Ronald Gelaro

The North Pacific Experiment (NORPEX-98): Targeted Observations for Improved North American Weather Forecasts

Abstract The objectives and preliminary results of an interagency field program, the North Pacific Experiment (NORPEX), which took place between 14 January and 27 February 1998, are described. NORPEX represents an effort to directly address the issue of observational sparsity over the North Pacific basin, which is a major contributing factor in short-range (less than 4 days) forecast failures for land-falling Pacific winter-season storms that affect the United States, Canada, and Mexico. The special observations collected in NORPEX include approximately 700 targeted tropospheric soundings of temperature, wind, and moisture from Global Positioning System (GPS) dropsondes obtained in 38 storm reconnaissance missions using aircraft based primarily in Hawaii and Alaska. In addition, wind data were provided every 6 h over the entire North Pacific during NORPEX, using advanced and experimental techniques to extract information from multispectral geostationary satellite imagery. Preliminary results of NORPEX dat...

Observation Sensitivity Calculations Using the Adjoint of the Gridpoint Statistical Interpolation (GSI) Analysis System

The adjoint of a data assimilation system provides an efficient way of estimating sensitivities of analysis or forecast measures with respect to observations. The NASA Global Modeling and Assimilation Office (GMAO) has developed an exact adjoint of the Gridpoint Statistical Interpolation (GSI) analysis scheme developed at the National Centers for Environmental Prediction (NCEP). The development approach is unique in that the adjoint is derived from a line-by-line tangent linear version of the GSI. Availability of the tangent linear scheme provides an explicit means of assessing not only the fidelity of the adjoint, but also the effects of nonlinear processes in the GSI itself. In this paper, the development of the tangent linear and adjoint versions of the GSI are discussed and observation sensitivity results for a near-operational version of the system are shown. Results indicate that the GSI adjoint provides accurate assessments of the sensitivities with respect to observations of wind, temperature, satellite radiances, and, to a lesser extent, moisture. Sensitivities with respect to ozone observations are quite linear for the ozone fields themselves, but highly nonlinear for other variables. The sensitivity information provided by the adjoint is used to estimate the contribution, or impact, of various observing systems on locally defined response functions based on the analyzed increments of temperature and zonal wind. It is shown, for example, that satellite radiances have the largest impact of all observing systems on the temperature increments over the eastern North Pacific, while conventional observations from rawinsondes and aircraft dominate the impact on the zonal wind increments over the continental United States. The observation impact calculations also provide an additional means of validating the observation sensitivities produced by the GSI adjoint.

Initial Condition Sensitivity and Error Growth in Forecasts of the 25 January 2000 East Coast Snowstorm

Abstract Short- and medium-range (24–96-h) forecasts of the January 2000 U.S. east coast cyclone and associated snowstorm are examined using the U.S. Navy global forecast model and adjoint system. Attention is given to errors on the synoptic scale, including forecast position and central pressure of the cyclone at the verification time of 1200 UTC 25 January 2000. There is a substantial loss of predictive skill in the 72- and 96-h forecasts, while the 24- and 48-h forecasts capture the synoptic-scale features of the cyclone development with moderate errors. Sensitivity information from the adjoint model suggests that the initial conditions for the 72-h forecast starting at 1200 UTC 22 January 2000 contained relatively small, but critical, errors in upper-air wind and temperature over a large upstream area, including part of the eastern Pacific and “well observed” areas of western and central North America. The rapid growth of these initial errors in a highly unstable flow regime (large singular-vector gro...

The THORPEX Observation Impact Intercomparison Experiment

Abstract An experiment is being conducted to directly compare the impact of all assimilated observations on short-range forecast errors in different forecast systems using an adjoint-based technique. The technique allows detailed comparison of observation impacts in terms of data type, location, satellite sounding channel, or other relevant attributes. This paper describes results for a “baseline” set of observations assimilated by three forecast systems for the month of January 2007. Despite differences in the assimilation algorithms and forecast models, the impacts of the major observation types are similar in each forecast system in a global sense. However, regional details and other aspects of the results can differ substantially. Large forecast error reductions are provided by satellite radiances, geostationary satellite winds, radiosondes, and commercial aircraft. Other observation types provide smaller impacts individually, but their combined impact is significant. Only a small majority of the tota...

Singular Vector Calculations with an Analysis Error Variance Metric

Abstract Singular vectors of the navys global forecast model are calculated using an initial norm consistent with an estimate of analysis error variance provided by the Naval Research Laboratorys (NRL) Atmospheric Variational Data Assimilation System (NAVDAS). The variance estimate is based on a decomposition of the block diagonal preconditioner for the conjugate-gradient descent algorithm used in NAVDAS. Because the inverse square root of the operator that defines the variance norm is readily computed, the leading singular vectors are obtained using a standard Lanczos algorithm, as with diagonal norms such as total energy. The resulting singular vectors are consistent with the expected distribution of analysis errors. Compared with singular vectors based on a total energy norm, the variance singular vectors at initial time have less amplitude over well-observed areas, as well as greater amplitude in the middle and upper troposphere. The variance singular vectors are in some ways similar to the full cov...

Examination of various-order adjoint-based approximations of observation impact

The necessity, and potential implications, of considering higher-than-first-order approximations of the impact of observations on numerical weather forecasts are investigated. In particular, clarification is sought on issues raised by ERRICO (2007) concerning the interpretation of an adjoint-based measure of observation impact developed by LANGLAND and BAKER (2004). Various-order adjoint-based approximations of observation impact are examined in this context using adjoint versions of the NASA Goddard Earth Observing System (GEOS) atmospheric data assimilation system. Attention is given to examining the effects of nonlinearity on partial sums used to estimate the impact of particular subsets of observations, and especially whether contributions to these sums from observations outside a particular subset might cloud their interpretation. It is shown that higher-than-first-order accuracy (in terms of innovations) is required to capture adequately the impact of observations measured by the change in an energy-based metric of forecast error. When accounting for the impact of the entire set of observations, the error of the first-order approximation is roughly four times larger than that of the second- or third-order approximations. Just as importantly, no substantial evidence is found to suggest that nonlinear approximations of the impacts of selected subsets of observations, in this case corresponding to specific satellite and conventional observing systems assimilated in GEOS-5, are altered in any discernible way by cross terms with different observation types. An explanation for this is offered based on the relative contributions from linear and nonlinear terms in these approximations.

Transient and asymptotic perturbation growth in a simple model

The relationship between asymptotic and finite-interval instabilities in nonlinear, time-dependent flows is examined in the context of a quasi-geostrophic model. For a chosen interval and metric, perturbation growth is related to the singular vectors (SVs) of the linear propagator, while long-term or asymptotic growth is determined by the leading Lyapunov vector (LV), which is independent of metric and grows at the mean rate of the leading Lyapunov exponent. It is shown that the growth rates of the leading LVs vary significantly about their mean values over periods of a few days. For the leading LV, episodes of greater (or lesser) growth correspond to significant variations in vertical structure, and are highly correlated with its projection onto the leading SVs optimized for short (e.g. 24-hour) intervals. The LV exhibits maximum growth over east Asia and the Pacific, where its projection onto rapidly growing SVs in the vicinity of the Pacific storm track is greatest. For a given 24-hour interval, the 30 leading SVs at initial time account for only a few per cent of the total variance of the LV, but account for most of its growth. Filtering these leading SV components from the evolving LV structure over successive intervals reduces its mean (asymptotic) growth rate dramatically in a piecewise continuous sense. The results make clear the importance of transient growth in maintaining the positive mean growth rates of the leading LVs, and in determining the asymptotic stability properties of time-dependent flows. Copyright

Cloud Coverage in the Joint OSSE Nature Run

A successful observing system simulation experiment (OSSE) is fundamentally dependent on the simulation of the global observing system used in the experiment. In many applications, a free-running numerical model simulation, called a nature run, is used as the meteorological truth from which the observations are simulated. To accurately and realistically simulate observations from any nature run, the simulated observations must contain realistic cloud effects representative of the meteorological regimes being sampled. This study provides a validationof the clouds in the Joint OSSE nature rungeneratedat ECMWF. Presented is the methodology used to validate the nature run cloud fraction fields with seasonally aggregated combined CloudSat/Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud geometric profile retrievals and the Wisconsin High Resolution Infrared Radiation Sounder (HIRS) cloud climatology. The results show that the Joint OSSE nature run has a correct vertical distribution of clouds but lacks globally in cloud amount compared to the validation data. The differences between the nature run and validation datasets shown in this study should be considered and accounted for in the generation of the global observing system for use in full OSSE studies.

A Determination of Balanced Normal Modes for Two Models

Abstract Two versions of the NOGAPS model are used to generate normal-mode balanced datasets. The various forces that act on gravitational modes are then examined to determine the modes whose coefficient time tendencies are significantly smaller than terms which force them. Those modes are said to be balanced. Results for three different equivalent depths are presented. They indicate that only modes with natural periods shorter than one day appear balanced. That balance is adiabatic. These results agree with those reported by Errico for the NCAR CCM.

Observed and simulated Northern Hemisphere intraseasonal circulation anomalies and the influence of model bias

Abstract The ability of an atmospheric general circulation model to simulate the observed primary modes of intraseasonal variability in the Northern Hemisphere upper-tropospheric winds during boreal winter is examined. The model used is the Navy Operational Global Atmospheric Prediction System. The authors examine differences between the observed and modeled modes of variability in the context of various model deficiencies, where the observed modes are derived from the European Centre for Medium-Range Weather Forecasts analyses. Rotated empirical orthogonal function analysis is used to determine the primary modes of variability in the Pacific and Atlantic regions. EOFs are computed for both the zonal and meridional wind components. Time-lagged composite analysis is used to examine the temporal evolution of these modes, as well as their relationship to tropical convection. Wave activity flux vectors are used to examine further the characteristics of these intraseasonal modes and their relationship to tropi...