Historic Ellicott City Flood of 30 July 2016 by

Richard H. Grumm and

Norman W. Junker Satellite Contributions by Sheldon Kusselson

National Weather Service State College, PA 16803

1. Introduction

Intense convective rainfall brought 75 to 100 mmhr-1 rainfall rates in the western suburbs of Baltimore, MD (Fig. 1). The heaviest rainfall and highest rainfall rates were observed over Ellicott City, MD. The combination of extremely heavy rainfall (Fig. 2) and urbanization produced ideal conditions for an extreme flash flood event. The Stage-IV data (Fig. 2) implied that 125 to 150 mm of rain fell over Ellicott City in the 2-hour period from 2300 UTC 31 through 0100 UTC 31 July 2016. Rain gage date suggested around 150 mm of rain fell in and around Ellicott City.

The intense rainfall over a short interval produced rapid run-off and catastrophic flooding. Video evidence and new stories showed city streets turned into raging rivers sweeping cars and people down the streets. Despite the raging water there were only 2 fatalities during the event (WP 2016). The extreme flooding was likely the combination of regional geography, urbanization, and the intense short duration rainfall.

Flash flooding is a significant cause of loss of life and property. Advanced warning for such events can reduce the loss of life and to a lessor some degree the loss of property. The significant property losses are often businesses and structures which cannot be moved. But they can be engineered to withstand certain interval floods such a 1% event (100 year flood) or a 0.1% event (1000 year flood). Some assets such as automobiles can be moved if significant advanced warning. It will be shown that in this case the lead-time was relatively limited.

From a flooding event type perspective, it will be shown that this event shared many of the characteristics of a Maddox (1979) Mesohigh and Frontal event. There was a 250 hPa jet entrance region to the north with southerly flow at low-levels. The southerly flow produced a region of high precipitable water in the Mid-Atlantic region aligned in a general south-to-north direction. Radar data is used to show how locally the event was a close approximation to a Jessup and Colucci (2012) Multiple MCS merging features event (see their Fig 5c). This event featured a larger scale linear convective system interacting with leading convective elements.

Many extreme rainfall events are often associated with extremely high rainfall rates (Brooks and Stensrud 2000). Thus, in addition to extreme rainfall amounts flash flooding is typically associated with extreme rainfall rates. They showed that for the 1978 Johnstown flood that rain fell over about a 9 hour period with 3 hours of rainfall rates on the order of 1.5 to 2.0 inches per hour (see Fig. 2: Brooks and Stensrud 2000). Using hourly rates of 1 to 1.5 inches per hour they showed that extreme rainfall rates peak in the summer reaching a maximum in July. There data for July indicated that rainfall rates above 4 inches are relatively rare occurring about once

per year (see their Fig. 4). As might be expected extreme rainfall rates are maximized near the Gulf Coast but expand northward in summer reaching and peaking in the Mid-Atlantic region in the summer months.

This paper will present the pattern associated with the historic and devastating Ellicott City flood of 30 July 20161. This paper will also examine the forecast issues in the NCEP models and several more advanced convective allowing models (CAMs). In this event there was a weak signal implying the potential for rapidly updating CAMS to predict mesoscale flash flood events.

2. Methods and data

The climate forecast system re-analysis (CFSR) data was used to reconstruct the pattern and the standardized anomalies associated with the event. The CFSR is used to show the pattern, which forecasters often use to gain confidence in a potential significant weather event. These same patterns, when forecast may produce high end QPF which may reinforce confidence in the forecast.

The Stage-IV rainfall data (Seo 1998) was used to estimate the rainfall over several 24 hour periods on 21 and 22 May 2016. The rainfall pattern also reveals some interesting information about the track of the 500 hPa cyclone.

Data was produced locally using archived GRIB files from the CFSRV2, GFS, GEFS, and HRRR. Other data from CAMS were provided by NCEP, GSD, and NCAR.

The Average Recurrence interval images for the GFS were produced using NOAA14 ARI data in GRIB format.

3. Results

a. The pattern

The large scale pattern over eastern United States and western Atlantic featured a strong subtropical ridge over the western Atlantic and a weak trough over the Ohio Valley (Fig. 3). The ridge was slowly retrograding. The 850 hPa flow around the ridge was generally from the south-southwest in the eastern United States (Fig. 4) prior to 0000 UTC 31 July 2016. In this south-southwesterly flow there was a plume of deep moisture, with precipitable water (PW) values of 45 to 55 mm in the Mid-Atlantic region (Fig. 5c). The PW anomalies peaked around +1.5σ above normal in the Mid-Atlantic region around 0000 UTC 31 July 2016 (Fig. 5c) and the 850 hPa v-winds peaked at +2σ above normal around 0000 UTC 31 July 2016 (Fig. 4b-c).

At 250 hPa (Fig. 6) there was strong 250 hPa jet moving over the ridge. The axis of the jet displaced well north of Maryland on the cold side of a baroclinic zone at 850 hPa (note shown) which was close to the Pennsylvania and New York border.

b. Radar evolution

1 The 30 July flood is based on local time. They heavy rainfall spanned 31 July using UTC time.

A line of convection developed to the west of Ellicott City and moved into the City shortly after 2300 UTC. Prior to the larger scale convective lines arrival several weaker south-to-north convective elements moved over the city. More apparent in the 0.5 degree velocity than in the 0.5 degree reflectivity data, there was a complex interaction with cold pools which moved to the north, northwest and eventually to the northeast. (Animation).

Figure 7 shows the early stage with south-north convective elements moving over Columbia and Ellicott City, MD at 2256 UTC before the large line to the west interacted with these convective elements. These cells were low-topped and did not show up well on GOES-R imagery. As the line interacted with the leading cells several cold pools developed and changed the evolution of the convection. By 2337 UTC there was a strong area of inbounds (Fig. 8: green) over Ellicott City and outbounds to the southwest. This produced an area of convergence and allowing new convection to develop and move over the boundary to the north. This boundary persisted as it slowly moved to the north and was still present at 2359 UTC (Fig. 9). The cold pool as analyzed in the velocity data moved east of Ellicott City by 0008 UTC. However, the east moving north-to-south line continued to produce new convection which moved north to south along the line (Fig. 10) through 0044 UTC when the more north-south oriented convective line finally pushed east of Ellicott City.

The evolution, including the large linear convective system to the west interacting with convective elements to the east was classified as a Multi-Merge (MULTMERG) eastern flash flood type by Jessup and Colucci (2012: See their Fig. 5c). In this case the leading cells were relatively unorganized and not associated with a mesoscale convective area.

The GOES IR satellite loops (Fig. 11) showed early convection develop in southern Pennsylvania around 1845 UTC (not shown) these storms moved east initiating a line along the outflow to the south and east around 1945 UTC (Fig. 11a). This line merged with other developing convection and moved over central Maryland. After 0045 UTC 31 July the tops began to slowly cool and accelerate to the east. Satellite loops show a complex evolution of a linear feature with perhaps two lines moving across the region of interest2.

c. GEFS Forecasts

The GEFS probability of 25 mm or more of QPF (Fig. 12) and the ensemble mean QPF with each members 50 mm contour is shown in Figure 13. The GEFS forecast a north-south axis of heavy rain over east-central Pennsylvania. The mean QPF showed around 25 mm in and around Ellicott City.

2 Satellite analysis was provided by Sheldon Kusselson and loop links he sent were used to make images at 3 times. http://rammb.cira.colostate.edu/ramsdis/online/loop_timestamp.asp?data_folder=goes-west_goes-east%2Fgeir404&width=640&height=480&ending_image=geir404_20160731061500.gif&starting_image=geir404_20160730121500.gif

d. SREF Forecasts of Maximum QPF

Similar to the GEFS the SREF forecast a considerably large area of QPF over 25 mm and is not shown. Instead the maximum 3-hour QPF in the SREF is shown in Figure 14. The SREF had two nodes of high QPF, one over western Maryland and the secondary maximum over northeastern Maryland. The western maximum indicated the potential for 90 to 100 mm and the eastern maxima indicated 50 to 60 mm of QPF.

The maximum QPF in the SREF was likely a function of where the model had the most instability and thus where the convective parameterization scheme produced “convection”. Overall, the SREF was extremely wet and if used a provided would have led to over forecasting the rainfall and areas of potential heavy rainfall. The best signal for heavy rainfall in the SREF was well west of Ellicott City likely terrain and convective response with flow into the terrain related. The secondary maximum north of Baltimore was too far north of Ellicott City and may be related to the south-southeasterly flow up the Chesapeake Bay.

e. Convective allowing model (CAMS) forecasts

The NCEP HRRRV1 was replaced by the HRRRV2 after this event. For brevity only the HRRRV2 imagery was used. GSD was running the HRRRV2 and NCEP had a parallel HRRRV2 feed running in July 2016. The two forecast cycles from the HRRR time-lagged ensemble (HRRR-TLE) from 18 and 1900 UTC 30 July are shown in Figures 15 & 16 respectively. These data show that the HRRR-TLE had an axis of heavy rainfall, 1 inch in 1 hour from Virginia into Pennsylvania west of Ellicott City and closer and aligned much like the shape of the Appalachian Mountains in central Maryland and Pennsylvania (upper panels Figs. 15 & 16).

The probability of 3 inches or more QPF in 3-hours also peaked close to 0000 UTC 31 July. The 1900 UTC data was a bit more robust with higher probabilities of over 3 inches of rainfall at the 40% to 50% confidence level. However the maximum was in Pennsylvania. The 1800 UTC guidance too was focused in Pennsylvania but had probabilities more in the 30 to 40% range.

Individual HRRR runs leading up to the event (Fig.17) showed that the HRRR had local maximum values of 2-4 inches in Maryland by 0100 UTC from the 2200 UTC HRRR. The 4 HRRR (HRRRV2) cycles showed maximized the QPF in southern Pennsylvania and Maryland at different times. The area affected by the highest QPF values showed considerable run-to-run variation. No run got the highest or close to the observed QPF in Ellicott City. However these data had a coherent signal that the potential for 2-6 inches or rain was potential issue over portions of Maryland and southern Pennsylvania.

The 4 HRRR cycles shown in Figure 17 were used in the HRRR-TLE. The spatial and temporal variability clearly impacted the HRRR-TLE probabilities and showed the difficulty and thus the uncertainty with forecasting convection.

4. Conclusions

Locally heavy rainfall associated with convection brought devastating flooding to the Ellicott City, MD. Rainfall rates near 4 inches per hour were observed. Rainfall rates of this value are relatively rare occurring less than 0.1% of the time in most locations in the Mid-Atlantic region and if they occur only occur in the warm season. Such rates are not observed in the autumn through spring. The extreme rainfall rates and the urbanization produced severe flooding. The flooding produced extensive damage and led to at least 2 fatalities.

The radar and satellite data showed the complex evolution of lines and clusters of thunderstorms. The implications based on radar velocity data was that the relatively weak flow allowed outflow boundaries to remain quasi-stationary and interact with more organized convection to the west. The slow moving boundary likely played the role to focusing the convection over the same region for a prolonged period of time. It fit the MULRMERGE model outlined by Jessup and Colucci (2012).

The larger scale models forecast rainfall but they were incapable of the outlining the region where the record rainfall and rainfall rates were observed. They showed a signal at the coast of over forecasting the QPF and under forecasting the maximum QPF. These larger scale models and ensembles are hydrostatic models and require convective parameterization schemes (CPS). In convectively forced situations, hydrostatic models are of limited value. The SREF as shown had too much QPF over too large an area and its maximum from all members was well west of the observed location.

The CAMS, represented by the HRRR and the derived HRRR-TLE had a signal here. The HRRR was shown because it is updated hourly and may be better suited to deal with environments which are modified by recent or ongoing convection. Other CAMS were examined but lacking rapid updating they were of limited value. Convection modifies the environment, thus rapid updating models have some signals which may be of value and of value over a smaller regions.

In this case, the HRRR and HRRR-TLE showed the potential for heavy rainfall in the southern Pennsylvania and Maryland. Similar to the hydrostatic models, the HRRR could not get the location of the extreme rainfall. To the HRRR’s credit, it had a signal for the potential for heavy rainfall. How forecasters can leverage this signal to be more mindful of the potential of flooding is another issue and may require some training. These models will likely never forecast events of this nature.

Thus, a forecast strategy requires using rapid updating CAMS. Noting the signals for regionally heavy and extreme rainfall. This may be identified by the probability of rainfall rates in excess of 3 inches in 1 and 3 hours. When the CAMS have a signal, real-time data from sources such as radar and spotters is still required. Only by monitoring the environment with radar and observational data can effective warnings be issued for events of this scale and nature.

5. Acknowledgements

The Pennsylvania State University for real-time data access. Thanks to Curtiss Alexander and Trevor Alcott for information on the GSD HRRR and facilitating use of the GSD HRRR-TLE

website. Thanks to NCAR for access to their high resolution ensemble. We examined but did not show the data for this case. Sheldon Kusselson provided satellite links, a formal summary and static images. 6. References

Benjamin, S.G, and contributors: 2016: A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh. MWR, 144, 1669-1693.

Brooks, HE and D.J. Stensrud: 200: Climatology of Heavy Rain Events in the United States from Hourly Precipitation Observations. MWR, 128, 1194-1201.

Ebert, E. E., 2001: Ability of a poor man’s ensemble to predict the probability and distribution of precipitation. Mon. Wea. Rev., 129, 2461–2480.

Juanzhen Sun, Ming Xue, James W. Wilson, Isztar Zawadzki, Sue P. Ballard, Jeanette Onvlee-Hooimeyer, Paul Joe, Dale M. Barker, Ping-Wah Li, Brian Golding, Mei Xu, and James Pinto, 2014: Use of NWP for Nowcasting Convective Precipitation: Recent Progress and Challenges. Bull. Amer. Meteor. Soc., 95, 409–426.

Maddox,R. A,, C. F. Chappell, and L. R. Hoxit, 1979: Synoptic and Meso-α Scale Aspects of Flash Flood Events, Bull Amer. Meteor. Soc., 60, 115–123, DOI: http://dx.doi.org/10.1175/1520-0477-60.2.115

Doswell, C.A,, H. E. Brooks, and R.A. Maddox, 1996: Flash Flood Forecasting: An Ingredients-Based Methodology, Wea. Forecasting, 11, 560–581:DOI: http://dx.doi.org/10.1175/1520-0434(1996)011<0560:FFFAIB>2.0.CO;2

WP 2016: Two dead after severe flash flood in Maryland. Washington Post 31 July 2016.

WP 2016: This is how and “off-the-charts” flood ravaged Ellicott City. Washington Post 1 August 2016.

Weaver, S. C., and S. Nigam, 2008: Variability of the Great Plains low level jet: Large scale circulation context and hydroclimate impacts. J. Climate,21,1532–1551.

Figure 1. Maximum 1-hour rainfall rate (mmhr-1) from the Stage-IV estimated rainfall data. Data were computed using the maximum 1-hour rainfall over the 3-hour period of 2200 UTC 30 July through 0100 UTC 31 July 2016. Return to text.

Figure 2. The Stage-IV estimated rainfall for the 2-hour period of heavy rainfall from 2300 UTC 30 t0 0100 UTC 31 July 2016. Return to text.

Figure 3. CFSR pattern of 500 hPa heights in 6-hour increments from a) 1200 UTC 30 July through f) 1800 UTC 31 July 2016. Return to text.

Figure 4.As in Figure 3 except for 850 hPa winds and v-winds anomalies. Return to text.

Figure 5. As in Figure 4 except for preciitable water. . Return to text.

Figure 6. As in Figure 4 except for 250 hPa winds. Return to text.

Figure 7. Radar at 2256 UTC showing 0.5 degree reflectivity and velocity. South to north elements is present over Columbia and Ellicott City, MD. The more southwest to northeast line of convection is entering from the west. Return to text.

Figure 8. As in Figure 7 except at 2237 UTC showing the enhanced echoes over Ellicott City and the area of inbounds in the cold pool over Ellicott City. Enhanced convergence is implied in the region of inbounds and outbounds south and west of Ellicott City near Columbia, MD. Return to text.

Figure 9. As in Figure 8 except valid at 2359 UTC. Return to text.

Figure 10. As in Figure 9 except valid at 0030 UTC. Return to text.

a. IR 30 July 1900

b. IR 30 July 2145

c. IR 31 July 0045

Figure 11. GOES IR Images showing early convection in Pennsylvania at a) 1900 UTC, the line over Virginia and Maryland at 2145 UTC, and c) the second evolution of the line as it was about to move east of the flood area at 0045 UTC. Return to text.

Figure 11. GEFS forecasts valid for the 12-hour period ending at 0600 UTC 31 July 2016 showing the probability of 25 mm or more QPF and the ensemble mean 25 mm QPF contour. Forecasts are from 6 GEFS forecast cycles initialized at a) 1200 UTC 28 July, b) 0000 UTC 29 July, c) 1200 UTC 29 July, d) 0000 UTC 30 July, e) 0600 UTC 30 July, and f) 1200 UTC 30 July 2016 . Return to text.

Figure 13. As in Figure 11 except for the ensemble mean QPF and each members 50 mm contour if forecast by the member. Return to text.

Figure 12. SREF maximum 3-hour QPF valid 0300 UTC 31 July 2016. Data was computed by keeping the highest 3-hour QPF forecast by each SREF member at each model grid point. Return to text.

09Z 30 July SREF maximum 3-hour accumulated QPF valid 20160331 0300 UTC

Figure 15. HRRRV2 time lagged ensemble (HRRR-TLE) initialized at 1800 UTC 30 July showing the probability of a) 1 inch and b) 3 inches or more QPF in 1 and 3 hours respectively. The maximum 1 inch time was valid at 0000 UTC 31 July. The 3 inch probabilities maximized at 0000 UTC 31 July. Return to text.

Figure 16. As in Figure 15 except from the HRRR-TLE using the latest 1900 UTC HRRR as a member of the ensemble. Return to text.

Figure 17. HRRRV2 run initialized clockwise from top 2000, 2100, 2200, and 2300 UTC 30 July 2016 showing the accumulated QPF. The ending times vary based on when the highest values were achieved in the Maryland and southern Pennsylvania. Return to text.