 Thank you all for joining us this Friday afternoon and welcome back to the CAP LTDR seminar. As you might remember, the seminar series sort of aims to provide a space for CAP members to meet and interact more regularly and share ideas. As a reminder, everyone is encouraged to nominate speakers to share their work with the CAP community. So nominate your students, your advisors, your colleagues. Links to the nomination form are available in some of the emails that Mark sent out earlier, but I'll also drop it in the chat box. So if you think of anybody, please feel free to add them. We do have speakers lined up for the rest of the semester, but we are looking for speakers for the fall series. And so for today, I'm delighted to announce our first speaker for the semester, Dr. Inwe Geva Voni. Dr. Voni is a duly appointed professor in the schools of Earth and Space Exploration and Sustainable Engineering in the built environment, as well as the associate dean of the college, the grad college at ASU. He's a member of the Water and Fluxes IRT and his research group focuses on hydrological processes in natural and urban environments and their interactions with ecological, atmospheric and geomorphic phenomena. Today, Dr. Voni will be talking to us about water, carbon and energy fluxes in an urban park in Phoenix. Enrique, take it away. Thank you, Marina, for your kind introduction and for you all for joining us here. Hopefully you can hear me well. Yes, I apologize for any interruptions and chatting from home and someone decided to take a shower right now. And the water through the pipes is laudable. So that water feature is part of the show today. I'm really excited to speak about this topic. Looking forward to your comments and to your questions. And let's get started. This is a photo of Encanto Park and maybe you might have been there before and I'll be speaking about that today. I've arranged to talk to, I've arranged to talk to go over these four areas. We'll start with some motivation and some background in particular about what is this oasis effect that he's speaking about. Then I'll focus on some methods, then the results and finally some conclusions. I'm going to do something different with the conclusions. I'll do some summary, but I also want to describe the interactions that we've had with the public agencies in the city of Phoenix as well as some media interactions and reactions from this work to get a sense of how do we disseminate our work to the broader public and to other scientists and managers, in this case park managers. So let's get started. What is this oasis effect? The glossary of meteorology by the American Meteorological Society defines it as shown here. An evaporative cooling effect due to heat infection when a source of water exists in an otherwise arid area. Boy, that's confusing. So here's an example. We have an oasis. It's sort of an exaggerated example of an oasis palm trees and a water feature. This is part of incanto park. And so this location with lots of water undergoes evaporative cooling, but it's more than that. There's advection of heat, lateral advection of heat in the atmosphere that's being brought into the oasis. And that energy is also consumed in the evaporative cooling. And so this phenomenon has been studied in desert just before. Especially imagine you're surrounded by sands and you find this groundwater spring. Background water spring created a small town that is very common in the Middle East that depends on that semi-permanent water source, an oasis in the desert. We'll be looking at oasis in a desert but more of the impact of the city within a desert on evaporation in an urban park. And I ran across this concept of the oasis effect in the book of Tom Warner, Desert Meteorology 2004. This is an interesting book. If you're working in our region, it has lots to offer in many different topics as it relates to the climate and the hydrology and the ecosystems of desert areas globally with some examples from Southwestern North America. So Tom describes the oasis as a surface that is moist from irrigation and contains transpiring vegetation. Okay, we have plenty of that. Because of the dry air that flows across the oasis from other areas, there is a large evaporation rate with an associated rapid loss of heat from the surface. Okay, so that oasis is losing heat rapidly. This maintains a low surface temperature over the oasis. It's very helpful. And he presents some examples shown here on the left of what the surface energy budget looks like for an oasis and for a non-noasis labeled semi-arid. Now, these plots are diurnal cycles and I'll be showing several types of diurnal cycles. I'm going to be using this as a plotting space. So let me describe that. The x-axis is local time, noon is 12, evenings are right before 6 in the morning, 0 to 6 after 18. And then on the y-axis, we have the energy fluxes. The unit here is calories per square centimeter per minute. It's usually energy per time per square area or per area. And I've labeled the fluxes here according to the nomenclature I'll use in the remaining part of the seminar. Rn is net radiation. That's the net amount of incoming energy. And it's the dashed line in both of these. Lambda ET is latent heat flux. So think of that as the evaporation expressed in energy units. Sensible heat flux is the amount of heat going into the soil surface. And H, sensible heat flux is the amount of heat leaving the surface up into the atmosphere. Lambda ET and H are turbulent fluxes. G is a conduction of heat into the soil. And so you see some signatures of the oasis effect. First of all, latent heat is dominant. It's the dominant component of the three fluxes that release heat. The incoming is Rn and the three other ones release it in some way. You can see in the semi-arid case, it was dry. There's no latent heat. It disappears. And in the semi-arid case, the dominant one becomes H, the sensible heat, that amount of heat that's being transported by eddies away from the surface. Ground heat flux is about the same in both cases. So we're going to try to look for some signatures in Phoenix that have these behaviors of the oasis. First, the latent heat flux is greater than net radiation, in particular in the late afternoon. Second, sensible heat flux becomes negative, which means the air is warming the surface. So that's our goal. Do we see this in Phoenix, these signatures? Also through the Book of Warner, I ran across this study in science in 1963 done in Tempe, Arizona by researchers in the Agricultural Research Service, Van Bavle et al., 1963. They did a study where they took Sudan grass and they measured transpiration by calculating the amount of water and soil. And they did this for a fully covered vegetated area and one in which they had removed plants around a central location. And they measured transpiration as a function of time during a day. And they found that transpiration was higher when the area around the grass was drier, meaning advected energy from surrounding the grass, added energy to the grass and the grass, according to them, transpired more. The transpiration amount is phenomenal, 15 million meters in a day. That's a lot more than open water evaporation. So these folks inside the weak land of Sudan grass under the conditions of temperature, high radiation, low humidity, and sufficient soil moisture can transpire upon atmospheric demand. And so we then thought to ourselves, well, if there are OACs out there, they'll out OK. Now, the OACs for advected from surrounding the earth, that's denoted by those squiggly dash lines labeled advected energy. In the park, there's several, but I'm going to speak about two budgets, the surface energy budget and the carbon dioxide budget. I've used simplified forms of these budgets. There are limitations in the two equations shown here. So the surface energy budget is net radiation minus ground heat flux is equal to sensible heat flux plus latent heat flux. If that's equality is not true, then there must be other sources of energy that are not accounted for. The carbon dioxide budget here is the net ecosystem exchange is equal to the ecosystem respiration, which is a loss term minus the gross primary productivity, which is a gain term. And I've listed the units of the two budgets. And as I said, these are very simplified first order types of budgets for urban systems. Urban systems have the addition of CO2 from transportation from other fossil fuel emissions. Urban systems have much more heat storage that affect the energy budget. So give me the break here of treating it simply. And then we'll see what the data says about the budgets. OK, so what are the signatures of the Oasis effect that we're looking for in the data set number one, a period of negative sensible heat flux, which would imply downward movement of heat from the air to the surface. Number two, a late afternoon period where the late heat flux is greater than that radiation. Think about what that means. You have more energy going into the phase change of water than is available directly in a vertical sense from the sun because of these lateral inputs. And the final one is positive late heat flux at night. OK, Warner showed it for his example of an Oasis. So in the absence of the sun, evaporations happening. Let's see if that's true in an urban park. So these are the questions we pose to guide us. What is the impact of turf grass irrigation on the surface energy balance in an urban park under differing meteorological conditions? And number two, what evaporative processes are responsible for the increased evaporation rates when there is this lateral advection of heat? So question number one, sort of standard. Question number two, can't only be done with a surface energy budget. It's really helpful to have the CO2 fluxes to address question number two. OK, so here's the study site I mentioned in Kanto Park. Let's dive in to more details. This is a close up image. The red star and the yellow triangle are the locations of the sensors established for the study to one year study. March 2019 to March 2020. This is the 14th hole of the Kanto golf course. Those of you that are golfers, you can see the location from 19th Avenue here. There's a residential community, relatively large lots just to the west. And the park is huge. We're in the northwest corner of the park. I've outlined the fairways. These polygons are the fairways where the grass is kept really short and well maintained, well irrigated year round. And anything in between those is called the rough, where the grass is allowed to dry out. So Bermuda grass is a warm season grass. During fall period, it's allowed to go dormant and it's not replaced. Whereas the fairways go through a process called overseeding. A different species called ryegrass, a wintergrass, is established for the winter period. On the right hand side is the normalized difference vegetation index for that same area obtained from a constellation of satellites run by a company called Planet. I'll tell you a little bit more in a second. Green colors imply chlorophyll and plant biomass. And red colors imply impervious surfaces, asphalt, concretes. So you can see the difference here between the park and just outside the park. And the polygons depict the footprint of a few different sensors that I'll be describing. The blue circle is the footprint of the radiometer. It measures the different components of net radiation. And the other two diagrams are different percentage levels of the footprint that's measured by the tower. So 50% is the inner one, 80% is the outer one. And this is for the warm season, averaged over all days in the warm season. These footprints vary from day to day, within a day. So this just gives you a sense of the representative area that the turbulent fluxes see or observe. These are the instruments. We established the educovarian station inside a fenced area. This fenced area is part of an AZMET weather station in the park that's been there for about 30 years. So we were benefiting from science done by the AZMET network, which is part of the University of Arizona's Agricultural Extension Service. They use it for estimating turf grass irrigation requirements in Phoenix. And they're used by homeowners associations, park managers, golf courses, et cetera. We added the tower. And that tower contains a three-dimensional sonic enemometer, an infrared gas analyzer that measures high-frequency concentrations of water vapor in CO2, a radiometer, a rain gauge, and a few other ancillary sensors in the soil, soil thermometers, soil moisture sensors, obviously some ancillary measurements in the atmosphere, air temperature, relative humidity. So that's the station. And you're seeing sort of a view in the summertime in the warm season when the grass in the rough area is green. This particular method is by now very well-established. It's only about 20 years old as a method. The experimental part of eddy covariance happened in the 1990s up to the year 2000. From then on, it's become something that you can essentially purchase and use and their software to help you go through many, many different processing steps in arriving at the flux, in this case, of carbon dioxide or the flux of water vapor in either direction between this atmospheric layer and the surface layer below it. If you're interested in speaking more about this, I'd be happy to. What does the tower see? This is a good cartoon of a tower in a domain. And it sees this time variable footprint, which shifts according to wind direction and wind speed. And you can track this because you're measuring wind direction and speed for every time you measure a flux. So sometimes the flux footprint is really close to the tower. Sometimes it expands and includes some of the urban area, a little bit of that lake, for instance. And one can estimate the flux footprint using analytical models. In this case, it's a two-dimensional model. And shown here on the left-hand side are some examples. The flux footprint for the warm season is much larger than the flux footprint for the cool season. They have about the cool season's almost circular in shape. The 50% tells you, well, 50% of the fluxes are coming from that really small location close to the tower. The 100%, well, that extends a kilometer away. Hard to track where that's coming from. The 80% is a good compromise that gives you a sense of where those contributions are coming from. Now, there is the surface energy balance to worry about. So the eddy covariance gives you h and lambda et. The radiometer gives you rn. Ground heat flux place gives you g. Do these actually lead to an energy balance? In other words, is that equal sign equal on both sides of the equation? It turns out, you could do the analysis, that most of the times that you use eddy covariance, you're going to be unable to capture 5% to 20% of the available energy. You're not going to measure the available energy in the turbulent fluxes. In this case, we captured in the warm season about 94% of the available energy. And in the cool season, about 82%. So there's some portions where you don't close the energy balance, but it's within what we would expect for this methodology. Why is this doomed? One, there's a mismatch in what the radiometer sees as compared to the eddy covariance method. The radiometer sees a smaller area than the eddy covariance method. There's also a mismatch between a single heat flux plates that measures g and what the eddy flux measurements see. That's one. So spatial mismatch. The other aspect is there is these energy storages and energy inputs in urban areas that are not accounted for well in this particular method. So take what I say later on with this asterisk that there's uncertainty in these measurements on the order of 6% to 18%. We really wanted to know how the park changes in time during this one year study. And one way of doing that is go visit the park and take a photo. Another way of doing that is using these really cool, small satellites pictured here on the lower right that are orbiting the Earth. There's about 150 of them. Low Earth orbit producing near daily high-resolution imagery. High resolution here is like three meters near daily because we don't have much cloud cover. And so we were able to track the normalized difference vegetation index. It has this capacity because it has a near infrared band and map out the different conditions of the golf course to the human management. That's really cool. So for instance, in February of 2019, there's only grasses in the fairways. And all the rough is like the image behind me, yellow, or as shown here, red, low values of vegetation index. Now we proceed in time and water gets added to the rough. The rough bermuda grass greens up and starts to fill in. The warm season has some patches. These patches have to do with irrigation issues. You have a sprinkler that's not working appropriately. That little yellow patch develops. But we're over irrigating over here, and that bermuda grass becomes really green. That's in the warm season. In October of every year, they do the overseeding process, which basically creates like a bare soil surface as they're adding the rye grass seed. So everything is uniformly non-vegetated. And then we go into the cool season again where only the fairways have green grass. It's pretty cool stuff. OK, so we know the dynamics of what the turf grass is doing. And we've talked a little bit about the measurements. So what are the outcomes here? Well, first, here is sort of visual evidence of the warm season green state for bermuda grass, and the cool season dormant state for bermuda grass. And on the right hand side, we have the measured evapotranspiration millimeters per day over the study period. And it's compared to an estimate at the AZMET station. The estimate at the AZMET station is based on meteorological data only. So I went into it thinking, oh, that estimate must be really bad. Lo and behold, these turf grass irrigation specialists know how to estimate evapotranspiration from limited observations. The fit is surprisingly good between the two methods and gives confidence in AZMET stations. A few things to note, the warm season in white and the cool season in the shaded gray have radically different amounts of evapotranspiration. I drew these horizontal lines to guide you. Let's say there's about six millimeters per day of evapotranspiration in the warm season and only about two millimeters per day in the cool season. That's a difference, a factor of three, which leads to a very large difference in total evapotranspiration. There's about a meter difference in evapotranspiration between warm and cool season. And you have that nice seasonal pattern corresponding to radiation input. If someone asks you how much turf grass irrigation ET happens, here it is. Up to what? Up to about eight millimeters per day, down to one millimeter per day. Does this get up to van Bevel's 15 millimeters per day? No way. So I'm not sure where they got that value from. So we have evapotranspiration, daily amounts. We talked about how they vary. And then we did an analysis. What controls evapotranspiration? So we did regressions against all the other meteorological values, air temperature, relative humidity, soil moisture, soil temperature. And it turns out that the dominant ones are the ones that I've shown here, relative humidity and air temperature. And they're readily available, which is a good thing. I could get those for any park. I could get those with handheld devices. Okay. So the other good thing about these two variables is that they're proxies for what really matters. TA is a proxy for the available energy. And RH is a proxy for the vapor pressure deficit or the gradient in vapor pressure between the transpiring leaves and the atmosphere. Readily available proxies for the main controls. Then we said, how do we identify which days during this record have the oasis effect? Okay. The good thing about co-locating the tower with the AZMET is that we have a one year record of the tower that compares well with the one year of AZMET. But we have 15 years of AZMET. So we exploited the full AZMET record. And what the right hand side shows is our approach for classifying days where the oasis effect occurs. What we have here is a space, the two main controls, TA versus RH, they create the space. And the dots tell us individual days of 15 years. So there's thousands of points here. And the color is indicative of the evapotranspiration amount as obtained by AZMET. So any of those low values, one, two millimeters, they fall out here. Low air temperature, low or high relative humidity. The high values, the ones that are occurring when you have lateral input of energy, they all fall in this corner. High air temperature makes sense. It's in the summertime. Low relative humidity makes sense. Low relative humidity means high vapor pressure deficit. So then I spent like three days without sleeping to understand how to create a simple way to characterize this. So this sinusoidal function shown there is a threshold between the non-oasis days and the oasis days. That is a simple relationship that only needs air temperature and relative humidity. I'm proposing it as a way of indicating in any park in Phoenix, if you have an oasis effect or not. If you know relative humidity, RH, calculate the air temperature from that equation compared to your measured air temperature. If your measured air temperature is higher than that value, you're on the right-hand side of that threshold. It's an oasis day. If you're on the left-hand side, it's a non-oasis day. Now, this stuff is really cool because the method developed here identifies oasis days. And all of the oasis days identified during the study period, well, all of the excessive heat warnings during the study period are also oasis days. So the National Weather Service is the one that issues excessive heat warnings. In the summer of 2019, there was 26 of them. In the summer of 2020, there were 48 of them. When there's an excessive heat warning, things happen, right? Watering stations open. There's the city services for the homeless change. We are instructing not to go out for certain periods of the day. We limit our outdoor activity. Society responds to the issuing of these warnings. Well, all of these excessive heat warning days are oasis effect days. And there's other oasis effect days in addition to those. We found 65 oasis days in 2019 using this method. And we developed a nice little chart that could be used to identify oasis days. It uses the heat index as a concept and relative humidity. So why is this important? It's practical. It's related to the method that the National Weather Service uses. So these lines, the red line is the approximate solution and the full solution is the dashed line. If you are above those relationships, you are in oasis conditions, low relative humidity, high heat index. If you're below those lines, you're in non-oasis conditions. You shouldn't see the effects of the affected energy on the surface energy balance. So now that we have a method to determine oasis conditions from really available data, let's talk about what happens during those conditions and what happens at the park. Okay, here's the first take. As I mentioned, this is a one-year study. I'll walk you through some of the observations. And orange is net radiation, daily value, warm season is high, cool season is low. That looks a lot like ET, surprise, surprise. The warm season for 2019 was very dry, as in almost no rainfall, or what we are now calling a nonsoon. So there's no rainfall, in a monsoon region is a nonsoon. Contrary to that, the cool season in 2019 was really wet. These events are not actually very common. So there was a above average wet season, a cool season and a below average warm season. NDVI or the vegetation condition is basically following management. If this were a natural system, you'd see an NDVI pulse when there's rain and NDVI go down when there's not rain. We irrigate a lot. So the plants are not really responding to rain. Perhaps one could say these did here to some extent. Okay, irrigation amounts. These are city of Phoenix monthly values of water added by a sprinkler system adding contour part. Take a look at those values. In the summertime, say July, they add 300 millimeters of water per month. 300 millimeters is bigger than our annual rainfall, on average, Phoenix has 200 millimeters per year. So in one month, they give the park the equivalent of a full year's worth of water and they do that for six or seven months. So irrigation input overwhelms rainfall by a huge margin. Irrigation input is such that check out what soil moisture is doing. We have soil moisture traces at 515 and 30 centimeter depths. In the warm season, soil moisture is increasing over time. I don't think you'd find a natural system that behaves this way. So first of all, it's not very sensitive to water input from rainfall. And it's growing over time as you get hotter and hotter and enhanced in the excessive heat warning days. Somewhere around October 1st, they crack down on the sprinklers and soil moisture starts to decay. And in the wintertime, in the cool season, it does respond to those precipitation events. The values of soil moisture here are really high in terms of magnitude as well. And so wet soils down to at least 30 centimeters create conditions described by Werner as oasis conditions. And the first sign of that is the comparison of air temperature with soil temperature shown here in the bottom. Air temperature in black, soil temperature in orange. And these track each other very well. If you look at a natural system, soil temperature has wild variations as compared to air temperature. Because soils, right? They can heat up a lot, 60, 70 degrees C in the soil at the surface can be measured. And then soils cool a lot at night. And so they have much wider fluctuations. This soil is kind of like just following what the air temperature is doing, almost in equilibrium. Okay, so let's dig a little deeper here. We have three temperature comparisons or measurements we can compare. One is air temperature TA, another is soil temperature. Soil temperature here is the average of a sensor at two centimeters or the sensor at six centimeters. So we're talking, you know, the shallow soil. And then land surface temperature LST is kind of the skin temperature you see from the radiometer. It's a bigger area and it's sort of what the grass, temperature of the grass. The bars represent different periods. Okay, warm season is hotter than the cool season. That's kind of obvious. In the warm season, when you have an oasis day, it's hotter than a non-oasis day. Okay, oasis days are hotter. Fine, we've established that. I think the more interesting piece here is that there's almost no difference between air temperature, soil temperature and land surface temperature. Okay, suggesting that the amount of water being added is really buffering temperature fluctuations in the soil and in the air. You can see that on the right hand plot where if you look at the diurnal pattern of temperature, the soil and the air have essentially the same temperature between seven in the morning and five in the afternoon, which is not possible if it weren't so irrigated. Okay, we looked at soil moisture to see, is there a diurnal signature in soil moisture? There isn't. Soil moisture is higher in the warm season, lower in the cool season. We've established that before. There's no diurnal cycle. There's not much of a difference in soil moisture across seasons. Now the warm season is slightly wetter than the cool season. Oasis days and non-oasis days doesn't matter too much. So fully wet all the time. Think of this as a system that doesn't have a water limit. Water is fully available. Okay, so we have a system that's green. We have it in the warm season, we have a system that has no water limitation. So what does limit the system? Well, perhaps it's energy. Although we're in Phoenix, perhaps it's energy. So here what we're showing is the effect of these oasis conditions as air blows into the park from different directions. Okay, so let me first remind you, we have this residential area just to the west. That would be in the system used here, winds from the residential area are coming from angles from degrees 240 to 300 and that little pizza slice are winds coming from the west. Everything else in the pizza is coming from other directions. Coming from the north is zero, coming from the south is 180. Okay, so the circles are oasis days, those 65 oasis days. They, most of them all have high evapotranspiration rates that exceed what you would expect under average conditions, okay? What I mean by that is what the upper plot is showing is the evapotranspiration that year as compared to the evapotranspiration averaged over many years. And an oasis day isn't always gonna fall June 1st, right? It's gonna fall whenever it falls. And so the average over many years erases the oasis conditions. And these peaks tend to be the oasis days are much higher than the average condition for that date of the year. Those oasis days have high solar radiation and high vapor pressure deficit because those are the two controls that we mentioned. If we plot them in this space of where the winds are coming from, some oasis days fall in that pizza slice where you have this neighborhood effect, the nearby neighborhood. But there is oasis days coming from all other directions. And so it isn't that it has to blow, the wind has to blow from the nearby neighborhood for there to be an oasis effect here. Now, the oasis effect can occur if the wind's blowing from the north, south or east. And why is that? That's because Encanto Park lives in this huge urban fabric. So here's Encanto Park in this inner box and around it, commercial zones. The pavements of the Arizona State Fair are huge. I-17, I-10, residential communities. So the oasis effect can come from any direction. We call that the omnidirectional effect. As long as you have high heat conditions in the summer, high air temperature and low relative humidity and some winds have to blow from any direction, then you'll get additional energy input into the park. And so we'll see where the energy goes here in a second. Just to give you a sense of the energy balance and the plotting style I'll use a bit later, here's a comparison of the warm season and the cool season, net radiation in black. These are averages over many days. The average is the symbol or the line, the envelopes are center deviations, lane heat flux or evapotranspiration in blue, sensible heat flux in red, ground heat flux in green. In the warm season, there's clearly a dominance of evapotranspiration. As you go into the cool season, net radiation falls, evapotranspiration also falls. Sensible heat flux remains about the same in both seasons. Let's take a look at the carbon fluxes. In the warm season, we have no nighttime productivity, as expected from plants, the daytime carbon uptake of plants, positive GPPs. Respirations happening all the time, day and night. These are coming from soil, micro biological activity, from plant roots, respiration. And you could see there's very little in terms of a diurnal signal on respiration. It's high, it's positive, it happens throughout the day. The net effect is what we call net ecosystem exchange. So at night, it's positive, meaning there's a CO2 efflux toward the atmosphere. During the day, it's negative, which means CO2 is being captured. So CO2 sink in the day. And the warm season and the cool season look very similar. Of course, the warm season exaggerates things because there's more plants, right? There's more water, there's more air temperature. All of these lead to greater carbon fluxes. Okay, so what is the oasis effect doing? Here's a comparison of warm season oasis days. Now we're familiar with this space. And warm season non-oasis days. The easiest way of looking at this is comparing the solid and the dashed line in B. The solid lines are the warm season non-oasis days. There's 118 of them. And the dashed lines are the excessive heat warning days. There's 26 of them. The excessive heat warning days behave like an oasis day. So any difference noted by the arrows here is the oasis effect. What does the oasis effect do? It increases net radiation, not in the morning, from noon to late afternoon, okay? What does the oasis effect do? It greatly increases latent heat flux. It really increases latent heat flux. Throughout the day, starting at dawn, throughout the night as well, okay? So this advected energy is going somewhere. It's going into evaporation. What does it do to sensible heat flux? Oasis conditions reduce sensible heat flux, make it more negative as predicted by Warner. Now, those are averages over many days. Every day is different. The wind comes from a different direction or you irrigated more at night or the wind speed is lower. We're gonna look at two days to get a sense of the physics of the problem. August five and August 30. And I'm gonna step you through a few things here. August five, the wind direction is from 43 degrees. 43 degrees is coming from the northeast. August 30, the wind direction is 241. That's coming from the west. So August fifth, omnidirectional effect from far away urban sites. August 30, neighborhood effect from that nearby location. And we're gonna look at the diagrams here in a second. Let me point out these top lines. The solid gray line is a normalized maximum wind speed. I've done some normalization of fitting the plot. When you have high values, it's a wind gust. Low values, steady winds. The dotted light-colored gray line is soil moisture. So moisture is decreasing. Then there's an irrigation effect. This happened in midday. They irrigated in midday. So moisture goes up and it comes down and they irrigate again at night and so forth. So what's happening? The day where the winds are coming from the west, okay, from the residential area. There was a wind gust starting around noon and ending around 4 p.m. So more than a gust, you know, a consistent rise in winds. And as that was happening, we get this big pulse of evapotranspiration in the park, which is greater than the net radiation. That's a direct impact of a wind gust over the residential area, adding heat to the irrigated park. Brief, intense pulse of evaporation. During the day. Now, when we have this increase in evapotranspiration due to that pulse, we have sensible heat coming to zero, sometimes becoming negative. So here's like the effect of a gust. For the other day, we don't have a gust. We have something else that's happening and it's worth describing. We have irrigation at night. This irrigation at night led to a nighttime pulse in evaporation, which I'm highlighting here with the arrow. The system is so energetic at night. They turn the sprinklers on. The plants cannot photosynthesize at night. The sprinkler water evaporates as it travels through the air or evaporates when it's falling on top of the turf grass or maybe evaporates from the soil directly and leads to a pulse of evaporation at night. And that pulse of evaporation happens at the same time than a pulse of CO2 at night, efflux from the soil to the atmosphere. So these nighttime processes are really important as we'll see here in a second. So what's happening with these nighttime pulses? It turns out that the nighttime pulses dominate the CO2 budget to the point of converting a system that we envision as being a net carbon sink into a net carbon source. Throughout the warm season and especially for oasis days, net ecosystem exchange is positive at the daily scale. A net source of CO2 to the atmosphere. That's happening because of the nighttime irrigation leading to the soil CO2 efflux at night. During the day, plants are still trapping CO2. It's just that there's more CO2 lost at night that there is consumed during the day. That's because the plants have reached their physiological limit. They can't photosynthesize anymore. They can't do more gross primary productivity when you've added more energy to them. So they're not energy limited and well, they're not water limited. And if you add more energy, it doesn't do anything else to them. They're at their, I'll say biological maximum. So that's some food for thought related to these anthropogenic systems. Did we find evidence for the oasis effect? We have all of the features noted by Warner exist at Incanto Park. We have spikes of latent heat flux that are greater than net radiation in the late afternoons. We have nighttime evapotranspiration, mostly evaporation. We have zero or negative sensible heat flux during the day. So that part I think is shown well. What we didn't expect is to find that the CO2 would disprove van Bavle. The CO2 fluxes tell us those plants cannot adjust to the additional infected energy and transpire more. The evaporative losses are not related to transpiration. They're related to nighttime evaporation of sprinkler water, either as it's traversing the air or when it's on top of the grass or it goes into the soil and at nighttime evaporates from the soil. And that's what's responsible for the soil efflux. We have warm, wet soils at night, warm, right? Remember the soils and the air are about the same temperature. So if we have a nighttime temperature in an excessive heat warning day, that is 95 degrees, that means the soils are 95 degrees at night as well. And this was a great project to work. First, because of the great interactions with graduate students pictured here are Mercedes Kindler, who's doing her master's degree on this topic and Elieperis Ruiz, who's a PhD student. We worked for three years with the city of Phoenix to get the permission to install at the park, to get the park managers to support our efforts, to provide the irrigation data, to tell them what was going on in our measurements and get some feedback, constructive feedback. And so it was a great sort of interaction with the public agency experience. In this case, it was the Parks and Recreation Department of the city of Phoenix. City of Phoenix provided some small funding opportunities and we were able to complement that with some other sources from the Central Arizona Project and the Innovative Conservation Program. In addition to Mercedes and Elie, Xiao Cheng Wang did the remote sensing work that I showed earlier. And we bundled this together in a paper that came out in Geophysical Research Letters shown here. So this paper comes out and it gets picked up by certain news agencies. And this is a good thing, I suppose, but it also presents some challenges. And so we had some contrasting media coverage. KJZZ did a little radio piece on it and a published written piece with this title. ASU research finds surprising inefficiencies in a Phoenix Parks Irrigation Plan. I almost had my head chopped off by the city of Phoenix after this came out, whom I'd been working with for three years to exactly avoid this problem. Then the Irrigators Association, there's a whole professional group of people dedicated themselves to managing turf grass. They took the same piece of information and their title is, ASU research aims to increase the irrigation efficiency at a Phoenix Park. Two contrasting views of exactly the same study. And here's Xiao Cheng and Elie and I at a little photo op that we had at the park with masks. So I'm presenting this to you all to spur some ideas. We might not have time for a full discussion today, but there are several things that could come afterwards. Well, we have an idea here that irrigation at night has some unintended consequences. Can we do an experiment where we irrigate a dawn or we irrigate only in non-excessive heat warning days or we irrigate during the day? So how do we devise an irrigation plan that keeps the infrastructure working but minimizes the CO2 losses? Another area that's fruitful for any of you interested in this topic, how do we take what was learned here and apply it to other parks? Does the oasis effect happen in all parks for excessive heat warning days or does it depend on the size of the park? Maybe it's big parks, not the small ones. Since we can identify the oasis effect based on relative humidity and air temperature, that's an easy observation to do. So that's a subject that someone could pursue. And one thing that I really think is necessary is what are the downwind benefits of the oasis effect? Who benefits? Which neighborhood is receiving the heat reduction and thanks to the irrigation that is happening in Canto Park? And of course that has consequences on human comfort, consequences on energy use in their home, consequences on property value, consequences on health. So a study that at least had three sites, an upwind site, a park site and a downwind site to understand the relative differences across this oasis. Okay, that's what I had for you today. I'm happy to take questions and thanks again for the invitation. Thanks for the great presentation. Yeah, does anyone have questions? Dan. Enrique, it's good to see you again. It's been a while. That was an awesome seminar, really, really cool stuff. I live in the neighborhood just east of in Canto Park. So I'm not sure that we're getting any oasis effect from your study area. I'm sure you are, you just haven't measured it. Right? So my question is thinking about comparative data. So you started with several, sort of more theoretical plots from past work that should have compared an arid place, an oasis place in the same climate zone. And so my question is, we've got this Maryvale Eddy Flux Tower that has been collecting data for a long time. And the footprint of that tower has very, very little, if any, vegetation in it. I mean, it is just solid impervious surface and buried around. And I guess I'm wondering if there would be any value to comparing on the same days that you have data from in Canto Park, Flux data from the tower at Maryvale. We've given some thoughts to it. And we spoke to, I remember if it was Stephen or Sally to try to get the Maryvale data for those periods, but there's, I think the radiometer has been down for a long time. Don't know that for a fact, we couldn't do it. We couldn't do the comparison. The other thing that keep in mind, it's a really tall tower that measures a huge area versus a small tower that's measuring a local area. I'm not sure we could. Having said that, Winston-Chow's paper in 2014 on the Maryvale Flux Tower shows something that looks like it could be the oasis effect. It's not definitive, but the footprint has 10 to 15% irrigated tree and grass patches. Oh, it does. Okay, that's higher than I thought. Okay. So there is a signal, it's just not very strong because as you say, it's mixed up with lots of roads, lots of residential areas, empty pools, backyards that have had their turf grass ripped out, et cetera. Mm-hmm, mm-hmm. But yeah, it would be interesting to do a cross-site comparison. Just so you know, we have pulled, after getting scolded by the city of Phoenix, I have pulled out the instrumentation. No, I'm kidding. Oh, no. No, no, no, it wasn't that way. Mercedes had finished her fieldwork, we pulled out the instrumentation. It's ready to deploy somewhere else if needed. Got it. Well, your seminar is actually really timely because in our, we have cap managers meetings every two weeks and in the one we had earlier this week, Steven brought up the point, Steven and Quincy both brought up the question about the Maryville Tower because nobody's using those data. We're collecting tons and tons of subhertz data from that tower that are occupying, you know, huge amounts of server space and data land and nobody's using any of those data. And so what we talked about was, you know, the tower was built so that it can telescope down and basically go offline if somebody doesn't need it. And so we're considering just doing that because we spend a lot of time and effort making sure that those instruments work and downloading the data and managing those data. And I guess I'd be curious to know your input. Is there any reason to be continuously sampling a tower that nobody cares about? Look, these are very, very complicated systems. The data processing is an enormous task. I would first check, are all the sensors working? That would be my first check because if you're missing the radiometer, then you can't really do this check against what we call energy balance closure. And if you can't do the energy balance closure check, you don't know how good the turbulent flux measurements are. I can't speak for the current condition of the tower, but I have asked students to interact with Steven and Quincy and others. And for these dates, we couldn't do the comparison. That's such a change. Okay. Well, that's good to know. Thank you. You're welcome. Dr. Wang, nice to see you. Hi, Ricky. First of all, I doubt whether they will really receive any benefit of Oasis by leaving downwind to the park. I mean, I doubt basically Oasis affects local cooling and by more evapotranspiration, you're actually sending more moisture down to the wind. And was that actually increased, I mean, was that actually decreased thermal comfort instead of the internet? That's a good point. But what I'm thinking is in the absence of the park, what would the conditions have been at Dan's house? Because if you removed the heat sink, he would suffer more energy cost. That's true. Yeah. Okay. And thank you. That's a great question. Yeah. On the bright side, Dan, we are still using the tower. We are keep on using that tower. So we keep on publishing a technology cap. So I really think it's necessary to keep the tower keep on running. And it's really beneficial to, at least to my research, as our fathers can see, and probably cannot talk for others, but it's really beneficial to ours. That is exactly what I needed to hear, Ziwa. Thank you so much. We will keep the tower going just for you. Great. Great. Can we find a way to contribute to the tower somehow? Hey, there is eight years of processing that needs to be done on the raw data. You've done some of it. I've done some of it sitting down and putting that together in a consistent fashion is a good task. Enrique, can I jump in with a couple of quick methods questions? Sure, Sam. I was, from the start of your talk, you mentioned that you'd have to know CO2 concentrations to really close the heat budget. And I was just making sure that I understand I heard you correctly. And the question is, if that's strictly transpiration, is the mechanism why you need to know? And then the other is the difference in the footprint of your tower between cool season and warm season and why maybe like the dumbed down version of why that change, the footprint changes from warm to cool. Sure, I apologize. I must have misspoken. The carbon budget is separate from the energy budget. There is no common term. But what the carbon dioxide budget allows you to look at, as you're measuring the surface energy budget, are the sources of evapotranspiration. If it's transpiration, then the plants need to be photosynthesizing as they're releasing the water vapor. And you would see a signal in the carbon budget. We find no signal in the carbon budget during the day, during Oasis days, which means the plants are doing whatever they did across all days. So there's no increase in transpiration when they have more energy. That was the first part of the question. The second part of the question is, evapotranspiration has multiple components, the transpiration being one of them. But imagine a sprinkler. And these are not sprinklers at your house. These sprinklers are going like 30 feet. And they go up 20 feet into the air. And so you've got this spray of water going through an air that's hot and has huge demand because of vapor pressure deficit. And so those airdrops are just instantaneously evaporating at night. So to me, this is a problem we can solve. We could probably keep the golfers happy. We could probably keep the vegetation green. And we could reduce water losses to the deep subsurface and water losses to the atmosphere by altering the timing of irrigation. If we irrigated in the day, the plants could use it. If we irrigated at night, it goes to non-biological water. This study, I mean, I had so much fun. I think you could tell with this study. Why? Because we create these novel ecosystems that are so weird that they tell you so much about the fundamental problems that we deal with on a normal basis and natural systems that are not as weird and therefore not driven to such extreme and member states, if you will, right? Are there any more questions for Enrique? All right, well, we did go a little bit over, but I think it was a good conversation. So thank you again for giving a great talk. And thank you all for coming. I hope to see you next time. Great, see you all. Thank you very much.