Comparison of Soil Moisture Response in Hurricanes Harvey and Irma

Comparison of Soil Moisture Response in Hurricanes Harvey and Irma

After a record [nearly] 12 years between landfalling major hurricanes [cat 3 or higher], the United States has now experienced two major hurricanes making landfall less than three weeks apart from one another.  Hurricane Harvey brought exceptional record rainfall to southeastern Texas and southwestern Louisiana because it stalled shortly after landfall due to a lack of atmospheric steering currents.  Less than 3 weeks later, Major Hurricane Irma made landfall twice in Florida: once in the Lower Keys and again near Marco Island on the southwestern coast.  A long-lived cat 5 hurricane prior to landfall, Irma had a very large wind field which resulted in far-reaching impacts along the Florida East Coast, up to Charleston, SC, and inland to Atlanta, GA, with millions of households and businesses without electricity and/or water.

Here at the NASA SPoRT Center, we have been closely monitoring these two hurricanes through numerous social media and blog posts of unique satellite products and through SPoRT’s real-time instance of the NASA Land Information System (“SPoRT-LIS”).  This blog post serves to compare the soil moisture responses to hurricanes Irma and Harvey rainfall, as depicted by the real-time SPoRT-LIS output.  The Relative Soil Moisture (RSM) variable is shown throughout this article, since it takes into account the variations in soil composition by scaling the moisture availability between the wilting point (plants cannot uptake moisture) and saturation point (soil cannot hold any more water).  The SPoRT-LIS runs the Noah land surface model, which estimates soil moisture through 4 layers: 0-10, 10-40, 40-100, and 100-200 cm depth.  We first examine the response during Irma in the top 0-10 cm layer, followed by 0-100 cm layer for both storms, and then compare the total column (0-200 cm) values relative to historical values from a climatological database spanning 1981-2013 (33 years).

Figure 1 compares the weekly rainfall accumulation primarily from Hurricane Irma over the Southeastern U.S. to the August monthly rainfall total over Texas/Louisiana, primarily contributed from Hurricane Harvey during the final week of August. Rainfall from Irma was quite substantial in the Florida peninsula up to coastal South Carolina, where numerous locations measured over 10″ of rain in less than 2 days. Rainfall of 3-5″ extended inland to northern Georgia and central South Carolina, with lesser amounts generally below 3″ across eastern and northern Alabama (Fig 1, left panel).  The highest totals were along the southwestern and eastern Florida coasts.  This rainfall still pales in comparison to the widespread 20″+ that fell across a huge part of southeastern Texas and western Louisiana, albeit over a 5-6 day span.  Highest totals exceeded 50″ near Beaumont/Port Arthur, TX!

PrecipComparison

Fig 1.  Comparison of weekly rainfall estimate associated with Hurricane Irma (left), and August monthly rainfall estimate associated with Hurricane Harvey (right).

The 0-10 cm RSM animation in Fig 2 for hurricane Irma shows how quickly the top soil layer responds to incoming rainfall within the Noah land surface model in SPoRT-LIS.  The heavy rainfall rates up to 4″ per hour or more led to a quick saturation during 10 September across the Florida peninsula, eventually extending up to coastal Georgia and South Carolina on the 11th.  Similarly, as rainfall ends we can see the 0-10 cm RSM quickly decrease from south to north as the moisture infiltrates into deeper model layers and/or evaporates back to the atmosphere.  We also see that the top soil layer does not completely saturate across interior Georgia and Alabama, likely due to lower rain rates, drier initial soils, and different soil composition compared to the fast-responding sandy soils across Florida.

rsoim0-10_hurricaneIrma_10-12Sep_anim

Fig 2.  Hourly animation of SPoRT-LIS 0-10 cm relative soil moisture (RSM) and Multi Radar Multi Sensor (MRMS) quantitative precipitation estimates (QPE) from 0000 UTC 10 September through 1200 UTC 12 September 2017, associated with Hurricane Irma.

Meanwhile, the RSM averaged over the top 3 layers (0-100 cm; Fig 3) takes a longer time to moisten up during the heavy rainfall of Irma. We do see values approaching saturation across southwestern, central, and particularly northeastern Florida near the end of the rainfall event as the deeper soils have had an opportunity to recharge.

Over southeastern Texas and Louisiana (Fig 4), the 0-100 cm RSM animation shows how the prolonged, training heavy rainfall led to near saturation of the top meter of the Noah model, despite dry antecedent conditions (especially west of the Houston metro, where the RSM transitioned from less than 10% to nearly saturation!).  The much longer rainfall duration with hurricane Harvey led to sustained higher values of soil moisture in the top one meter.

rsoim0-100_hurricaneIrma_10-12Sep_anim

Fig 3.  Hourly animation of SPoRT-LIS 0-100 cm RSM and MRMS QPE from 10-12 September 2017, associated with Hurricane Irma.

rsoim0-100_hurricaneHarvey_25-30aug_anim

Fig 4.  Hourly animation of SPoRT-LIS 0-100 cm RSM and MRMS QPE from 25-30 August 2017, associated with Hurricane Harvey.

Finally, the total column 0-200 cm layer can require months or years to respond to rainfall events (or lack thereof), depending on the soil composition.  However, with major rainfall events like hurricanes Harvey and Irma, the total column RSM does respond dramatically and subsequently can depict substantial wet anomalies.  To that end, the SPoRT-LIS has a daily, county-based climatological database of modeled soil moisture from 1981-2013 from which current conditions can be compared to depict anomalies via percentiles relative to the 33-year distribution.  Fig 5 shows these percentiles color-coded to depict dry anomalies (less then 30th percentile) or wet anomalies (greater than 70th percentile) according to the scales beneath the figure.

Following hurricane Irma, we see that portions of southwestern and northeastern Florida have 0-200 cm RSM greater than the 98th percentile, as well as parts of west-central Georgia (Fig 5; left panel).  In general, the extreme wet percentiles are fairly spotty across the domain.  However, following hurricane Harvey (Fig 5; right panel), the 0-200 cm RSM percentiles are “off the charts” high, with dozens of counties experiencing soil moisture exceeding the [33-year] historical 98th percentile.  In fact, the soil moisture was SO anomalously moist following hurricane Harvey that the average daily value across all of Jefferson County, TX (Beaumont/Port Arthur) exceeded all values in the entire 33-year database by the end of August!  This unusual condition is highlighted in Fig 6, which shows a daily animation of historical 0-200 cm RSM histograms for Jefferson County, TX, with the current 2017 county-averaged values in the vertical dashed line.  We see that by the end of hurricane Harvey, the vertical dashed line is well above any values from the 33-year historical distribution, thereby quantifying how exceptionally unusual this rainfall event was in southeastern Texas.

PercentileComparison

Fig 5.  SPoRT-LIS 0-200 cm RSM percentile, valid at 1200 UTC on 12 September 2017 (post-Irma; left), and 30 August 2017 (post-Harvey; right).

Jefferson_County_TX_30day_realtimeLoop

Fig 6. Animation of daily distributions of 0-200 cm RSM for all SPoRT-LIS grid points residing in Jefferson County, TX (Beaumont/Port Arthur) during the month of August 2017.  Gray bars are the frequencies of 0-200 cm RSM from the 33-year SPoRT-LIS climatology; colored vertical lines are reference percentiles according to the legend in the upper right; and the bold vertical dashed line is the county-averaged value for the present day in August 2017.

Soil Moisture Conditions over Southeast Texas Prior to Hurricane Harvey

Soil Moisture Conditions over Southeast Texas Prior to Hurricane Harvey

As much-anticipated Hurricane Harvey approaches the southern and eastern coast of Texas today, it is worth examining the pre-existing soil moisture over the region to understand the capacity of the land surface to absorb the upcoming rainfall.  Granted, the amount of rainfall simulated by numerical guidance is off-the-charts high (e.g., today’s 0600 UTC initialized NAM model [Fig. 1] shows 84-hour maximum accumulated rainfall of over 60″ between Corpus Christie and Houston!!).  Thus, extreme flooding is anticipated, regardless of the amount that can be absorbed by the soils.

Fig1_NAMFLT_prec_precacc_084

Figure 1.  The NCEP/NAM model 84-hour forecast of total accumulated precipitation (inches) over Southeastern Texas, from the simulation initialized at 0600 UTC 25 August 2017 [image courtesy of College of DuPage forecast page].

SPoRT manages a real-time simulation of the NASA Land Information System (hereafter, “SPoRT-LIS“), running over the Continental U.S. at ~3-km grid resolution.  The SPoRT-LIS product is a Noah land surface model climatological and real-time simulation over 4 model soil layers (0-10, 10-40, 40-100, and 100-200 cm).  The climatological simulation spans 1981-2013 and forms the basis for daily-updated total-column soil moisture percentiles (forthcoming in Fig. 3), in order to place current soil moisture values into historical context.  For real-time output, the Noah simulation is regularly updated four times per day as an extension of the long-term climatology simulation.  It includes NOAA/NESDIS daily global VIIRS Green Vegetation Fraction data, and the real-time SPoRT-LIS component also incorporates quantitative precipitation estimates (QPE) from the Multi-Radar Multi-Sensor (MRMS) gauge-corrected radar product.  The climatological SPoRT-LIS is based exclusively on atmospheric analysis input from the NOAA/NASA North American Land Data Assimilation System – version 2.

Relative Soil Moisture output from the SPoRT-LIS over the 0-100 cm layer is shown in Fig. 2 over Southeastern Texas and Louisiana at 1200 UTC this morning.  A marked gradient between very dry soils to the west and moist soils to the east occurs in the vicinity of the greater Houston metropolitan area.  The soils in the region bounded by Corpus Christi, San Antonio, Austin, and Houston (areas forecast to have the greatest rainfall from Hurricane Harvey) are extremely dry prior to Harvey’s landfall.  This dryness will help to some extent in absorbing the initial rainfall from Hurricane Harvey.  But with such excessive rainfall being forecast over a prolonged time period (3-5+ days), it won’t be long before the upper portions of the soil column saturates and widespread areal flooding occurs.  In addition, the high forecast rainfall rates could easily result in flash flooding (despite prevailing soil dryness), especially further inland where terrain plays a more important role in runoff and flash flooding.

The total column relative soil moisture percentile from 24 August shows that historically-speaking, the soil moisture is slightly drier than normal, particularly along the coastal plain between Corpus Christi and Houston (Fig. 3).  In this corridor, the soil moisture is generally between the 10th and 30th percentile compared to the 1981-2013 climatological distribution for 24 August.

Fig2_rsoim0-100_20170825_12z_tx_cityLabels

Figure 2.  SPoRT-LIS relative soil moisture (RSM) distribution in the 0-1 meter layer across Southeastern Texas and Louisiana, valid 1200 UTC 25 August 2017.  RSM values of 0% represent wilting (vegetation cannot extract moisture from soil) and 100% represents saturation (subsequent rainfall becomes runoff).

Fig3_rsm02percent_20170824_12z_tx

Figure 3.  Total column (0-2 m) relative soil moisture percentile valid 24 Aug 2017, as compared to all 24 August soil moisture values from a 33-year climatological simulation of the SPoRT-LIS.

Finally, an hourly animation of the 1-day changes in 0-10 cm (top model layer) relative soil moisture show that the near-surface soils are quickly moistening between Corpus Christi and Houston, as the initial rainbands of Hurricane Harvey began impacting the coastal plain this morning.  As the soils continue to moisten rapidly from the top-down, subsequent rainfall will quickly lead to runoff and flooding.

Fig4_rsoim0-10diff1_20170825_anim

Figure 4.  Hourly animation of 1-day change in top-layer (0-10 cm) relative soil moisture, for the time period spanning 0000-1400 UTC 25 August 2017.  Each hourly image is a simple difference in 0-10 cm relative soil moisture between the current and previous day at the same valid hour.  Line contours depict one-hour QPE from the MRMS product, as input to the real-time SPoRT-LIS.

Multiple Atmospheric Rivers Impact California in Early 2017

The state of California has been suffering from a multi-year drought that has severely depleted water resources and reservoir levels. Recent winters have failed to produce precipitation and mountain snows to replenish the losses during the dry summers. However, the situation has rapidly changed this winter, particularly in the past week when multiple atmospheric rivers have impacted the state.

An atmospheric river is a concentrated channel of deep moisture that is transported from the tropical Pacific Oceanic regions to the West Coast of the United States.  These events are often associated with prodigious amounts of rainfall and mountain snows that lead to flooding, mudslides, and avalanches.  We have seen such events this past week impact California, especially the central and northern parts of the state.  CIRA’s total precipitable water product in Figures 1a and 1b depict two separate atmospheric rivers impinging on central California from 8 and 10 January 2017, respectively. The first wave transported a plume of tropical moisture from the south-southwest, which led to massive rainfall and high snow levels.  The second atmospheric river on the 10th was less directly connected to the tropics (coming in from the west-southwest), but nonetheless exhibited a well-focused transport of high moisture content.  Widespread flooding and mountain avalanches have resulted from these moisture plumes as the impacted California, as well as dramatic replenishment of reservoirs.

fig1_cira-tpw

Figure 1.  CIRA total precipitable water product (inches) valid at (a) 2100 UTC 8 Jan 2017, and (b) 2100 UTC 10 Jan 2017.

 

SPoRT’s real-time instantiation of the Land Information System (aka “SPoRT-LIS”) has nicely depicted the substantial replenishment of the moisture content in the soils over California.  The SPoRT-LIS is an observations-driven, ~3-km resolution run of the Noah land surface model that consists of a 33-year climatology spanning 1981-2013, and real-time output at hourly intervals sent to select NOAA/NWS partnering forecast offices.  The one-year change in the SPoRT-LIS total column soil moisture at 1200 UTC 11 January (Fig. 2) shows large increases over most of California, particularly in the higher terrain (given by blue and purple shading).  [At the same time, annual degradation in soil moisture can be seen across the central and eastern U.S.]  Interestingly, a substantial portion of California’s annual soil moisture increases has occurred in just the past week (Fig. 3; SPoRT-LIS total column soil moisture change over the past week).  One can certainly see the important role that atmospheric rivers play in being “drought busters”!

fig2_swetdiff365_20170111_12z_conus

Figure 2.  One-year change in the SPoRT-LIS total column relative soil moisture, valid 1200 UTC 11 January 2017.

 

fig3_swetdiff_20170111_12z_conus

Figure 3.  One-week change in the SPoRT-LIS total column relative soil moisture, valid 1200 UTC 11 January 2017.

 

A map of the SPoRT-LIS daily soil moisture percentiles from 11 January highlight the very wet anomaly over California relative to the 33-year soil moisture climatology (Fig. 4; similar to the pattern of annual soil moisture change from Fig. 2).  Blue shading denotes greater than or equal to the 98th percentile, thus indicating unusually wet soils on the tail end of the historical distribution.

fig4_rsm02percent_20170111_12z_conus

Figure 4.  SPoRT-LIS total column relative soil moisture percentile from 11 January 2017.

 

Finally, SPoRT is acquiring and assimilating in real time the Soil Moisture Active Passive (SMAP) Level 2 (L2) retrievals produced by NASA/JPL into an experimental version of the SPoRT-LIS.  SPoRT is a SMAP Early Adopter and has a funded project to conduct soil moisture data assimilation experiments with LIS and evaluate impacts on land surface and numerical weather prediction models.  Figure 5 shows SMAP L2 retrievals of the evening overpasses from ~0000 UTC 11 January.  Panel (a) is the 36-km resolution radiometer product, while panel (b) shows the enhanced-resolution product, obtained from the SMAP radiometer by using Backus-Gilbert optimal interpolation techniques to provide data on a finer (9 km) grid.  The enhanced-resolution product provides much more detail of the wet soils in California, while retaining the same overall regional patterns as the original 36-km retrieval.  Given the loss of the active radar component of the SMAP mission, SPoRT plans to assimilate both the 36-km and 9-km products separately, and compare results on model accuracy.

fig5_smap-l2-11jan2017

Figure 5. SMAP Level 2 soil moisture retrievals for the evening overpasses from ~0000 UTC 11 January 2017; (a) 36-km resolution product; (b) enhanced 9-km resolution product.

Stark contrast in Eastern U.S. soil moisture following Hurricane Matthew

Stark contrast in Eastern U.S. soil moisture following Hurricane Matthew

Major Hurricane Matthew left a trail of destruction in its wake from the Caribbean up through the U.S. East Coast.  As Hurricane Matthew tracked northward along a large portion of the U.S. Southeast Coast from Florida to North Carolina, the rainfall impacts worsened.  Figure 1 shows the weekly rainfall spanning 4-11 October, ranging from ~2-8 inches along the Florida East Coast to 10-20 inches in the eastern Carolinas.  Since antecedent soil moisture was highest in the eastern Carolinas (Fig. 2), the extreme rainfall led to the most serious flooding in this area.

fig1

Fig. 1.  Weekly rainfall totals from 4 – 11 October 2016.

fig2

Fig. 2.  Total Column (0-2 m) relative soil moisture prior to Hurricane Matthew’s impact on North and South Carolina, valid at 0000 UTC 7 October 2016.

Referring back to the precipitation totals in Fig. 1, we can see that there was a sharp rainfall gradient on the northwestern edge in the Middle Atlantic region.  Interestingly, this gradient in Hurricane Matthew’s rainfall coincided with a pre-existing transition zone between wet conditions near the Atlantic coast and drought conditions further inland from the Appalachians through New England.  The net result was to accentuate the wet-dry contrast already in place.  The animation in Fig. 3 highlights this contrast nicely by presenting the SPoRT-LIS daily total-column relative soil moisture percentiles from 1-12 October.  The percentiles are based off a 1981-2013 daily soil moisture climatology that SPoRT produced from its ~3-km resolution SPoRT-LIS simulation.  By 9 October, notice the incredible transition from excessively wet soil moisture exceeding the 98th percentile (Carolinas through the southern half of Delaware) to extremely dry soil moisture less than the 5th percentile across Pennsylvania into the Northeast (as well as much of the inland Southeastern U.S.).  In fact, total column soil moisture values are less than the 2nd percentile over a large part of Ohio, Pennsylvania, New York, and the New England states, indicative of the ongoing severe drought there.

fig3_loop

Fig. 3. Daily animation of SPoRT-LIS total column relative soil moisture percentile from 1 to 12 October 2016.

Transition to CONUS SPoRT LIS Underway…

So, we’ve finally begun the process of transitioning over fully to the new CONUS version of the SPoRT LIS.  This “new” version of the SPoRT LIS has been under development actually for several years now, and underwent initial testing and evaluation at the Huntsville WFO in spring 2015, followed by an evaluation by several WFOs and RFCs in summer 2015.  Image 1 below shows the differences in the domains.  The new version of the SPoRT LIS encompasses the entire CONUS and surrounding areas of southern Canada and northern Mexico, albeit with some anticipated degradation especially in the border regions due to lack of consistent radar/precipitation coverage.

lispostimage1_28sep2016

Image 1. The CONUS SPoRT LIS (left) and the approximate domain of the old Southeast CONUS version (right).  Note: the images are from different periods.

Not only does the CONUS version offer a geographic expansion over the previous version of the LIS, but new variables are a part of the new SPoRT LIS, including 0-200 cm relative soil moisture changes on several timescales (weekly, bi-weekly, monthly, seasonal, semi-annual and annual) soil moisture percentiles and soil temperatures.  The soil moisture percentiles and change values can be especially useful for the drought designation and analysis process, and have been used in this capacity at the Huntsville office since their inception.  Of course, there are other applications for hydrology, fire weather and blowing dust.  We’re planning to explore more of these latter unique and interesting applications with several of SPoRT’s collaborative Western CONUS WFOs next spring and summer.  The SPoRT LIS soil temperature data have shown promising application for impacts during winter weather events during evaluation of a few events in the previous winter, with more evaluation expected during the upcoming winter.  In addition to the new variables, the new version of the SPoRT LIS is using NSSL’s Multi-Radar Multi-Sensor data for precipitation forcing in the near term and is also solely incorporating the VIIRS GVF over the legacy MODIS GVF.

lispostimage2_28sep2016

Image 2. Examples of SPoRT LIS 0-200 cm relative soil moisture weekly change (left) and 0-200 cm relative soil moisture percentile (right)

Users of the SPoRT LIS and GVF data for their local modeling purposes will need to make the appropriate changes to their EMS/UEMS model runs to properly incorporate these new data sets.  Please contact Jon Case at SPoRT or me (Kris White) if you have any questions.  Thanks for reading!

U.S. Deep South flooding as depicted by NASA’s SMAP satellite and SPoRT-LIS

U.S. Deep South flooding as depicted by NASA’s SMAP satellite and SPoRT-LIS

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.

Fig1_MRMS2dayPrecip

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.

Fig2_SMAPL2_LIS

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.

Fig3_LISrsm02m

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.

Fig4_percentile_20160310

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).

Fig5_flooding

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.

From drought to flooding in less than a week over the Carolinas, as depicted by SPoRT-LIS

A closed upper low over the Southeastern U.S. combined with a deep tropical moisture connection with Hurricane Joaquin led to historic rainfall and flooding over North and especially South Carolina over the weekend.  A wide swath of central South Carolina from the coast to Columbia received over 20 inches of rainfall in the past week (Fig. 1), much of it in the last 2-3 days.  Figure 2 shows the NASA Integrated Multi-satellitE Retrievals for GPM (IMERG) 24-h rainfall estimates displayed in AWIPS II compared to the official NWS/River Forecast Center rainfall estimate for the period ending 1200 UTC on 4 October.  This is erasing the prevailing drought in the Carolinas, which still had moderate to severe drought in the most recent U.S. Drought Monitor weekly product valid 29 September (Fig. 3).

SPoRT’s real-time configuration of the NASA Land Information System (SPoRT-LIS) runs the Noah land surface model to generate a “best modeled” soil moisture estimate at ~3-km resolution for enhanced situational awareness and input to local/regional numerical weather prediction models.  The SPoRT-LIS was assessed during summer/fall 2014 by the NOAA/NWS weather forecast offices (WFOs) at Houston, TX, Raleigh, NC, and Huntsville, AL. Following an expansion to a full Continental U.S. domain, the SPoRT-LIS was also evaluated more informally by the NWS WFOs at Tucson, AZ and Albuquerque, NM this past summer.  The primary areas of utility has been in drought monitoring and assessing areal and river flooding potential.  However, the Southwestern U.S. offices applied SPoRT-LIS soil moisture fields to enhance situational awareness for wildfire and blowing dust situations as well. Overall, a majority of the users during these assessments expressed substantial utility of the product due to a lack of other real-time high-resolution soil moisture products, and were confident enough to use the product as part of operational, public forecasts.

This extreme rainfall event in the Carolinas was captured nicely by the real-time SPoRT-LIS, which depicted some of the most dramatic changes in total column soil moisture ever documented by SPoRT collaborators.  Figure 4 compares the SPoRT-LIS 0-2 m total column relative soil moisture (RSM) from 28 September (left panel) and 5 October (right panel), with Figure 5 highlighting the 1-week change in 0-2 m RSM as displayed in AWIPS II.  The RSM represents how the volumetric soil moisture scales between wilting (0%) and saturation (100%) for a given soil composition, where the wilting point indicates that vegetation can no longer extract moisture from the soil and saturation indicates no more infiltration is possible (thus all new precipitation goes to runoff). Previous experience by the Huntsville WFO found that total column RSM values of ~60% and above tend to indicate an enhanced threat for areal and river flooding over northern Alabama; however, these thresholds can vary depending on river basin properties and regional soil composition.

Values of total column RSM typically ranged from ~25-35% on 28 September, prior to the significant rain event.  However, by 5 October, total column RSM increased to well above 65% in most areas of central South Carolina, and parts of southern and far western North Carolina.  The maximum weekly change in 0-2 m RSM (Fig. 5) exceeds 58% in central South Carolina — a value never documented in the recent years of real-time SPoRT-LIS output!  Most areas of SPoRT-LIS 0-2 m RSM exceeding ~60% correspond to areas of active minor to major river flooding across parts of southern Virginia and the Carolinas, as depicted in the USGS/NOAA river gauge network this morning (Fig. 6).

Finally, SPoRT is producing an experimental daily, real-time soil moisture percentile product based on a 33-year LIS-Noah county-by-county soil moisture climatology.  The soil moisture percentile map indicates where the current 0-2 m RSM soil moisture values lie in the present day’s historical soil moisture distribution for every county in the Continental U.S. The percentile product valid at 1200 UTC 27 September and 4 October is shown in Figure 7.  Primarily dry soil moisture values between ~5th-30th percentile are prevalent across the Carolinas on 27 September, corresponding reasonably well to the U.S. Drought Monitor moderate to severe drought areas from Figure 3. However, after the 10-20+ inches of rainfall over the past week, the 4 October soil moisture percentiles completely reversed across the region, with values > 98th percentile occurring in central South Carolina where the most severe flooding is taking place.  SPoRT plans to develop a brief training module on this percentile product prior to dissemination for display in AWIPS II at NWS WFOs, along with the current suite of SPoRT-LIS fields already available in AWIPS II.

Fig. 1. NWS River Forecast Center rainfall analysis for the week ending 1200 UTC 5 October 20125.

Fig. 1. NWS River Forecast Center rainfall analysis for the week ending 1200 UTC 5 October 2015.

Fig. 2. Comparison of NASA Integrated Multi-satellitE Retrievals for GPM (IMERG) rainfall estimate to the NWS/River Forecast Center analysis for the 24-hour period ending 1200 UTC 4 October 2015.

Fig. 2. Comparison of NASA Integrated Multi-satellitE Retrievals for GPM (IMERG) rainfall estimate to the NWS/River Forecast Center analysis for the 24-hour period ending 1200 UTC 4 October 2015.

Fig. 2. U.S. Drought Monitor weekly drought product valid 29 September 2015.

Fig. 3. U.S. Drought Monitor weekly drought product valid 29 September 2015.

Fig. 3. SPoRT-LIS total column (0-2 m) relative soil moisture valid on (left panel) 28 September, and (right panel) 5 October 2015.

Fig. 4. SPoRT-LIS total column (0-2 m) relative soil moisture valid on (left panel) 28 September, and (right panel) 5 October 2015.  Masked white areas represent water or urban pixels.

Fig. 4. One-week change in SPoRT-LIS total column relative soil moisture for the week ending 5 October 2015, as displayed in AWIPS II.

Fig. 5. One-week change in SPoRT-LIS total column relative soil moisture for the week ending 5 October 2015, as displayed in AWIPS II.  Maximum weekly change value > 58% is highlighted by the cursor position.  Masked black areas represent water or urban pixels.

Fig. 6. USGS and NWS River Forecast Center river gauge plot for the morning of 5 October 2015. River gauges experiencing flooding are indicated by the legend in the lower-right.

Fig. 6. USGS / NWS River Forecast Center river gauge plot for the morning of 5 October 2015. River gauges experiencing flooding are indicated by the legend in the lower-right.

Fig. 5. Experimental SPoRT-LIS total column relative soil moisture percentile product, valid at 1200 UTC on (left panel) 27 September, and (right panel) 4 October 2015.

Fig. 7. Experimental SPoRT-LIS total column relative soil moisture percentile product, valid at 1200 UTC on (left panel) 27 September, and (right panel) 4 October 2015.  Masked white areas represent water or urban pixels.