 Great. So I want to spend a few minutes with you this afternoon talking about how Nimbus as the granddaddy of learning how to take measurements of precipitation and how far we've gone in the 40 years since Nimbus started doing precipitation measurements from space. So I will start by going to the next slide. So I have a little bit of an outline here. I'm going to talk a little bit about the history of the Nimbus measurements and instrument launches for that data. I'll explain in as layman terms as I can how these radiometers work to measure precipitation. And then I'm going to talk about some of the science results that have happened in terms of precipitation from Nimbus all the way through the decades to the global precipitation measurement mission which I'm the project scientist of and we launched in February and I'll show you some of that data as well. And we'll talk about that. All right. So a little bit of a launch history here. So there were these and you probably already talked about this. I'm sorry I had to sneak out for another important event in the middle of the afternoon. But here's some of the history here. Really the scanning microwave spectrometer scams was the beginning of taking measurements of precipitation from space before then they weren't really looking at that type of data. And then so over the years you know microwave sounding units have been launched in 1997 the tropical rainfall measuring mission was launched which the whole focus was on precipitation and had a radar built by the Japanese. AMSUS, ATMS have come out of this and then as we just said the global precipitation measurement mission was just launched and it has great capabilities to be able to measure rain and snow from space. All right so this is the scams instrument. Some of the things I want to point out here 110 kilometer footprint that's gigantic. Think about trying to resolve a convective core a thunderstorm of the summer in 110 kilometers. It's going to be completely washed out so yes this was good and it got data but it was pretty big. It also had this set up this series of channels and 31 gigahertz was basically the only channel that was sensitive to precipitation. The falling part of precipitation the 22 was sensitive to or water vapor in the atmosphere but it really didn't see the precipitating stuff. The other channels were just for temperature at different altitudes so this would typically see around four kilometers 11 kilometers and 18 kilometers these different channels here. Okay so the next slide is GPM. So GPM launched just this year has 13 channels VNH that's two channels each so we have 13 channels we go from 10 gigahertz which is sensitive to very heavy rain rates up to 110 millimeters an hour and then we go all the way down to 183 gigahertz which is sensitive to the falling snow and down to 0.2 millimeters an hour. So we have a range from 0.2 millimeters an hour all the way up to 110 and then we also are able to detect and estimate falling snow with this device. We also have the dual frequency precipitation radar which has two frequencies KU which is about 35 gigahertz no 13 gigahertz and then KA which is 35 gigahertz and really what the other thing I want to point out is we get down to five kilometer footprints so now you can start seeing those little pop-up storms that hit one part of your neighborhood but not another you know when you drive through it's raining and then it's dry so this at that resolution we can start seeing the regional scale cloud effects. Now there's some parts of our scientific community that one is down at one kilometer or less so you can get more detail at the processes but this is pretty good. So I've already talked about the 0.2 to 110 millimeters an hour and snow let me talk a little bit more about here it was designed for a three-year life five years of fuel was put on it but based on our projections we might last a 10 to 15 years now trim launched in 1997 has just run out of fuel so 96 or like 16 or 17 years and we hope to last at least that long but you don't know what the solar cycles the solar cycles cause drag and it pulls the spacecraft down so you need fuel to boost it back up to keep it at its its altitude. All right the other really cool thing about this is this instrument the radiometer when I talked to high school students middle school students the radiometer is like taking an x-ray through the clouds you see where there's lots of rain and lots of ice with this radiometer with the radar that the Japanese provided you get layer by layer information about the particles within the cloud and I like to describe that kind of as a CAT scan and just like doctors use CAT scans and x-rays to understand what's happening within the human body and diagnose what's going on we use our information to understand the layers and levels within the cloud and we can use that information then to improve weather forecasting models and climate change models because those models have fairly simplistic representations of precipitating particles within the cloud. All right okay so how do passive microwave radiometers work I'm not going to talk about the radar the CAT scan one I don't have enough time to talk about that but let's talk about the passive radiometers because Nimbus really started this passive device thing here so really what they are they're instruments they see everything in their field of view all the way down to the surface and if you got the right frequency you can also see into the soil a little bit so what happens with ice is you tend to get scattering so cosmic background comes down there's ice particles they scatter reflects back up to the spacecraft and you see a cooling in your brightness temperatures that's the measurement there rain can cause scattering which causes the cooling but it also has a mission and absorption which would cause a warming so if you're looking at an ocean the ocean is really cold background very reflective of the cosmic background then you get a cloud over it you see a big spike of warming in the brightness temperatures so that's how you can tell you about a cloud and the temperatures change based on whether there's rain or if it's just liquid the surface also contributes you can have scattering from say snow packs or you can have a mission and absorption from you know asphalt or trees warmer bodies like that and so all of that contributes to the brightness temperature so what do you get so this is some work I did probably 15 years ago and what this plot is and I'm hopefully kind of make this simple is so I had a convective rain storm and so in the solid line there so this is frequency from 10 gigahertz to a thousand gigahertz and then this is the brightness temperature value and so like this is a convective rain in solid precipitating snow is in this dotted line right here and then anvil cloud so it's an anvil cloud no precipitation falling out is in this dashed line and then a shorter dashed line is high relative humidity and then low relative humidity with the dot dash so you can see that if you're here in this you know 180 or so gigahertz range you can see distinct patterns for all of these different cloud conditions but where you're down here there's really only two distinct patterns the rain or all the other cases so the idea is to try to get the channels that are sensitive to give you the most degrees of freedom so scams had these channels already mentioned the channels before so you can see that we're you know sensitive to high relative humidity so now you know you've got cloud water sensitive to the the rain which is the solid thing here and then this is kind of a all the other pieces so you could kind of learn a little bit of information and then you could use additional separation between this one and this one to get at the rain in the cloud I mean the rain yeah the rain in the cloud and then this provided additional information at at the 30 37 no these were the the temperature sounding channels so they're not you see them all coming together right here so you're not getting much information at all about the rain that's all about those those channels are for temperature sounding all right so typical precipitation radiometers today have channels from 10 through 89 gigahertz and you can see here when you add the 10 you get this very heavy rain when you add the 90 gigahertz you get a lot more separation there so you're basically getting two or three more degrees of freedom for being able to distinguish between convective rain falling snow high relative humidity low relative humidity and things like that so the gpm radiometer actually added three well added these additional frequencies up here at 166 183 plus or minus 3 and plus or minus 7 so we're getting a lot more information so that allows us to resolve between these different characteristics we don't have any radiometers way up here yet there are instruments that have those channels but not designed for this all right so let's go back to the science this is a science team meeting for the the scams instrument in 1977 anybody in this room in this picture just one all right i want to shake your hand you're right here yeah okay you want to stand up and see how you changed over the years love the hairstyles love the hairstyles i hope that uh there's no pictures of me that are floating around in about four years but no this is great this this is a great science team i you know these names here i've seen in papers my whole life um you know key papers for precipitation science so this is great um and this is some of the data that they they came up with this is the cover of science in 1977 where they were able to do the first global image images of the water vapor they separated water vapor from cloud liquid water and so this is the the results that they got and good enough to get on the cover of science at that time but the the lead author was uh dave stalin who actually happens to be my grand advisor does that make sense one of his graduate students was my advisor so i'm related to this work right and unfortunately he passed away several years ago um anyway uh so now here's the trim and gpm science team we're massive we had almost 200 people at our last science team meeting we have international representation we had um about 16 people from japan coming they are a partner so they do work carefully with us but we had 12 other um countries represented at this science team meeting and the reason is is because we can't rest on just measuring precipitation in the us or japan precipitation is a global phenomenon and we really need to know where it's precipitating how is that precipitating changing during climate change or other patterns we need to know both globally we need to know at the local scale at that five kilometer scale uh and we need to know it frequently and so one of the great things about gpm is that we um design the instrument so carefully that we're using it to basically intercalibrate all the other precipitation sensors out there no has given us data international satellites are giving us data and we will have rain rate estimates everywhere in the world every three hours and as you can imagine that's great for applications no for predicting floods for landslides for improving our our climate models and our um uh precipitation models so all right and i'll just note that um arthur how dr arthur howe who was the project scientist for the submission uh passed away about 11 months ago and we also had a very nice memorial symposium for him at that time so what have we learned from trim so this is trim this is climatology millimeters per day it's averaged over a whole year over uh about uh 11 nine years of data so you can see these patterns heavy precipitation um just north of the equator and the oceans and a little bit down here you know so and then this is the standard deviation among all the input so you can see that well maybe there's some problems measuring our rain here maybe a little bit in there there's some issues with the ways the different ways of um developing this data and then bob adler uh put this data set together another interesting thing is okay we know that el nino and la nina typically they measure that index based on the sea surface temperature and how that changes with the long record of trim they're actually can use an index of precipitation to see where the when the precipitation starts to change you can actually tie that to el nino and la nina so um so the red here is basically indicating an el nino effect and the blue is la nina and so what you can see here is basically when the precipitation and then okay so this is cut off but this is a plus one and a minus one once you get above and so these are averages over precipitate calm down all right so the average over precipitation over this long time period from uh 79 through 2014 this is using gpcp data which goes back and forth and time goes back in time as early as data as we got and then so this is an average over a lot of time and that's the zero line here and so these precipitation changes if it's one standard deviation above or one standard deviation below you could start telling what's happening so in el nino we have we tend to have more precipitation and these are boxes in the el nino la nino region so it's not global it's just a focused area so what you see is then you have an increase here and a very low decrease in precipitation um so this basically says there's no la nina we've got an el nino and so you can kind of see the up and down going back and forth between precipitation and el nino la nina so this is just a different way to look at predicting el nino la nina all right so from term to gpm term was launched in 97 as i said it just recently ran out of fuel the summer ran out of fuel it'll probably last into the spring maybe summer before we have to turn off all the instruments we can actually still take data even though it's slowly descending trim has shown the importance of having data for predicting floods and landslides and other things like that and we know that those operational users are already taken in gpm data for that i've already talked mostly about this information but one of the really interesting things is because trim had operational users gpm made it a requirement to get the data out to the public as soon as possible so one to three hours after an event the data is on our websites freely available to anybody that wants to get it and that's really great if you're a you know emergency management planner and you know that the last nine hours ago you had three inches an hour of rain and six hours ago it was four inches an hour rain and now it's two inches and you've got a flooding basin you can say let's get our people out of here you know let's evacuate and this can also be used by for hurricanes as well so the other thing to point out is trim only went from plus or minus 35 degrees latitude gpm goes higher so we can actually track things like hurricane sandy and look at it as it goes into the extra tropics and mid latitudes so this is this is really great for the state of the science in terms of precipitation so this is an event the march 17 snowstorm that was here in dc and if you were in the area they shut down a lot of things i got it was closed and this is some of the data that we are able to get this is actually only about two and a half weeks after we launched and this is the data it took us a lot longer to render this data than to actually take it so off the coast of the carolina as you can see this rain event the reds and the greens are rain and then over inland you have this very cold falling snow shown in blues and so you can see the x-ray that really long strip of data that goes from there to there that's just projected onto the surface in terms of of rain but also that the CAT scan like data from the radar and really interesting things to note you know the rain actually has a higher cloud top than the snow it's a much shallower cloud you can see that there's a melting layer here so above the melting layer you have all your ice and below it it's melting and raining and so this data gives us great insight and you know we can use this stuff to start measuring snowpack information to help us understand our water resources many areas of the world do use this data i need need to know how much is precipitating so that they can monitor their freshwater resources all right so i'm already talking about this so i've already talked about flood monitoring landslide hazard forecast we can use this in all in models um freshwater management crop forecasting so all of these instruments can tell you when it's raining and when it's not raining if it's not raining you've got drought conditions which affects your crop productions so some of the trim data has actually been used to send food to Africa early because they knew that they would they were having a drought and they would not be able to produce enough food in time other interesting things where it rains you get puddles where you have puddles you get mosquitoes and if you're in some parts of the world those mosquitoes might have malaria so we've actually done some really interesting stuff with the trim data and that's all i have so oh i'm sorry yes oh two more things there's a gpm model over here so you can actually come up and take a look at the spacecraft and then the other thing was um chuck gave me an email from some of the first people that were working on nimbus um garret cambell which i saw in the previous presentation is one of the names um they have new new scientific results based on some of the first observations from nimbus and this is uh dr garret cambell and david galleher they've recovered the first observations by the nimbus series of satellites august 31st 1964 they've used that image and many more to derive sea ice content in the 1960s around Antarctica and they're showing very large fluctuations um uh around 1964 to 1966 and they published this um and they um uh recently uh they published it along with some corroborating information that showed up in the ice core measurements from that um from the Antarctic so what they're saying is nimbus data is still being scientifically used and still producing new results so good good for the scientist out there now i'll stop talking