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EXECUTIVE COMMITTEE, D. Atlas, C. L. Hosler Jr., D. S. Johnson, W. H. Best Jr., P. M. Austin, E. S. Epstein, K. C. Spengler, and D. F. Landrigan
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Ghassan J. Alaka Jr., Xuejin Zhang, Sundararaman G. Gopalakrishnan, Zhan Zhang, Frank D. Marks, and Robert Atlas

Abstract

Hurricane Joaquin (2015) was characterized by high track forecast uncertainty when it approached the Bahamas from 29 September 2015 to 1 October 2015, with 5-day track predictions ranging from landfall in the United States to east of Bermuda. The source of large track spread in Joaquin forecasts is investigated using an ensemble prediction system (EPS) based on the Hurricane Weather Research and Forecasting (HWRF) Model. For the first time, a high-resolution analysis of an HWRF-based EPS is performed to isolate the factors that control tropical cyclone (TC) track uncertainty. Differences in the synoptic-scale environment, the TC vortex structure, and the TC location are evaluated to understand the source of track forecast uncertainty associated with Joaquin, especially at later lead times when U.S. landfall was possible. EPS members that correctly propagated Joaquin into the central North Atlantic are compared with members that incorrectly predicted U.S. landfall. Joaquin track forecasts were highly dependent on the evolution of the environment, including weak atmospheric steering flow near the Bahamas and three synoptic-scale systems: a trough over North America, a ridge to the northeast of Joaquin, and an upper-tropospheric trough to the east of Joaquin. Differences in the steering flow were associated with perturbations of the synoptic-scale environment at the model initialization time. Ultimately, members that produced a more progressive midlatitude synoptic-scale pattern had reduced track errors. Joaquin track forecast uncertainty was not sensitive to the TC vortex structure or the initial TC position.

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Hui W. Christophersen, Brittany A. Dahl, Jason P. Dunion, Robert F. Rogers, Frank D. Marks, Robert Atlas, and William J. Blackwell

Abstract

As part of the NASA Earth Venture-Instrument program, the Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission, to be launched in January 2022, will deliver unprecedented rapid-update microwave measurements over the tropics that can be used to observe the evolution of the precipitation and thermodynamic structure of tropical cyclones (TCs) at meso- and synoptic scales. TROPICS consists of six CubeSats, each hosting a passive microwave radiometer that provides radiance observations sensitive to atmospheric temperature, water vapor, precipitation, and precipitation-sized ice particles. In this study, the impact of TROPICS all-sky radiances on TC analyses and forecasts is explored through a regional mesoscale observing system simulation experiment (OSSE). The results indicate that the TROPICS all-sky radiances can have positive impacts on TC track and intensity forecasts, particularly when some hydrometeor state variables and other state variables of the data assimilation system that are relevant to cloudy radiance assimilation are updated. The largest impact on the model analyses is seen in the humidity fields, regardless of whether or not there are radiances assimilated from other satellites. TROPICS radiances demonstrate large impact on TC analyses and forecasts when other satellite radiances are absent. The assimilation of the all-sky TROPICS radiances without default radiances leads to a consistent improvement in the low- and midtropospheric temperature and wind forecasts throughout the 5-day forecasts, but only up to 36-h lead time in the humidity forecasts at all pressure levels. This study illustrates the potential benefits of TROPICS data assimilation for TC forecasts and provides a potentially streamlined pathway for transitioning TROPICS data from research to operations postlaunch.

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G. R. Halliwell Jr., A. Srinivasan, V. Kourafalou, H. Yang, D. Willey, M. Le Hénaff, and R. Atlas

Abstract

A new fraternal twin ocean observing system simulation experiment (OSSE) system is validated in a Gulf of Mexico domain. It is the first ocean system that takes full advantage of design criteria and rigorous evaluation procedures developed to validate atmosphere OSSE systems that have not been fully implemented for the ocean. These procedures are necessary to determine a priori that the OSSE system does not overestimate or underestimate observing system impacts. The new system consists of 1) a nature run (NR) stipulated to represent the true ocean, 2) a data assimilation system consisting of a second ocean model (the “forecast model”) coupled to a new ocean data assimilation system, and 3) software to simulate observations from the NR and to add realistic errors. The system design is described to illustrate the requirements of a validated OSSE system. The chosen NR reproduces the climatology and variability of ocean phenomena with sufficient realism. Although the same ocean model type is used (the “fraternal twin” approach), the forecast model is configured differently so that it approximately satisfies the requirement that differences (errors) with respect to the NR grow at the same rate as errors that develop between state-of-the-art ocean models and the true ocean. Rigorous evaluation procedures developed for atmospheric OSSEs are then applied by first performing observing system experiments (OSEs) to evaluate one or more existing observing systems. OSSEs are then performed that are identical except for the assimilation of synthetic observations simulated from the NR. Very similar impact assessments were realized between each OSE–OSSE pair, thus validating the system without the need for calibration.

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R. Atlas, R. N. Hoffman, S. M. Leidner, J. Sienkiewicz, T.-W. Yu, S. C. Bloom, E. Brin, J. Ardizzone, J. Terry, D. Bungato, and J. C. Jusem

Satellite scatterometer observations of the ocean surface wind speed and direction improve the depiction of storms at sea. Over the ocean, scatterometer surface winds are deduced from multiple measurements of reflected radar power made from several directions. In the nominal situation, the scattering mechanism is Bragg scattering from centimeter-scale waves, which are in equilibrium with the local wind. These data are especially valuable where observations are otherwise sparse—mostly in the Southern Hemisphere extratropics and Tropics, but also on occasion in the North Atlantic and North Pacific. The history of scatterometer winds research and its application to weather analysis and forecasting is reviewed here. Two types of data impact studies have been conducted to evaluate the effect of satellite data, including satellite scatterometer data, for NWP. These are simulation experiments (or observing system simulation experiments or OSSEs) designed primarily to assess the potential impact of planned satellite observing systems, and real data impact experiments (or observing system experiments or OSEs) to evaluate the actual impact of available space-based data. Both types of experiments have been applied to the series of satellite scatterometers carried on the Seasat, European Remote Sensing-1 and -2, and the Advanced Earth Observing System-1 satellites, and the NASA Quick Scatterometer. Several trends are evident: The amount of scatterometer data has been increasing. The ability of data assimilation systems and marine forecasters to use the data has improved substantially. The ability of simulation experiments to predict the utility of new sensors has also improved significantly.

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Arthur Y. Hou, David V. Ledvina, Arlindo M. da Silva, Sara Q. Zhang, Joanna Joiner, Robert M. Atlas, George J. Huffman, and Christian D. Kummerow

Abstract

This article describes a variational framework for assimilating the SSM/I-derived surface rain rate and total precipitable water (TPW) and examines their impact on the analysis produced by the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The SSM/I observations consist of tropical rain rates retrieved using the Goddard Profiling Algorithm and tropical TPW estimates produced by Wentz.

In a series of assimilation experiments for December 1992, results show that the SSM/I-derived rain rate, despite current uncertainty in its intensity, is better than the model-generated precipitation. Assimilating rainfall data improves cloud distributions and the cloudy-sky radiation, while assimilating TPW data reduces a moisture bias in the lower troposphere to improve the clear-sky radiation. Together, the two data types reduce the monthly mean spatial bias by 46% and the error standard deviation by 26% in the outgoing longwave radiation (OLR) averaged over the Tropics, as compared with the NOAA OLR observation product. The improved cloud distribution, in turn, improves the solar radiation at the surface. There is also evidence that the latent heating change associated with the improved precipitation improves the large-scale circulation in the Tropics. This is inferred from a comparison of the clear-sky brightness temperatures for TIROS Operational Vertical Sounder channel 12 computed from the GEOS analyses with the observed values, suggesting that rainfall assimilation reduces a prevailing moist bias in the upper-tropospheric humidity in the GEOS system through enhanced subsidence between the major convective centers.

This work shows that assimilation of satellite-derived precipitation and TPW can reduce state-dependent systematic errors in the OLR, clouds, surface radiation, and the large-scale circulation in the assimilated dataset. The improved analysis also leads to better short-range forecasts, but the impact is modest compared with improvements in the time-averaged signals in the analysis. The study shows that, in the presence of biases and other errors of the forecast model, it is possible to improve the time-averaged “climate content” in the data without comparable improvements in forecast. The full impact of these data types on the analysis cannot be measured solely in terms of forecast skills.

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EXECUTIVE COMMITTEE, C. L. Hosler, W. A. Baum, D. Atlas, P. M. Austin, E. S. Epstein, R. L. Leep Jr., K. C. Spengler, and D. F. Landrigan
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David M. Tratt, John A. Hackwell, Bonnie L. Valant-Spaight, Richard L. Walterscheid, Lynette J. Gelinas, James H. Hecht, Charles M. Swenson, Caleb P. Lampen, M. Joan Alexander, Lars Hoffmann, David S. Nolan, Steven D. Miller, Jeffrey L. Hall, Robert Atlas, Frank D. Marks Jr., and Philip T. Partain

Abstract

The prediction of tropical cyclone rapid intensification is one of the most pressing unsolved problems in hurricane forecasting. The signatures of gravity waves launched by strong convective updrafts are often clearly seen in airglow and carbon dioxide thermal emission spectra under favorable atmospheric conditions. By continuously monitoring the Atlantic hurricane belt from the main development region to the vulnerable sections of the continental United States at high cadence, it will be possible to investigate the utility of storm-induced gravity wave observations for the diagnosis of impending storm intensification. Such a capability would also enable significant improvements in our ability to characterize the 3D transient behavior of upper-atmospheric gravity waves and point the way to future observing strategies that could mitigate the risk to human life caused by severe storms. This paper describes a new mission concept involving a midinfrared imager hosted aboard a geostationary satellite positioned at approximately 80°W longitude. The sensor’s 3-km pixel size ensures that the gravity wave horizontal structure is adequately resolved, while a 30-s refresh rate enables improved definition of the dynamic intensification process. In this way the transient development of gravity wave perturbations caused by both convective and cyclonic storms may be discerned in near–real time.

Open access
Wayman E. Baker, George D. Emmitt, Franklin Robertson, Robert M. Atlas, John E. Molinari, David A. Bowdle, Jan Paegle, R. Michael Hardesty, Robert T. Menzies, T. N. Krishnamurti, Robert A. Brown, Madison J. Post, John R. Anderson, Andrew C. Lorenc, and James McElroy

The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate.

This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds.

Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.

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Wayman E. Baker, Robert Atlas, Carla Cardinali, Amy Clement, George D. Emmitt, Bruce M. Gentry, R. Michael Hardesty, Erland Källén, Michael J. Kavaya, Rolf Langland, Zaizhong Ma, Michiko Masutani, Will McCarty, R. Bradley Pierce, Zhaoxia Pu, Lars Peter Riishojgaard, James Ryan, Sara Tucker, Martin Weissmann, and James G. Yoe

The three-dimensional global wind field is the most important remaining measurement needed to accurately assess the dynamics of the atmosphere. Wind information in the tropics, high latitudes, and stratosphere is particularly deficient. Furthermore, only a small fraction of the atmosphere is sampled in terms of wind profiles. This limits our ability to optimally specify initial conditions for numerical weather prediction (NWP) models and our understanding of several key climate change issues.

Because of its extensive wind measurement heritage (since 1968) and especially the rapid recent technology advances, Doppler lidar has reached a level of maturity required for a space-based mission. The European Space Agency (ESA)'s Atmospheric Dynamics Mission Aeolus (ADM-Aeolus) Doppler wind lidar (DWL), now scheduled for launch in 2015, will be a major milestone.

This paper reviews the expected impact of DWL measurements on NWP and climate research, measurement concepts, and the recent advances in technology that will set the stage for space-based deployment. Forecast impact experiments with actual airborne DWL measurements collected over the North Atlantic in 2003 and assimilated into the European Centre for Medium-Range Weather Forecasts (ECMWF) operational model are a clear indication of the value of lidar-measured wind profiles. Airborne DWL measurements collected over the western Pacific in 2008 and assimilated into both the ECMWF and U.S. Navy operational models support the earlier findings.

These forecast impact experiments confirm observing system simulation experiments (OSSEs) conducted over the past 25–30 years. The addition of simulated DWL wind observations in recent OSSEs performed at the Joint Center for Satellite Data Assimilation (JCSDA) leads to a statistically significant increase in forecast skill.

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