Search Results

You are looking at 1 - 10 of 21 items for :

  • Author or Editor: David P. Baumhefner x
  • Monthly Weather Review x
  • Refine by Access: All Content x
Clear All Modify Search
David P. Baumhefner

Abstract

A pilot study that evaluates the potential forecast skill of winter 10–30-day time-mean flow from a low-resolution (R15) climate simulation model is presented. The hypothesis tested is that low-resolution climate model forecasts might be as skillful as high-resolution numerical weather prediction model forecasts at extended-range timescales, if the low-frequency evolution is primarily a large-scale process and if the systematic error of the climate model is less detrimental than high-resolution forecast model error.

Eight forecast cases, each containing four ensemble members, are examined and compared to high-resolution forecasts discussed by Miyakoda et al. The systematic error of the climate model is examined and then used to reduce the forecast error in an a posteriors fashion. The operational utility of these climate model forecasts is also assessed.

The low-resolution climate model is quite successful in duplicating the skill of the high-resolution forecast model. If the forecast systematic component of error evaluated from the same eight cases is removed, the climate model forecasts improve in a comparable fashion to the high-resolution results. When information from the low-resolution climate simulation is used to estimate the forecast systematic error, the improvement in skill is less successful. These results show that a low-resolution climate model can be a viable tool for numerical extended-range forecasting and imply that large ensembles can be integrated for the same cost as higher-resolution model integrations.

Full access
DAVID P. BAUMHEFNER

Abstract

A number of global real-data numerical forecasts have been calculated using the two-layer NCAR (National Center for Atmospheric Research) general circulation model. The purpose of these experiments was threefold: 1) to evaluate the model's ability to predict the real atmosphere, 2) to develop a global forecasting model which will make use of the data obtained by the proposed GARP (Global Atmospheric Research Program), and 3) to help determine some of the internal, empirical constants of the model. In order to evaluate the accuracy of the predictions, several “skill scores” were calculated from the forecasted and observed variables. A by-product of this research was the testing of five different types of data-initialization schemes. Over 50, 4-day forecasts have been run, in which the initialization schemes and internal constants were varied.

The results from these experiments indicate that the present two-layer model is capable of forecasting the real atmosphere with reasonable skill out to 2 days at the surface and 4 days in the middle troposphere. The best initialization scheme for this particular model, thus far, appears to be the complete balance equation. However, several of the simplified initialization techniques are very close in terms of forecasting skill.

Full access
DAVID P. BAUMHEFNER

Abstract

A diagnostic, nonlinear balanced model is applied in order to describe numerically the three dimensional structure of the tropical atmosphere. Several comparisons and experiments are made to gain insight into the physical processes and reliability of the model. These include different types of stream functions and temperature analyses, and the addition of surface friction and latent heat. A comparison between the kinematic vertical motion and the final numerical result is performed.

Obtained by using the complete form of the balance model, the derived vertical motion for August 12–14, 1961, in the Caribbean is presented in the form of cross sections. The vertical velocity fields, which are displayed in partitioned form, are compared with the analyzed moisture distribution. The validity of the computed vertical motion is discussed along with its possible influence on the tropical weather.

Full access
David P. Baumhefner

Abstract

No abstract available.

Full access
Stephen J. Colucci
and
David P. Baumhefner

Abstract

The forecastability of a blocking episode during January 1985 over Europe and the eastern Atlantic Ocean is studied with forecast ensembles. Ten-member ensembles from version CCM2 (at T42 resolution) of the Community Climate Model of the National Center for Atmospheric Research are initialized at various lead times prior to the analyzed block onset and run out to 14 days. Particular attention is focused on the ensemble initialized five days prior to block onset since, of all the ensembles, this one was characterized by the greatest variability concerning the block-onset prediction. Two of the 10 members of this particular ensemble predicted a transition from unblocked to blocked flow over the Atlantic–Europe half of the Northern Hemisphere during the 14-day forecast range, but not without error; details regarding the timing and/or location of the block were misforecast. A comparison of these ensemble members, plus one other that did not predict a transition to blocking, with the corresponding analyses revealed that the block forecast errors could be traced to a model failure to predict the anomalously weakened midtropospheric planetary-scale geostrophic westerlies analyzed upstream of and prior to the block onset. The forecast error appeared to be attributable to a model bias toward an erroneously southward displacement of the midtropospheric zonal jet over Europe and the eastern Atlantic Ocean. On the other hand, the interaction between the planetary-scale flow and synoptic-scale activity, as measured by the midtropospheric advection of synoptic-scale quasigeostrophic potential vorticity by the planetary-scale geostrophic wind, was well predicted by the ensemble members, but perhaps fortuitously. The results demonstrate that the forecast ensemble was able to overcome the influence of the systematic error by indicating the possibility of a transition to blocked flow over the domain and within the forecast range.

Full access
Steven L. Mullen
and
David P. Baumhefner

Abstract

The impact of initial condition uncertainty on short-range (0–48 h) simulations of explosive surface cyclogenesis is examined within the context of a perfect model environment. Eleven Monte Carlo simulations are performed on 10 cases of rapid oceanic cyclogenesis that occurred in a long-term, perpetual January integration of a global spectral model. The perturbations used to represent the initial condition error have a magnitude and spatial decomposition that closely matches estimates of global analysis error.

Large variability characterizes the error growth rates, both among the individual Monte Carlo simulations and among the case-average values. Some individual simulations display error growth doubling times as fast as approximately 12 h during the 24-h period of most rapid intensification, while others exhibit virtually no error growth. The variability is also reflected in the wide 90% confidence bounds for many surface weather elements such as the cyclone position and central pressure. However, no statistically significant differences are found between the initial states leading to large simulation errors and those leading to negligible errors. These results attest to the importance of initial condition uncertainty as the major cause of forecast variability and indicate a strong sensitivity to subtle differences in initial perturbation location and structure.

The effect that simple ensemble averaging has on reducing uncertainty is discussed. Averaging a 16-member ensemble decreases the random component of the initial data error by 80%–90% and the 90% confidence bounds by 70%–80% for cyclone position, central pressure, and 12-h pressure change. It is hypothesized that ensemble forecasting could benefit the utility of short-range forecasts for many weather elements of operational interest and conclude that research efforts should be directed at examining its effectiveness in an operational setting.

Full access
Byron A. Boville
and
David P. Baumhefner

Abstract

The error growth associated with the usual upper boundary formulation (and location) in numerical weather prediction (NWP) and general circulation models (GCMs) is studied. The experimental strategy is to look at the growth of differences between the equilibrated climate simulation of a control simulation and three ensembles of 30 day simulations branching off of the control. The control simulation is a seasonal integration of a medium horizontal-resolution GCM with 30 levels extending from the surface to the upper mesosphere. Each ensemble consists of nine cases with initial conditions taken at 10-day intervals from the control. The main experiment uses a model identical to that of the control except that only the bottom 15 levels (below 10 mb) are retained. The additional experiments either perturb the initial conditions or alter the physical parameterizations (horizontal diffusion) to obtain information on the significance of the results of the main experiment.

It is found that random error growth rate in the troposphere for the case of the altered upper boundary is slightly faster than that for initial-condition uncertainty alone. However, this is not likely to make a significant impact in operational forecast models at present because the uncertainty in the initial conditions is so large.

Systematic errors in the troposphere due to the upper boundary are relatively small prior to day 20. However, the ten day mean errors from days 20–30 are about the same magnitude as the anomalies that extended range forecasts are attempting to predict. The upper boundary treatment is likely to cause significant systematic errors in such forecasts. In the lower stratosphere, the errors are substantial within the first few days, particularly in the winter hemisphere.

Full access
Steven L. Mullen
and
David P. Baumhefner

Abstract

The impact of initial condition uncertainty on short-range (up to 48 h) forecasts of large-scale explosive cyclogenesis is examined. Predictability experiments are conducted on 11 cases of rapid oceanic cyclogenesis that occurred in a long-term, perpetual January integration of a global, high-resolution, spectral model. Results are derived from the 11-case ensemble average. The perturbation used to represent the initial condition error in this study has a magnitude and spatial distribution that closely matches estimates of global analysis error. Results from the predictability experiments are compared to a set of physics sensitivity experiments which are used to represent an estimate of a “typical” modeling, error.

Compared to the control simulations, the inclusion of initial error produces a composite cyclone with maximum deepening rate that is slightly reduced and a 24 h period of most rapid deepening that is somewhat delayed. The absolute position error in the surface cyclone is approximately 100 km the first +36 h of the forecast then abruptly increases to 300 km by +48 h. We estimate that, on the average, the forecast error due to initial condition uncertainty is as large as that due to the modeling error associated with today's best operational models, whereas five years ago modeling error was much more important.

The relative importance of initial condition uncertainty for explosive cyclogenesis is compared to that for the entire midlatitude flow in general. Error growth rates in an explosive cyclogenetic environment are 50% greater in the upper troposphere (500 mb and above) and two times faster near the surface (850 mb and below). The rapid growth rates indicate that short-range forecasts of explosive cyclogenesis are much wore sensitive to initial error than those for ordinary flows.

The case-to-case variability exhibited by the 11-member ensemble is examined. Noteworthy departure from the aggregate results are evident In individual cases, initial condition error can lead to short-range forecast differences which can be either greater than those due to a typical modeling error or much less. This variability implies a strong sensitivity to initial condition perturbation location and structure.

Full access
Steven L. Mullen
and
David P. Baumhefner

Abstract

The relative importance of different parameterized physical process and baroclinic dynamics in numerical simulations of explosive oceanic cyclogenesis is examined. The numerical simulations are derived from a global spectral model having nine vertical levels and a rhomboidal 31 truncation. Eleven cases of rapid cyclogenesis over the North Pacific Ocean that occurred in a 150-day simulation of perpetual January conditions are used as initial conditions for model sensitivity experiments. Statistical techniques based on predictability theory are employed to estimate the relative importance of the sensitivity experiments.

Results from the simulation comparisons indicate that the total diabatic heating accounts for about one-half of the cyclone's deepening rate, with baroclinic dynamics accounting for the remaining part. The absence of diabatic heating also leads to a systematic error in the position of the cyclone. Surface fluxes of sensible heat are responsible for about one-half of the deepening rate due to diabatic processes, while latent heating due to grid-scale resolvable precipitation in conjunction with surface latent heat flux accounts for most of the remaining half. An increase in the surface drag over the ocean to its larger land value was found to be of comparable importance to both surface sensible heat flux and latent beat release, but was only half as important as the total diabatic heating. These changes in the model were judged to produce highly significant response especially at low levels. The addition of radiative heating, the substitution of a Kuo-type cumulus parameterization scheme for the model's default moist convective adjustment scheme, and a factor of 4 increase in the horizontal diffusion did not produce significant responses.

The case-to-case variability exhibited by the 11-member ensemble is examined. The potential danger in attempting to generalize results from a single case of explosive cyclogenesis as being representative of those for the ensemble average is illustrated.

Full access
Thomas W. Bettge
and
David P. Baumhefner

Abstract

The total and systematic errors in the 500 mb geopotential height forecasts from the NMC grid-point and spectral operational models are compared and contrasted for two recent winters. The spectral model is shown to be an improvement in the forecasts through a more skillful prediction of the planetary-scale (zonal wavenumbers 1-2) quasi-stationary wave amplitudes, and through the elimination of the grid-point model's large systematic error at low latitudes.

In agreement with estimates from related studies, the systematic error in the NMC spectral model accounts for 15-20% of the total error variance. Approximately one-half of the total systematic error resides in the planetary scales.

Full access