Joseph J. Charney

Observing The Dynamics Of Wildland Grass Fires: FireFlux -A Field Validation Experiment

The first comprehensive set of in situ measurements of turbulence and dynamics in an experimental wildland grass fire should help improve fire models.

The importance of fire–atmosphere coupling and boundary-layer turbulence to wildfire spread

The major source of uncertainty in wildfire behavior prediction is the transient behavior of wildfire due to changes in flow in the fire’s environment. The changes in flow are dominated by two factors. The first is the interaction or ‘coupling’ between the fire and the fire-induced flow. The second is the interaction or ‘coupling’ between the fire and the ambient flow driven by turbulence due to wind gustiness and eddies in the atmospheric boundary layer (ABL). In the present study, coupled wildfire–atmosphere large-eddy simulations of grassland fires are used to examine the differences in the rate of spread and area burnt by grass fires in two types of ABL, a buoyancy-dominated ABL and a roll-dominated ABL. The simulations show how a buoyancy-dominated ABL affects fire spread, how a roll-dominated ABL affects fire spread, and how fire lines interact with these two different ABL flow types. The simulations also show how important are fire–atmosphere couplings or fire-induced circulations to fire line spread compared with the direct impact of the turbulence in the two different ABLs. The results have implications for operational wildfire behavior prediction. Ultimately, it will be important to use techniques that include an estimate of uncertainty in wildfire behavior forecasts.

Evaluation of Real-Time High-Resolution MM5 Predictions over the Great Lakes Region

Real-time high-resolution mesoscale predictions using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) over the Great Lakes region are evaluated for the 2002/03 winter and 2003 summer seasons using surface and upper-air observations, with a focus on near-surface and boundary layer properties that are important for applications such as air quality and fire weather predictions. The summer season predictions produce a cold bias in maximum daily temperature and a warm bias in minimum temperature that together lead to a good prediction of daily mean temperature but a smallerthan-observed diurnal temperature cycle. In winter, the predicted near-surface temperatures are lower both day and night, yielding good agreement with the observed amplitude of the diurnal temperature cycle but relatively large cold bias in daily mean temperature. The predicted temperatures in the boundary layer are also systematically lower than the observed temperatures in the two seasons. The cold bias is consistent with the wetter-than-observed lower atmosphere in the model prediction, which in turn can be attributed to an inadequate specification of soil moisture. In both seasons, the model produced substantially more precipitation in all categories, especially in the heavy precipitation category, and the overprediction is primarily associated with more widespread area coverage in the model prediction. The chances of producing a false precipitation forecast are substantially higher than missing an observed precipitation event. Small systematic errors are found in the predictions of low-level winds, but above the boundary layer, the predicted winds are predominantly from the west, while the observed winds are from the west-northwest. The model is able to capture the general development and evolution of the lake–land breezes in areas surrounding Lake Michigan during summer, although errors exist in the strengths of the breezes and the timing of their transition. Predicted early morning inversions are slightly stronger than observed in winter and weaker than observed in summer. The weak summer morning inversion results in a rapid inversion breakup followed by an earlier growth of a mixed layer after sunrise. Despite the head start, the predicted mixed-layer heights in late afternoon are lower than those observed, suggesting that either the predicted surface sensible heat flux may be too low or the boundary layer flux divergence may be too high. Decreasing horizontal grid spacing from 12 to 4 km results in little improvement in the predictions of near-surface and boundary layer properties except for precipitation, for which the model bias is significantly reduced by the increase in horizontal resolution. The cold and wet biases and errors in inversion strengths and mixed-layer development call for extra caution when using products from mesoscale forecasts in applications such as air pollution and fire weather prediction.

A Terminal Area PBL Prediction System at Dallas–Fort Worth and Its Application in Simulating Diurnal PBL Jets

Abstract A state–of–the–science meso–b–scale numerical weather prediction model is being employed in a prototype forecast system for potential operational use at the Dallas–Fort Worth International Airport (DFW). The numerical model is part of a unique operational forecasting system being developed to support the National Aeronautics and Space Administrations (NASA) Terminal Area Productivity Program. This operational forecasting system will focus on meso–b–scale aviation weather problems involving planetary boundary layer (PBL) turbulence, and is named the Terminal Area PBL Prediction System (TAPPS). TAPPS (version 1) is being tested and developed for NASA in an effort to improve 1–6–h terminal area forecasts of wind, vertical wind shear, temperature, and turbulence within both stable and convective PBLs at major airport terminal areas. This is being done to enhance terminal area productivity, that is, aircraft arrival and departure throughput, by using the weather forecasts as part of the Aircraft Vort...

Numerical Simulations of Grassland Fire Behavior from the LANL-FIRETEC and NIST-WFDS Models

Grassland fires on level terrain offer a good basic scenario for test wildland fire behavior models, due to the simplicity and homogeneity of the fuels and terrain. Two physics based models, FIRETEC and WFDS, are briefly described, applied fire spread in grassland fuel, followed by a discussion of the results. It is important to note that both models have undergone appreciable development since the writing of this conference paper in 2005.

Mesoscale model simulation of the meteorological conditions during the 2 June 2002 Double Trouble State Park wildfire

On the morning of 2 June 2002, an abandoned campfire grew into a wildfire in the Double Trouble State Park in east-central New Jersey, USA. The wildfire burned 526 ha (1300 acres) and forced the closure of the Garden State Parkway for several hours due to dense smoke. In addition to the presence of dead and dry fuels due to a late spring frost prior to the wildfire, the meteorological conditions at the time of the wildfire were conducive to erratic fire behaviour and rapid fire growth. Observations indicate the occurrence of a substantial drop in relative humidity at the surface accompanied by an increase in wind speed in the vicinity of the wildfire during the late morning and early afternoon of 2 June. The surface drying and increase in wind speed are hypothesised to result from the downward transport of dry, high-momentum air from the middle troposphere occurring in conjunction with a deepening mixed layer. This hypothesis is addressed using a high-resolution mesoscale model simulation to document the structure and evolution of the planetary boundary layer and lower-tropospheric features associated with the arrival of dry, high-momentum air at the surface coincident with the sudden and dramatic growth of the wildfire.

Regimes of Dry Convection above Wildfires: Idealized Numerical Simulations and Dimensional Analysis*

Abstract Wildfires are capable of inducing atmospheric circulations that result predominantly from large temperature anomalies produced by the fire. The fundamental dynamics through which a forest fire and the atmosphere interact to yield different convective regimes is still not well understood. This study uses the Advanced Regional Prediction System (ARPS) model to investigate the impact of the environmental (i.e., far upstream, undisturbed by fire) wind profile on dry convection above a prescribed heat source of an intensity and spatial scale comparable to a wildfire. Dimensional analysis of the fire–atmosphere problem provides two relevant parameters: a surface buoyancy parameter that addresses the amount of heat a parcel of air receives in transiting above the fire and an advection parameter that addresses the degree to which the environmental wind advects updrafts away from the fire. Two-dimensional simulations are performed in which the upstream surface wind speed and mixed layer mean wind speed ar...

Synoptic-Scale and Mesoscale Environments Conducive to Forest Fires during the October 2003 Extreme Fire Event in Southern California

This study has employed both observational data and numerical simulation results to diagnose the synoptic-scale and mesoscale environments conducive to forest fires during the October 2003 extreme fire event in southern California. A three-stage process is proposed to illustrate the coupling of the synoptic-scale forcing that is evident from the observations, specifically the high pressure ridge and the upper-level jet streak, which leads to meso-α-scale subsidence in its exit region, and the mesoscale forcing that is simulated by the numerical model, specifically the wave breaking and turbulence as well as the wave-induced critical level, which leads to severe downslope (Santa Ana) winds. Two surges of dry air were found to reach the surface in southern California as revealed in the numerical simulation. The first dry air surge arrived as a result of moisture divergence and isallobaric adjustments behind a surface cold front. The second dry air surge reached southern California as the meso-α- to meso-β-scale subsidence and the wave-induced critical level over the coastal ranges phased to transport the dry air from the upper-level jet streak exit region toward the surface and mix the dry air down to the planetary boundary layer on the lee side of the coastal ranges in southern California. The wave-breaking region on the lee side acted as an internal boundary to reflect the mountain wave energy back to the ground and created severe downslope winds through partial resonance with the upward-propagating mountain waves.

A North American regional reanalysis climatology of the Haines Index

A warm-season (May through October) Haines Index climatology is derived using 32-km regional reanalysis temperature and humidity data from 1980 to 2007. We compute lapse rates, dewpoint depressions, Haines Index factors A and B, and values for each of the low-, mid- and high-elevation variants of the Haines Index. Statistical techniques are used to investigate the spatial and temporal variability of the index across North America. The new climatology is compared with a previous climatology derived from 2.5° (~280 km) global reanalysis data. Maps from the two climatologies are found to be very similar for most of North America. The largest differences appear along the eastern coastline and in regions of large elevation gradients, where the orography in the 32-km climatology is better resolved than that of the 2.5° climatology. In coastal areas of eastern North America and where there is steeply sloping terrain, the new climatology can augment the information from the 2.5° climatology to help analyse the performance and interpret the results of the Haines Index in these regions. A linear trend analysis of the total number of high-Haines Index days occurring in each warm season reveals no significant linear trends over the 28-year data period.

Multiscale Simulation of a Prescribed Fire Event in the New Jersey Pine Barrens Using ARPS-CANOPY

Smoke prediction products are one of the tools used by land management personnel for decision making regarding prescribed fires. This study documents the application to a prescribed fire of a smoke prediction system that employs ARPS-CANOPY, a modified version of the Advanced Regional Prediction System (ARPS) model containing a canopy submodel, as the meteorological driver. In this paper, the performance of ARPS-CANOPY in simulating meteorological fields in the vicinity of a low-intensity fire is assessed using flux-tower data collected prior to and during a low-intensity prescribed fire in the New Jersey Pine Barrens in March 2011. A three-dimensional high-resolution plant area density dataset is utilized to define the characteristics of the canopy, and the fire is represented in ARPS-CANOPY as a heat flux to the atmosphere. The standard ARPS model is compared with reanalysis and upper-air data to establish that the model can simulate the observed synoptic-mesoscale and planetary boundary layer features that are salient to this study. ARPS-CANOPY profiles of mean turbulent kinetic energy, wind speed/direction, and temperature exhibit patterns that appear in the flux-tower observations during both the preburn phase of the experiment and the period of time the flux tower experienced perturbed atmospheric conditions due to the impinging fire. Last, the character and source of turbulence in and around the fire line are examined. These results are encouraging for smoke prediction efforts since transport of smoke from low-intensity fires is highly sensitive to the near-surface meteorological conditions and, in particular, turbulent flows.