John W. Nielsen-Gammon

Evaluation of Three Planetary Boundary Layer Schemes in the WRF Model

Abstract Accurate depiction of meteorological conditions, especially within the planetary boundary layer (PBL), is important for air pollution modeling, and PBL parameterization schemes play a critical role in simulating the boundary layer. This study examines the sensitivity of the performance of the Weather Research and Forecast (WRF) model to the use of three different PBL schemes [Mellor–Yamada–Janjic (MYJ), Yonsei University (YSU), and the asymmetric convective model, version 2 (ACM2)]. Comparison of surface and boundary layer observations with 92 sets of daily, 36-h high-resolution WRF simulations with different schemes over Texas in July–September 2005 shows that the simulations with the YSU and ACM2 schemes give much less bias than with the MYJ scheme. Simulations with the MYJ scheme, the only local closure scheme of the three, produced the coldest and moistest biases in the PBL. The differences among the schemes are found to be due predominantly to differences in vertical mixing strength and entr...

Enhancement of cloud-to-ground lightning over Houston, Texas

Cloud-to-ground lightning flash data have been analyzed for the twelve-year period 1989–2000, for a geographical area centered on Houston, Texas. Of the 1.6 million cloud-to-ground flashes in this area of study, approximately 752,000 flashes occurred in the summer months of June, July, and August, and 119,000 flashes in the months of December, January, and February. The highest flash densities, greater than 4 flashes km−2 in the summer and 0.7 flashes/km−2 in the winter, are near the urban areas of Houston. We suggest that the elevated flash densities could result from several factors, including, 1) the convergence due to the urban heat island effect, and 2) the increasing levels of air pollution from anthropogenic sources producing numerous small droplets and thereby suppressing mean droplet size. The latter effect would enable more cloud water to reach the mixed phase region where it is involved in the formation of precipitation and the separation of electric charge, leading to an enhancement of lightning.

Anatomy of an Extreme Event

AbstractThe record-setting 2011 Texas drought/heat wave is examined to identify physical processes, underlying causes, and predictability. October 2010–September 2011 was Texas’s driest 12-month period on record. While the summer 2011 heat wave magnitude (2.9°C above the 1981–2010 mean) was larger than the previous record, events of similar or larger magnitude appear in preindustrial control runs of climate models. The principal factor contributing to the heat wave magnitude was a severe rainfall deficit during antecedent and concurrent seasons related to anomalous sea surface temperatures (SSTs) that included a La Nina event. Virtually all the precipitation deficits appear to be due to natural variability. About 0.6°C warming relative to the 1981–2010 mean is estimated to be attributable to human-induced climate change, with warming observed mainly in the past decade. Quantitative attribution of the overall human-induced contribution since preindustrial times is complicated by the lack of a detected cent...

A Bad Air Day in Houston

Abstract A case study from the Texas Air Quality Study 2000 field campaign illustrates the complex interaction of meteorological and chemical processes that produced a high-pollution event in the Houston area on 30 August 2000. High 1-h ozone concentrations of nearly 200 ppb were measured near the surface, and vertical profile data from an airborne differential-absorption lidar (DIAL) system showed that these high-ozone concentrations penetrated to heights approaching 2 km into the atmospheric boundary layer. This deep layer of pollution was transported over the surrounding countryside at night, where it then mixed out the next day to become part of the rural background levels. These background levels thus increased during the course of the multiday pollution episode. The case study illustrates many processes that numerical forecast models must faithfully represent to produce accurate quantitative predictions of peak pollutant concentrations in coastal locations such as Houston. Such accurate predictions ...

Using Tropopause Maps to Diagnose Midlatitude Weather Systems

The use of potential vorticity (PV) allows the efficient description of the dynamics of nearly balanced atmospheric flow phenomena, but the distribution of PV must be simply represented for ease in interpretation. Representations of PV on isentropic or isobaric surfaces can be cumbersome, as analyses of several surfaces spanning the troposphere must be constructed to fully apprehend the complete PV distribution. Following a brief review of the relationship between PV and nearly balanced flows, it is demonstrated that the tropospheric PV has a simple distribution, and as a consequence, an analysis of potential temperature along the dynamic tropopause (here defined as a surface of constant PV) allows for a simple representation of the upper-tropospheric and lower-stratospheric PV. The construction and interpretation of these tropopause maps, which may be termed ‘‘isertelic’’ analyses of potential temperature, are described. In addition, techniques to construct dynamical representations of the lower-tropospheric PV and near-surface potential temperature, which complement these isertelic analyses, are also suggested. Case studies are presented to illustrate the utility of these techniques in diagnosing phenomena such as cyclogenesis, tropopause folds, the formation of an upper trough, and the effects of latent heat release on the upper and lower troposphere.

Ensemble-Based Simultaneous State and Parameter Estimation in a Two-Dimensional Sea-Breeze Model

The performance of the ensemble Kalman filter (EnKF) in forced, dissipative flow under imperfectmodel conditions is investigated through simultaneous state and parameter estimation where the source of model error is the uncertainty in the model parameters. A two-dimensional, nonlinear, hydrostatic, nonrotating, and incompressible sea-breeze model is used for this purpose with buoyancy and vorticity as the prognostic variables and a square root filter with covariance localization is employed. To control filter divergence caused by the narrowing of parameter variance, a “conditional covariance inflation” method is devised. Up to six model parameters are subjected to estimation attempts in various experiments. While the estimation of single imperfect parameters results in error of model variables that is indistinguishable from the respective perfect-parameter cases, increasing the number of estimated parameters to six inevitably leads to a decline in the level of improvement achieved by parameter estimation. However, the overall EnKF performance in terms of the error statistics is still superior to the situation where there is parameter error but no parameter estimation is performed. In fact, compared with that situation, the simultaneous estimation of six parameters reduces the average error in buoyancy and vorticity by 40% and 46%, respectively. Several aspects of the filter configuration (e.g., observation location, ensemble size, radius of influence, and parameter variance limit) are found to considerably influence the identifiability of the parameters. The parameter-dependent response to such factors implies strong nonlinearity between the parameters and the state of the model and suggests that a straightforward spatial covariance localization does not necessarily produce optimality.

Mesoscale Predictability of an Extreme Warm-Season Precipitation Event

Abstract A mesoscale model is used to investigate the mesoscale predictability of an extreme precipitation event over central Texas on 29 June 2002 that lasted through 7 July 2002. Both the intrinsic and practical aspects of warm-season predictability, especially quantitative precipitation forecasts up to 36 h, were explored through experiments with various grid resolutions, initial and boundary conditions, physics parameterization schemes, and the addition of small-scale, small-amplitude random initial errors. It is found that the high-resolution convective-resolving simulations (with grid spacing down to 3.3 km) do not produce the best simulation or forecast. It was also found that both the realistic initial condition uncertainty and model errors can result in large forecast errors for this warm-season flooding event. Thus, practically, there is room to gain higher forecast accuracy through improving the initial analysis with better data assimilation techniques or enhanced observations, and through impr...

Ensemble-based simultaneous state and parameter estimation with MM5

] The performance of the ensemble Kalman filter(EnKF) under imperfect model conditions is investigatedthrough simultaneous state and parameter estimation for anumerical weather prediction model of operationalcomplexity (MM5). The source of model error is assumedto be the uncertainty in the vertical eddy mixing coefficient.Assimilations are performed with a 12-hour interval withsimulated sounding and surface observations of horizontalwinds and temperature. The mean estimated parametervalue nicely converges to the true value within a satisfactorylevel of variability due to sufficient model sensitivity toparameter uncertainty and detectable (relative to ensemblesampling noise) correlation signal between the parameterand observed variables.

Documentation of Uncertainties and Biases Associated with Surface Temperature Measurement Sites for Climate Change Assessment

The objective of this research is to determine whether poorly sited long-term surface temperature monitoring sites have been adjusted in order to provide spatially representative independent data for use in regional and global surface temperature analyses. We present detailed analyses that demonstrate the lack of independence of the poorly sited data when they are adjusted using the homogenization procedures employed in past studies, as well as discuss the uncertainties associated with undocumented station moves. We use simulation and mathematics to determine the effect of trend on station adjustments and the associated effect of trend in the reference series on the trend of the adjusted station. We also compare data before and after adjustment to the reanalysis data, and we discuss the effect of land use changes on the uncertainty of measurement. A major conclusion of our analysis is that there are large uncertainties associated with the surface temperature trends from the poorly sited stations. Moreover...

Piecewise Tendency Diagnosis of Dynamical Processes Governing the Development of an Upper-Tropospheric Mobile Trough

Abstract The intensification and evolution of midlatitude upper-tropospheric mobile troughs may be viewed in terms of the isentropic advection and deformation of the tropopause potential vorticity gradient. The potential vorticity viewpoint allows one to qualitatively assess observed events in the context of existing theories of mobile trough genesis, such as baroclinic instability or downstream development. In order to quantitatively determine the role of distinct dynamical process, the method of piecewise tendency diagnosis, or PTD, is developed. PTD is an extension of piecewise potential vorticity inversion applied to height tendencies, with the forcing terms in the quasigeostrophic height tendency equation partitioned into potential vorticity advection associated with distinct dynamical processes. A particular case of mobile trough genesis, which occurred during 1–4 December 1980 over North America is diagnosed using PTD. Although about 20% of the intensification of the trough was due to superposition...