Archive for the ‘Data Assimilation’ Category

A significant flooding event occurred over the U.S. Deep South from 8-10 March 2016 due to a slow-moving low pressure/front from southern Texas to the Mississippi River, combined with a deep tropical moisture plume.  Tremendous rainfall totals of 4-8″+ were depicted by the Multi-Radar Multi-Sensor (MRMS) 1-km gauge-corrected radar rainfall estimate product for consecutive 24-hour periods ending 1200 UTC 9 March and 10 March 2016 (Fig. 1).  The MRMS gridded product provides short-term input precipitation estimates to the real-time Land Information System (LIS) run at the NASA Short-term Prediction Research and Transition (SPoRT) Center.


Fig. 1.  Rainfall estimates from the Multi-Radar Multi-Sensor (MRMS) gauge-adjusted radar product for the 24-h period ending (a) 1200 UTC 9 Mar 2016, and (b) 1200 UTC 10 Mar 2016.

The soil moisture response to the heavy rainfall was captured nicely by NASA’s Soil Moisture Active-Passive (SMAP) satellite Level 2 retrieval product of 0-5 cm volumetric soil moisture for the early morning overpass across the Central U.S from 9 March (Fig. 2a).  Very high retrieved volumetric soil moisture of 0.45 or higher is seen from eastern Texas across much of northern Louisiana and southern/central Arkansas, aligned well with the areas that received the heaviest rainfall.  The corresponding SPoRT-LIS modeled soil moisture analysis for the 0-10 cm layer of the Noah land surface model (Fig. 2b) shows a reasonable agreement with the SMAP retrieved soil moisture but with slightly less dynamic range than the SMAP data — a reasonable result given that the SMAP retrieval is valid over a shallower, near-surface layer than the LIS top model layer.


Fig. 2.  (a) Soil Moisture Active-Passive (SMAP) 0-5 cm volumetric soil moisture retrieval valid 1223 UTC 9 Mar 2016, and (b) corresponding SPoRT-Land Information System (LIS) 0-10 cm volumetric soil moisture analysis valid 1200 UTC 9 Mar 2016.

The SPoRT-LIS total column relative soil moisture (RSM) has been found to qualitatively correlate with areas of river/areal flooding when exceeding ~60% across northern Alabama.  The depiction of total column RSM from the early morning of 10 March shows a large area exceeding 65% (blue  shading in Fig. 3a) across eastern Texas, northern Louisiana, and southern/central Arkansas.  The weekly change in total column RSM (Fig. 3b) highlights the regions that experienced the largest increases in soil moisture in response to the heavy rainfall.  As the soil approaches saturation/field capacity, most new rainfall goes directly to runoff, thereby exacerbating the flooding situation.


Fig. 3.  SPoRT-LIS analysis valid 1200 UTC 10 Mar 2016 of (a) total column relative soil moisture (RSM), and (b) one-week change in total column RSM.

Another product available from the real-time SPoRT-LIS is the total column RSM percentile, which shows how anomalous the current soil moisture conditions are relative to a historical, 33-year climatological database of modeled soil moisture. The percentile product from the morning of 10 March (Fig. 4) shows that areas of eastern Texas and northwestern Louisiana (and a few other spots) exceed the 98th percentile for the current day — indicating that these present-day soil moisture values are about the most moist it has been in the last 33+ years for 10 March.

Notice that there are a few anomalous “bulls-eyes” of dry percentiles in southern/eastern Arkansas.  These areas are caused by corrupt input precipitation data driving the SPoRT-LIS land surface model simulation.  The issue is currently being corrected by the operational organizations managing the rain gauge input.  However, it should be noted that SPoRT is working to implement near real-time data assimilation of the SMAP Level 2 soil moisture retrievals into its LIS simulation.  Routine assimilation of SMAP satellite soil moisture will help correct anomalies caused by poor input precipitation, thereby resulting in more robust soil moisture analyses for situational awareness and disaster-response applications.


Fig. 4. SPoRT-LIS total column RSM percentile valid 1200 UTC 10 Mar 2016.

Finally, the areas of active flooding at U.S. Geological stream gauges and the NOAA/NWS flood watch/warning map are given in Fig. 5 for the afternoon of 10 March.  The axis of flash flood warnings (dark red color) aligns quite well with the total column RSM percentiles exceeding the 98th percentile in Fig. 4, whereas the broader footprint of all flood warnings/watches corresponds closely with the total column RSM above the 65% value (blue shading in Fig. 3a).


Fig. 5.  Plot of U.S. Geological Survey stream gauges with active flooding (top), and NOAA/NWS active [flash] flood watches and warnings (bottom-right) for the afternoon of 10 Mar 2016.

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The NESDIS Snowfall Rate (SFR) product assessment is in full swing at NWS Albuquerque and forecasters are already capturing some good cases over data sparse regions. The first week of January 2016 was very active across New Mexico as back to back winter storm systems crossed the area. The second system in the series crossed over the Four Corners region on 4 January 2016, producing light to moderate snowfall rates for several hours. The forecaster on shift noted the observation at Farmington, NM (KFMN) indicated light snow with a visibility of 5 statute miles. A quick glance at the SFR procedure used in Figure 1a shows the extent of any precipitation echoes well to the east of KFMN at 0000 UTC 5 January 2016. The nearest radar (KABX, not shown) is located roughly 150 miles southeast of KFMN near Albuquerque, NM. The arrival of a SFR product at 0010 UTC 5 January 2016 showed the extent of the precipitation was much greater with the merged POES image overlaid on the radar data (Figure 1b). Sampled liquid equivalent values in the light green areas to the east of KFMN were near 0.03″/hour.

Figure 1a. Liquid equivalent values of the merged SFR product valid 0000 UTC 5 January 2016. KFMN is denoted by the white circle. Note the extent of the radar coverage is well east of KFMN.

Figure 1b. Liquid equivalent values of the merged SFR product valid 0010 UTC 5 January 2016. KFMN is denoted by the white circle. Note the extent of the snowfall coverage is much greater with the addition of the POES image.

The Terminal Aerodrome Forecast (TAF) issued for KFMN shortly before the receipt of this image indicated temporary fluctuations in the visibility to 1 statute mile with light snow and an overcast ceiling near 1,200 ft between 0000 UTC and 0400 UTC (Instrument Flight Rules, IFR). It is not clear whether any operational changes occurred based on the receipt of the merged SFR product or whether the product increased confidence on the IFR forecast. However, it is entirely possible given the improvement in product latency compared to the 2015 assessment that the imagery could be used in this way.

The webcam available at San Juan College just a short distance from the KFMN observation showed significant decreases in the visibility between 330pm and shortly after sunset (Figure 2a and 2b). The two images below show the decrease in surface visibility as well as notable accumulations on grassy surfaces in front of the college. An observer 3 miles southeast of Farmington did report a total accumulation of 1″ from this event. The merged SFR product did in fact show higher rates immediately to the east of KFMN. The last image in the series shows the impact on travel conditions noted by the NM Department of Transportation web page (Figure 3). The areal coverage of the difficult travel impacts (yellow highlights) was greater than that depicted by what can be seen based on poor radar coverage.

Figure 2a. Webcam at San Juan College around 330pm. Note the light snowfall beginning to develop over the distant mesas behind the college.

Figure 2a. Webcam at San Juan College around 330pm. Note the light snowfall beginning to develop over the distant mesas behind the college.

Figure 2b. Webcam at San Juan College shortly after sunset. Note the dramatic decrease in visibility and light snow accumulations on grassy surfaces in front of the college.

Figure 2b. Webcam at San Juan College shortly after sunset. Note the dramatic decrease in visibility and light snow accumulations on grassy surfaces in front of the college.

Figure 3. Screen capture of NM DOT web page showing areal coverage of difficult travel conditions (yellow highlights) and some text summaries detailing the impacts.

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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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