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URMA MinRH Obs grid vs Obs

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Kelly Butler, modified 13 Days ago.

URMA MinRH Obs grid vs Obs

Youngling Posts: 1 Join Date: 12/15/18 Recent Posts

To whom it may concern,

At OTX, we've observed a consistent wet bias in the URMA observation grid, particularly with minimum relative humidity (minRH) values often appearing 5% to 15% too high when copied into the forecast grid.

This inaccuracy significantly impacts our fire weather forecasts (FWF) and spot forecasts, as trends are populated from these observations. We frequently have to make manual edits to correct errors in the trends, some of which show a trend in the opposite direction than reality. These trends are read over the radio during fire season and significantly affect our fire partners.

According to our iMETs, referencing S290/S390 courses, RAWS/ASOS sites being off by 5% or more is considered unacceptable. We are hoping for a resolution to this issue or guidance on any adjustments we might be missing locally.

We have compiled examples from April 27th through May 10th, including tables and images, which detail these discrepancies. Please refer to the attached Google Slides for more information. We are also happy to provide further examples upon request.

https://docs.google.com/presentation/d/10U7RblAe3VPOIcuyEvwhuv9__-hgkASaztSSollPNCs/edit?slide=id.g33d6df8f36c_0_61#slide=id.g33d6df8f36c_0_61

 

Thanks for any help you can provide!

 

MM
Matthew Morris, modified 5 Days ago.

RE: URMA MinRH Obs grid vs Obs

Youngling Posts: 174 Join Date: 12/6/17 Recent Posts
Hi Kelly,

Thank you for bringing this issue to our attention.  First of all, a reminder that the minRH in URMA is computed by taking the minimum RH from the hourly 18Z-06Z analyses.  However, the control variable in the URMA hourly analyses is specific humidity (q) rather than RH.  Also, recall that we generate KML files for URMA that can be found here.  You can view these in Google Earth, but restricted observations are not included in these files [complete files can be shared upon request].  There are no KML files for RH, as the field is not analyzed directly, while the files for dewpoint are incomplete, as a station must report T/Q/P in order to be included in these.  Therefore, for moisture issues, we recommend viewing the files for specific humidity (i.e., "moist").

We started our investigation by taking a look at the minRH for the May 10, 2025 case, specifically the 22Z URMA (3:00 PM PDT) as a starting point.  Our findings for this particular cycle suggest that non-representative observations are at least partially responsible for the higher-than-expected minRH values you are seeing in your area.  The following slide deck shows the specific humidity background, analysis, and analysis increment figures, as well as OB/GES/ANL values for select stations.


1) For KEAT, there is a collocated WSAgMet station (WS183) that is consistently more moist than the background fields.  At 22Z on May 10th, the observed value was 7.06 g/kg, while the background was 4.26 g/kg.  There are also several observations on the opposite side of the Columbia River near Wenatchee that may be worth flagging.  For example, WS058 had an observed value of 6.13 g/kg vs. the background value of 4.50 g/kg, which appears to be causing a positive analysis increment in the vicinity.

2) For KGEG, it appears that there may be some influence from observations to the northwest near Ford/Suncrest.  These include 09023, F7716, 07452, F2380, and E1164.  There is also a malfunctioning and/or non-representative CWOP station just to the northeast of KGEG: G3968.  Details are included in the slide deck.  We recommend flagging these stations to see if the minRH analyses improve in the area.

3) Considering KMWH, there are several nearby mesonet (SYNOPTIC/DAVIS, WSAgMet, AWS) observations that appear to be non-representative.  These include 03559, 03560, 08744, 0897V, 9042D, WS024, WS181.  We recommend flagging these stations, as well.

4) For Pullman, WA (KPUW), it appears that the culprit might be observations located ~30 km north of Pullman near Garfield.  F9216, 02507, 02470, and E7584 are all more moist than the background with the analysis increment extending south towards Pullman.  Note: E7584 was rejected through the prepbufr file for this particular cycle.  We also recommend flagging these stations.

5) For the Stehekin RAWS (STRW1), the figures in the slide deck suggest that the moist bias is originating in the background fields, which for temperature, moisture, and pressure is a blend of the HRRR and NAM Nest data.  At 22Z, the specific humidity observation was 3.49 g/kg while the background value was 5.78 g/kg, so it's not immediately obvious whether these observations are representative.  It's also worth noting that this particular RAWS observation is being rejected through the diurnal (day) reject list for q.  However, there is a known bug in the GSI code that computes the sun angles to apply these diurnal lists, so the observations are likely rejected at all hours as a result.  It would require a system implementation to remove this station from the reject list.  However, if you are able to confirm this is a good quality station, we can consider removing it later on, should we have the opportunity for an upgrade.

I hope this helps.  Please let us know if you'd like to try flagging any of the observations listed above or if you have any further questions.  It may take a few iterations to identify all of the problematic observations, but we hope this is at least a good start towards resolving this issue.  I've started taking a look at one of the other cases (May 7th) and will follow-up later today or tomorrow with my findings.

Thanks,
Matt

On Thu, Jul 3, 2025 at 1:24 PM VLab Notifications <VLab.Notifications@noaa.gov> wrote:

To whom it may concern,

At OTX, we've observed a consistent wet bias in the URMA observation grid, particularly with minimum relative humidity (minRH) values often appearing 5% to 15% too high when copied into the forecast grid.

This inaccuracy significantly impacts our fire weather forecasts (FWF) and spot forecasts, as trends are populated from these observations. We frequently have to make manual edits to correct errors in the trends, some of which show a trend in the opposite direction than reality. These trends are read over the radio during fire season and significantly affect our fire partners.

According to our iMETs, referencing S290/S390 courses, RAWS/ASOS sites being off by 5% or more is considered unacceptable. We are hoping for a resolution to this issue or guidance on any adjustments we might be missing locally.

We have compiled examples from April 27th through May 10th, including tables and images, which detail these discrepancies. Please refer to the attached Google Slides for more information. We are also happy to provide further examples upon request.

https://docs.google.com/presentation/d/10U7RblAe3VPOIcuyEvwhuv9__-hgkASaztSSollPNCs/edit?slide=id.g33d6df8f36c_0_61#slide=id.g33d6df8f36c_0_61

 

Thanks for any help you can provide!

 


--
Kelly Butler RTMA/URMA Discussion Group Virtual Lab Forum https://vlab.noaa.gov/web/715073/discussions-forums-/-/message_boards/view_message/45705351VLab.Notifications@noaa.gov


--
Matthew Morris
SAIC at NOAA/NWS/NCEP/EMC
5830 University Research Ct., Rm. 2038
College Park, MD 20740
301-683-3758
MM
Matthew Morris, modified 5 Days ago.

RE: URMA MinRH Obs grid vs Obs

Youngling Posts: 174 Join Date: 12/6/17 Recent Posts
Hi Kelly,

We have taken a look at the minRH for the May 7, 2025 case using the 22Z URMA (3:00 PM PDT) as our starting point.  As before, our findings suggest that non-representative observations are at least partially responsible for the higher-than-expected minRH values you are seeing in your area.  The following slide deck shows the specific humidity background, analysis, and analysis increment figures, as well as OB/GES/ANL values for select stations.


1) For KCOE, there is a nearby CWOP station (E4369) that appears to be high-biased.  There are also a couple CWOP stations to the southwest of Hayden (G3204 and D9063) that could be contributing to this issue.

2) For KOMK, there is a WSAgMet station (WS031) in the vicinity that appears to be non-representative. In addition, WS175 appears to be responsible for the large positive analysis increment centered to the north of Omak.  We recommend flagging both of these stations to see if this leads to improved analyses. Although the Oroville RAWS site (OVLW1) wasn’t listed as needing to be adjusted for this particular case, the figures in the slide deck suggest that the observations from WS175 are likely degrading the analyses near Oroville, as well.

3) For the Winthrop RAWS site (NCSW1), there are several mesonet observations near Winthrop that could be resulting in analyses that are too moist. These include F6772 and 08810.
Please let us know if you’d like to proceed with flagging any of these stations or if you have any further questions.

Thanks,
Matt

On Fri, Jul 11, 2025 at 11:16 AM VLab Notifications <VLab.Notifications@noaa.gov> wrote:
Hi Kelly,

Thank you for bringing this issue to our attention.  First of all, a reminder that the minRH in URMA is computed by taking the minimum RH from the hourly 18Z-06Z analyses.  However, the control variable in the URMA hourly analyses is specific humidity (q) rather than RH.  Also, recall that we generate KML files for URMA that can be found here.  You can view these in Google Earth, but restricted observations are not included in these files [complete files can be shared upon request].  There are no KML files for RH, as the field is not analyzed directly, while the files for dewpoint are incomplete, as a station must report T/Q/P in order to be included in these.  Therefore, for moisture issues, we recommend viewing the files for specific humidity (i.e., "moist").

We started our investigation by taking a look at the minRH for the May 10, 2025 case, specifically the 22Z URMA (3:00 PM PDT) as a starting point.  Our findings for this particular cycle suggest that non-representative observations are at least partially responsible for the higher-than-expected minRH values you are seeing in your area.  The following slide deck shows the specific humidity background, analysis, and analysis increment figures, as well as OB/GES/ANL values for select stations.


1) For KEAT, there is a collocated WSAgMet station (WS183) that is consistently more moist than the background fields.  At 22Z on May 10th, the observed value was 7.06 g/kg, while the background was 4.26 g/kg.  There are also several observations on the opposite side of the Columbia River near Wenatchee that may be worth flagging.  For example, WS058 had an observed value of 6.13 g/kg vs. the background value of 4.50 g/kg, which appears to be causing a positive analysis increment in the vicinity.

2) For KGEG, it appears that there may be some influence from observations to the northwest near Ford/Suncrest.  These include 09023, F7716, 07452, F2380, and E1164.  There is also a malfunctioning and/or non-representative CWOP station just to the northeast of KGEG: G3968.  Details are included in the slide deck.  We recommend flagging these stations to see if the minRH analyses improve in the area.

3) Considering KMWH, there are several nearby mesonet (SYNOPTIC/DAVIS, WSAgMet, AWS) observations that appear to be non-representative.  These include 03559, 03560, 08744, 0897V, 9042D, WS024, WS181.  We recommend flagging these stations, as well.

4) For Pullman, WA (KPUW), it appears that the culprit might be observations located ~30 km north of Pullman near Garfield.  F9216, 02507, 02470, and E7584 are all more moist than the background with the analysis increment extending south towards Pullman.  Note: E7584 was rejected through the prepbufr file for this particular cycle.  We also recommend flagging these stations.

5) For the Stehekin RAWS (STRW1), the figures in the slide deck suggest that the moist bias is originating in the background fields, which for temperature, moisture, and pressure is a blend of the HRRR and NAM Nest data.  At 22Z, the specific humidity observation was 3.49 g/kg while the background value was 5.78 g/kg, so it's not immediately obvious whether these observations are representative.  It's also worth noting that this particular RAWS observation is being rejected through the diurnal (day) reject list for q.  However, there is a known bug in the GSI code that computes the sun angles to apply these diurnal lists, so the observations are likely rejected at all hours as a result.  It would require a system implementation to remove this station from the reject list.  However, if you are able to confirm this is a good quality station, we can consider removing it later on, should we have the opportunity for an upgrade.

I hope this helps.  Please let us know if you'd like to try flagging any of the observations listed above or if you have any further questions.  It may take a few iterations to identify all of the problematic observations, but we hope this is at least a good start towards resolving this issue.  I've started taking a look at one of the other cases (May 7th) and will follow-up later today or tomorrow with my findings.

Thanks,
Matt

On Thu, Jul 3, 2025 at 1:24 PM VLab Notifications <VLab.Notifications@noaa.gov> wrote:

To whom it may concern,

At OTX, we've observed a consistent wet bias in the URMA observation grid, particularly with minimum relative humidity (minRH) values often appearing 5% to 15% too high when copied into the forecast grid.

This inaccuracy significantly impacts our fire weather forecasts (FWF) and spot forecasts, as trends are populated from these observations. We frequently have to make manual edits to correct errors in the trends, some of which show a trend in the opposite direction than reality. These trends are read over the radio during fire season and significantly affect our fire partners.

According to our iMETs, referencing S290/S390 courses, RAWS/ASOS sites being off by 5% or more is considered unacceptable. We are hoping for a resolution to this issue or guidance on any adjustments we might be missing locally.

We have compiled examples from April 27th through May 10th, including tables and images, which detail these discrepancies. Please refer to the attached Google Slides for more information. We are also happy to provide further examples upon request.

https://docs.google.com/presentation/d/10U7RblAe3VPOIcuyEvwhuv9__-hgkASaztSSollPNCs/edit?slide=id.g33d6df8f36c_0_61#slide=id.g33d6df8f36c_0_61

 

Thanks for any help you can provide!

 


--
Kelly Butler RTMA/URMA Discussion Group Virtual Lab Forum https://vlab.noaa.gov/web/715073/discussions-forums-/-/message_boards/view_message/45705351VLab.Notifications@noaa.gov


--
Matthew Morris
SAIC at NOAA/NWS/NCEP/EMC
5830 University Research Ct., Rm. 2038
College Park, MD 20740
301-683-3758

--
Matthew Morris RTMA/URMA Discussion Group Virtual Lab Forum http://vlab.noaa.gov/web/715073/home/-/message_boards/view_message/45806028VLab.Notifications@noaa.gov


--
Matthew Morris
SAIC at NOAA/NWS/NCEP/EMC
5830 University Research Ct., Rm. 2038
College Park, MD 20740
301-683-3758