Urban-Meteorology-Reading / WRF-SUEWS

WRF-SUEWS coupling project
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MMS forrest test-SUEWS #65

Closed hamidrezaomidvar closed 4 years ago

hamidrezaomidvar commented 5 years ago

I did a test run of SUEWS on MMS. The only things that I changes from configuration of London run are: 1- Land cover fraction -> sfr=[0,0,0,1,0,0,0] 2- Lat and Lng

Here are the results (I think before focusing on g1-g6, we should see if there is any other parameter that need to be changed): MMS_out

suegrimmond commented 5 years ago

Can you check what happens with starting file://smd smd=0 LAI off – winter And Deep soil

Best wishes Sue

Prof Sue Grimmond Dept. of Meteorology, University of Reading, Reading, RG6 6BB T: 44 118 378 6248 – messages get emailed to me O:Met Building (#58 on map) rm:1U14 E: c.s.grimmond@reading.ac.ukmailto:c.s.grimmond@reading.ac.uk W: http://micromet.reading.ac.uk/

From: Hamidreza Omidvar notifications@github.com Sent: 06 September 2019 11:22 To: Urban-Meteorology-Reading/WRF-SUEWS WRF-SUEWS@noreply.github.com Cc: Subscribed subscribed@noreply.github.com Subject: [Urban-Meteorology-Reading/WRF-SUEWS] MMS forrest test-SUEWS (#65)

I did a test run of SUEWS on MMS. The only things that I changes from configuration of London run are: 1- Land cover fraction -> sfr=[0,0,0,1,0,0,0] 2- Lat and Lng

Here are the results (I think before focusing on g1-g6, we should see if there is any other parameter that need to be changed): [MMS_out]https://user-images.githubusercontent.com/44125994/64420980-659e7280-d098-11e9-8319-57d4ecfe27d8.png

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hamidrezaomidvar commented 5 years ago

Here is the SMD for the period of the run (July). MMS_SMD

The initial SMD is zero since the initial soilstore (soilstore_id at the begining) is equal to soilcap (150 as you can see here). It also show the soilstore at the end of the run (I think it is deep soil you mentioned):

Screenshot 2019-09-06 at 12 21 41

And here is the LAI for this period of the run: MMS_LAI

suegrimmond commented 5 years ago

Sorry it is just a few days not a year?

Best wishes Sue

Prof Sue Grimmond Dept. of Meteorology, University of Reading, Reading, RG6 6BB T: 44 118 378 6248 – messages get emailed to me O:Met Building (#58 on map) rm:1U14 E: c.s.grimmond@reading.ac.ukmailto:c.s.grimmond@reading.ac.uk W: http://micromet.reading.ac.uk/

From: Hamidreza Omidvar notifications@github.com Sent: 06 September 2019 12:35 To: Urban-Meteorology-Reading/WRF-SUEWS WRF-SUEWS@noreply.github.com Cc: Sue Grimmond c.s.grimmond@reading.ac.uk; Comment comment@noreply.github.com Subject: Re: [Urban-Meteorology-Reading/WRF-SUEWS] MMS forrest test-SUEWS (#65)

Here is the SMD for the period of the run (July). [MMS_SMD]https://user-images.githubusercontent.com/44125994/64424987-781da980-d0a2-11e9-8e9d-f3d236ac8c37.png

The initial SMD is zero since the initial soilstore (soilstore_id at the begining) is equal to soilcap (150 as you can see here). It also show the soilstore at the end of the run (I think it is deep soil you mentioned): [Screenshot 2019-09-06 at 12 21 41]https://user-images.githubusercontent.com/44125994/64425011-866bc580-d0a2-11e9-87e6-538c35ed7411.png

And here is the LAI for this period of the run: [MMS_LAI]https://user-images.githubusercontent.com/44125994/64425015-89ff4c80-d0a2-11e9-84cf-4db622033fb9.png

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hamidrezaomidvar commented 5 years ago

also all the initial wetness of surface are zero (pavedState,bldgstate..)

hamidrezaomidvar commented 5 years ago

No, let me try to run it for the entire year

suegrimmond commented 5 years ago

Depth of soil layer

Best wishes Sue

Prof Sue Grimmond Meteorology, University of Reading


From: Hamidreza Omidvar notifications@github.com Sent: Friday, September 6, 2019 12:40:30 PM To: Urban-Meteorology-Reading/WRF-SUEWS WRF-SUEWS@noreply.github.com Cc: Sue Grimmond c.s.grimmond@reading.ac.uk; Comment comment@noreply.github.com Subject: Re: [Urban-Meteorology-Reading/WRF-SUEWS] MMS forrest test-SUEWS (#65)

No, let me try to run it for the entire year

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hamidrezaomidvar commented 5 years ago

depth of soil layer = 350

hamidrezaomidvar commented 5 years ago

Here are the results for entire year:

MMS_out

LAI and SMD:

MMS_LAI MMS_SMD

and Here is the surface wetness and QE in the same plot:

MMS_state_QE

suegrimmond commented 5 years ago

Great. So we definitely need to modify G/2-6. Thanks

Best wishes Sue

Prof Sue Grimmond Meteorology, University of Reading


From: Hamidreza Omidvar notifications@github.com Sent: Friday, September 6, 2019 12:53:25 PM To: Urban-Meteorology-Reading/WRF-SUEWS WRF-SUEWS@noreply.github.com Cc: Sue Grimmond c.s.grimmond@reading.ac.uk; Comment comment@noreply.github.com Subject: Re: [Urban-Meteorology-Reading/WRF-SUEWS] MMS forrest test-SUEWS (#65)

Here are the results for entire year:

[MMS_out]https://user-images.githubusercontent.com/44125994/64425923-20cd0880-d0a5-11e9-9b80-edd4e5857dea.png

LAI and SMD:

[MMS_LAI]https://user-images.githubusercontent.com/44125994/64425938-29254380-d0a5-11e9-9db3-46c6858494fc.png [MMS_SMD]https://user-images.githubusercontent.com/44125994/64425939-29bdda00-d0a5-11e9-9a4d-e4c00df56de6.png

and Here is the surface wetness and QE in the same plot:

[MMS_state_QE]https://user-images.githubusercontent.com/44125994/64425968-3b9f7d00-d0a5-11e9-96b8-19fa3dc247d0.png

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hamidrezaomidvar commented 5 years ago

Great. I start the process of bringing them from namelist.suews to grid base parameters so we can change them in grids. But I think we need to do some changes in SUEWS side like giving different values of g1-g6 and assign them based on the dominant land cover. We can decide this later on.

hamidrezaomidvar commented 5 years ago

In order to drive g1-g6 for different vegetation cover, I did the following: (I put g1=1 and calculated g_max, and optimised for g2-g6) For each vegetation type, I calculated g_max and g2-g6 for one site for one year, then I tested the calculated g2-g6 over 3 more cases: one for the same site that g2-g6 was calculated but different year, and two other sites with the same vegetation type. Here is the summary of what I explained:

Screenshot 2019-09-10 at 17 19 53

And here are the results of the tests:

DecTr

US-MMS-2016 ![compare_test-US-MMS](https://user-images.githubusercontent.com/44125994/64631871-edb1ae80-d3ef-11e9-9efd-c4e81a9cc6e9.png) ![diurnal_test-US-MMS](https://user-images.githubusercontent.com/44125994/64631872-edb1ae80-d3ef-11e9-96c7-3da41bef89ae.png)

US-UMB-2014 ![compare_test-US-UMB](https://user-images.githubusercontent.com/44125994/64631951-15087b80-d3f0-11e9-97ed-c2f09de3794b.png) ![diurnal_test-US-UMB](https://user-images.githubusercontent.com/44125994/64631952-15087b80-d3f0-11e9-898e-8aefba56b3a0.png)
US-Oho-2011 ![compare_test-US-Oho](https://user-images.githubusercontent.com/44125994/64631975-218cd400-d3f0-11e9-8682-c64c39decb7c.png) ![diurnal_test-US-Oho](https://user-images.githubusercontent.com/44125994/64631976-218cd400-d3f0-11e9-9676-aa3b785e0627.png)

EveTr

US-Blk-2005 ![compare_test-US-Blk](https://user-images.githubusercontent.com/44125994/64632055-4a14ce00-d3f0-11e9-8b06-df680c9074bc.png) ![diurnal_test-US-Blk](https://user-images.githubusercontent.com/44125994/64632057-4a14ce00-d3f0-11e9-92b5-51bebaadeccd.png)
US-GLE-2014 ![compare_test-US-GLE](https://user-images.githubusercontent.com/44125994/64632104-5e58cb00-d3f0-11e9-9528-10f2c30aa48c.png) ![diurnal_test-US-GLE](https://user-images.githubusercontent.com/44125994/64632106-5e58cb00-d3f0-11e9-9461-919ac4602f69.png)

CA-Obs-2008 ![compare_test-CA-Obs](https://user-images.githubusercontent.com/44125994/64632123-66b10600-d3f0-11e9-90c3-11d12d34d8a2.png) ![diurnal_test-CA-Obs](https://user-images.githubusercontent.com/44125994/64632124-66b10600-d3f0-11e9-8bbd-d29a0ca3b213.png)

Grass

US-SRG-2016 ![compare_test-US-SRG](https://user-images.githubusercontent.com/44125994/64632256-a841b100-d3f0-11e9-9880-a4cd812a3f00.png) ![diurnal_test-US-SRG](https://user-images.githubusercontent.com/44125994/64632257-a841b100-d3f0-11e9-9502-32c8b1d6c104.png)
US-Goo-2006 ![compare_test-US-Goo](https://user-images.githubusercontent.com/44125994/64632284-b1cb1900-d3f0-11e9-9058-4440797e06e4.png) ![diurnal_test-US-Goo](https://user-images.githubusercontent.com/44125994/64632285-b1cb1900-d3f0-11e9-8989-ba97a9d3e45f.png)
US-KUT-2008 ![compare_test-US-KUT](https://user-images.githubusercontent.com/44125994/64632362-d58e5f00-d3f0-11e9-9104-6d918095b7d3.png) ![diurnal_test-US-KUT](https://user-images.githubusercontent.com/44125994/64632363-d58e5f00-d3f0-11e9-8c86-46f0f479515a.png)

So using these calculated g2-g6, we can have a better (at least better than using the g1-g6 of Helen's) estimation of QE for the land covers dominated one type of vegetations.

suegrimmond commented 5 years ago

Looking very good

Best wishes Sue

Prof Sue Grimmond Meteorology, University of Reading


From: Hamidreza Omidvar notifications@github.com Sent: Tuesday, September 10, 2019 6:34:31 PM To: Urban-Meteorology-Reading/WRF-SUEWS WRF-SUEWS@noreply.github.com Cc: Sue Grimmond c.s.grimmond@reading.ac.uk; Comment comment@noreply.github.com Subject: Re: [Urban-Meteorology-Reading/WRF-SUEWS] MMS forrest test-SUEWS (#65)

In order to drive g1-g6 for different vegetation cover, I did the following: (I put g1=1 and calculated g_max, and optimised for g2-g6) For each vegetation type, I calculated g_max and g2-g6 for one site for one year, then I tested the calculated g2-g6 over 3 more cases: one for the same site that g2-g6 was calculated but different year, and two other sites with the same vegetation type. Here is the summary of what I explained:

[Screenshot 2019-09-10 at 17 19 53]https://user-images.githubusercontent.com/44125994/64631544-3cab1400-d3ef-11e9-9bc9-9d57efdfedd5.png

And here are the results of the tests:

DecTr US-MMS-2016

[compare_test-US-MMS]https://user-images.githubusercontent.com/44125994/64631871-edb1ae80-d3ef-11e9-9efd-c4e81a9cc6e9.png [diurnal_test-US-MMS]https://user-images.githubusercontent.com/44125994/64631872-edb1ae80-d3ef-11e9-96c7-3da41bef89ae.png

US-UMB-2014

[compare_test-US-UMB]https://user-images.githubusercontent.com/44125994/64631951-15087b80-d3f0-11e9-97ed-c2f09de3794b.png [diurnal_test-US-UMB]https://user-images.githubusercontent.com/44125994/64631952-15087b80-d3f0-11e9-898e-8aefba56b3a0.png

US-Oho-2011

[compare_test-US-Oho]https://user-images.githubusercontent.com/44125994/64631975-218cd400-d3f0-11e9-8682-c64c39decb7c.png [diurnal_test-US-Oho]https://user-images.githubusercontent.com/44125994/64631976-218cd400-d3f0-11e9-9676-aa3b785e0627.png

EveTr US-Blk-2005

[compare_test-US-Blk]https://user-images.githubusercontent.com/44125994/64632055-4a14ce00-d3f0-11e9-8b06-df680c9074bc.png [diurnal_test-US-Blk]https://user-images.githubusercontent.com/44125994/64632057-4a14ce00-d3f0-11e9-92b5-51bebaadeccd.png

US-GLE-2014

[compare_test-US-GLE]https://user-images.githubusercontent.com/44125994/64632104-5e58cb00-d3f0-11e9-9528-10f2c30aa48c.png [diurnal_test-US-GLE]https://user-images.githubusercontent.com/44125994/64632106-5e58cb00-d3f0-11e9-9461-919ac4602f69.png

CA-Obs-2008

[compare_test-CA-Obs]https://user-images.githubusercontent.com/44125994/64632123-66b10600-d3f0-11e9-90c3-11d12d34d8a2.png [diurnal_test-CA-Obs]https://user-images.githubusercontent.com/44125994/64632124-66b10600-d3f0-11e9-8bbd-d29a0ca3b213.png

Grass US-SRG-2016

[compare_test-US-SRG]https://user-images.githubusercontent.com/44125994/64632256-a841b100-d3f0-11e9-9880-a4cd812a3f00.png [diurnal_test-US-SRG]https://user-images.githubusercontent.com/44125994/64632257-a841b100-d3f0-11e9-9502-32c8b1d6c104.png

US-Goo-2006

[compare_test-US-Goo]https://user-images.githubusercontent.com/44125994/64632284-b1cb1900-d3f0-11e9-9058-4440797e06e4.png [diurnal_test-US-Goo]https://user-images.githubusercontent.com/44125994/64632285-b1cb1900-d3f0-11e9-8989-ba97a9d3e45f.png

US-KUT-2008

[compare_test-US-KUT]https://user-images.githubusercontent.com/44125994/64632362-d58e5f00-d3f0-11e9-9104-6d918095b7d3.png [diurnal_test-US-KUT]https://user-images.githubusercontent.com/44125994/64632363-d58e5f00-d3f0-11e9-8c86-46f0f479515a.png

So using these calculated g2-g6, we can have a better (at least better than using the g1-g6 of Helen's) estimation of QE for the land covers dominated one type of vegetations.

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