High Winds Impacting Olympic Events Captured by NASA/SPoRT Model and Satellite Products

High Winds Impacting Olympic Events Captured by NASA/SPoRT Model and Satellite Products

As summarized in a previous blog post, NASA/SPoRT is providing one of many numerical weather prediction (NWP) model solutions to South Korea during the 2018 PyeongChang Winter Olympic and Paralympic Games during February and March.  The field campaign is known as the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP). In combination with the suite of radar, satellite, and in situ observations during the field campaign, the SPoRT configuration of the NASA Unified-Weather Research and Forecasting (NU-WRF) will serve as a benchmark for future research to improve our understanding of snowfall in complex terrain, our ability to estimate snow using satellites, and for improving prediction models that parameterize these intricate processes.

A key component of the Olympics field campaign is to improve forecast models through comparison to observations and satellite retrieval products.  The constellation of passive microwave imagers being assembled in support of the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement mission (IMERG) precipitation dataset also provide information on near-surface meteorology necessary to estimate the surface turbulent fluxes. Algorithms designed to retrieve surface temperature, humidity, and wind speed are used together with bulk-flux algorithms to estimate the latent and sensible heat fluxes over the ocean surface. These fluxes are a source of energy and moisture for the overlying atmosphere.  One of the research goals of ICE-POP is to improve heat and moisture fluxes in prediction models through assimilation of these retrieval products.

During this past weekend, the Men’s Downhill Alpine was postponed until Thursday, and the Women’s Giant Slalom Qualifiers were canceled due to high winds that impacted Jeongseon Hill.  Figure 1 shows a 24-hour animation of NU-WRF simulated maximum 10-m wind speeds in 30-minute intervals on 11 February, on the 1-km nested grid centered on the Olympic venues.  We can see a substantial maximum in wind speed impacting the mountains along the eastern Korean Peninsula as well as offshore in the Sea of Japan.  Simulated wind speeds reached 15-20+ m s-1 (~35-45 mph) in the vicinity of Jeongseon and other mountain Olympic locations.  Wind speed observations at nearby Daegwallyeong (north-east of Jeongseon; not shown) peaked around 13 m s-1 (~30 mph) on 11 February, but speeds were most likely stronger in the higher terrain around Jeongseon.  In this particular situation, the higher resolution of the 1-km grid was critical to resolve the fine-scale variations in wind speeds within the complex terrain.

Figure1_maxwind10md03_2018021100_anim

Figure 1.  Twenty-four hour animation of NU-WRF simulated 10-m maximum wind speeds in 30-minute increments, valid from 0000 UTC 11 February through 0000 UTC 12 February 2018.

Meanwhile, the 10-m wind speeds, sensible, and latent heat fluxes are shown in Figure 2, comparing the 9-km model grid simulation with the satellite flux retrievals produced by NASA/SPoRT.  In Figure 2, the retrievals are hourly-averaged composites produced for the ICE-POP campaign, derived from swaths of the constellation of passive microwave satellites.  As the bitter cold Siberian air mass flows over the warmer open waters of the Sea of Japan, Yellow Sea, and western Pacific Ocean, substantial heat and moisture fluxes are directed from the sea surface to the atmosphere.

The 10-m model and retrieved wind speeds both depict a similar broad pattern of high wind speeds up to and exceeding 15 m s-1 across favored corridors downwind of the Korean Peninsula, China, and Russia (Figs. 2a and b).  The model sensible heat flux on the 9-km grid valid at 0600 UTC 12 February (panel c) has a broad pattern similar to the retrieval composite (panel d), but with an axis exceeding 500 W m-2 from the east coast of the Korean Peninsula to central Japan, and a broader amplitude between ~200-400 W m-2, generally higher than the retrievals values  The model latent heat flux (panel e) shows a similar pattern, except for a larger coverage of values exceeding 500 W m-2 between the Korean Peninsula and Japan, and offshore of central and southern Japan.  The maxima offshore of Japan show good agreement between the model and retrieval patterns (panels e and f).

The NU-WRF flux amplitudes are generally higher than that of the retrieval, likely due to several factors such as the retrieval being an hourly-averaged composite compared to instantaneous model fluxes, differences in product resolution, input sea surface temperatures, and model errors in simulated wind speed, and near-surface temperatures and moisture.  Following the Olympics, additional research as part of ICE-POP will involve examining the viability and benefits of assimilating the surface meteorology retrievals into the model for improving the predictions of oceanic heat and moisture transports into the atmosphere and their attendant impacts on air-mass modification.

Figure2_fluxComparison_match

Figure 2. Comparison between NU-WRF 6-h forecast and passive-microwave hourly-averaged composite retrievals of 10-m wind speed (m s-1), sensible, and latent heat flux (W m-2) valid 0600 UTC 11 February 2018. (a) NU-WRF 10-m wind speed, (b) 10-m wind speed retrieval, (c) NU-WRF sensible heat flux, (d) sensible heat flux retrieval, (e) NU-WRF latent heat flux, and (f) latent heat flux retrieval.

NASA/SPoRT Providing Real-time Numerical Weather Prediction Guidance for 2018 Winter Olympics

The NASA/SPoRT Center has developed a real-time numerical weather prediction (NWP) configuration that is being provided to forecasters in South Korea in support of the 2018 PyeongChang Olympics and Paralympic games.  The real-time modeling solution is part of a broader initiative known as the International Collaborative Experiment for the PyeongChang Olympics and Paralympic Winter 2018 Games (ICE-POP), which focuses on the measurement, physics, modeling, and prediction of heavy orographic snow in the PyeongChang Region of South Korea from January to March, 2018.  ICE-POP is led by the Korean Meteorological Administration (KMA) as a component of the World Meteorological Organization’s (WMO) World Weather Research Program (WWRP) Research and Development and Forecast Demonstration Projects (RDP/FDP).

The overarching ICE-POP goal is to gain a better understanding of orographic frozen precipitation processes, with the expectation that ICE-POP activities will also improve real-time weather forecasts and KMA-led decision support during the 2018 Winter Olympics. A coordinated array of surface, air and ship-borne meteorological instrumentation, radars, and NWP tools from numerous international partners (including NASA) support the ICE-POP objectives.  NASA’s participation in the ICE-POP RDP/FDP involves Marshall and Goddard Space Flight Centers collaborating as a team on a variety of common forecast and research goals.  The outcome of NASA’s involvement in ICE-POP will be the contribution of observational and modeling data that, as part of the larger ICE-POP dataset, will provide a more comprehensive understanding of orographic snowfall processes — a necessary step for improving and/or developing satellite-based snowfall retrieval algorithms and improved snow microphysics in NWP models.

For the real-time NWP solution as part of the ICE-POP FDP, SPoRT has configured the NASA Unified-Weather Research and Forecasting (NU-WRF) modeling framework to generate 24-hour forecasts four times per day, with initialization times at 0000, 0600, 1200, and 1800 UTC.  The model physics suite features the advanced 4-ice microphysics and short- and long-wave radiation parameterization schemes developed at Goddard Space Flight Center.  The NU-WRF grid setup consists of a triple-nested domain at 9-km, 3-km, and 1-km horizontal spacing, and 62 terrain-following vertical levels, covering regions spanning eastern Asia (9-km grid), the Korean peninsula and surrounding waters (3-km grid), and the eastern Korean peninsula centered on the Olympics venue (1-km grid; Fig. 1).  Initial and (lower) boundary conditions are provided by the NCEP Global Forecast System model and SPoRT’s own 2-km resolution sea surface temperature composite product.

Fig1_icepop_domain

Figure 1. Depiction of the triple-nested grid configuration for the real-time NU-WRF forecast guidance, consisting of 9-km (upper-left), 3-km (right), and 1-km (lower-left) mesh grids.

Model fields are output every 3 hours on the 9-km grid, and every 30 minutes on the 3-km and 1-km grids.  The high-resolution output from the 1-km nest centered on the Olympics venue is being delivered in real time to South Korea forecasters for decision support during the games. SPoRT is sending full grids as well as point forecasts of model fields of interest at each specific game site.  Additionally, numerous graphics of temperature, moisture, winds, precipitation, snowfall, etc. are produced for each grid and hosted to a live model web page, accessible to the public.  The SPoRT/NU-WRF model output along with other models from participating international organizations will provide unique forecast guidance for advanced decision support during the Winter Olympics.  For more information and access to all the SPoRT modeling and remote-sensing products being served for ICE-POP, please link to the SPoRT ICE-POP project page.

Finally, an examination of the SPoRT/NU-WRF model guidance initialized at 1200 UTC 7 February offers a preview of anticipated conditions for the opening ceremony on 8 February.  A weak low pressure is forecast to move southeastward across the Yellow Sea, as indicated by the simulated mean sea level pressure and composite reflectivity from the 3-km grid in Figure 2.  However, this system should not impact the Korean peninsula, so the Olympic venues are forecast to remain free of precipitation.  Temperatures will be seasonably cold, as they are expected to remain below freezing at the venues for the next 24 hours (Fig. 3 animation of forecast 2-meter temperatures on the 1-km nested grid).  Visibility looks good, as it is forecast to remain above 10 km (Fig. 4 animation) with little to no low-level cloud cover being simulated by the 1200 UTC initialization of NU-WRF (not shown).  Enjoy the games and be sure to visit the SPoRT/NU-WRF modeling page often for short-term forecast weather conditions during the 2018 Winter Olympics!

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Figure 2.  Animation of 30-minute mean sea level pressure (hPa), 10-m winds (m/s), and composite reflectivity (dBZ) from the 3-km nested grid of the SPoRT/NU-WRF simulation initialized on 1200 UTC 7 Feb 2018.

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Figure 3.  Animation of 30-minute 2-m temperatures (deg C) and 10-m winds (m/s) from the 1-km nested grid of the SPoRT/NU-WRF simulation initialized on 1200 UTC 7 Feb 2018.

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Figure 4.  Animation of 30-minute surface visibility (km) and 10-m winds (m/s) from the 1-km nested grid of the SPoRT/NU-WRF simulation initialized on 1200 UTC 7 Feb 2018.

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.

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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.

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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”!

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

 

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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.

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

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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.

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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!