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R. Atlas

Abstract

A study of the evolution of sounding data impact in the high-resolution GLAS model forecasts from 19 February 1976 has been conducted. The significant prognostic differences which develop in this case are shown to be traceable to specific initial state differences which resulted from the assimilation of satellite-derived temperature soundings.

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N. Wolfson, R. Atlas, and Y. C. Sud

Abstract

A series of numerical forecast experiments has been conducted with the Goddard Laboratory for Atmospheres (GLA) fourth-order general circulation model in order to study the role of (i) sea-surface temperature (SST) anomalies in the North Pacific, (ii) soil moisture anomalies over the continental United States, as derived from observations of precipitation and surface temperature, and (iii) solar radiational forcing in the maintenance and breakdown of the severe heat wave over the United States in the summer of 1980.

Results from these experiments show opposite effects of the SST and soil moisture anomalies on the model's medium-range (ten-day) simulations of the maintenance of the heat wave. The lower than normal soil moisture over the United States during the summer of 1980 resulted in reduced surface evaporation, higher ground temperature, increased sensible heat flux from ground to air, higher surface temperature, lower sea-level pressure and higher 500 mb height over much of the Great Plains in the model forecasts. In contrast, the SST anomalies in the North Pacific during the same period resulted in an enhanced northerly flow of cooler and dryer air, increased evaporation, decreased ground and air temperature and reduced 500-mb heights over the Great Plains. These results suggest that once established, soil moisture deficits contribute to maintaining warm, dry conditions. Although long-term effects of North Pacific SST anomalies may be to create or enhance the heat wave, ten-day simulations showed that such anomalies contributed to lower temperatures over shorter time scales.

A limited number of experiments, with modified solar radiational forcing, showed a dramatic weakening of the heat wave pattern in the model forecasts and indicated that the interaction of changing solar declination with the prevailing synoptic situation was probably responsible for the breakdown of the heat wave in September 1980.

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M. Ghil, M. Halem and R. Atlas

Abstract

Methods are derived for the time-continuous four-dimensional assimilation of satellite sounding temperatures. The methods presented include time-continuous versions of direct insertion, successive correction and statistical linear regression. They are applied to temperature sounding data obtained from radiance measurements taken by instruments aboard the polar-orbiting satellites NOAA 4 and Nimbus 6. The data were collected during the U.S. Data System Test in January-March 1976.

A comprehensive series of experiments was performed to study the effects of using various amounts of satellite data and differing methods of assimilation. The experiments included the assimilation of data from the NOAA 4 satellite only, from Nimbus 6 only, and of data from both satellites combined. Other experiments involved variations in the application of our time-continuous statistical assimilation methods and of asynoptic successive correction methods. Intermittent assimilation of the sounding data was also tested, and its results compared with those of time-continuous assimilation.

Atmospheric states determined in the assimilation experiments served as initial states for a sequence of evenly spaced 3-day numerical weather forecasts corresponding to each experiment. The effects of the satellite data were evaluated according to the following criteria: 1) differences between the initial states produced with and without utilization of satellite data, 2) differences between numerical predictions made from these initial states, and. 3) differences in local weather forecasts resulting from the large-scale numerical predictions.

Initial-state differences were evaluated in terms of magnitude and location of large-scale differences between meteorological fields. Numerical prediction differences were evaluated in terms of SI skill scores and rms errors, as well as by synoptic case studies. An automated forecasting model (AFM) based on quasi-geostrophic theory and on subjective forecasting principles was developed to facilitate the objective evaluation of differences produced in local weather forecasts, especially precipitation forecasts.

These studies suggest the following conclusions: 1) satellite-derived temperature data can have a modest, but statistically significant positive impact on numerical weather prediction in the 2-3 day range; 2) the impact is highly sensitive to the quantity of data available, and increases with data quantity; and 3) the method used to assimilate the satellite data can influence appreciably the magnitude of the impact obtained for the same data.

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R. Atlas, M. Ghil, and M. Halem

Abstract

No abstract available.

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R. Atlas, M. Ghil, and M. Halem

Abstract

An experiment was performed to study the effect of increased model resolution on satellite sounding data impact. Assimilation cycles were carried out with data from 0000 GMT 29 January to 0300 GMT 21 February 1976, using coarse- and fine-resolution versions of the GLAS second-order general circulation model (GCM). For each model resolution, an assimilation cycle was performed using both conventional and experimental data, which included temperature soundings from the NOAA-4 and Nimbus-6 satellites. A second cycle was run using the same data but excluding the satellite-derived temperature soundings.

The objective analyses produced by the assimilation cycles were used as initial states for a series of evenly spaced 72 h numerical weather forecasts. Eleven forecasts with the same resolution in the forecast model as in the data assimilation were performed at 48 h intervals for each assimilation. Additional forecasts were made with the higher resolution forecast model from the lower resolution assimilation cycle and vice versa. Initial state differences were evaluated in terms of the magnitude, location and structure of large-scale differences between meteorological fields. Numerical prediction differences were evaluated by means of objective scores and subjective comparisons.

Objective scores show a substantially larger beneficial impact of the sounding data at 48 and 60 h with the higher resolution version of the model. Subjective evaluation also revealed a larger positive impact of satellite sounding data with the higher resolution model.

This study has two important limitations: it was carried out with two versions of one model, the GLAS GCM, and the number of forecast cases analyzed is small. Within these limitations, our results indicate that model improvement enhances the impact of satellite data.

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J. M. Vergin, D. R. Johnson, and R. Atlas

Abstract

The results of a quasi-Lagrangian diagnostic study of two 72 h Goddard Laboratory for Atmospheric Sciences (GLAS) model cyclone predictions from 0000 GMT 19 February 1976 are presented and compared with observed results. One model forecast (SAT) was generated from initial conditions which included satellite sounding data, and the other model forecast (NOSAT) was generated from initial conditions that excluded satellite sounding data. Examination of the mass and angular momentum budget statistics for the SAT and NOSAT forecasts reveals substantial differences. The improvement in the SAT forecast is established from the more realistic SAT budget statistics, and results from the modifications of initial atmospheric structure due to satellite information.

The assimilation of satellite data caused modifications of the horizontal mass and eddy angular momentum transports at the zero hour. The assimilation of satellite data resulted in colder temperatures and weaker stabilities in the lower layers of the northwest quadrant of the budget volume, and thus an improved structure of the cold polar air mass over a relatively warm ocean surface. In the southwest quadrant of the budget volume, the SAT assimilation produced an increase in the stability of the middle and lower layers and an increase in temperatures throughout much of the troposphere. These modifications in the temperature structure were the primary reasons for the improved mass and eddy angular momentum transports which contributed to the better SAT forecast for the cyclone event.

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Allen J. Lenzen, Donald R. Johnson, and Robert Atlas

Abstract

Quasi-Lagrangian diagnostics of mass, angular momentum, water vapor, and kinetic energy are evaluated for four different Goddard Laboratory for Atmospheres model simulations of the Queen Elizabeth II storm of 9–11 September 1978 to study the impact of Seasat-A satellite Scatterometer (SASS) winds and horizontal resolution in numerical prediction. In a four-way comparison, the diagnostics investigate the impact of including dealiased SASS winds in the initial conditions of the model and doubling the horizontal resolution on 36 h simulations of the QE II storm. The largest impact on the simulation stemmed from doubling the model's horizontal resolution from 4° × 5° to 2° × 2.5°. The increased resolution resulted in a storm track much closer to that observed, a much deeper surface development, a stronger mass circulation, stronger heating, and stronger increase of angular momentum. The inclusion of SASS data resulted in an approximately 2–3-mb-deeper surface cyclone for both the 2° × 2.5° and 4° × 5° resolution simulations. The inclusion also led to substantial increases in the horizontal mass circulation and heating for the 2° × 2.5° simulation. During the early explosive deepening phase of the cyclone, the inward lateral transport of water vapor in lower layers was larger in the 2° × 2.5° SASS than in the 2° × 2.5° NOSASS (exclusion of SASS surface winds) simulation. During the period of most rapid development, the results from the SASS simulation revealed a larger generation of kinetic energy throughout the troposphere and increased outward transport of kinetic energy in upper layers.

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W. E. Baker, R. Atlas, M. Halem, and J. Susskind

Abstract

In this study we examine the sensitivity of forecast to individual components of the First GARP (Global Atmospheric Research Programme) Global Experiment database as well as to some modifications in the data analysis techniques. Several short assimilation experiments (0000 GMT 18 January 1979 through 0000 21 January) are performed in order to test the effects of each database or analysis change. Forecasts are then generated from the initial conditions provided by these experiments. The 0000 21 January case is chosen for a detailed investigation because or the poor forecast skill obtained earlier over North America for that particular case. Specifically, we conduct experiments to test the sensitivity of forecast skill to: 1) the addition of individual satellite observing system components; 2) temperature data obtained with different satellite retrieval methods; and 3) the method of vertical interpolation between the mandatory pressure analysis levels and the model sigma levels.

For the single case examined, TIROS-N infrared land retrievals produced operationally are found to degrade the forecast, while the use of TIROS-N retrievals produced with a physical inversion method as part of an analysis/forecast cycle results in an improved forecast. The use of oceanic VTPR (Vertical Temperature Profile Radiometer) satellite retrievals also results in an improved forecast over North America. The forecast is also found to be sensitive to the method of vertical interpolation between the mandatory pressure analysis levels and the model sigma levels.

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L. Cucurull, R. Atlas, R. Li, M. J. Mueller, and R. N. Hoffman

Abstract

Experiments with a global observing system simulation experiment (OSSE) system based on the recent 7-km-resolution NASA nature run (G5NR) were conducted to determine the potential value of proposed Global Navigation Satellite System (GNSS) radio occultation (RO) constellations in current operational numerical weather prediction systems. The RO observations were simulated with the geographic sampling expected from the original planned Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) system, with six equatorial (total of ~6000 soundings per day) and six polar (total of ~6000 soundings per day) receiver satellites. The experiments also accounted for the expected improved vertical coverage provided by the Jet Propulsion Laboratory RO receivers on board COSMIC-2. Except that RO observations were simulated and assimilated as refractivities, the 2015 version of the NCEP’s operational data assimilation system was used to run the OSSEs. The OSSEs quantified the impact of RO observations on global weather analyses and forecasts and the impact of adding explicit errors to the simulation of perfect RO profiles. The inclusion or exclusion of explicit errors had small, statistically insignificant impacts on results. The impact of RO observations was found to increase the length of the useful forecasts. In experiments with explicit errors, these increases were found to be 0.6 h in the Northern Hemisphere extratropics (a 0.4% improvement), 5.9 h in the Southern Hemisphere extratropics (a significant 4.0% improvement), and 12.1 h in the tropics (a very substantial 28.4% improvement).

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Lisa R. Bucci, Sharanya J. Majumdar, Robert Atlas, G. David Emmitt, and Steve Greco

Abstract

This study examines how varying wind profile coverages in the tropical cyclone (TC) core, near environment, and broader synoptic environment affects the structure and evolution of a simulated Atlantic Ocean hurricane through data assimilation. Three sets of observing system simulation experiments are examined in this paper. The first experiment establishes a benchmark for the case study specific to the forecast system used by assimilating idealized profiles throughout the parent domain. The second presents how TC analyses and forecasts respond to varying the coverage of swaths produced by polar-orbiting satellites of idealized wind profiles. The final experiment assesses the role of TC inner-core observations by systematically removing them radially from the center. All observations are simulated from a high-resolution regional “nature run” of a hurricane and the tropical atmosphere, assimilating with an ensemble square root Kalman filter and using the Hurricane Weather and Research Forecast regional model. Results compare observation impact with the analyses, domainwide and TC-centric error statistics, and TC structural differences among the experiments. The study concludes that the most accurate TC representation is a result of the assimilation of collocated and uniform thermodynamic and kinematics observations. Intensity forecasts are improved with increased inner-core wind observations, even if the observations are only available once daily. Domainwide root-mean-square errors are significantly reduced when the TC is observed during a period of structural change, such as rapid intensification. The experiments suggest the importance of wind observations and the role of inner-core surveillance when analyzing and forecasting realistic TC structure.

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