Closed hamidrezaomidvar closed 4 years ago
Can you check what happens with starting file://smd smd=0 LAI off – winter And Deep soil
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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Here is the SMD for the period of the run (July).
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):
And here is the LAI for this period of the run:
Sorry it is just a few days not a year?
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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also all the initial wetness of surface are zero (pavedState,bldgstate..)
No, let me try to run it for the entire year
Depth of soil layer
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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depth of soil layer = 350
Here are the results for entire year:
LAI and SMD:
and Here is the surface wetness and QE in the same plot:
Great. So we definitely need to modify G/2-6. Thanks
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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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.
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:
And here are the results of the tests:
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.
Looking very good
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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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):