Evolution of the NASA SPoRT LIS 0 to 10cm Below Ground Relative Soil Moisture Product During an Extreme Rainfall Event

NASA SPoRT has developed a real-time application of the NASA Land Information System (LIS) that runs over much of the central and eastern United States.  The LIS produces several products, including a suite of soil moisture products that can be used to help assess drought and flooding potential.  WFO Raleigh is currently evaluating these soil moisture products.

A significant rain event occurred across central and eastern North Carolina on 08 and 09 September 2014 as surface low moved northeast along a stalled cold front that was located in the Coastal Plain of the Carolinas. Radar estimates which match fairly well with surface observations indicated a large area of 2 to 4 inches of rain fell across eastern NC with several locations receiving between 6 and 8 inches of rain (Fig. 1).

Fig. 1. The 48 hour precipitation estimate for North Carolina for the period ending at 12 UTC on 9 September 2014.

Fig. 1. The 48 hour precipitation estimate for North Carolina for the period ending at 12 UTC on 9 September 2014.

This heavy rain resulted in a significant increase in the 0 to 10cm below ground Relative Soil Moisture (RSM) as noted in the animation of RSM from 12 UTC on 7 September through 00 UTC on 09 September, 2014 shown below (Fig. 2). The 0 to 10cm RSM product provides the ratio of the water content per total soil volume between the wilting and saturation points for a given soil type, expressed as a percentage. The RSM product provides information about the soil saturation state. Since this RSM product highlights the moisture in a very shallow layer between the surface and about 4 inches below ground, the values change quickly as the heavy rain begins and diminishes.

Fig. 2. An animation of the LIS 0 to 10cm below ground Relative Soil Moisture product from 12 UTC on 7 September through 00 UTC on 09 September, 2014.

Fig. 2. An animation of the LIS 0 to 10cm below ground Relative Soil Moisture product from 12 UTC on 7 September through 00 UTC on 09 September, 2014.

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Hurricane Arthur Marine Wind Gust Factor Analysis

Note this is a multi-part review of Arthur, with the focus in this post on the validation of marine wind gust forecasts.

Earlier this summer Jonathan posted an analysis of Hurricane Arthur’s Wind Gust Factors for land locations in an effort to evaluate the performance of CSTAR related research to operations activities. This post addresses wind gust factors for marine locations using data from nine buoys off the Southeast, Mid-Atlanitic, and Southern New England coasts (see map below).

Track_Buoy_combinedData for this analysis were obtained from the National Data Buoy Center and follow the methodology outlined in a previous post titled “A Wind Gust Factor Database of Marine Observations from 10 Tropical Cyclones.” As a reminder, only observations in which wave data were available with the wave heights less than 5 meters were included. This was done to remove any uncertainty in the quality of the wind observations in large waves. High sea states associated with high surface winds can shelter the buoy and reduce the buoy’s wind sampling (Skey et al. 1995). Also worth noting is that large waves may change the vertical wind profile in the boundary layer. In addition, in strong winds, tethered buoys may be shifted out of the vertical and tilted downwind likely making the wind data unrepresentative.
Hurricane Arthur Buoy TableA total of 331 gust factors were computed for Hurricane Arthur  The average gust factor was 1.23 with a median of 1.22. The standard deviation was just 0.06 around the mean of 1.23. The wind speeds ranged from 10 to 44 knots and the wind gusts ranged from 11 to 58 knots.

Hurricane Arthur Marine Sustained Winds vs Gust Factor

Hurricane Arthur Marine Gust Factor FrequencyA key point from this analysis is that the average marine gust factor of 1.23 closely matches the database of 10 tropical cyclones which also found a marine wind gust factor of 1.23 across the study area. Marine gust factors from Hurricane Irene were 1.24, also very similar to the values observed with Hurricane Arthur, which is interesting given the larger wind field with Irene versus the small wind field of Arthur. Future analysis comparing large vs. small wind fields may yield different results and should be explored. However, at this time these results give credence to the default gust factor value of 1.25 in the CSTAR Wind Gust smart tool for marine locations. Hurricane Arthur also demonstrated a notable CSTAR research to operation success of the new CSTAR motivated wind gust forecast methodology.

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Impact of lack of rain seen on LIS soil moisture imagery

Originally posted on The Wide World of SPoRT:

NASA SPoRT has developed a real-time configuration of the NASA Land Information System (LIS) that runs over much of the central and eastern United States at 3-km grid spacing.  The LIS produces several products, including a suite of soil moisture products that can be used to help assess drought and flooding potential.  WFO Raleigh is pleased to be participating (along with WFOs Houston and Huntsville) in an assessment of these products from August through October.

Central North Carolina has been in a short-term relative dry spell of late, with much of the area having seen little to no rainfall in the last week (Fig. 1). One ramification of this lack of rainfall is the soil drying evident in the 1-week difference in column relative soil moisture imagery (Fig. 2), which shows marked drying over all of Central NC in the last week. Interestingly, in coastal sections of NC that actually…

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An Example of How GOES-14 Super Rapid Scan Operations for GOES-R Helped During Warning Operations at NWS WFO Raleigh, NC on 18 August 2014

GOES-14 Super Rapid Scan Operations for GOES-R (SRSOR) was operating over North Carolina on Monday August 19th during severe weather operations at WFO Raleigh. During the event, there were several instances where having the increased temporal resolution was very advantageous during radar interrogation and warning operations. At around 2000 UTC a multi-cellular broken line of showers and thunderstorms approached the Greensboro and Winston-Salem area from the northwest (Fig. 1).

KRAX 1951 UTC 18 AUG 2014

Figure 1. KRAX reflectivity data from 1951 UTC 18 Aug 2014 showing a multi-cellular line of convection moving into the Triad. A perceived boundary is indicated on the image.

 

 

 

 

 

 

 

 

 

 

 

 

 

Based on differential heating patterns, surface observations, and the linear structure to the convective pattern, it was clear that there was some kind of boundary in the area, but it was not clearly defined by surface observations (too far apart) or by radar observations (large gaps between cells). By looking at the one-minute Super Rapid Scan data, the boundary was clear and continuous in the cloud pattern, stretching from Iredell County northeastward to Orange County (Highlighted on Fig. 2).

GOES-14 Visible Imagery 1953 UTC 18 August 2014

Figure 2. GOES-14 visible image from 1953 UTC 18 AUG 2014 showing a boundary across the northwest Piedmont region of NC. An overshooting top of a storm producing a waterspout can also be seen over the Pamlico Sound.

 

An overshooting top can clearly be seen over Alamance County indicating a developing storm prior to it showing any severe characteristics on radar. This overshooting top seen at 1953 UTC would identified 45 minutes before a severe thunderstorm warning was issued on the same cell. In addition, the location of a meso-low was also clear as lower altitude clouds were seen traveling northward to the east of the storm, and southward to the west of the storm, indicating the counterclockwise motion seen with a low pressure system. Also of note in figure 2 is the special marine warning over the Pamlico Sound. Here an overshooting top can also be seen from a storm producing a waterspout at the time in the Newport/Morehead City, NC county warning area.

The motion of the boundary was easily traceable with subsequent one-minute visible images and were used to anticipate where future convection might occur. A bit later in the event, it was clear that the western side of this boundary began to accelerate to the southeast. Meanwhile, the eastern side remained fairly slow moving and toward the south. A small meso-low could be seen moving through the boundary with an area of strong low-level convergence over northern Alamance County (Fig. 3).

GOES-14 Visible image from 2038 UTC 18 AUG 2014

Figure 3. GOES-14 Visible image from 2038 UTC 18 AUG 2014 showing progression of a boundary along with a surface meso-low near Greensboro, NC.

The result was a strong thunderstorm that was deemed worthy of a severe thunderstorm warning with radar reflectivity presentation of a large 65 dBz reflectivity core up to 20 kft, indicative of potential severe hail (Fig. 4).

4.0 degree KRAX Reflectivity from 2039 UTC 18 AUG 2014

Figure 4. KRAX 4.0 degree reflectivity image from 2039 UTC 18 AUG 2014, showing a 65 dBz hail core near 20 kft over Northern Alamance County, NC.

So how did having the Super Rapid Scan Operations for GOES-R impact our warning operations here at WFO RAH? First, knowing where the boundary was at all times, how fast it was moving, and in what direction allowed us to narrow down our area of focus for potential severe convection. This boundary was also a catalyst for some weak low level rotation within several small cells along the NC/VA border. Knowing how the boundary was evolving led us to begin to see small features in the flow, such as the meso-low pressure and associated area of low-level convergence on the east side of the low which led to the growth of the storm over Northern Alamance County.

Did having the Super Rapid Scan push us over the edge to warn on a storm before radar indications of its severity? No, but warning operations involve so much more than that one warn/no warn decision point. So much of warning operations hinges on forecaster confidence in their decision and evidence leading up to the issuance of a warning. While the greater temporal resolution of the satellite imagery did not ultimately make us warn based on that data alone, it certainly increased our confidence in our warning decisions and ultimately made the process more efficient because that evidence was coming in quicker than ever before. That alone made having the Super Rapid Scan data very valuable and very worthwhile, and something that should be able to be built into everyday operations at NWS weather forecast offices around the country.

To see SRSOR data from other cases please visit http://cimss.ssec.wisc.edu/goes/srsor2014/GOES-14_SRSOR.html.

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GOES-14 will be in Super Rapid Scan Operations with imagery over the Carolina’s and Virginia’s available today and Monday

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GOES-14 Super Rapid Scan visible satellite imagery from 1441 UTC on 17 August viewed via the CIRA web site.

GOES-14 Super Rapid Scan Operations for GOES-R (SRSOR) began on 14 August and will continue for through 28 August. Super Rapid Scan Operations (SRSO) will provide 1-minute imagery to support multiple research and GOES-R/S user readiness activities. The SRSO domain is usually selected a day or two in advance. The domain schedule along with selected imagery from prior days is available at:  http://cimss.ssec.wisc.edu/goes/srsor2014/GOES-14_SRSOR.html#sched_and_movies

Regional partners were able to have the SRSO domain centered such that it will include portions of the Carolina’s and Virginia’s today and with an even more favorable location on Monday. This will be a great opportunity to view the data over our region. For the first time, forecasters at WFO Charleston, SC and Raleigh, NC will have access to some of this data in real-time in AWIPS.

Imagery including visible, infrared, and water vapor is available on the web at the links below…

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NASA SPoRT LIS Soil Moisture Assessment – Application for the U.S. Drought Monitor

NASA SPoRT has developed a real-time configuration of the NASA Land Information System (LIS) that runs over much of the central and eastern United States at 3-km grid spacing.  The LIS produces several products including a suite of soil moisture products that can be used as a tool for assessing drought and flooding potential.  WFO Raleigh along with WFOs Houston and Huntsville are participating in an assessment of these products during August and September. SPoRT created a couple of training modules (LIS Primer module and LIS Applications Module) to prepare NWS forecasters for this new dataset.

There are four LIS soil moisture products that are made available to WFO Raleigh forecasters in AWIPS-2 and which are available online at http://weather.msfc.nasa.gov/sport/case_studies/lis_SEUS.html for the Southeast and http://weather.msfc.nasa.gov/sport/case_studies/lis_NC.html for North Carolina.  The products include:

  1. Volumetric Soil Moisture (0 to 10cm) [SOIM0-10]
  2. Below Ground Relative Soil Moisture (0 to 10cm) [RSOIM]
  3. Below Ground Relative Soil Moisture (0 to 200cm) [INT-RSOIM]
  4. Below Ground One Week Change in Column Relative Soil Moisture (0 to 200cm) [RSOIMDIFF]

Each week, WFO Raleigh Hydrologist Michael Moneypenny serves as a member of the North Carolina Drought Management Advisory Council (NCDMAC) which provides recommendations to the U.S. Drought Monitor (USDM).  The USDM consists of a consortium of academic and government partners, including the University of Nebraska-Lincoln National Drought Mitigation Center (NDMC) and various other federal and state agencies.

WFO Raleigh started receiving the LIS soil moisture products in July and evaluating the products in August. The products were first used during the weekly NCDMAC collaboration call on Tuesday August 5th.  The LIS data was used to expand the D0 (abnormally dry) category at a sub-county level into portions of Robeson and Scotland Counties. In particular, the 0-200 cm Relative Soil Moisture Weekly Change product was used to show changes in the deep layer soil moisture. In figure 1 below, the upper image was referenced by the NCDMAC during the August 5th collaboration call to recommend expansion of D0 at the sub-county scale in the area circled.

In addition, a more formal demonstration of the full suite of LIS soil moisture products was conducted during the weekly NCDMAC collaboration call on Tuesday August 12th. In figure 1 below, the lower image was used to inspect the short time scale improvement of soil moisture conditions in the areas under D0 drought designation. While the graphic shows marked improvement from significant rainfall, the D0 areas were not modified as lingering 30 and 60 day rainfall deficits in these areas (in addition to crop reports), overshadowed the short term improvement.

The NCDMAC will be examining how best to utilize these products for drought assessment. Preliminary ideas include: 1) how the products can be correlated to the observed well level observations available via the USGS and state networks, and 2) how the SPoRT products can be used to enhance or complement the Standardized Precipitation Index product produced by the NC State Climate office.

Figure 1. The 0-200 cm Relative Soil Moisture Weekly Change products ending at 08/05/2014(top) and 08/12/2014(bottom) are shown above. The U.S. Drought Monitor status is shown in the insert in the lower left with the area of abnormally dry conditions (D0) shown in the yellow shading.

Figure 1. The 0-200 cm Relative Soil Moisture Weekly Change products ending at 08/05/2014 (top) and 08/12/2014 (bottom) are shown above. The U.S. Drought Monitor status is shown in the insert in the lower left with the area of abnormally dry conditions (D0) shown in the yellow shading.

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Hurricane Arthur’s Wind Gust Factors and a CSTAR Research to Operations Success

Note this is a multi-part review of Arthur, with the focus in this post on the creation the wind gust forecasts.

To evaluate the performance of CSTAR related research to operations activities, we examined the sustained winds, wind gusts, and gust factors for Hurricane Arthur (2014) across coastal North Carolina. The map below is a subjective analysis of the maximum wind gusts observed during Hurricane Arthur. Many locations across and near the Outer Banks reported wind gusts in excess of 70 MPH with a few locations in the southern and central Outer Banks reporting wind gust greater than 90 MPH. The western edge of the enhanced wind gusts directly associated with Arthur extended to near Interstate 95 with values of around 25 MPH.

Subjective analysis of the maximum wind gusts (MPH) observed from 03 July to 04 July 2014 during Hurricane Arthur.

Subjective analysis of the maximum wind gusts (MPH) observed from 03 July to 04 July 2014 during Hurricane Arthur.

Hourly observations of winds and wind gusts from 16 regular ASOS or AWOS METAR locations impacted by the over land wind field associated with Hurricane Arthur were examined. The locations examined in this analysis include KECG, KEDE, KEWN, KFFA, KHSE, KMQI, KMRH, KNBT, KNCA, KNJM, KNKT, KOAJ, KOCW, KONX, KPGV, and KSUT. Only observations from routine hourly METARs were used (special observations and observations not at the top of the hour were excluded). In addition, gust factors were only calculated for sustained winds of 10 MPH or greater. For each observation, the hourly wind gust factor was computed. The gust factor is defined as the ratio between the wind gust of a specific duration to the mean (sustained) wind speed for a period of time.  A total of 344 gust factors were computed for Arthur.

Note that a previous blog post highlighted the examination of gust factors for ten tropical cyclones across the Carolinas and Virginia – A Wind Gust Factor Database from 10 Tropical Cyclones for Use with GFE Tool Development.  This previous post discusses the creation of the database used to develop a regression equation included within a GFE smart tool that is used to create a wind gust factor grid. The discussion below examines the winds, wind gusts, and gust factors associated with Arthur and compares them to the database of 10 tropical cyclones.

Scatter plot of sustained winds and gust factors for Hurricane Arthur for 16 METAR locations in eastern North Carolina.

Scatter plot of sustained winds and gust factors for Hurricane Arthur for 16 METAR locations in eastern North Carolina.

The chart to the right is a scatter plot of the sustained winds in MPH versus gust factors for the 344 observations included in the study along with a best fit regression curve (y = -0.274ln(x) + 2.3599). In general, the chart demonstrates an inverse relationship between the wind speed and gust factor as well as a decrease in the number and variability of observations as wind speeds increase. This chart is very similar to the scatter plot created from the database of the 10 tropical cyclones.

The gust factors with Arthur were rather variable at low sustained wind speeds but generally converged and decreased with increasing sustained wind speed. The maximum sustained wind contained in the Arthur data set was only 48 MPH and the maximum wind gust was 71 MPH. The data set contained a large number of lower end sustained winds and wind gusts. More than 69% or 239 out of the 344 observations contained in this data-set had sustained winds less than 20 MPH.  Only 30 observations or less than 9% of all observations had sustained winds of 30 MPH or more.

Histogram of 344 gust factors for Hurricane Arthur across 16 observing locations in eastern North Carolina.

Histogram of 344 gust factors for Hurricane Arthur across 16 observing locations in eastern North Carolina.

A histogram of the frequency of gust factors for Arthur across the North Carolina is shown to the right.  The average gust factor for Arthur was 1.58 which is somewhat higher than the average of 1.47 for the database of 10 tropical cyclones. The average gust factor for Arthur was identical to the average gust factor for Hurricane Sandy. Both Arthur and the 10 tropical cyclone database had gust factors that were very similar to several previous studies (see comparison chart from a previous blog post). Schroder (2002) found an average gust factor of 1.49 during tropical cyclones at several airport locations while Krayer and Marshall (1992) found an average gust factor of 1.55 in a data set standardized to open terrain.  The histogram data noted that the gust factors were most frequently in the bin between 1.5 and 1.6. While the distribution of gust factors for Arthur is shifted to the right with higher gust factors when compared to the 10 storm database, the pattern and character of the distribution for Arthur is very similar to the 10 storm study.

Forecasters at NWS offices in Charleston, Newport, Raleigh, and Wilmington tested an experimental GFE methodology during Hurricane Arthur based on research activities associated with the CSTAR project. In this methodology, the forecaster initially populates a WindGustFactor grid based on the regression equation derived from the dataset of 10 tropical cyclones that uses the sustained wind speed as an input. The forecaster can then adjust the WindGustFactor grid to account for local effects such as boundary layer stability, prior to calculating the wind gust. The product of the wind forecast and the WindGustFactor is then computed as the wind gust forecast.

The 23-hour NDFD Wind gust forecast from midnight EDT on 3 July valid at 11pm EDT on 3 July, 2014. WFOs Charleston, Newport, Raleigh, and Wilmington which are located to the east or right of the thin yellow line used the new methodology.

The 23-hour NDFD Wind gust forecast from midnight EDT on 3 July valid at 11pm EDT on 3 July, 2014. WFOs Charleston, Newport, Raleigh, and Wilmington which are located to the east or right of the thin yellow line used the new methodology.

The example to the right is the 23-hour NDFD wind gust forecast from midnight EDT on 3 July valid at 11pm EDT on 3 July, 2014 which demonstrates a consistent and well collaborated wind gust forecast from the 4 WFOs using the new methodology. The area to the right or east of the thin yellow line encompasses the WFOs that used this experimental methodology. It is difficult to identify the CWA borders among the 4 offices within the yellow semi circle but the CWA borders among other WFOs or between participating and non-participating WFOs straddling the yellow line can be more easily identified. During Arthur, forecasters provided positive feedback on this methodology and noted the much improved consistency and an improved quality of the forecast wind gusts using this approach when compared to past experiences.  This event demonstrated a notable CSTAR research to operation success of the new CSTAR motivated methodology.

References

A Wind Gust Factor Database from 10 Tropical Cyclones for Use with GFE Tool Development

Krayer, William R., Richard D. Marshall, 1992: Gust factors applied to hurricane winds. Bull. Amer. Meteor. Soc., 73, 613–618.  [Available online at http://dx.doi.org/10.1175/1520-0477(1992)073<0613:GFATHW>2.0.CO;2]

Schroeder, J. L., M. R. Conder, and J. R. Howard, 2002: “Additional Insights into Hurricane Gust Factors,” Preprints, Twenty-Fifth Conference on Hurricanes and Tropical Meteorology, San Diego, California, 39-40.

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