Temperature/Moisture

Precipitable Water (in.)

is the amount (or depth) of liquid water that would accumulate at the surface after precipitating all of the water vapor in a vertical column over a given location. This column usually extends from the surface to 300 mb.

Thermodynamics

Mixed-Layer Convective Available Potential Energy (MLCAPE) (J kg^-1)

is a measure of instability in the troposphere. This value represents the mean potential energy available to be released via moisture phase change when a parcel is lifted to its level of free convection (LFC) and then rises to its equilibrium level. Calculations use the lowest 100 hPa average parcel properties then lifted from the mid-layer. No parcel entrainment is considered. The CAPE calculations use the virtual temperature correction.

Surface–Based Convective Available Potential Energy (SBCAPE) (J kg^-1)

is a measure of instability in the troposphere. This value represents the total amount of potential energy available to a parcel of air originating at the surface and being lifted to its level of free convection (LFC). No parcel entrainment is considered. The CAPE calculations use the virtual temperature correction.

Most Unstable Convective Available Potential Energy (MUCAPE) (J kg^-1)

is a measure of instability in the troposphere. This value represents the total amount of potential energy available to the parcel with the maximum equivalent potential temperature (within the lowest 300-mb of the atmosphere) while being lifted to its level of free convection (LFC). No parcel entrainment is considered. The CAPE calculations use the virtual temperature correction.

Mixed-Layer Convective Inhibition (MLCIN) (J kg^-1)

is represented by the area on a skew-T enclosed by the environmental temperature profile and the temperature of a parcel lifted from the lowest 100mb to the LFC. This area indicates the amount of energy required to lift the parcel to the LFC.

Winds

0-1 km Shear (kts)

Surface to 1 km vertical shear is the difference between the surface wind and the wind at 1-km above ground level (AGL). These data are plotted as vectors with shear magnitudes shaded (kts). Supercell tornadoes are often associated with vertical shear values of 15-20 knots and greater through this depth.

0-6 km Shear (kts)

Surface to 6 km vertical shear is the difference between the surface wind and the wind at 6 km above ground level (AGL). These data are plotted as vectors with shear magnitudes shaded (kts). Supercells are often associated with vertical shear values of 35 – 40 knots and greater through this depth.

0-500 m Storm Relative Helicity (m² s^-2)

is a measure of the possibility for cyclonic updraft rotation in right-moving supercells. There is no definite threshold value for SRH when forecasting supercells since the formation of supercells seems to be more closely linked to deep-layer vertical shear. However, a study by Coffer et al. (2019) found the lowest 500 m above ground level (AGL) to be a better discriminator than effective SRH between significant tornadoes and non-tornadic supercells.

0-1 km Storm Relative Helicity (m² s^-2)

is a measure of the possibility for cyclonic updraft rotation in right-moving supercells. There is no definite threshold value for SRH when forecasting supercells since the formation of supercells seems to be more closely linked to deep-layer vertical shear. Larger values of 0-1 km SRH (greater than 100 m^-2 s^-2), however, do suggest an increased threat of tornadoes with supercells (Thompson et al. 2003). Generally, larger SRH values are better, but there is no clear threshold distinguishing non-tornadic and significant tornadic supercells.

0-3 km Storm Relative Helicity (m² s^-2)

is a measure of the possibility for cyclonic updraft rotation in right-moving supercells. There is no definite threshold value for SRH when forecasting supercells since the formation of supercells seems to be more closely linked to deep-layer vertical shear. Larger values of 0-3 km SRH (greater than 250 m^-2 s^-2), however, do suggest an increased threat of tornadoes with supercells (Thompson et al. 2003). Generally, larger SRH values are better, but there is no clear threshold distinguishing non-tornadic and significant tornadic supercells.

Composite Indices

Bunkers Storm Motion (kts)

Based on the original work by Bunkers et al. (2000), the orthogonal vector represents mean supercell propagation off the shear vector. The orthogonal vector is added to the right for right-moving supercells and to the left for left-moving supercells.

Corfidi Upshear (kts)

is a calculation used to estimate net storm motion for a “backbuilding” MCS. This calculation involves the low-level storm inflow being subtracted from the mean wind.

Corfidi Downshear (kts)

is a calculation used to estimate net storm motion for a “forward propagating” MCS. This calculation involves the low-level storm inflow being added to the mean wind.

0-500 m SRH Significant Tornado Parameter (STP)

is a multiple ingredient, composite index that includes effective bulk wind difference (EBWD), effective storm-relative helicity (ESRH), 100-mb mean parcel CAPE, 100-mb mean parcel CIN, and 100-mb mean parcel LCL height. Most significant tornadoes (EF2 or greater damage) have been associated with STP values greater than 1 within an hour of tornado occurrence, while most non-tornadic supercells have been associated with values less than 1 in a large sample of RAP analysis proximity soundings. Replacing ESRH with 0-500 m SRH improves discrimination between significant tornadoes and non-tornadic supercells (Coffer et al. 2019).

0-1 km SRH Significant Tornado Parameter (STP)

is a multiple ingredient, composite index that includes 0-6 km bulk wind difference, 0-1 km storm-relative helicity, mixed-layer CAPE, and surface parcel LCL height. This version of STP adopts the formulation presented by Thompson et al. (2012) by using fixed-layer calculations of vertical shear. Most significant tornadoes (F2 or greater damage) have been associated with STP values greater than 1, while most non-tornadic supercells have been associated with values less than 1 in a large sample of RAP analysis proximity soundings.

Supercell Composite Parameter

a multiple ingredient, composite index that includes effective storm-relative helicity (ESRH, based on Bunkers supercell motion), most unstable parcel CAPE, convective inhibition (muCIN), and effective bulk wind difference (EBWD). Each ingredient is normalized to supercell “threshold” values, and larger values of SCP denote greater “overlap” between the three supercell ingredients. Only positive SCP values are displayed, corresponding to environments favoring right-moving supercells.

Storm Mode

this multi-hazard product determines the probability of storm mode. This classification scheme consists of seven-modes and operates on storm properties computed from composite reflectivity and mid-level rotation fields (Potvin et al. 2022). Red shading indicates the probability of supercell mode, blue shading shows the probability of QLCS mode, and green shading represents the probability of “other” modes.

Ensemble Paintball Plots

Fire Weather Environment/Composite Indices

Relative Humidity at Lowest Model Level (%)

The ensemble mean of relative humidity at the lowest model level is shown with warmer values indicating lower relative humidity while cooler colds indicate higher relative humidity values. This product is scaled for fire weather applications with a relative humidity < 25% corresponding with red-flag criteria.

Fosberg Fire Weather Index (FWI)

is defined by a quantitative model that uses combined meteorological variables such as relative humidity and wind speed to determine the behavior of wildfires. The index only takes into account weather conditions and not the fuels involved. The numbers in the index range from 0 to 100, with a value of 100 representing zero moisture content and wind speed of 30 mph. If any number is greater than 100, it is set back to 100. The FWI is useful in measuring changes in fire weather conditions. Over several years of use, the Fosberg index values of 50 or greater are generally considered significant on a national scale.

Reg Flag Threat Index (LOW)

is an index derived from expected relative humidity and wind speed values to quantify the severity of critical fire weather conditions. The index was modeled after the Haines Index, (Haines 1988), in that it used meteorological variables to rate fire danger independently of fuels. Values ranging from 1-2 are "Elevated", 3-4 are "Critical-Low", 5-6 are "Critical-High", 7-8 are "Extremely Critical", and 9-10 are "Historically Critical". "LOW" is a version created using climatology based on a Red Flag criteria of surface RH < 20%, sustained surface winds > 9 m/s, and surface wind gusts > 11m/s. Corresponding "HIGH" thresholds are 15%, 9 m/s, and 15 m/s, respectively. The LOW version is designed for use where Southern Plains Reg Flag criteria may not be applicable.

Air Quality Index (AQI)

is a parameter representing outdoor air quality and health. AQI is separated into 6 catergories defined as good, moderate, unhealthy for sensitive groups, unhealthy, very unhealthy, and hazardous. In WoFS, AQI is calculated from nearn surface smoke (PM2.5) concentration forecasts.

Surface Visibility

represents the estimated distance one can reasonable see objects from a vantage point on the surface. Forecast visibility is calculated by combining the effects of both cloud hydrometeor and smoke concentrations near the surface.

PBL Height

refers to the altitude of the lowest layer of the atmosphere directly influenced by the surface conditions, where turbulent mixing occurs. This provides an estimate of smoke injection height among other things.

Smoke

Integrated Smoke (mg m^-2)

represents the overall effect of smoke, including both smoke in the boundary layer and aloft. The ensemble mean of vertically integrated smoke generated by the WoF-Smoke model emanates from the locations of satellite-detected wildfires. PM2.5 is defined as “smoke” in this system.

Smoke Height (km)

Height above the surface where total smoke concentration drops below 0.01 mg m^-2.

0-200m AGL Smoke (mg m^-2)

The ensemble mean of near-surface (0-200 m) above ground level (AGL) vertically integrated smoke.

2 km AGL Smoke (ug kg^-1)

The ensemble mean of smoke aerosol concentration at 2 km above ground level (AGL). This product is a layer and is not integrated from the surface to this level.

6 km AGL Smoke (ug kg^-1)

The ensemble mean of smoke aerosol concentration at 6 km above ground level (AGL). This product is a layer and is not integrated from the surface to this level.

Aerosol Optical Depth (at 0.55 micron)

The ensemble mean of the total column aerosol optical depth from forecast smoke aerosols. This currently does not include dust and other aerosol types.

Smoke Ens. Probabilities > 50(mg m^-2) (9km, 15km, 27km)

Ensemble probabilities of total column smoke aerosol concentration showing the fraction of individual members that have greater than 50 mg m^-2 out of 18 members (a probability of 1 indicates that all ensemble member forecasts exceed this threshold with warm areas indicating high agreement). Various neighborhoods are available (9km, 15km, and 27km).

Smoke Ens. Probabilities > 100(mg m^-2) (9km, 15km, 27km)

Ensemble probabilities of total column smoke aerosol concentration showing the fraction of individual members that have greater than 100 mg m^-2 out of 18 members (a probability of 1 indicates that all ensemble member forecasts exceed this threshold with warm areas indicating high agreement). Various neighborhoods are available (9km, 15km, and 27km).

Smoke Ens. Percentiles (90th)

Given this is an 18-member ensemble, the 90th percentile display indicates that at least 2 of the ensemble members are equal to or greater than the smoke concentration value plotted at each grid point. Represents the potential high-end for smoke concentration forecasts.

0-200 Smoke Ens. Probabilities > 25 (mg m^-2) (9km, 15km, 27km)

Ensemble probabilities of 0-200 meter (near surface) smoke aerosol concentration showing the fraction of individual members that have greater than 25 mg m^-2 out of 18 members (a probability of 1 indicates that all ensemble member forecasts exceed this thresold with warm areas indicating high agreement). Various neighborhoods are available (9km, 15km, and 27km).

AOD Ens. Probabilities > 0.5 (9km, 15km, 27km)

Ensemble probabilities of aerosol optical thickness showing the fraction of individual members that have greater than 0.5 out of 18 members (a probability of 1 indicates that all ensemble member forecasts exceed this threshold with warm areas indicating high agreement. Various neighborhoods are available (9km, 15km, 27km).

RFTI > 3, 5, and 7

Ensemble probabilities of RFTI (HIGH) showing the fraction of individual members that have greater than 3, 5, or 7 threshold out of 18 members (a probability of 1 indicates that all ensemble member forecasts exceed this threshold with warm areas indicating high agreement). Various neighborhoods are available (9km, 15km, 27km).

Radar/Satellite

Simulated Radar (dBz)

Composite reflectivity radar product (dBz) displays the maximum reflectivities from a layer from each individual member (18 members total, on the right panel). Ensemble probabilities indicate the fraction of individual members that have > 40 dBz within a neighborhood distance of a grid point (A probability of 1 indicates that all ensemble member forecasts exceed this threshold). Warm areas indicate high agreement on future storm location or location of a given hazard. Various neighborhoods are available (3km, 15km, 27km), where smaller neighborhoods better highlight individual thunderstorms while larger neighborhoods can boost signals when forecast uncertainty is larger. Ensemble percentiles are also available. Given this is an 18-member ensemble, the 90th percentile display suggests that at least 2 of the ensemble members are equal to or greater than the value plotted at each grid point. (The uppermost or maximum member is shown as “Max,” which is the 100th percentile plot).

Simulated Echo Tops (kft)

Echo tops are defined at the highest height where a reflectivity signal of >= 18 dBz is present. Individual member echo top heights (kft) are displayed (18 members total, on the right panel). Ensemble probabilities indicate the fraction of individual members that have echo tops > 25 kft within a neighborhood distance of a grid point. (A probability of 1 indicates that all ensemble member forecasts exceed this threshold; also available are ensemble probabilities > 30kft, > 35 kft, and > 40 kft). Warm areas indicate high agreement on future storm location or location of a given hazard. Various neighborhoods are available (3km, 15km, 27km), where smaller neighborhoods better highlight individual thunderstorms while larger neighborhoods can boost signals when forecast uncertainty is larger.

Satellite

Various synthetic products are available including visible satellite, which can identify suspended aerosols and cloud features; infrared, which can identify clouds at night by inferring the heights of clouds and intensity of convective systems, and water vapor at low, mid, and upper levels, which is effective in identifying large-scale patterns. Each individual member of visible and infrared imagery is located on the right with a total of 18 members. Derived products such as downward shortwave flux and cloud top pressure are also available.

Severe

Max Hail (in.)

Hail size is estimated using the HAILCAST model which forecasts the maximum expected hail diameter at the surface by using a profile of nearby atmospheric temperature, moisture and winds. Hail ensemble probabilities indicate the fraction of individual members that have > 1 inch hail out of 18 members (A probability of 1 indicates that all ensemble member forecasts exceed this threshold). Warm areas indicate high agreement on future storm location or location of a given hazard. Various neighborhoods are available (9km, 15km, 27km), where smaller neighborhoods better highlight individual thunderstorms while larger neighborhoods can boost signals when forecast uncertainty is larger. Ensemble percentiles are also available. Given this is an 18-member ensemble, the 90th percentile display suggests that at least 2 of the ensemble members are equal to or greater than the value plotted at each grid point. (The uppermost or maximum member is shown as “Max,” which is the 100th percentile plot).

Max Surface Winds (kts)

Max surface wind products use the 80m model level winds designed to match expected magnitudes of high winds in convective storms. Ensemble probabilities of surface wind indicate the fraction of individual members that have surface wind gusts > 50 kts out of 18 members (A probability of 1 indicates that all ensemble member forecasts exceed this threshold). Warm areas indicate high agreement on future storm location or location of a given hazard. Various neighborhoods are available (9km, 15km, 27km), where smaller neighborhoods better highlight individual thunderstorms while larger neighborhoods can boost signals when forecast uncertainty is larger. Ensemble percentiles are also available. Given this is an 18-member ensemble, the 90th percentile display suggests that at least 2 of the ensemble members are equal to or greater than the value plotted at each grid point. (The uppermost or maximum member is shown as “Max,” which is the 100th percentile plot).

Vertical Motion (m/s)

Ensemble probabilities of vertical motion indicate the fraction of individual members that have max updraft speeds > 10 m/s out of 18 members (A probability of 1 indicates that all ensemble member forecasts exceed this threshold). Warm areas indicate high agreement on future storm location or location of a given hazard. Various neighborhoods are available (9km, 15km, 27km), where smaller neighborhoods better highlight individual thunderstorms while larger neighborhoods can boost signals when forecast uncertainty is larger. Ensemble percentiles are also available; the 90th percentile displays the value where at least 2 of the ensemble members are equal to or greater than the value at each grid point. (The uppermost or maximum member is shown as “Max”, which is the 100th percentile plot).

Rotation

Mid-Level Updraft Helicity (2-5 km) (m² s-2)

Updraft helicity (UH) represents the colocation of vertical vorticity and a storms updraft. UH has been used as a proxy for identifying right-moving, rotating storms. Ensemble probabilities of mid-level updraft helicity (2-5 km) indicate the fraction of individual members that have updraft helicity > 60 m2s-2 out of 18 members (A probability of 1 indicates that all ensemble member forecasts exceed this threshold). Warm areas indicate high agreement on future storm location or location of a given hazard. Various neighborhoods are available (9km, 15km, 27km), where smaller neighborhoods better highlight individual thunderstorms while larger neighborhoods can boost signals when forecast uncertainty is larger. Ensemble percentiles are also available; the 90th percentile displays the value where at least 2 of the ensemble members are equal to or below the value at each grid point. (The uppermost or maximum member is shown as “Max”, which is the 100th percentile plot). Ensemble minimum of 2-5 km updraft helicity is also provided to represent anti-cyclonic rotation (m2s-2).

Low-Level Updraft Heilcity (0-2 km) (m² s-2)

Updraft helicity (UH) represents the colocation of vertical vorticity and a storms updraft. UH has been used as a proxy for identifying right-moving, rotating storms. Ensemble probabilities of low-level updraft helicity (0-2 km) indicate the fraction of individual members that have updraft helicity > 20 m2s-2 out of 18 members (A probability of 1 indicates that all ensemble member forecasts exceed this threshold). Warm areas indicate high agreement on future storm location or location of a given hazard. Various neighborhoods are available (9km, 15km, 27km), where smaller neighborhoods better highlight individual thunderstorms while larger neighborhoods can boost signals when forecast uncertainty is larger. Ensemble percentiles are also available; the 90th percentile displays the value where at least 2 of the ensemble members are equal to or below the value at each grid point. (The uppermost or maximum member is shown as “Max”, which is the 100th percentile plot). Ensemble minimum of 0-2 km updraft helicity is also provided to represent anti-cyclonic rotation (m2s-2).

Low-Level Vertical Vorticity (0-2 km) (s^-1)

Low-level vertical vorticity is defined as the component of the vorticity vector along the vertical axis integrated over the lowest 2 km. Ensemble probabilities of low-level vertical vorticity indicate the fraction of individual members that have vertical vorticity > 0.003 s-1 out of 18 members (A probability of 1 indicates that all ensemble member forecasts exceed this threshold). Warm areas indicate high agreement on future storm location or location of a given hazard. Various neighborhoods are available (9km, 15km, and 27km), where smaller neighborhoods better highlight individual thunderstorms while larger neighborhoods can boost signals when forecast uncertainty is larger. Ensemble percentiles are also available; the 90th percentile displays the value where at least 2 of the ensemble members are equal to or below the value at each grid point. (The uppermost or maximum member is shown as “Max”, which is the 100th percentile plot).

Machine-Learning Products

WoFS-ML-Severe

is designed to predict the probability of at least one local storm report occurring in the specified time window by a given storm or storm cluster as identified in WoFS member forecasts. The probability of severe hail is trained on 1-inch Maximum Estimated Size of Hail (MESH) from NSSL's Multi-Radar Multi-Sensor (MRMS) dataset; research showed training on MESH to yield superior results for hail prediction compared to LSRs (Flora et al. 2024). For this product, storm reports refer to LSRs and 1-inch MESH. The spatial swaths that make up the prediction areas are known as ML Severe objects. Each object is shaded according to its associated probability of a storm report, and said probability, rounded to the nearest 5 percent, is stamped at the center of the object. While up to 18 members may contribute to the probability associated with an object, the object area is confined to where the tracks of at least four of the contributing members overlap. WoFS ML Severe products are provided for the individual hazards: hail; wind; tornado, and also for combined hazards (any one of them predicted to occur) at severe threhold, and separately, signifcant severe intensity (2-inch diameter hail, 65 knot winds; EF-2+ tornadoes). Time windows of 30-min, 1-hr, and 4-hr are provided, all representing the maximum probability within an object during the respective window. The 30-min product is comparable to convective warning timescales, while larger time windows result in longer and larger swaths that better describe mesoscale trends.

WoFS ML Hail size (30 min, 1 hour, 4 hour)

This product uses ML to predict the maximum expected hail size (i.e., the largest hailstone) that could be expected to be reported (LSRs) within an ML Severe object space and time. Color-fill corresponds to the maximum expected hail size. The 30-min plot combines this size information with the probability of any severe (1-inch or greater) hail occurring. Therefore, the plot actually shows output from two different WoFS ML Severe algorithms. On the 30-min plot each object is tagged with the maximum expected hail size in bold text, and beneath that is the probability of any severe hail occurring within that object space and time. Note that the algorithms can deliver maximum expected hail size less than one inch while also delivering a non zero probability of greater than one inch. The 1-hour and 4-hour plots display only the maximum expected hail size associated with an ML Severe object, and only as color-fill with no text stamps.

WoFS ML Severe Explainability Graphics (found when clicking a WoFS ML Severe object)

Explainability graphics give the user some physical insight into a particular ML-based prediction. While an exhaustive listing of ML imputs is not feasible, the explainability graphics do show several of the inputs that are most greatly influencing a particular prediction. Explainability consists of several box and whisker plots that describe the distrubution of a particular meteorological variable across the ML training dataset, along with a bright red marker showing the value for the currently active object. Comparing the current object/storm of interest to the training dataset can give a sense of why the predicted probability is low, high, or mid-range. The explainability GUI initially shows "Global" variables; these are the top five most influential variables for a given hazard, as determined by years of WoFS ML Severe research. The top five for a given hazard do not change. The user can also select "Local" variables using the toggle at the bottom of the explainability pop-up. This loads five varaiables that are exhibiting proportionately large influence on the prediction for the currently active object. These variables may change depending on the object.

WoFS-PHI (Blended)

blends information from WoFS and ProbSevere Version 2 (PS2) to produce spatial probabilites of individual hazards within a radius and time window. PS2 (WoFS) influences the forecast more at earlier (later) lead times. This product is best used to highlight preferred spatial corridors of future severe weather occurrence. Two versions of WoFS-PHI are available. The first is located under "ML products" tab, is updated once per WoFS initalization, and predicts out to 4 hours of lead time. The second is available as a contour overlay, updates every 5 minutes, and always predict for the net 1h or 2h.

WoFS W2W

The Watch-to-Warning (W2W) machine-learning products are designed to produce an SPC-style 4-hour outlook. Each product predicts the likelihood of severe weather for a specific hazard within 36 km (22 mi) of a point in the 2-6 hour window. The W2W ML products are updated only at the top of the hour forecast runs.

QPF

Rainfall Rates (in.)

A measure of the intensity of rainfall by calculating the amount of rain that would fall in a 5-min period if the rainfall intensity were constant over that time period. Each individual member is provided (18 members total, on the right panel).

Accumulated Rainfall (in.)

Accumulated rainfall is defined as the total amount of precipitation that is predicted to fall from model initialization time up to the time displayed. Ensemble probabilities of accumulated rainfall indicate the fraction of individual members that have accumulated rainfall > 0.5 inches out of 18 members (A probability of 1 indicates that all ensemble member forecasts exceed this threshold. Ensemble probabilities of > 1.00 inch, > 2.00 inches, > 3.00 inches, and > 5.00 inches are also available). Warm areas indicate high agreement on future storm location or location of a given hazard. Various neighborhoods are available (3km, 15km, 27km), where smaller neighborhoods better highlight individual thunderstorms while larger neighborhoods can boost signals when forecast uncertainty is larger. Ensemble percentiles are also available; the 90th percentile displays the value where at least 2 of the ensemble members are equal to or below the value at each grid point. (The uppermost or maximum member is shown as “Max”,which is the 100th percentile plot and median is shown as “50th percentile”).

Lightning

Flash Extent Density (5-min^-1 pixel^-1)

Flash extent density (FED) is defined as the count of flashes, both cloud-to-ground and intracloud, that pass through a grid within a 5-minute period. Ensemble probabilities of lightning flash extent density indicate the fraction of individual members that have flash densities > 10 flashes 5-min^-1 pixel^-1 out of 18 members (A probability of 1 indicates that all ensemble member forecasts exceed this threshold, also available ensemble probabilities > 25 flashes and > 50 flashes). Warm areas indicate high agreement on future storm location or location of a given hazard. Various neighborhoods are available (9km, 15km, 27km), where smaller neighborhoods better highlight individual thunderstorms while larger neighborhoods can boost signals when forecast uncertainty is larger. Ensemble percentiles are also available; the 90th percentile displays the value where at least 2 of the ensemble members are equal to or below the value at each grid point. (The uppermost or maximum member is shown as “Max”, which is the 100th percentile plot and the average of all 18 members is shown as “Ens Mean”).

Note: All ensemble percentiles products show the location of the maximum value within the domain is noted with a black plus sign (+) and values associated with this max are located in the bottom right.