, do I want to measure the weather, or do I want to measure the micro climate? Do we need to step back and define those? I think we’re just kind of taking it for granted that everyone knows what that means.

JEFF RITTER 16:05
Uh yeah, I think, I think we could, okay, go for it. So there is a microclimate. Is just, you know what it sounds like, where, if you are if you have this in a hole in the ground, because there’s an animal that lives there, and you want to know the weather that that animal experiences, that’s where you need to have a weather station is in that hole in the ground with the animal. But that doesn’t tell you a lot about how weather is impacting things at your county level or something else. And so being able to understand how to site a station for a microclimate is very different, versus citing it to be representative for a wide area.

CHRIS CHAMBERS 16:29
And this is kind of easier just to I think you can kind of intuitively describe it by, okay, we’re, we’ve got the station in a forest. Are we measuring microclimate or weather?

JEFF RITTER 17:01
Are you asking me? Yeah, measuring the microclimate of that places microclimate.

CHRIS CHAMBERS 17:06
Let’s see a park inside a city. Are we measuring microclimate or weather?

JEFF RITTER 17:12
Depends on the park?

CHRIS CHAMBERS 17:14
Ooh, so a weather station. We want to have two meters above the ground, right?

JEFF RITTER 17:20
If it’s an all in one station, you want to have that two meters above the ground.

CHRIS CHAMBERS 17:25
And if it’s not an all in one follow the WMO standards for how to place those different sensors, because there are standards for each sensor, and you want it to be away from any of those influences, like trees or buildings, so that it’s actually up kind of getting the broader.

JEFF RITTER 17:45
Yeah, and there are guidelines for that too. And so depending on which standards you want to go by, if you are going with World meteorological organization, they’ve got standards for how far to be away from obstructions ASABE’s, similar, but they go into more depth as to you know for what measurements you make and what sort of obstruction distance you need so.

CHRIS CHAMBERS 18:06
That’s the Society for biological engineers, right? Okay.

BRAD NEWBOLD 18:09
How do you recommend combining infield stations with regional virtual weather models?

JEFF RITTER 18:17
This is timely. You actually just shared a paper with me, similar in a similar vein, of looking at infield stations versus using satellite weather products.

CHRIS CHAMBERS 18:32
And you know, it’s really easy to get caught up on the AI models or global circulation models, or, you know, any of these complicated, fancy models will solve everything, right? Why should we even measure anything anymore? And there can be large differences between virtual virtual weather products and the actual conditions at any given site. It depends some on the variables. It depends a lot on the distance away from the the station that the virtual weather models are generated from. And you know, just for some examples, temperature is actually fairly good. You can get a good, probably get a good virtual of virtual weather product for temperature that’s going to be pretty close for where you are. Precipitation, probably not so much. The variability in precipitation is so high and depends on so many things. Shotgun pattern maybe?

JEFF RITTER 19:43
Yeah, and I used to think, I think infield stations, I think gridded weather products can be very powerful. You can scale to levels that that would be nearly impossible for most infield data collection projects. Yeah, but I think you always need to have boots on the ground in some way to do ground truthing. I think it’s important that, even as students are coming up now who are working almost entirely in virtual weather station products, that they have experience installing and working with real infield data, because it’s so important for correcting biases, validating models, validating your models, absolutely so I think you need to have a I don’t have a great sense for how many infill stations you need for virtual products, but it is important yeah.

BRAD NEWBOLD 20:46
Which sensors are most critical in calculating evapotranspiration?

JEFF RITTER 20:52
Well, if you’re not able to directly measure evapotranspiration from like Eddy Covariance or something like Eddy Covariance, typically the most convenient option is to model it through meteorological parameters and energy balance, right? So what you’re ultimately looking at is the evaporation of water from a surface. So as long as we know the energy that goes into there, from solar radiation, air temperature, relative humidity and wind speed do a pretty good job of modeling it so.

CHRIS CHAMBERS 21:28
And you kind of need to realize the influence that they have on the measurement too, because the net solar radiation is it’s going to be your most powerful predictor for ET and so that’s something where you probably want to have a really good sensor there, or realize the limitations when you’re using just detected incoming shortwave and then trying to model that radiation.

JEFF RITTER 21:52
Yeah, and that’s that’s a pretty common way that this is done. So the the Food and Agriculture Organization, paper 56 spells that out. Is that what FAO stands for. That’s FAO, great. So that’s that’s spelled out in there, how you actually model net radiation from incoming shortwave radiation with the understanding that that is limited to a specific surface type. So you can’t, for example, take, take that and go model et over, over a parking lot.

CHRIS CHAMBERS 22:29
That’s right. It’s not just the measurements that you’re taking. It’s also the assumptions that are in the model that you should take a look at. Some are, well, I think they’re both well watered canopies, right? For the reference, evapotransport, fully closed well watered fully closed. That’s right, and where. Be mindful of where your real world conditions might not line up with the assumptions in the model.

JEFF RITTER 22:54
So increasingly, there are data products that will calculate reference et for you. And I think that’s great. It makes it much more broadly applicable and usable. But it’s still important to understand the assumptions that are baked into a model like that, because it’s otherwise really easy to to misuse and to, you know, you can’t, again, put this out into any any any garden space, and say this is exactly how much water my plants are using during the day, that that’s just not what the model is built for.

BRAD NEWBOLD 23:27
This next question is for cloud management options like ZENTRA Cloud, what are the pros and cons of real time dashboards versus manual Excel analysis?

JEFF RITTER 23:40
So I have a confession to make on this one in that I have for the longest time. I’ve always felt that anything anybody else can do in their data program, I can do in Excel. I’m not challenging and so, but you really run into problems with data ingestion. I’m too lazy I don’t want data handling. It takes a lot of work, and working in Excel is not a database. Excel is not, you know, automatically backed up onto onto servers that are protected and redundant. And so I’ve had to back off of that stance a little bit because the convenience of having a data platform automatically store my data and have it at my fingertips without me having to remember exactly how I save data, right 10 years ago, when I was a different person, is is convenient.

CHRIS CHAMBERS 24:34
But leaving, leaving the specific spreadsheet out of this cloud, cloud data is extremely valuable for backing up your data, storing your data, sharing your data with collaborators, and even if something like ZENTRA cloud doesn’t have all the features you want, there’s generally an API. So if you want to pull that data directly into R or SAS or whatever, uh you are going to use to do more complicated statistical analyzes, that option is there, and you can keep your data up to date based on the cloud data source.

BRAD NEWBOLD 25:11
So this question here is asking, what are the common installation mistakes that most degrade sensor accuracy over time?

CHRIS CHAMBERS 25:18
Or give you crap data from the beginning? Yeah, right. Because that you do in the installation, you do need to pay attention to some things with the ATMOS 41 and we’ll focus on that. Every weather station is going to have some some idiosyncrasies or nuances. But we’re installing an ATMOS 41 most important thing in any instrument is generally power, right? Without that, you’re not you’re not doing anything, yeah, ATMOS 41W is self contained, but you do want to get the solar panels oriented correctly, right, so having it face the proper direction, so that you get your wind speed set properly and solar radiation optimized. It’s got to be tilted the right direction, right or it’s got to be level gonna be level, okay? And so what happens if we don’t get our station level?

JEFF RITTER 26:19
Well, I mean, there’s a couple measurements that are assuming horizontal parallel to the ground surface. So we, most weather stations, are just measuring two dimensional wind speed. So if you don’t have it horizontal, you are introducing some amount of a vertical component that’s not accounted for, or that won’t be representative, and it’s going to be some uncertainty in the data. That’s right, and you won’t it’s it’s not something you can just easily correct for once you even once you see the tilt right. Solar radiation is the same, where most, most solar radiation sensors are using are giving you global horizontal irradiance. So it needs to be a horizontal sensor. And there’s other the ATMOS 41 as an example, has another sensor that measures individual rain droplets that that can be thrown off. If it’s not, it’s not level, ah, it might miss forming a drop altogether. Yeah, the the drop can just miss the miss the sensor as it falls through its pathway.

CHRIS CHAMBERS 27:22
Does pathway? Does it? Does the tipping bucket tip up, pick up on that? Or can it be biased, too? If the station, I guess it depends on how out of level it is.

JEFF RITTER 27:29
Yeah, I mean, it definitely is less sensitive. But I mean, a tipping bucket, if the station is fully on its side, isn’t going to come out the same.

CHRIS CHAMBERS 27:38
And fully on the side no one, there’s nothing sadder than seeing your logger or your weather station laying on the ground when you make a field visit. So a stable a stable pole.

JEFF RITTER 27:49
Yeah, a stable pole. And I would say to take another step back, is making sure that if you’re installing more than one, that your sensors are all put at the same height. So there’s some measurements that it doesn’t really matter if they’re at the same height. When you’re measuring solar radiation, that doesn’t really matter. But for a lot of other measurements, wind speed, air temperature, these things do have an important height component. So if you’re not accounting for that, when you install you can’t compare between stations.

CHRIS CHAMBERS 28:12
That’s right. Especially if you want to compare data between stations, you’ve got to have them at you’ve got to have them at the same height. If it’s a long term installation, I think concreting your pole in so that it’s going to be stable over time. You know, temporary weather stations use guidelines on your tripod or whatever.

JEFF RITTER 28:38
Yeah, and I would Don’t, don’t just assume that you know driving a PVC pole into the ground is going to be good enough. I mean, if the data matter, then you need to spend a little bit of time making sure that you do have a good way to set this up.

CHRIS CHAMBERS 28:52
And your pole has to be rigid enough so that it doesn’t vibrate when it, when it, when the wind is on it that it doesn’t get knocked over easily if there’s grazing in that area, or wildlife.

JEFF RITTER 29:07
Yeah, wildlife is a big one to take into account. You need a way to whether it’s with an exclusion fence or something else. You need to understand how you can exclude wildlife from chewing on your weather station without actually impacting the measurement.

CHRIS CHAMBERS 29:25
Or rubbing on it, or whatever it is, wildlife wants to do with this odd thing that it has come across out in the environment.

BRAD NEWBOLD 29:32
Okay, next question, what field tools or methods do you recommend to ensure precise orientation to true north?

CHRIS CHAMBERS 29:39
True North is the key here.

JEFF RITTER 29:42
True North is is important, but the so if you’re going to actually do this yourself, you’re going to need a compass, and you’re going to need to know what the magnetic declination is for wherever you are. With the understanding that that magnetic declination does change slowly over time.

CHRIS CHAMBERS 30:04
And compasses have uncertainty too. Like I’ve got a pretty nice forestry compass from that stage of my life, and it’s, you know, plus or minus, I think, two degrees.

JEFF RITTER 30:16
So the easier way, typically, that tends to get pretty good results is that if you have a phone that has a Compass app on it, it probably has an option to set to true north. So what I found is that most of them are defaulted to measuring to magnetic north, but it’s pretty useless. So look for that setting in your phone and change it. Typically, there’s a setting in your phone to set that to true north, and then that’s, you know, for somebody like me who’s not an expert at orienteering, it’s probably better than what I would be able to do myself with when I’m out there in the wild so.

BRAD NEWBOLD 30:54
What are the most effective deterrents to prevent birds from nesting on anemometers or rain gages?

CHRIS CHAMBERS 31:01
Jeff, what’s okay what’s the weirdest slash, grossest thing you’ve ever found in a in a rain gage when you’re cleaning out the funnel?

JEFF RITTER 31:09
I mean, we’ve seen owl pellets, owl pellets, and so they’ve got, you know, all of a sudden, found an, owl pellet.

CHRIS CHAMBERS 31:16
Found half a mouse. Yeah,

Unknown Speaker 31:19
[inaudible]

JEFF RITTER 31:22
The big one, and it’s actually gross with an owl pellet, I think is just bird poop itself. I mean, they when they’re sitting up there, perching, looking out over, over the landscape, you know, their their rear end is hanging into the rain funnel. And so it happens, it happens, and that gets clogged up.

CHRIS CHAMBERS 31:42
So using bird deterrence is is recommended. We have a bird spike kit for the ATMOS 41 and it does. There is a trade off for it, because it does impact solar radiation, right?

JEFF RITTER 31:57
Yeah, that’s the reason why you don’t see one. You don’t see a bird deterrent on every single weather station because it it does have a small negative impact on the solar radiation data, and it’s about 5% right depending on conditions. Yeah, it can be up to 5% decrease or increase in error, about 5% at times. But, yeah, it just prevents them. It doesn’t hurt the birds at all. It’s sometimes people for as a bird spike, but really just prevents them from from perching.

BRAD NEWBOLD 32:31
Yep, all right. This next question is asking, Which metadata elements, for example, panoramic photos, slope or aspect, ground cover. Have you found most critical for reproducibility and future troubleshooting?

JEFF RITTER 32:46
I am a huge fan of site pictures. I think even if you go out and you just do a visual inspection, you don’t think anything’s changed. To take a site picture, there’s so much data that you can get later if you are having to do some sort of a QA, QC, having that picture to know what was happening at the time is, yeah, I’m a big fan of that.

CHRIS CHAMBERS 33:10
Slope aspect are also key, particularly if you’re interpreting solar radiation or anything like that, plant cover is going to be really important. And sometimes you can get some of that information from the site photo too. So you might kill multiple birds with one stone, so to speak. Can you think of any other metadata we might need?

JEFF RITTER 33:33
No, I think that’s I think that’s right. And sometimes they do play. There is Interplay there. I have seen weird solar radiation data before that, a simple site picture, picture would not have picked up. And then if you go out right at the time each day where you see that radiation dip, you find that there just happened to be a shadow, because, you know it was, there was a certain issue with the nearby slope right that happened to shade it during that exact time. So I think you need a bunch of different types of metadata and tie them together so you understand what’s going on with it.

CHRIS CHAMBERS 34:12
You, and especially the height of the measurements on your device, the height of the installation, if it’s an all in one or each individual component, if it’s modular.

JEFF RITTER 34:20
Yeah, I would take a notebook, and anytime it’s it’s moved or touched at all, you have whoever’s doing that record what they did when they did it, like date and time. So you can flag those data later if you see any issues.

BRAD NEWBOLD 34:35
As a follow up to that. What are your thoughts on? Say, for instance, we have some people who have installed game cameras near their stations. Any thoughts on that kind of, you know, near real time or real time metadata, as you know, valuable to the project?

JEFF RITTER 34:52
I think cameras on weather station is a is becoming more and more of a important factor. Yeah. Being able to have near real time images of what’s going on at your site, not just for security, but also for QA, QC. You can use it for as a phenocam, I think that is growing in popularity, and it’s going to be something that we see in the next next five or 10 years become more and more adopted.

CHRIS CHAMBERS 35:23
And it can help let you know if birds are perching on your weather station or things like that.

BRAD NEWBOLD 35:29
Next question, what’s your recommended cadence for monitoring battery levels post installation to prevent data gaps?

JEFF RITTER 35:37
Yeah, this is my answer from grad school will be very different from it is now, because back then it’s, you know, every time you go out there, gotta check how your batteries are doing, and maybe that’s only once every two weeks. But to kind of tie it back into data platform, I think that really having something that can alert you if there are issues that’s right is hugely important.

CHRIS CHAMBERS 36:07
That’s right so you don’t have to check in. I think it’s a good idea to check in on your data frequently anyway, maybe just once a week, just see if anything looks odd, and check in on your battery while you’re doing that, but setting up an alert to let you know if your battery A is declining if it gets below 50% you can get alert or gets towards the red zone in ZENTRA Cloud gives you tools to do that.

JEFF RITTER 36:33
One of the real, really powerful tools that you get out of these data platforms nowadays is the ability for custom alerts, so they can send you an email or a text, let you know that you know once your battery is below 50% or 20% whatever you set it up so you can make the trek out and figure out what’s going on, or replace batteries.

CHRIS CHAMBERS 36:33
Or at least keep an eye on it to know that it needs attention.

BRAD NEWBOLD 36:58
This question asks, how do small measurement errors translate into inaccuracies in model implementation? Is there a threshold where error becomes unacceptable?

JEFF RITTER 37:10
Hmm, that’s a good question, and I could see that being asked in two different contexts, where, one, I have a solar radiation sensor that is drifted over time it’s giving me bad data, yeah, or is it dusty? Or is dusty? Or two, I’ve got my weather station in the wrong location, and all of them are giving me non representative data. You know, how does that impacting, impacting the model?

CHRIS CHAMBERS 37:35
Let’s start with, say, the ET model, because it’s it has some clear, some clear variables that we’ve already talked about to talked about today. And just to recap, net radiation is the single most influential variable on that model. So if you have dust or bird poop on your solar radiation sensor and it’s reading 15% low, which isn’t implausible, that’s not a very small error, but it might be difficult to detect, since cloud cover can be really variable, then that’s going to have an outsized underestimation on your ET, whereas if you’re looking at a more typical error in, say, vapor pressure, you can If you see a one to 2% difference in there, vapor pressure is important for the model, but it doesn’t have as much influence on the output as, say, solar radiation does, so you know a same size error on relative humidity or vapor pressure will have a smaller effect on your model.

JEFF RITTER 38:40
So the second part of this question is there a threshold where error becomes unacceptable. And I see it’s hard to define that threshold for some models, but for other it’s pretty clear cut anytime that your model is influencing decision making. So if you have a model that says, hey, it’s now unsafe to be outside, you know, understanding that where that error is going to lead you to make the wrong decision,

CHRIS CHAMBERS 39:10
Right.

JEFF RITTER 39:10
And in that case, it could be your temperature measurement or your relative humidity measurement which affects the heat index, right.

BRAD NEWBOLD 39:19
When data gaps occur due to maintenance or power outages. What methods are preferred to maintain continuity for downstream models?

CHRIS CHAMBERS 39:26
Data gaps, I hate data gaps.

JEFF RITTER 39:29
Yeah, it really depends on data gaps in what and for how long.

CHRIS CHAMBERS 39:35
Sometimes, if it’s a transmission problem, it might catch up a little bit later, so you might have a temporary gap that fills in when the data comes in, which can actually be problematic if you’re making real time decisions.

JEFF RITTER 39:48
Yeah, I mean, for small gaps in certain parameters, you can do some data interpolation.

CHRIS CHAMBERS 39:55
What about when wind speed goes out on a 2D sonic for precipitation?

JEFF RITTER 39:59
I mean. And if you need data to fill in those gaps, a lot of the time, you’re left with pulling from another station and flagging it or going with environmental averages for the area.

CHRIS CHAMBERS 40:12
And there might be some autocorrelation techniques you could use right up into the outage, depending on the duration. I’m not really qualified to go into any more detail than that, though.

JEFF RITTER 40:23
I would consult a statistician if you are, especially if it’s critical data that you’re making decisions using or publishing on. Consult somebody who knows what they’re talking about. Yep.

BRAD NEWBOLD 40:33
All right, this question is asking, what calibration or validation steps do you run after deployment to ensure data remain with an expected bounce, for example, comparing to nearby stations, etc?

CHRIS CHAMBERS 40:45
We don’t really recommend that very much there are some tests do we? Do we do things after other than look at the data and see if that makes sense.

JEFF RITTER 40:53
I mean, I think there are things that you can do and comparing to nearby stations. Again, it depends on what parameter you’re looking at.

CHRIS CHAMBERS 41:04
Careful with that.

JEFF RITTER 41:05
Can be very problematic, yeah.

CHRIS CHAMBERS 41:08
But when you’re at the site, you can do a couple quick things like check solar radiation. If you’ve got a clear sky day, you should expect it to be 600 800 watts per meter squared, right? Yeah. It depends time of year. Depends on the time of year. Temperature is pretty easy to have a..

JEFF RITTER 41:25
But if you have a historic record of even you know something close by in the area, so you kind of know what to expect as far as extreme weather goes, right, setting up some sort of alerts to tell you is this weather station continuously pushing into the extreme weather events that can tell you that you know it doesn’t mean it’s wrong. It just means that this weather station is either in an area that gets very extreme weather for that region, or there’s some bias going on there. So you can set up, up and lower bounds, just as sanity checks, and then again, there are verification measurements you can make for a lot of parameters.

CHRIS CHAMBERS 42:05
Precipitation has a very good one. Just drip in a known amount of water over a certain measurement, and then you can verify that that’s reading accurately, right.

BRAD NEWBOLD 42:14
Can you elaborate on how sensors distinguish between short wave and long wave radiation, and how important it is to account for both when modeling ET?

CHRIS CHAMBERS 42:22
Net radiation is what you need of both shortwave and long wave, right? So the sensors that measure that measure net radiation, though, can get pretty pricey. Shortwave radiation is generally much easier to measure. So when we say net radiation, bear in mind that we are taking the incoming minus the reflected incoming, plus the reflected anyway, it accounts for the incoming and the reflected radiation, right? Some people don’t like using or don’t want to pay the price for a full net radiometer, and so they’ll just measure short wave incoming and model the rest. But you can expect to get some more error using that method than if you measure net radiation.

JEFF RITTER 43:13
And they both can be measured in essentially the same way if you’re using like a thermopile, and it’s just differentiated with the filter that they have on there so.

BRAD NEWBOLD 43:22
This question is asking, in budget limited projects, what are the first accuracy related compromises you’d accept, and which ones should never be sacrificed?

CHRIS CHAMBERS 43:33
I don’t know that I would have any never sacrifice categories.

JEFF RITTER 43:40
Yeah, I think generally, if it’s a budget limited project, it’s more important to have some data than to have data gaps with highly precise data. So if I was going to sacrifice it would be probably on sacrificing some precision. But the question comes to are we looking at specific measurements that we are willing to sacrifice that precision on more than others.

CHRIS CHAMBERS 44:08
Right, we just talked about measuring short wave incoming radiation versus a net radiometer, you know? And that’s kind of the sacrifice we’re talking about here. You can still get a good ET measurement with shortwave incoming not as accurate as if you’re using a full net radiometer, so, but it’s more than an order of magnitude difference in the prices between those two, right. So it’s I that kind of backs up my say, never, say never. On sacrificing some accuracy or precision, it really just depends on the most important things you need to measure with the resources that you have to purchase a weather station.

JEFF RITTER 44:54
Absolutely, yeah, I think there’s going to be some measurements that are nice to have, but aren’t mission critical. And so I can’t say what those are for any given application, but.

CHRIS CHAMBERS 45:04
Like on a solar farm, measuring incoming radiation is one of the most important things they need to know, so they’re not going to skimp on that. Whereas someone in the field measuring ET for agriculture is probably going to go with a cheaper solar radiation sensor, and I think you can make the same case on almost every variable there, wind speed to vapor pressure deficit to to air temperature, absolutely.

BRAD NEWBOLD 45:34
All right, we’re hitting the end of our time. This is going to be our last question, and it’s kind of a wrap up question here, as models, methods and practices evolve, how do you ensure a weather station or network remains fit for purpose over five to 10 years?

CHRIS CHAMBERS 45:49
This partly connects with the type of weather station you’re you’re purchasing up front, right? You might want to go with a higher end weather station if you wanted to go 10 years. How often do we have a recommended lifespan for replacing ATMOS 41’s?

JEFF RITTER 46:08
Not for, not exactly, but about five to 10 years is what we typically see across most applications. It’s important to consider, you know, there’s no weather station out there that can go 10 years without maintenance.

CHRIS CHAMBERS 46:27
But some common things that people can do to extend the lifespan and the accuracy of their instrument, follow your maintenance schedule.

JEFF RITTER 46:35
Absolutely. And I think that’s one of the ways that you ensure your network remains fit for purpose long term, is getting a weather station that you are able to follow the maintenance schedule on.

CHRIS CHAMBERS 46:45
And it’s going to make your your trends over time easier to make sense of, too. If you have a drifty relative humidity sensor that you don’t replace for four years, you know then year three and year four, when you get a new sensor in there, they might look a little bit off. Number two, cleaning, right? Yep, and you’re going to want to clean solar panels. You’re going to want to clean your funnel, and especially if there’s any agricultural fertilizer added or spray for pesticides, you’re going to want to get out there and get out there and get that cleaned off.

JEFF RITTER 47:22
And those things shouldn’t be an afterthought. They should not just be accounted for, but they should be planned and budgeted for upfront to know that maintenance takes time and money. So I think the best way to ensure that any weather station network remains purposeful for a long period of time is planning for that ahead of time with budgeting.

CHRIS CHAMBERS 47:50
Look a little bit at the materials that your weather station is made of. The ATMOS 41 is marine grade plastic, molded plastic, which stands up really well to UV, and even the puck is made of that material now too, right?

JEFF RITTER 48:06
That’s right.

CHRIS CHAMBERS 48:06
Thank you, Brad.

BRAD NEWBOLD 48:08
All right, that’s going to wrap it up for us. Thank you again for joining us today. We hope that you enjoyed this discussion, and thank you again for such great questions. Also, if you have any questions we didn’t answer, please contact us via our website at metergroup.com, finally subscribe to the METER Group YouTube channel and accept notifications to see previous episodes of Office Hours and to get notified when future videos are available. Thanks again. Stay safe and have a great day.