Extreme Precipitation Estimation and Prediction William R. Cotton With Ray L. McAnelly and Travis Ashby Colorado State University Dept. of Atmospheric.

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Extreme Precipitation Estimation and Prediction William R. Cotton With Ray L. McAnelly and Travis Ashby Colorado State University Dept. of Atmospheric Science

Outline Extreme precipitation estimation. The Fort Collins flash flood case. Example of heavy rainfall NWP with 3-km grid spacing – What the future may bring.

Extreme Precipitation Project Outline  Perform inhomogeneous, nested simulations of at least 20 historical cases in the Colorado mountainous region.  Compare simulations with observations for each.  Perturb initial conditions for each case: vary moisture mixing ratio, winds, and soil moisture distributions, move synoptic fields relative to terrain.  Develop a systematic methodology for perturbing initial condition based on above simulations.  Develop a GUI in which a user identifies coordinates (point and click) for extreme precipitation estimation over Colorado. The GUI then selects historical synoptic setting most appropriate for the selected site, moves the synoptic field, then run through a sequence of pre-determined perturbations to estimate extreme precipitation values for that location.

Approximate hydroclimatic regions of Colorado used to describe and characterize precipitation events

Numerical Simulation of the 28 July 1997 Fort Collins Flash Flood C. Travis Ashby and William R. Cotton To assess the ability of a mesoscale model to reproduce extreme precipitation events along the Colorado Rocky Mountain foothills. To determine the parameters to which the model solution is sensitive. To better understand the physical mechanisms for producing and maintaining quasi-stationary, heavily precipitating convection near topography.

Introduction 10”+ rain fell over southwest Fort Collins between 5:30 pm and 11:10 pm July people killed. Over $200 million in property damage. 13 counties declared federal disaster areas during 28 July –12 August time period.

Model Configuration Model: RAMS v. 3b Parameterizations: Cumulus Convection:Modified Kuo (Tremback, 1990) Turbulence Closure:Smagorinsky deformation K (Smagorinsky, 1963; Lilly, 1962; Hill, 1974) Microphysics:RAMS single moment scheme: (Walko et. al., 1995) Soil/Vegetation:(Tremback and Kessler, 1985; Avissar and Mahrer, 1988)

DOMAIN: 4-fixed, nested grids Grid 1:  x =  y = 80 km  t = 90 sec. Grid 2:  x =  y = 20 km  t = 45 sec. Grid 3:  x =  y = 5 km  t = 15 sec. Grid 4:  x =  y = 1.67 km  t = 5 sec.

Topography is at native resolution of each grid Cumulus parameterization active on Grid 1 only  z vertical coordinate; 37 levels;  z = 100 m at ground with geometric expansion ratio of 1.12 to maximum vertical spacing of 800 m. Model top at 19.5 km. Each grid uses full moist physics (hail, graupel, aggregates, snow, pristine ice, rain, cloudwater, and vapor).

Input Data RUC analyses, rawinsonde observations and surface observations at 12Z July 28, 00Z and 12Z July 29. ETA soil moisture analysis for initialization only at 12Z July 28. Antecedent Precipitation Index (API) used for soil moisture initialization (“API” simulation).

Time Integration Spin up run started at 12Z and run through 15Z without microphysics or cumulus parameterization active. Restart at 15Z w/microphysics and cuparm (on grid 1) active until 1800Z on grids 1-3; Grid 4 not present. Grid 4 activated at 1800Z and run through 05Z July 29.

ETA estimated soil moisture

ETA

ETA soil moisture analysis run

ETA run shifted 23km to NW

API soil moisture from gauge data

API run

API

API run

API and ETA Facts ETA sim. predicted precipitation maximum has correct magnitude (just over 10 inches). API sim. has reduced domain maximum (5.9 inches) and reduced accumulated precip. gradient surrounding maximum. Location of precipitation maximum is located within 23 km of Fort Collins in ETA simulation and within 38 km in the API simulation. Bow echo reproduced and timing is correct in ETA simulation, but is absent in the cloud resolving griad in the API simulation. The bow-echo plays no role in the ETA simulation flood. The ETA precip event is characterized by a single storm (max precip rate of 21+ cm/hr) which becomes stationary at maturity. The API event is characterized by training cells (max precip rate of  15 cm/hr) which initiate along a low-level convergence zone that was produced by the initial soil moisture distribution. Neither simulation reproduces the in situ development and anchoring of convection over the foothills. Both simulations generate the domain precip maxima before 00Z. The FCL flood, the Big Thompson flood and the Rapid City floods occurred after 00Z. We have demonstrated we can move storms, but not in any predictable position/timing.

Experiment examining effects of moving synoptic pattern 234km south

Discussion and Summary The simulation indicates that, given a realistic initial condition corresponding to a flood producing meteorological environment, potential flood-producing precipitation can be generated in a numerical model in the vicinity of a realized flood event. This simulation reproduced the precipitation amount to within one inch of the observed amount. However, the location of the domain maximum is 23 km to the southeast of the observed site (Fort Collins). Additionally, the precipitation, which is responsible for the domain maximum occurs 4 hours earlier than observed. An observational study by Petersen et. al. (1999) provided reasonable evidence that the most intense precipitation over Fort Collins, which occurred between 0300Z and 0400Z, was influenced by a low-level flow perturbation associated with the bow- echo. In this simulation 21 cm of rain fell at the domain maximum before the bow-echo had even become established in the simulation.

In this simulation a variety of storm movement characteristics prevail. The storms which produce the flooding precipitation at the domain maximum initiate to the east of the domain maximum, moving westward with the low-level flow until they finally become quasi- stationary around 2200Z. A second quasi-stationary system develops with much lower precipitation rates than the first, between 0100Z and 0200Z. At the same time, eastward moving storms are dominant in the southern half of the domain, the bow-echo being the most obvious example. While the bow-echo produced precipitation rate maxima comparable to the quasi- stationary convection, the persistent east-northeastward propagation of the bow-echo precluded a comparable flood event in association with this feature.

RAMS Realtime Forecast - 29 August Aug 0000 UTC Initialization - localized flooding in northern Denver metro area on afternoon/evening of 29 Aug Two-grid set-up (48-km and 12-km grids) Three-grid set-up (3-km fine grid)