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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SPoRT has been collaborating with Don Morton and Kayla Harrison at the University of Alaska-Fairbanks to bring AIRS profile data into the High-Resolution Rapid Refresh for Alaska (HRRRAK), which is being developed for operational use at Alaska Region National Weather Service Offices.  In this research activity, SPoRT provided AIRS profile observations in PREPBUFR format for assimilation into the Gridpoint Statistical Interpolation (GSI) used to initialize the HRRRAK.  The following figures show the impact of the AIRS profile data on the GSI analysis.

1000 hPa analysis increment of conventional observations assimilated into HRRRAK at 0000 UTC on 20 August 2011

1000 hPa analysis increment of conventional observations and AIRS profiles assimilated into HRRRAK at 0000 UTC on 20 August 2011


It is clear that the assimilation of both conventional observations and AIRS profiles has a larger impact on the analysis than assimilation of conventional observations alone at this time for this pressure level.  More work will be done to determine the forecast impact when the HRRRAK is initialized with each of these analyses and the forecasts are compared to in situ observations of sensible weather parameters.

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The 19 May SPoRT run of the Weather Research and Forecasting (WRF) model captured a band of strong convection that developed in advance of a dryline across Kansas and Oklahoma. The mode and orientation of the convection appeared quite similar to the observed radar reflectivity in the late afternoon and evening hours. On the multi-model comparison page as part of the 2011 Hazardous Weather Testbed’s Spring Experiment, the SPoRT-WRF model is compared to the National Severe Storms Laboratory (NSSL) and the National Center for Atmospheric Research (NCAR) WRF runs. For this particular day, the SPoRT-WRF best captured the intensity and timing of the convection over Oklahoma and parts of Kansas during the late afternoon and evening hours (see Figure below of reflectivity comparisons valid at 0000 UTC 20 May 2011). The SPoRT WRF model configuration is nearly identical to the NSSL configuration, but incorporates real-time MODIS vegetation fraction, high-resolution land surface initialization data from the NASA Land Information System, MODIS/AMSR-E SSTs, and also assimilates AIRS temperature and moisture profiles to improve initial conditions and subsequent forecast parameters.  Of course, this is only one case; SPoRT team members plan to continue examining the model comparisons throughout the duration of the Spring Experiment and beyond.

Twenty-four hour forecast reflectivity from the NSSL (upper-left), NCAR (upper-right), and SPoRT-WRF (lower-left), along with the verifying radar image (lower-right), valid at 0000 UTC 20 May 2011.

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In the past few months, the NASA SPoRT Center has acquired two new “desktop supercomputers” as part of NASA’s broader “Climate in a Box” program.  Locally, these machines are being configured to provide both real-time forecasting and research capabilities to the modeling and data assimilation team at SPoRT.  In real-time forecasting applications, the WRF model is being run over a CONUS domain with unique NASA/SPoRT Center data sets and contributions: inclusion of our high resolution sea surface temperature product, high resolution initialization of soil moisture and land cover characteristics via the Land Information System and vegetation composites provided by MODIS, and additional information from AIRS temperature and moisture profiles assimilated around 09 UTC.  Current plans are to compare this local run against a similar forecast produced as part of the NSSL Spring Program to identify changes between the forecasts, then to relate these changes to the unique initial conditions.  The second system will provide this research capability in an off-line mode and support other activities at SPoRT.

Some differences in forecasts were noted earlier this week in the prediction of a severe squall line moving through the Midwest.  In the SPoRT-WRF forecast, the line of thunderstorms appeared to bow out into a series of small segments and with faster propagation speed versus the NSSL run.  This case, and others, will be examined over the coming months to identify opportunities for further study.  Overall, the purpose is to identify the impacts of these data sets and to improve their use within high-resolution, short-term forecast models.

Simulated radar reflectivity for the 27th forecast hour (0300 UTC on April 20th) identifying a severe squall line with bowing segments in Kentucky, Indiana, and Ohio, based upon SPoRT-WRF output.

Radar reflectivity from the current NSSL WRF, valid at the same time period.

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