scholarly journals Characterizing Thunderstorm Gust Fronts near Complex Terrain

2020 ◽  
Vol 148 (8) ◽  
pp. 3267-3286
Author(s):  
Nicholas T. Luchetti ◽  
Katja Friedrich ◽  
Christopher E. Rodell ◽  
Julie K. Lundquist
Keyword(s):  
Great Plains ◽  
Complex Terrain ◽  
Structural Engineering ◽  
Microwave Radiometer ◽  
Fire Behavior ◽  
Vertical Motion ◽  
Colorado Front Range ◽  
Study Experience ◽  
Gust Fronts ◽  
Colorado Rocky Mountains

ABSTRACT Fire safety, aviation, wind energy, and structural-engineering operations are impacted by thunderstorm outflow boundaries or gust fronts (GFs) particularly when they occur in mountainous terrain. For example, during the 2013 Arizona Yarnell Hill Fire, 19 firefighters were killed as a result of sudden changes in fire behavior triggered by a passing GF. Knowledge of GF behavior in complex terrain also determines departure and landing operations at nearby airports, and GFs can induce exceptional structural loads on wind turbines. While most examinations of GF characteristics focus on well-organized convection in areas such as the Great Plains, here the investigation is broadened to explore GF characteristics that evolve near the complex terrain of the Colorado Rocky Mountains. Using in situ observations from meteorological towers, as well as data from wind-profiling lidars and a microwave radiometer, 24 GF events are assessed to quantify changes in wind, temperature, humidity, and turbulence in the lowest 300 m AGL as these GFs passed over the instruments. The changes in magnitude for all variables are on average weaker in the Colorado Front Range than those typically observed from organized, severe storms in flatter regions. Most events from this study experience an increase in wind speed from 1 to 8 m s−1, relative humidity from 1% to 8%, and weak vertical motion from 0.3 to 3.6 m s−1 during GF passage while temperature drops by 0.2°–3°C and turbulent kinetic energy peaks at >4 m2 s−2. Vertical profiles reveal that these changes vary little with height in the lowest 300 m.

Evaluating Thunderstorm Gust Fronts in New Mexico and Arizona

2020 ◽  
Vol 148 (12) ◽  
pp. 4943-4956
Author(s):  
Nicholas T. Luchetti ◽  
Katja Friedrich ◽  
Christopher E. Rodell
Keyword(s):  
New Mexico ◽  
Great Plains ◽  
Complex Terrain ◽  
Fire Behavior ◽  
Rio Grande Valley ◽  
Propagation Speed ◽  
Rio Grande ◽  
Gust Fronts ◽  
Mogollon Rim ◽  
Gust Front

AbstractStrong winds generated by thunderstorm gust fronts can cause sudden changes in fire behavior and threaten the safety of wildland firefighters. Wildfires in complex terrain are particularly vulnerable as gust fronts can be channeled and enhanced by local topography. Despite this, knowledge of gust front characteristics primarily stems from studies of well-organized thunderstorms in flatter areas such as the Great Plains, where the modification of gust fronts by topography is less likely. Here, we broaden the investigation of gust fronts in complex terrain by statistically comparing characteristics of gust fronts that are pushed uphill and propagate atop the Mogollon Rim in Arizona to those that propagate down into and along the Rio Grande Valley in New Mexico. Using operational WSR-88D data and in situ observations from Automated Surface Observing System (ASOS) stations, 122 gust fronts in these regions are assessed to quantify changes in temperature, wind, relative humidity, and propagation speed as they pass over the weather stations. Gust fronts that propagated down into and along the Rio Grande Valley in New Mexico were generally associated with faster propagation speeds, larger decreases in temperature, and larger increases in wind speeds compared to gust fronts that reached the crest of the Mogollon Rim in Arizona. Gust fronts atop the Mogollon Rim in Arizona behaved less in accordance with density current theory compared to those in the Rio Grande Valley in New Mexico. The potential reasons for these results, and their implications for our understanding of terrain influence on gust front characteristics, are discussed.

Observing the Dynamics of Wildland Grass Fires: FireFlux—A Field Validation Experiment

2007 ◽  
Vol 88 (9) ◽  
pp. 1369-1382 ◽  
Author(s):  
Craig B. Clements ◽  
Shiyuan Zhong ◽  
Scott Goodrick ◽  
Ju Li ◽  
Brian E. Potter ◽  
...  
Keyword(s):  
Great Plains ◽  
Forest Fires ◽  
Fire Behavior ◽  
The United States ◽  
Fire Season ◽  
Turbulent Structures ◽  
Tall Grass ◽  
Tall Grass Prairie ◽  
Validation Experiment ◽  
Turbulence Data

Grass fires, although not as intense as forest fires, present a major threat to life and property during periods of drought in the Great Plains of the United States. Recently, major wildland grass fires in Texas burned nearly 1.6 million acres and destroyed over 730 homes and 1320 other buildings. The fires resulted in the death of 19 people, an estimated loss of 10,000 head of livestock, and more than $628 million in damage, making the 2005/06 fire season the worst on record for the state of Texas. As an aid to fire management, various models have been developed to describe fire behavior. However, these models strongly emphasize fuels and fail to adequately consider the role of convective dynamics within the atmosphere and its interaction with the fire due to the lack of observational data. To fill this gap, an intensive field measurement campaign called FireFlux was conducted during February 2006 near Houston, Texas. The campaign employed a variety of instrument platforms to collect turbulence data at multiple levels within and immediately downwind of a 155 acre tall-grass prairie burn unit. This paper presents some first-time observations of atmospheric turbulent structures/fluxes associated with intense grass fires and provides a basis to further our understanding of the dynamics of grass fires and their interactions with the atmosphere.

scholarly journals Studying wildfire behavior using FIRETEC

2002 ◽  
Vol 11 (4) ◽  
pp. 233 ◽  
Author(s):  
Rodman Linn ◽  
Jon Reisner ◽  
Jonah J. Colman ◽  
Judith Winterkamp
Keyword(s):  
Environmental Conditions ◽  
Empirical Data ◽  
Complex Terrain ◽  
Fire Behavior ◽  
Meteorological Conditions ◽  
Decision Makers ◽  
Process Models ◽  
Behavior Model ◽  
Complex Processes ◽  
Wildfire Modeling

A coupled atmospheric/wildfire behavior model is described that utilizes physics-based process models to represent wildfire behavior. Five simulations are presented, four of which are highly idealized situations that are meant to illustrate some of the dependencies of the model on environmental conditions. The fifth simulation consists of a fire burning in complex terrain with non-homogeneous vegetation and realistic meteorological conditions. The simulated fire behavior develops out of the coupling of a set of very complex processes and not from prescribed rules based on empirical data. This represents a new direction in wildfire modeling that we believe will eventually help decision makers and land managers do their jobs more effectively.

scholarly journals Combining ground-based microwave radiometer and the AROME convective scale model through 1DVAR retrievals in complex terrain: an Alpine Valley case study

2017 ◽  
Author(s):  
Pauline Martinet ◽  
Domenico Cimini ◽  
Francesco De Angelis ◽  
Guylaine Canut ◽  
Vinciane Unger ◽  
...  
Keyword(s):  
Bias Correction ◽  
Complex Terrain ◽  
Microwave Radiometer ◽  
Scale Model ◽  
Field Campaign ◽  
Alpine Valley ◽  
Clear Sky ◽  
Convective Scale ◽  
Temperature Inversions ◽  
Sky Conditions

Abstract. A RPG-HATPRO ground-based microwave radiometer (MWR) was operated in a deep Alpine valley during the Passy-2015 field campaign. This experiment aims at investigating how stable boundary layers during wintertime conditions drive the accumulation of pollutants. In order to understand the atmospheric processes in the valley, MWR continuously provide vertical profiles of temperature and humidity at a high time frequency, providing valuable information to follow the evolution of the boundary layer. A one-dimensional variational (1DVAR) retrieval technique has been implemented during the field campaign to optimally combine MWR and 1 h forecasts from the French convective scale model AROME. Retrievals were compared to radiosonde data launched at least every 3 hours during two intensive observation periods (IOP). An analysis of the AROME forecast errors during the IOPs has shown a large underestimation of the surface cooling during the strongest stable episode. MWR brightness temperatures were monitored against simulations from the radiative transfer model ARTS2 (Atmospheric Radiative Transfer Simulator) and radiosonde launched during the field campaign. Large errorswere observed for most transparent channels (i.e., 51–52 GHz) affected by absorption model and calibration uncertainties while a good agreement was found for opaque channels (i.e., 54–58 GHz). Based on this monitoring, a bias correction of raw brightness temperature measurements was applied before the 1DVAR retrievals. 1DVAR retrievals were found to significantly improve the AROME forecasts up to 3 km but mainly below 1 km and to outperform usual statistical regressions above 1 km. With the present implementation, a root-mean-square-error (RMSE) of 1 K through all the atmospheric profile was obtained with values within 0.5 K below 500 m in clear-sky conditions. The use of lower elevation angles (up to 5°) in the MWR scanning and the bias correction were found to improve the retrievals below 1000 m. MWR retrievals were found to catch very well deep nearsurface temperature inversions. Larger errors were observed in cloudy conditions due to difficulty of ground-based MWR to resolve high level inversions that are still challenging. Finally, 1DVAR retrievals were optimized for the analysis of the IOPs by using radiosondes as backgrounds in the 1DVAR algorithm instead of the AROME forecasts. A significant improvement of the retrievals in cloudy conditions and below 1000 m in clear-sky was observed. From this study, we can conclude that MWR are expected to bring valuable information into NWP models up to 3 km altitude both in clear-sky and cloudy-sky conditions with the maximum improvement found around 500 m. With an accuracy between 0.5 and 1 K in RMSE, our study has also proved MWR to be capable of resolving deep near-surface temperature inversions observed in complex terrain during highly stable boundary layer conditions.

An Evaluation of a Hybrid, Terrain-Following Vertical Coordinate in the WRF-Based RAP and HRRR Models

2020 ◽  
Vol 35 (3) ◽  
pp. 1081-1096 ◽  
Author(s):  
Jeffrey Beck ◽  
John Brown ◽  
Jimy Dudhia ◽  
David Gill ◽  
Tracy Hertneky ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Wrf Model ◽  
Vertical Motion ◽  
Weather Research And Forecasting ◽  
Mountainous Terrain ◽  
Vertical Coordinate ◽  
Numerical Noise ◽  
Terrain Following ◽  
Model Equations ◽  
Real Time Simulations

Abstract A new hybrid, sigma-pressure vertical coordinate was recently added to the Weather Research and Forecasting (WRF) Model in an effort to reduce numerical noise in the model equations near complex terrain. Testing of this hybrid, terrain-following coordinate was undertaken in the WRF-based Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) models to assess impacts on retrospective and real-time simulations. Initial cold-start simulations indicated that the majority of differences between the hybrid and traditional sigma coordinate were confined to regions downstream of mountainous terrain and focused in the upper levels. Week-long retrospective simulations generally resulted in small improvements for the RAP, and a neutral impact in the HRRR when the hybrid coordinate was used. However, one possibility is that the inclusion of data assimilation in the experiments may have minimized differences between the vertical coordinates. Finally, analysis of turbulence forecasts with the new hybrid coordinate indicate a significant reduction in spurious vertical motion over the full length of the Rocky Mountains. Overall, the results indicate a potential to improve forecast metrics through implementation of the hybrid coordinate, particularly at upper levels, and downstream of complex terrain.

scholarly journals Accuracy of retrieving temperature and humidity profiles by ground-based microwave radiometry in truly complex terrain

2015 ◽  
Vol 8 (8) ◽  
pp. 3355-3367 ◽  
Author(s):  
G. Massaro ◽  
I. Stiperski ◽  
B. Pospichal ◽  
M. W. Rotach
Keyword(s):  
Complex Terrain ◽  
Microwave Radiometer ◽  
Radiosonde Data ◽  
Alpine Valley ◽  
Topographic Slope ◽  
Retrieval Algorithms ◽  
Temperature And Humidity ◽  
Upper Level ◽  
The One ◽  
Humidity Profiles

Abstract. Within the Innsbruck Box project, a ground-based microwave radiometer (RPG-HATPRO) was operated in the Inn Valley (Austria), in very complex terrain, between September 2012 and May 2013 to obtain temperature and humidity vertical profiles of the full troposphere with a specific focus on the valley boundary layer. In order to assess its performance in a deep alpine valley, the profiles obtained by the radiometer with different retrieval algorithms based on different climatologies are compared to local radiosonde data. A retrieval that is improved with respect to the one provided by the manufacturer, based on better resolved data, shows a significantly smaller root mean square error (RMSE), both for the temperature and humidity profiles. The improvement is particularly substantial at the heights close to the mountaintop level and in the upper troposphere. Lower-level inversions, common in an alpine valley, are resolved to a satisfactory degree. On the other hand, upper-level inversions (above 1200 m) still pose a significant challenge for retrieval. For this purpose, specialized retrieval algorithms were developed by classifying the radiosonde climatologies into specialized categories according to different criteria (seasons, daytime, nighttime) and using additional regressors (e.g., measurements from mountain stations). The training and testing on the radiosonde data for these specialized categories suggests that a classification of profiles that reproduces meaningful physical characteristics can yield improved targeted specialized retrievals. A novel and very promising method of improving the profile retrieval in a mountainous region is adding further information in the retrieval, such as the surface temperature at fixed levels along a topographic slope or from nearby mountaintops.

scholarly journals Carbon monoxide mixing ratios over Oklahoma between 2002 and 2009 retrieved from Atmospheric Emitted Radiance Interferometer spectra

2010 ◽  
Vol 3 (5) ◽  
pp. 1319-1331 ◽  
Author(s):  
L. Yurganov ◽  
W. McMillan ◽  
C. Wilson ◽  
M. Fischer ◽  
S. Biraud ◽  
...  
Keyword(s):  
Water Vapor ◽  
Great Plains ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Retrieval Algorithm ◽  
Southern Great Plains ◽  
Diurnal Cycles ◽  
Mixing Ratios ◽  
Clear Sky ◽  
The Tropics

Abstract. CO mixing ratios for the lowermost 2-km atmospheric layer were retrieved from downwelling infrared (IR) radiance spectra of the clear sky measured between 2002 and 2009 by a zenith-viewing Atmospheric Emitted Radiance Interferometer (AERI) deployed at the Southern Great Plains (SGP) observatory of the Atmospheric Radiation Measurements (ARM) Program near Lamont, Oklahoma. A version of a published earlier retrieval algorithm was improved and validated. Archived temperature and water vapor profiles retrieved from the same AERI spectra through automated ARM processing were used as input data for the CO retrievals. We found the archived water vapor profiles required additional constraint using SGP Microwave Radiometer retrievals of total precipitable water vapor. A correction for scattered solar light was developed as well. The retrieved CO was validated using simultaneous independently measured CO profiles from an aircraft. These tropospheric CO profiles were measured from the surface to altitudes of 4572 m a.s.l. once or twice a week between March 2006 and December 2008. The aircraft measurements were supplemented with ground-based CO measurements using a non-dispersive infrared gas correlation instrument at the SGP and retrievals from the Atmospheric IR Sounder (AIRS) above 5 km to create full tropospheric CO profiles. Comparison of the profiles convolved with averaging kernels to the AERI CO retrievals found a squared correlation coefficient of 0.57, a standard deviation of ±11.7 ppbv, a bias of -16 ppbv, and a slope of 0.92. Averaged seasonal and diurnal cycles measured by the AERI are compared with those measured continuously in situ at the SGP in the boundary layer. Monthly mean CO values measured by the AERI between 2002 and 2009 are compared with those measured by the AIRS over North America, the Northern Hemisphere mid-latitudes, and over the tropics.

scholarly journals Fire-Modified Meteorology in a Coupled Fire–Atmosphere Model

2015 ◽  
Vol 54 (3) ◽  
pp. 704-720 ◽  
Author(s):  
Mika Peace ◽  
Trent Mattner ◽  
Graham Mills ◽  
Jeffrey Kepert ◽  
Lachlan McCaw
Keyword(s):  
Initial Conditions ◽  
Fire Behavior ◽  
Wrf Model ◽  
South Australia ◽  
Vertical Motion ◽  
Propagation Speed ◽  
Atmospheric Model ◽  
Energy Fluxes ◽  
Spread Model ◽  
Atmosphere Model

AbstractThe coupled fire–atmosphere model consisting of the Weather and Forecasting (WRF) Model coupled with the fire-spread model (SFIRE) module has been used to simulate a bushfire at D’Estrees Bay on Kangaroo Island, South Australia, in December 2007. Initial conditions for the simulations were provided by two global analyses: the GFS operational analysis and ERA-Interim. For each NWP initialization, the simulations were run with and without feedback from the fire to the atmospheric model. The focus of this study was examining how the energy fluxes from the simulated fire modified the local meteorological environment. With feedback enabled, the propagation speed of the sea-breeze frontal line was faster and vertical motion in the frontal zone was enhanced. For one of the initial conditions with feedback on, a vortex developed adjacent to the head fire and remained present for over 5 h of simulation time. The vortex was not present without fire–atmosphere feedback. The results show that the energy fluxes released by a fire can effect significant changes on the surrounding mesoscale atmosphere. This has implications for the appropriate use of weather parameters extracted from NWP and used in prediction for fire operations. These meteorological modifications also have implications for anticipating likely fire behavior.

Improved Daytime Column-Integrated Precipitable Water Vapor from Vaisala Radiosonde Humidity Sensors

2008 ◽  
Vol 25 (6) ◽  
pp. 873-883 ◽  
Author(s):  
K. E. Cady-Pereira ◽  
M. W. Shephard ◽  
D. D. Turner ◽  
E. J. Mlawer ◽  
S. A. Clough ◽  
...  
Keyword(s):  
Water Vapor ◽  
Great Plains ◽  
Weather Prediction ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Atmospheric Radiation Measurement ◽  
Atmospheric Transmittance ◽  
Dry Bias

Abstract Accurate water vapor profiles from radiosondes are essential for long-term climate prediction, weather prediction, validation of remote sensing retrievals, and other applications. The Vaisala RS80, RS90, and RS92 radiosondes are among the more commonly deployed radiosondes in the world. However, numerous investigators have shown that the daytime water vapor profiles measured by these instruments present a significant dry bias due to the solar heating of the humidity sensor. This bias in the column-integrated precipitable water vapor (PWV), along with variability due to calibration, can be removed by scaling the humidity profile to agree with the PWV retrieved from a microwave radiometer (MWR), as has been demonstrated by several previous studies. Infrared radiative closure analyses have shown that the MWR PWV does not present daytime versus nighttime differences; thus, scaling by the MWR is a possible approach for removing the daytime dry bias. However, MWR measurements are not routinely available at all radiosonde launch sites. Starting from a long-term series of sonde and MWR PWV measurements from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, the authors have developed a simple correction to the column-integrated sonde PWV, derived from an analysis of the ratio of the MWR and sonde measurements; this correction is a function of the atmospheric transmittance as determined by the solar zenith angle, and it effectively removes the daytime dry bias at all solar zenith angles. The correction was validated by successfully applying it to an independent dataset from the ARM tropical western Pacific (TWP) site.

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