Search Results

You are looking at 1 - 10 of 10 items for

  • Author or Editor: James P. Nelson III x
  • Refine by Access: All Content x
Clear All Modify Search
Gary P. Ellrod, James P. Nelson III, Michael R. Witiw, Lynda Bottos, and William P. Roeder

Abstract

Several experimental products derived from Geostationary Operational Environmental Satellite (GOES) Sounder retrievals (vertical profiles of temperature and moisture) have been developed to assist weather forecasters in assessing the potential for convective downbursts. The product suite currently includes the wind index (WINDEX), a dry microburst index, and the maximum difference in equivalent potential temperature (θ e) from the surface to 300 hPa. The products are displayed as color-coded boxes or numerical values, superimposed on GOES visible, infrared, or water vapor imagery, and are available hourly, day and night, via the Internet. After two full summers of evaluation, the products have been shown to be useful in the assessment of atmospheric conditions that may lead to strong, gusty surface winds from thunderstorms. Two case studies are presented: 1) a severe downburst storm in southern Arizona that produced historic surface wind speeds and damage, and 2) multiple dry and wet downbursts in western Kansas that resulted in minor damage. Verification involved comparing the parameters with radiosonde data, numerical model first guess data, or surface wind reports from airports, mesonetworks, or storm spotters. Mean absolute WINDEX from the GOES retrievals differed from the mean surface wind gust reports by <2 kt (1 m s−1) for 82 events, but underestimated wind gusts for 7 nighttime events by 22 kt (11 m s−1). GOES WINDEX was also slightly better than that derived from the concurrent National Centers for Environmental Prediction’s Eta Model first guess. There are plans to incorporate these downburst parameters into a future upgrade of the National Weather Service’s Advanced Weather Interactive Processing System, with the option to derive them from either GOES Sounder data, radiosondes, or numerical model forecast data.

Full access
Tom H. Zapotocny, W. Paul Menzel, James A. Jung, and James P. Nelson III

Abstract

The impact of in situ rawinsonde (raob) data, remotely sensed Geostationary Operational Environmental Satellite (GOES), and Polar Operational Environmental Satellite (POES) data routinely used in NCEP’s Eta Data Assimilation/Forecast System (EDAS) is studied for extended-length time periods during four seasons. The work described in this paper is relevant for users of the Eta Model trying to compare and contrast the overall forecast impact of traditional, mostly land-based rawinsonde data with remotely sensed data that are available domainwide.

The case studies chosen consist of 15-day periods during fall 2001, winter 2001/02, spring 2002, and summer 2002. During these periods, a 32-km/60-layer November 2001 version of the EDAS is run four times at both 0000 and 1200 UTC. The four runs include a control run, which utilizes all data types routinely used in the EDAS, and three experimental runs in which either all rawinsonde, GOES, or POES data are denied. Differences between the experimental and control runs are then accumulated over the 15-day periods and analyzed to demonstrate the 24- and 48-h forecast impact of these data types in the EDAS. Conventional meteorological terms evaluated include mean sea level pressure as well as temperature, both components of the wind, and relative humidity. Comparisons are made on seven pressure levels extending from near the earth’s surface to the lower stratosphere. The diagnostics are computed over both the entire horizontal model domain, and within a subsection covering the continental United States and adjacent coastal waters (extended CONUS).

The 24-h domainwide results show that a positive forecast impact is achieved from all three data sources during all four seasons. Cumulatively, the rawinsonde data have the largest positive impact over both the entire model domain and extended CONUS. However, GOES data have the largest contribution for several fields, especially moisture during summer and fall 2001. In general, GOES data also provide larger forecast impacts than POES data, especially for the wind components. All three data types demonstrate comparable forecast impact in terms of relative humidity. Finally, raob and POES data display a “spike” in positive forecast impact in the lower stratosphere during three of the four seasons.

Two additional findings from this study are also important. The first is that the forecast impact of all data types drops by at least a factor of 2 during all seasons between 24 and 48 h. The second is that GOES data show a preference for providing nearly equal improvement to the 0000 and 1200 UTC forecast cycles, while rawinsonde and especially POES data provide consistently larger forecast impacts at 1200 than at 0000 UTC.

Full access
Tom H. Zapotocny, W. Paul Menzel, James P. Nelson III, and James A. Jung

Abstract

The impact of 10 data types used in the Eta Data Assimilation/Forecast System (EDAS) is studied for extended-length time periods during three seasons. Five of the data types are remotely sensed satellite data, and the other five are in situ. The satellite data types include three-layer and vertically integrated precipitable water, temperature data down to cloud top, infrared cloud-drift winds, and water vapor cloud-top winds. The five in situ data types consist of two rawinsonde and two aircraft observation types along with surface land observations. The work described in this paper is relevant for Eta Model users trying to identify the impact of remotely sensed, largely maritime data types and in situ, largely land-based data types. The case studies chosen consist of 11-day periods during December 1998, April 1999, and July 1999. During these periods, 11 EDAS runs were executed twice daily. The 11 runs include a control run, which utilizes all data types used in the EDAS, and 10 experimental runs in which one of the data types is denied. Differences between the experimental and control runs are then accumulated and analyzed to demonstrate the 0-h sensitivity and 24-h forecast impact of these data types in the EDAS. Conventional meteorological terms evaluated include temperature, u component of the wind, and relative humidity on five pressure levels. These diagnostics are computed over the entire model domain and within a subsection centered on the continental United States (CONUS). The entire domain results show that a modest positive forecast impact is achieved from all 10 data types during all three time periods. Rawinsonde temperature and moisture observations and infrared cloud-drift wind observations have the largest positive impact season to season; however, both precipitable water data types provide significant positive forecast impact during the summer and transition seasons. Rawinsonde temperature and moisture, rawinsonde winds, aircraft winds, and infrared cloud-drift winds have the largest positive impact season to season over CONUS. The three-layer precipitable water data type produces large positive forecast impact over CONUS during July. In general, the forecast impacts are smaller for nearly all data types over CONUS than over the entire model domain. There are also more negative forecast impacts for both the in situ and remotely sensed data types over CONUS than over the entire domain.

Full access
Tom H. Zapotocny, W. Paul Menzel, James A. Jung, and James P. Nelson III

Abstract

The impact of in situ rawinsonde observations (raob), remotely sensed Geostationary Operational Environmental Satellite (GOES), and Polar-Orbiting Operational Environmental Satellite (POES) observations routinely used in NCEP’s Eta Data Assimilation/Forecast System (EDAS) is studied for extended-length time periods during four seasons. This work examines the contribution of nine individual components of the total observing system. The nine data types examined include rawinsonde mass and wind observations, GOES mass and wind observations, POES observations from the Microwave Sounding Unit (MSU), the Advanced Microwave Sounding Unit (AMSU-A and AMSU-B), the High Resolution Infrared Radiation Sounder (HIRS), and column total precipitable water and low-level wind observations from the Special Sensor Microwave Imager (SSM/I). The results are relevant for users of the Eta Model trying to compare/contrast the overall forecast impact of traditional, largely land-based rawinsonde observations against remotely sensed satellite observations, which are available domainwide.

The case studies chosen consist of 15-day periods during fall 2001, winter 2001/02, spring 2002, and summer 2002. Throughout these periods, a November 2001 32-km version of the EDAS is run 10 times at both 0000 and 1200 UTC. The 10 runs include a control run, which utilizes all data types routinely used in the EDAS, and 9 experimental runs in which one of the component data types noted above is denied. Differences between the experimental and control runs are then accumulated over the 15-day periods and analyzed to demonstrate the 00-h sensitivity and 24-h forecast impact of these individual data types in the EDAS. The diagnostics are computed over the entire horizontal model domain and a subsection covering the continental United States (CONUS) and adjacent coastal waters on isobaric surfaces extending into the lower stratosphere.

The 24-h forecast impact results show that a positive forecast impact is achieved from most of the nine component data sources during all four time periods. HIRS, MSU, and SSM/I wind observations yield only a slight positive forecast impact to all fields. Rawinsonde and GOES wind observations have the largest positive forecast impact for temperature over both the entire model domain and the extended CONUS. The same data types also provide the largest forecast impact to the u component of the wind, while GOES wind observations provide the largest forecast impact to moisture.

Full access
Gary P. Ellrod, Rao V. Achutuni, Jaime M. Daniels, Elaine M. Prins, and James P. Nelson III

The Geostationary Operational Environmental Satellite-8 (GOES-8), the first in the GOES I–M series of advanced meteorological satellites was launched in April 1994 and became operational at 75 °W longitude the following year. GOES-8 features numerous improvements over prior GOES platforms such as 1) improved resolution in the infrared (IR) and water vapor bands, 2) reduced instrument noise, 3) 10-bit visible and IR digitization, 4) greater image frequency, 5) more spectral bands, and 6) an independent sounder. A qualitative and quantitative comparison of the imager data from GOES-8 and GOES-7 shows that imagery from the newer spacecraft is superior in most respects. Improvements in resolution and instrument noise on GOES-8 provide sharper, cleaner images that allow easier detection of significant meteorological or oceanographic features. Infrared temperature comparisons between GOES-8 and GOES-7 were within 0.5°–2.0°C for all IR bands, indicating consistency between the two spacecraft. Visible band albedos from GOES-8 were at least 50% greater than GOES-7 for a wide range of scenes, suggesting that output from the GOES-7 visible detectors had degraded since its launch in 1987. Products derived from GOES-8 imager data for observing fog at night, fire detection, heavy precipitation estimation, and upper-level winds based on cloud or water vapor motion have been shown to be superior to similar products from GOES-7. Early difficulties with image registration and IR striping were alleviated after the first year. Based on the performance of GOES-8, future spacecraft in the GOES I–M series can be expected to provide many years of useful service to meteorologists, oceanographers, and the environmental monitoring community.

Full access
Thomas L. Koehler, Charles J. Seman, James P. Nelson III, and Lyle H. Horn

Abstract

Alternatives to the retrieval techniques applied by NESDIS operations to derive the FGGF Level IIa soundings are examined. A physical iterative retrieval technique is compared to the operational statistical method, and the influence of using higher resolution subsets of the original infrared observations is examined. These alternatives are evaluated using TIROS-N observations from a January 1980 period over the conventional data-rich region of the United States. The evaluations involve colocation statistics and 700–300 mb thickness difference fields. The initial tests using operational (9 × 7 HIRS/2 fields of view) resolution show that the physical iterative retrieval makes substantial corrections to climatological first guesses, but only minor corrections to a first guess based on the operational soundings. Colocation statistics and 700–300 mb thickness difference fields indicate that the physical retrieval method does not offer significant improvements over the FGGE operational soundings. As in the operational soundings, there is a tendency for the sounding errors to be synoptically correlated with troughs ton warm and ridges too cold, thus reducing thermal gradients.

In an attempt to improve the thermal gradient information, the physical iterative method (using the operational sounding first guess) was also employed to retrieve soundings based on radiances obtained from higher (3 × 3 HIRS/2 fields of view) resolution. Four different subsets of the 3 × 3 sounding sets were studied with varying horizontal resolutions and with and without manual editing. Each set shows some improvement over the 9 × 7 retrievals, particularly through a reduction of the bias in the low and midtroposphere. Further analysis reveals that the improvement in retrieval accuracy is sounding-type dependent, with only the 3 × 3 clear retrievals showing definite improvement over 9 × 7 retrievals for this case. The 700–300 mb thickness fields obtained from the 3 × 3 FOV soundings also show synoptically correlated errors.

Full access
Jun Li, Christopher C. Schmidt, James P. Nelson III, Timothy J. Schmit, and W. Paul Menzel

Abstract

The potential for using Geostationary Operational Environmental Satellite (GOES) Sounder radiance measurements to monitor total atmospheric ozone is examined. A statistical regression using GOES Sounder spectral bands 1–15 radiances allows estimation of total atmospheric ozone. Hourly GOES ozone products have been generated since May 1998. GOES ozone estimates are compared with Total Ozone Mapping Spectrometer (TOMS) ozone measurements from the Earth Probe satellite and ground-based Dobson spectrometer ozone observations. Results show that the percentage root-mean-square (rms) difference between instantaneous TOMS and GOES ozone estimates ranges from 4% to 7%. Also, daily comparisons for 1998 between GOES ozone values and ground-based observations at Bismarck, North Dakota; Wallops Island, Virginia; and Nashville, Tennessee, show that the rms difference is approximately 21 Dobson units. Given the hourly measurements and high-spatial density provided by the GOES Sounder, GOES ozone estimates and associated products show promise.

Full access
Timothy J. Schmit, Wayne F. Feltz, W. Paul Menzel, James Jung, Andrew P. Noel, James N. Heil, James P. Nelson III, and Gary S. Wade

Abstract

The Geostationary Operational Environmental Satellite (GOES) sounders have provided quality hourly radiances and derived products over the continental United States and adjacent oceans for more than five years. The products derived from the radiances include temperature and moisture profiles; total precipitable water vapor (TPW); atmospheric stability indices, such as convective available potential energy (CAPE) and lifted index (LI); cloud-top properties; total column ozone; and midlevel motion. This paper focuses on validation and use of moisture profiles derived in clear regions. Validations are made with respect to collocated radiosondes, a microwave radiometer, and parallel runs of the regional Eta Model system. The ground-based microwave radiometer enables comparisons throughout the day, instead of only at conventional radiosonde launch times (0000 and 1200 UTC). The validations show that the sounder products provide unique information about the state of the atmosphere. The GOES sounder moisture data add information with considerably higher spatial and temporal resolution than is available from conventional radiosondes. Assimilation of three layers of moisture information retrieved from GOES sounder measurements has improved Eta Model precipitation forecasts even out to 48 h. Moreover, National Weather Service (NWS) forecasters are using GOES sounder products for a range of applications, with positive results.

Full access
Tom H. Zapotocny, Steven J. Nieman, W. Paul Menzel, James P. Nelson III, James A. Jung, Eric Rogers, David F. Parrish, Geoffrey J. DiMego, Michael Baldwin, and Timothy J. Schmit

Abstract

A case study is utilized to determine the sensitivity of the Eta Data Assimilation System (EDAS) to all operational observational data types used within it. The work described in this paper should be of interest to Eta Model users trying to identify the impact of each data type and could benefit other modelers trying to use EDAS analyses and forecasts as initial conditions for other models.

The case study chosen is one characterized by strong Atlantic and Pacific maritime cyclogenesis, and is shortly after the EDAS began using three-dimensional variational analysis. The control run of the EDAS utilizes all 34 of the operational data types. One of these data types is then denied for each of the subsequent experimental runs. Differences between the experimental and control runs are analyzed to demonstrate the sensitivity of the EDAS system to each data type for the analysis and subsequent 48-h forecasts. Results show the necessity of various nonconventional observation types, such as aircraft data, satellite precipitable water, and cloud drift winds. These data types are demonstrated to have a significant impact, especially observations in maritime regions.

Full access
James Edson, Timothy Crawford, Jerry Crescenti, Tom Farrar, Nelson Frew, Greg Gerbi, Costas Helmis, Tihomir Hristov, Djamal Khelif, Andrew Jessup, Haf Jonsson, Ming Li, Larry Mahrt, Wade McGillis, Albert Plueddemann, Lian Shen, Eric Skyllingstad, Tim Stanton, Peter Sullivan, Jielun Sun, John Trowbridge, Dean Vickers, Shouping Wang, Qing Wang, Robert Weller, John Wilkin, Albert J. Williams III, D. K. P. Yue, and Chris Zappa

The Office of Naval Research's Coupled Boundary Layers and Air–Sea Transfer (CBLAST) program is being conducted to investigate the processes that couple the marine boundary layers and govern the exchange of heat, mass, and momentum across the air–sea interface. CBLAST-LOW was designed to investigate these processes at the low-wind extreme where the processes are often driven or strongly modulated by buoyant forcing. The focus was on conditions ranging from negligible wind stress, where buoyant forcing dominates, up to wind speeds where wave breaking and Langmuir circulations play a significant role in the exchange processes. The field program provided observations from a suite of platforms deployed in the coastal ocean south of Martha's Vineyard. Highlights from the measurement campaigns include direct measurement of the momentum and heat fluxes on both sides of the air–sea interface using a specially constructed Air–Sea Interaction Tower (ASIT), and quantification of regional oceanic variability over scales of O(1–104 mm) using a mesoscale mooring array, aircraft-borne remote sensors, drifters, and ship surveys. To our knowledge, the former represents the first successful attempt to directly and simultaneously measure the heat and momentum exchange on both sides of the air–sea interface. The latter provided a 3D picture of the oceanic boundary layer during the month-long main experiment. These observations have been combined with numerical models and direct numerical and large-eddy simulations to investigate the processes that couple the atmosphere and ocean under these conditions. For example, the oceanic measurements have been used in the Regional Ocean Modeling System (ROMS) to investigate the 3D evolution of regional ocean thermal stratification. The ultimate goal of these investigations is to incorporate improved parameterizations of these processes in coupled models such as the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) to improve marine forecasts of wind, waves, and currents.

Full access