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Dennis Chesters, Anthony Mostek, and Dennis A. Keyser

Abstract

Local forecasts often rely upon the extrapolation of trends seen in images of clouds from the GOES satellite. This work presents correspondingly high resolution images of atmospheric soundings calculated from the VAS radiometer on GOES. These VAS sounding images vividly depict moisture and stability conditions in preconvective regions, as though GOES were observing the United States with “stability detectors” instead of infrared detectors at 1–3 h intervals and 60 km horizontal resolution. False color images are presented for VAS-derived precipitable water and lifted index fields during two midsummer days that contain a wide variety of preconvective and convective conditions. Since each sounding image requires only 5 min to calculate with an automated regression algorithm on a minicomputer, it should be possible to process VAS data operationally for real-time objective analysis of potential convective instabilities.

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Dennis A. Keyser and Donald R. Johnson

Abstract

The interaction between the mass circulations within a mesoscale convective complex (MCC) and the entrance region of an upper tropospheric polar jet streak is examined to investigate mechanisms responsible for linking these two scales of motion. During NASA's fourth Atmospheric Variability Experiment (AVE IV), maximum wind speeds within a jet streak increased nearly 15 m s−1 over three to six hours as the jet streak propagated eastward over the Great Lakes region. Severe convection located on the rear anticyclonic flank of the jet streak within the direct circulation of the entrance region also intensified and increased in areal extent.

The results analyzed within isentropic coordinates establish that latent heating in the MCC modified the direct mass circulation in the jet streak entrance region through the forcing of diabatic components of ageostrophic motion. The net isallobaric ageostrophic component in the entrance region, determined through the gradients of differential heating and mass flux, exceeded 4 m s−1. The mass divergence in the upper troposphere was due to the slight excess of the diabatic isallobaric mode over the opposing adiabatic mode, while mass convergence in the lower troposphere was due to the slight excess of the adiabatic isallobaric mode over the diabatic mode. The intensity of the other diabatically forced ageostrophic component, induced through vertical advection of momentum in a sheared environment, ranged from 5 to 10 m s−1 in the middle and upper troposphere of the jet's entrance region. Over much of the convective region, both the total isallobaric and the inertial diabatic ageostrophic components were directed from the anticyclonic to the cyclonic side of the jet streak at jet streak level in the same sense as pre-existing ageostrophic motion in the upper branch of the jet's direct mass circulation. This diabatically forced ageostrophic motion directed along the pressure gradient of the larger scale resulted in additional generation of kinetic energy which ultimately produced stronger winds in the jet streak downstream.

A comparison between actual and geostrophic momentum forms for ageostrophic motion revealed discrepancies of 20 m s−1 that were mainly due to differences in the horizontal fields of inertial advective ageostrophic motion. This expected result points out that the rapid evolution of ageostrophic motion within the shorter time scales of MCCs limits the applicability of geostrophic momentum theory in prescribing the structure of ageostrophic motion.

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Ralph A. Petersen, Louis W. UccellinI, Anthony Mostek, and Dennis A. Keyser

Abstract

Infrared and visible imagery from VAS are used to delineate mid- and lower-tropospheric moisture fields for a variety of severe storm cases in the southern and central United States. The ability of sequences of images to isolate areas of large negative vertical moisture gradients and apparent convective instability prior to the onset of convective storms is assessed. Midlevel dryness is diagnosed directly from the VAS 6.7 channel observations, while low-level water vapor is either inferred from the presence of clouds in visible and infrared imagery or, in cloud-free areas, calculated from VAS "split window" channels. A variety ofimage combination procedures are used to deduce the stability fields which are then compared with the available radiosonde data. The results for several severe storm cases indicate that VAS can detect mid- and low-level mesoscale water vapor fields as distinct radiometric signals. The VAS imagery shows a strong tendency for thunderstorms to develop along the edges of bands of midlevel dryness as they overtake either pre-existing or developing low-level moisture maxima. Image sequences depict the speed with which deep moist and dry layers can develop and move, often at scales not resolvable using conventional radiosonde data. The images thus demonstrate the ability of VAS radiance data to detect differential moisture advectionsin rapidly changing pre-convective environments.

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Steven E. Koch, William C. Skillman, Paul J. Kocin, Peter J. Wetzel, Keith F. Brill, Dennis A. Keyser, and Michael C. McCumber

Abstract

A large number of predictions from a regional numerical weather prediction model known as the Mesoscale Atmospheric Simulation System (MASS 2.0) am verified against routinely collected observations to determine the model's predictive skill and its most important systematic errors at the synoptic scale. The model's forecast fields are smoothed to obtain synoptic-scale fields that can be compared objectively with the observation. A total of 23 (28) separate 12 h (24 h) forecasts of atmospheric flow patterns over the United States are evaluated from real-time simulations made during the period 2 April-2 July 1982. The model's performance is compared to that of the National Meteorological Centers operational Limited-area Fine Mesh (LFM) model for this period. Temporal variations in normalized forecast skill statistics are synthesized with the mean spatial distribution of daily model forecast errors in order to determine synoptic-scale systematic errors.

The mesoscale model produces synoptic-scale forecasts at an overall level of performance equivalent to that of the LFM model. Lower tropospheric mass fields are, for the most part, predicted significantly better by the MASS 2.0 model, but it is outperformed by the LFM at and above 500 mb. The greatest improvement made by the mesoscale model is a 73% reduction of cold bias in LFM forecasts of the 1000–500 mb thickness field, primarily over the western United States. The LFM bias is the combined result of model overforecasts of surface anticyclone intensity and underforecasts of surface cyclone intensity and nearby 500 mb geopotential heights.

The poorer forecasts by the MASS 2.0 model in the middle and upper troposphere result primarily from a systematic mass loss which occurs only under a certain synoptic flow pattern termed the mass loss regime. Problems with specification of the lateral boundary conditions and, to a lesser extent, erroneous computation of the map factor seemed to contribute most to the systematic mass loss. This error is very significant since MASS 2.0 performance either equaled or surpassed that of the LFM model in forecasts of virtually every meteorological field studied when mass loss regime days were excluded from the sample.

Two other important systematic errors in MASS model forecasts are investigated. Underforecasts of moisture over the Gulf Coast states are found to be due in large part to a negative bias in the moisture initialization. Also, overforecasts of surface cyclone intensity and 1000–500 mb thickness values over the Plains states are traced to excessive latent beating resulting from the absence of a cumulus parameterization scheme in the model. Awareness of these synoptic-scale forecasts errors enables more effective use to be made of the (unfiltered) mesoscale forecast fields, which are evaluated in the companion paper by Koch.

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Shun Liu, Geoff DiMego, Shucai Guan, V. Krishna Kumar, Dennis Keyser, Qin Xu, Kang Nai, Pengfei Zhang, Liping Liu, Jian Zhang, Kenneth Howard, and Jeff Ator

Abstract

Real-time access to level II radar data became available in May 2005 at the National Centers for Environmental Prediction (NCEP) Central Operations (NCO). Using these real-time data in operational data assimilation requires the data be processed reliably and efficiently through rigorous data quality controls. To this end, advanced radar data quality control techniques developed at the National Severe Storms Laboratory (NSSL) are combined into a comprehensive radar data processing system at NCEP. Techniques designed to create a high-resolution reflectivity mosaic developed at the NSSL are also adopted and installed within the NCEP radar data processing system to generate hourly 3D reflectivity mosaics and 2D-derived products. The processed radar radial velocity and 3D reflectivity mosaics are ingested into NCEP’s data assimilation systems to improve operational numerical weather predictions. The 3D reflectivity mosaics and 2D-derived products are also used for verification of high-resolution numerical weather prediction. The NCEP radar data processing system is described.

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Bruce Ingleby, Patricia Pauley, Alexander Kats, Jeff Ator, Dennis Keyser, Alexis Doerenbecher, Enrico Fucile, Jitsuko Hasegawa, Eizi Toyoda, Tanja Kleinert, Weiqing Qu, Judy St. James, Warren Tennant, and Richard Weedon

Abstract

Some real-time radiosonde reports are now available with higher vertical resolution and higher precision than the alphanumeric TEMP code. There are also extra metadata; for example, the software version may indicate whether humidity corrections have been applied at the station. Numerical weather prediction (NWP) centers and other users need to start using the new Binary Universal Form for Representation of Meteorological Data (BUFR) reports because the alphanumeric codes are being withdrawn. TEMP code has various restrictions and complexities introduced when telecommunication speed and costs were overriding concerns; one consequence is minor temperature rounding errors. In some ways BUFR reports are simpler: the whole ascent should be contained in a single report. BUFR reports can also include the time and location of each level; an ascent takes about 2 h and the balloon can drift 100 km or more laterally. This modernization is the largest and most complex change to the worldwide reporting of radiosonde observations for many years; international implementation is taking longer than planned and is very uneven. The change brings both opportunities and challenges. The biggest challenge is that the number and quality of the data from radiosonde ascents may suffer if the assessment of the BUFR reports and two-way communication between data producers and data users are not given the priority they require. It is possible that some countries will only attempt to replicate the old reports in the new format, not taking advantage of the benefits, which include easier treatment of radiosonde drift and a better understanding of instrument and processing details, as well as higher resolution.

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Manuel S. F. V. De Pondeca, Geoffrey S. Manikin, Geoff DiMego, Stanley G. Benjamin, David F. Parrish, R. James Purser, Wan-Shu Wu, John D. Horel, David T. Myrick, Ying Lin, Robert M. Aune, Dennis Keyser, Brad Colman, Greg Mann, and Jamie Vavra

Abstract

In 2006, the National Centers for Environmental Prediction (NCEP) implemented the Real-Time Mesoscale Analysis (RTMA) in collaboration with the Earth System Research Laboratory and the National Environmental, Satellite, and Data Information Service (NESDIS). In this work, a description of the RTMA applied to the 5-km resolution conterminous U.S. grid of the National Digital Forecast Database is given. Its two-dimensional variational data assimilation (2DVAR) component used to analyze near-surface observations is described in detail, and a brief discussion of the remapping of the NCEP stage II quantitative precipitation amount and NESDIS Geostationary Operational Environmental Satellite (GOES) sounder effective cloud amount to the 5-km grid is offered. Terrain-following background error covariances are used with the 2DVAR approach, which produces gridded fields of 2-m temperature, 2-m specific humidity, 2-m dewpoint, 10-m U and V wind components, and surface pressure. The estimate of the analysis uncertainty via the Lanczos method is briefly described. The strength of the 2DVAR is illustrated by (i) its ability to analyze a June 2007 cold temperature pool over the Washington, D.C., area; (ii) its fairly good analysis of a December 2008 mid-Atlantic region high-wind event that started from a very weak first guess; and (iii) its successful recovery of the finescale moisture features in a January 2010 case study over southern California. According to a cross-validation analysis for a 15-day period during November 2009, root-mean-square error improvements over the first guess range from 16% for wind speed to 45% for specific humidity.

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Suranjana Saha, Shrinivas Moorthi, Hua-Lu Pan, Xingren Wu, Jiande Wang, Sudhir Nadiga, Patrick Tripp, Robert Kistler, John Woollen, David Behringer, Haixia Liu, Diane Stokes, Robert Grumbine, George Gayno, Jun Wang, Yu-Tai Hou, Hui-ya Chuang, Hann-Ming H. Juang, Joe Sela, Mark Iredell, Russ Treadon, Daryl Kleist, Paul Van Delst, Dennis Keyser, John Derber, Michael Ek, Jesse Meng, Helin Wei, Rongqian Yang, Stephen Lord, Huug van den Dool, Arun Kumar, Wanqiu Wang, Craig Long, Muthuvel Chelliah, Yan Xue, Boyin Huang, Jae-Kyung Schemm, Wesley Ebisuzaki, Roger Lin, Pingping Xie, Mingyue Chen, Shuntai Zhou, Wayne Higgins, Cheng-Zhi Zou, Quanhua Liu, Yong Chen, Yong Han, Lidia Cucurull, Richard W. Reynolds, Glenn Rutledge, and Mitch Goldberg

The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice model has three layers. The CFSR atmospheric model has observed variations in carbon dioxide (CO2) over the 1979–2009 period, together with changes in aerosols and other trace gases and solar variations. Most available in situ and satellite observations were included in the CFSR. Satellite observations were used in radiance form, rather than retrieved values, and were bias corrected with “spin up” runs at full resolution, taking into account variable CO2 concentrations. This procedure enabled the smooth transitions of the climate record resulting from evolutionary changes in the satellite observing system.

CFSR atmospheric, oceanic, and land surface output products are available at an hourly time resolution and a horizontal resolution of 0.5° latitude × 0.5° longitude. The CFSR data will be distributed by the National Climatic Data Center (NCDC) and NCAR. This reanalysis will serve many purposes, including providing the basis for most of the NCEP Climate Prediction Center's operational climate products by defining the mean states of the atmosphere, ocean, land surface, and sea ice over the next 30-yr climate normal (1981–2010); providing initial conditions for historical forecasts that are required to calibrate operational NCEP climate forecasts (from week 2 to 9 months); and providing estimates and diagnoses of the Earth's climate state over the satellite data period for community climate research.

Preliminary analysis of the CFSR output indicates a product that is far superior in most respects to the reanalysis of the mid-1990s. The previous NCEP–NCAR reanalyses have been among the most used NCEP products in history; there is every reason to believe the CFSR will supersede these older products both in scope and quality, because it is higher in time and space resolution, covers the atmosphere, ocean, sea ice, and land, and was executed in a coupled mode with a more modern data assimilation system and forecast model.

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