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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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D. Atlas
,
J. I. Metcalf
,
J. H. Richter
, and
E. E. Gossard

Abstract

Ultra-high resolution (2m) radar observations show the amplification of unstable Kelvin-Helmholtz (KH) waves, the development of roll vortices, their breaking and the resulting turbulence, and appear to represent our first view of the life cycle of clear air turbulence. The KH waves are initiated at the base of an inversion at which the Richardson number, Ri, is slightly positive just prior to wave action, and above which Ri≫0. Accordingly, only a small enhancement of the wind shear at the interface will reduce Ri to the critical value (0–0.25) required to trigger KH waves. The KH waves also trigger stable waves in the dynamically stable stratum immediately above. Quantitative measurements indicate reflectivities typically 10 times greater, and occasionally 300 times greater, than the previously recorded maximum, but in strata of only a few meters vertical extent. Large-volume averaging by the prior low-resolution radars accounts largely for the discrepancy. The thinness of some of the scatter layers and the smoothness of the reflectivity contours precludes turbulent eddies exceeding a few meters, but the high reflectivities require major centimetric scale perturbations in refractivity. Direct measurements of microscale perturbations of the required magnitude by Lane, though rare, support the deductions. The origin of this microscale turbulence, especially in layers of large dynamic stability, is a mystery deserving attention. The intermittency of the KH wave activity and the undulations of the layer of large refractivity variance explain the previously reported patchiness of turbulence in and near stable strata, but raise serious questions as to the validity of long-path (duration) measurements of turbulence spectra. Both the form and intensity of the turbulence spectrum are also strongly dependent on height and the “age” of CAT.

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Y. C. Sud
,
D. M. Mocko
,
K-M. Lau
, and
R. Atlas

Abstract

Past studies have suggested that the drought of the summer of 1988 over the midwestern United States may have been caused by sea surface temperature (SST) anomalies, an evolving stationary circulation, a soil-moisture feedback on circulation and rainfall, or even by remote forcings. The relative importance of various contributing factors is investigated in this paper through the use of Goddard Earth Observing System (GEOS) GCM simulations. Seven different experiments, each containing an ensemble of four simulations, were conducted with the GCM. For each experiment, the GCM was integrated through the summers of 1987 and 1988 starting from an analyzed atmosphere in early January of each year. In the baseline case, only the SST anomalies and climatological vegetation parameters were prescribed, while everything else (such as soil moisture, snow cover, and clouds) was interactive. The precipitation differences (1988 minus 1987) show that the GCM was successful in simulating reduced precipitation in 1988, but the accompanying low-level circulation anomalies in the Midwest were not well simulated. To isolate the influence of the model’s climate drift, analyzed winds and analyzed soil moisture were prescribed globally as continuous updates (in isolation or jointly). The results show that remotely advected wind biases (emanating from potential errors in the model’s dynamics and physics) are the primary cause of circulation biases over North America. Inclusion of soil moisture helps to improve the simulation as well as to reaffirm the strong feedback between soil moisture and precipitation. In a case with both updated winds and soil moisture, the model produces more realistic evapotranspiration and precipitation differences. An additional case also used soil moisture and winds updates, but only outside North America. Its simulation is very similar to that of the case with globally updated winds and soil moisture, which suggests that North American simulation errors originate largely outside the region. Two additional cases examining the influence of vegetation were built on this case using correct and opposite-year vegetation. The model did not produce a discernible improvement in response to vegetation for the drought year. One may conclude that the soil moisture governs the outcome of the land–atmosphere feedback interaction far more than the vegetation parameters. A primary inference of this study is that even though SSTs have some influence on the drought, model biases strongly influence the prediction errors. It must be emphasized that the results from this study are dependent upon the GEOS model’s identified errors and biases, and that the conclusions do not necessarily apply to results from other models.

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A. L. Conaty
,
J. C. Jusem
,
L. Takacs
,
D. Keyser
, and
R. Atlas

The realism of extratropical cyclones, fronts, jet streams, and the tropopause in the Goddard Earth Observing System (GEOS) general circulation model (GCM), implemented in assimilation and simulation modes, is evaluated from climatological and case-study perspectives using the GEOS-1 reanalysis climatology and applicable conceptual models as benchmarks for comparison. The latitude-longitude grid spacing of the datasets derived from the GEOS GCM ranges from 2° × 2.5° to 0.5° × 0.5°. Frontal systems in the higher-resolution datasets are characterized by horizontal potential temperature gradients that are narrower in scale and larger in magnitude than their lower-resolution counterparts, and various structural features in the Shapiro–Keyser cyclone model are replicated with reasonable fidelity at 1° × 1° resolution. The remainder of the evaluation focuses on a 3-month Northern Hemisphere winter simulation of the GEOS GCM at 1° × 1° resolution. The simulation realistically reproduces various large-scale circulation features related to the North Pacific and Atlantic jet streams when compared with the GEOS-1 reanalysis climatology, and conforms closely to a conceptualization of the zonally averaged troposphere and stratosphere proposed originally by Napier Shaw and revised by Hoskins. An extratropical cyclone that developed over the North Atlantic Ocean in the simulation features surface and tropopause evolutions corresponding to the Norwegian cyclone model and to the LC2 life cycle proposed by Thorncroft et al., respectively. These evolutions are related to the position of the developing cyclone with respect to upper-level jets identified in the time-mean and instantaneous flow fields. This article concludes with the enumeration of several research opportunities that may be addressed through the use of state-of-the-art GCMs possessing sufficient resolution to represent mesoscale phenomena and processes explicitly.

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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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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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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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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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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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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.

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