Archive for the ‘Data Assimilation’ Category



During the weekend of Mar 02-03 2014, several weather features moved northeast across the area. The precipitation started out as rain across West Virginia with some freezing rain, sleet and snow across portions of southeast Ohio. Colder air began to filter into the region and as it did, the precipitation changed from rain to freezing rain to sleet and finally to snow. By 603 AM, the precipitation had turned to snow across all of West Virginia, but for portions of the extreme southeast counties.

I have attached two images from around 6 AM on Mar 3rd. The first image showed the radar data from KRLX at 603 am while the second image was the 607 am SFR product and 6 AM surface observations. When comparing these images, the “best” SFR signal for heavy snow was located along a line where the precipitation transitioned from freezing rain to snow. The heaviest signal in the SFR images was actually located over Mingo County where a total of 8 inches of snow was reported from the storm.

Freezing rain was falling across portions of extreme southeast West Virginia. Bluefield WV (KBLF) is located southeast of the “SFR” heaviest snow signal in an area where the SFR product is not showing anything. The SFR product did a great job across that area as the 6 AM KBLF observation indicated freezing rain was falling at that time.

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On Jan 26 2014, an upper level shortwave caused an area of light snow across Ohio, western Pennsylvania and the northern counties of West Virginia. Surface temperatures were quite cold with readings generally in the teens. Even at these cold temperatures, the SFR product did indicate snowfall across the far northern counties of our forecast area.

The maximum snowfall rates indicated on the 1605 UTC product was about 0.3 to 0.4 inches per hour. Based on reports, these numbers appear to be representative of what actually was occurring.

While this is just one case, the SFR product appears to work reasonably well at temperatures below 22 DegF.

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On Jan 25 2014, a mid-level shortwave moved across the region generating light to moderate snow. I have included screen captures of the 1118 UTC regional radar mosaic and surface observations…along with a 1120 UTC Snowfall Rate Product and surface observations.

It looks like the SFR product did not detect all of the snow that was falling around 11 UTC. But the misses can generally be described as either (1) the surface temperatures being too cold or (2) the probabilistic model, that is part of the calulations, indicating probabilities that were too low to determine if there was snow.

Once you know all of the details on how the product is calculated, I think this product did a good job at detailing where the snowfall was occurring.

The highest snowfall rates indicated by this image was around 0.3 to 0.5 inches which seems to be representative of what was occurring.

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When I examined the 1522 UTC SFR product, I noticed there was an absence of snow across our forecast area. Radar and surface observations indicated that light to moderate snow was continuing across most of our counties.

Per the Quick Guide, I checked the surface observations to see if the temperatures were about 22 DegF or colder. The temperatures across our northern and western counties were actually 22 DegF or colder. So the SFR product was behaving as it should across those counties.

However, the temperatures across the remainder of our region were above 22 DegF. The snow is definitely not lake effect as the current snow was still related to a shortwave which had pushed to our east.

What could be causing the lack of indicated snow across the portions of our area that still had surface temnperatures above 22 DegF?

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Through collaborations partially funded by the Alaska Space Grant Program, SPoRT has been closely working with Dr. Don Morton at the Arctic Region Supercomputing Center at the University of Alaska Fairbanks to bring retrieved profiles from the Atmospheric Infrared Sounder (AIRS) into an operational forecast model.  Don works very closely with Alaska NWS WFOs by providing an operational version of the High Resolution Rapid Refresh configured for an Alaska domain (HRRRAK) to help improve short-term forecasts.  SPoRT has provided near-real-time AIRS retrieved profiles and guidance on configuring and running the Gridpoint Statistical Interpolation (GSI) data assimilation system to most effectively bring the observations into the operational forecasting system.  Testing of the impact of the AIRS profiles within the system will continue for a few weeks, after which forecasts including AIRS profiles will be provided each day to Alaska region WFOs.  An example of the initial analysis differences for 850 hPa temperatures from last Friday can be seen below.  SPoRT will continue to work with Dr. Morton to evaluate and validate the impact of AIRS on HRRRAK short-term forecasts.

Initial impacts from assimilated AIRS profiles provided in real-time for input into the HRRRAK for the 850 hPa temperature analysis on 30 March 2012.

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Starting Tuesday, February 28, and running through March 1, SPoRT will be hosting its 6th Science Advisory Committee (SAC) meeting at the NSSTC in Huntsville, AL.

One of the topics to be shared with the SAC is the SPoRT-WRF, a real-time, experimental high-resolution model that combines SPoRT research projects (Land Information System, SPoRT SST composite, MODIS Greenness Vegetation Fraction, and assimilation of hyperspectral profiles from AIRS and IASI) into a single cohesive model to address the WFO and SPC forecast challenge of convection in numerical weather prediction.  Today’s 00Z initialization of the SPoRT-WRF shows clearing conditions over the Huntsville area and only isolated afternoon and evening showers over the Atlanta area (one location some SAC members may be flying through this afternoon/evening) with clearing after around noon local time.

1-km AGL Reflectivity from SPoRT-WRF Initialized at 00Z on 27 February 2012 (click image to animate loop)

SPoRT looks forward to a great meeting!

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The dearth of upper air observations over the Pacific Ocean can lead to model initializations that contain very little observational data and revert to the background field.  While this may be adequate, improvements in the initial conditions can yield improved forecasts.  One particular forecast challenge for WFOs in Alaska, the Pacific and the West Coast of the United States is obtaining a correct moisture analysis over the Pacific Ocean.  Streams of moisture called atmospheric rivers can stream ashore the North American Coastline and produce intense rainfall due to orographic lifting and may not be well-represented in models and analyses.

Currently, some offices are using a total precipitable water (TPW) product from CIRA that SPoRT has helped transition to the operational community.  This product blends various satellite and GPS observations of TPW into a blended product that can be used to track atmospheric rivers and other moisture features.  However, this particular product is not available to be used in model initialization.  An additional source of satellite atmospheric moisture observations comes from NASA’s AIRS hyperspectral sounder.  AIRS is able to see temperature and moisture in clear and partly cloudy conditions and produce vertical profiles of temperature and moisture.  SPoRT is currently blending a GDAS analysis with AIRS temperature and moisture observations over the Pacific using the Gridpoint Statistical Interpolation data assimilation system to produce a three-dimensional moisture analysis product.

An example of the SPoRT AIRS 3D Moisture Analysis Product is given below for an atmospheric river case on 14 October 2009 that impacted the Western United States.

CIRA TPW product valid at 2301Z 13 October 2009

GDAS analysis valid at 0000Z 14 October 2009

SPoRT AIRS 3D Moisture Analysis Product valid at 0000Z 14 October 2009

In the above example, the CIRA TPW (top image) is taken as the observed state of the atmosphere.  The GDAS analysis (middle image) used to initialize the 00Z GFS shows the TPW pattern consistent with the atmospheric river; however, the atmospheric river is too wide and is slightly more intense than indicated in the CIRA TPW product.  Additionally, the areas surrounding the atmospheric river are too moist compared to the CIRA product.  Upon assimilation of the AIRS temperature and moisture profiles (bottom image), the width of the atmospheric river tightens and the surrounding areas are dried.  The resulting 3D analysis compares more favorably to the CIRA TPW product.

Future iterations of this same product will assimilate profile data from the  Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) using lessons learned from AIRS to produce an analysis valid at multiple times during the day.

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