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Dive into the research topics where Mitch Goldberg is active.

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Featured researches published by Mitch Goldberg.


Bulletin of the American Meteorological Society | 2010

The NCEP Climate Forecast System Reanalysis

Suranjana Saha; Shrinivas Moorthi; Hua-Lu Pan; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; Robert Kistler; John S. 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 T. Kleist; Paul Van Delst; Dennis Keyser; John Derber; Michael B. Ek; Jesse Meng; Helin Wei; Rongqian Yang; Stephen J. Lord

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 oceans 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 m...


Bulletin of the American Meteorological Society | 2006

AIRS: Improving Weather Forecasting and Providing New Data on Greenhouse Gases

Moustafa T. Chahine; Thomas S. Pagano; Hartmut H. Aumann; Robert Atlas; Christopher D. Barnet; John Blaisdell; Luke Chen; Murty Divakarla; Eric J. Fetzer; Mitch Goldberg; Catherine Gautier; Stephanie Granger; Scott E. Hannon; F. W. Irion; Ramesh Kakar; Eugenia Kalnay; Bjorn Lambrigtsen; Sung-Yung Lee; John Le Marshall; W. Wallace McMillan; Larry M. McMillin; Edward T. Olsen; Henry E. Revercomb; Philip W. Rosenkranz; William L. Smith; David H. Staelin; L. Larrabee Strow; Joel Susskind; David C. Tobin; Walter Wolf

Abstract The Atmospheric Infrared Sounder (AIRS) and its two companion microwave sounders, AMSU and HSB were launched into polar orbit onboard the NASA Aqua Satellite in May 2002. NASA required the sounding system to provide high-quality research data for climate studies and to meet NOAAs requirements for improving operational weather forecasting. The NOAA requirement translated into global retrieval of temperature and humidity profiles with accuracies approaching those of radiosondes. AIRS also provides new measurements of several greenhouse gases, such as CO2, CO, CH4, O3, SO2, and aerosols. The assimilation of AIRS data into operational weather forecasting has already demonstrated significant improvements in global forecast skill. At NOAA/NCEP, the improvement in the forecast skill achieved at 6 days is equivalent to gaining an extension of forecast capability of six hours. This improvement is quite significant when compared to other forecast improvements over the last decade. In addition to NCEP, ECM...


Bulletin of the American Meteorological Society | 2006

Improving Global Analysis and Forecasting with AIRS

J. Le Marshall; James A. Jung; John Derber; Moustafa T. Chahine; R. Treadon; Stephen J. Lord; Mitch Goldberg; Walter Wolf; Hanlan Liu; Joanna Joiner; John S. Woollen; R. Todling; P. Van Delst; Y. Tahara

AMERICAN METEOROLOGICAL SOCIETY | 891 AFFILIATIONS : LE MARSHALL, JUNG, DERBER, TREADON, LORD, GOLDBERG, WOLF, LIU, JOINER, WOOLLEN, TODLING, VAN DELST, AND TAHARA—NASA, NOAA, and U.S. Department of Defense Joint Center for Satellite Data Assimilation, Camp Springs, Maryland; CHAHINE—NASA Jet Propulsion Laboratory, Pasadena, California CORRESPONDING AUTHOR: John Le Marshall, Joint Center for Satellite Data Assimilation, NOAA Science Center, 5200 Auth Road, Camp Springs, MD 20746 E-mail: [email protected]


Bulletin of the American Meteorological Society | 2011

The Global Space-Based Inter-Calibration System

Mitch Goldberg; George Ohring; James J. Butler; Changyong Cao; R. Datla; David R. Doelling; V. Gärtner; T. Hewison; B. Iacovazzi; D. Kim; T. Kurino; J. Lafeuille; P. Minnis; D. Renaut; J. Schmetz; David C. Tobin; Likun Wang; Fuzhong Weng; Xiangqian Wu; Fangfang Yu; Peng Zhang; Tong Zhu

The Global Space-based Inter-Calibration System (GSICS) is a new international program to assure the comparability of satellite measurements taken at different times and locations by different instruments operated by different satellite agencies. Sponsored by the World Meteorological Organization and the Coordination Group for Meteorological Satellites, GSICS will intercalibrate the instruments of the international constellation of operational low-earth-orbiting (LEO) and geostationary earth-orbiting (GEO) environmental satellites and tie these to common reference standards. The intercomparability of the observations will result in more accurate measurements for assimilation in numerical weather prediction models, construction of more reliable climate data records, and progress toward achieving the societal goals of the Global Earth Observation System of Systems. GSICS includes globally coordinated activities for prelaunch instrument characterization, onboard routine calibration, sensor intercomparison of...


Journal of Geophysical Research | 2008

CO2 retrievals from the Atmospheric Infrared Sounder: Methodology and validation

Eric Maddy; Christopher D. Barnet; Mitch Goldberg; Colm Sweeney; Xingpin Liu

In this paper we describe the methodology of an offline retrieval of CO 2 from AIRS data and show comparisons of these retrievals with all available NOAA ESRL/GMD aircraft data during 2005. In general, we find that when compared to the aircraft the AIRS CO 2 estimates agree to approximately ±0.5% in middle-tropospheric CO 2 column abundances between ±65 degrees latitude.


Journal of Applied Meteorology and Climatology | 2010

Comparison of AIRS and IASI Radiances Using GOES Imagers as Transfer Radiometers toward Climate Data Records

Likun Wang; Xiangqian Wu; Mitch Goldberg; Changyong Cao; Yaping Li; Seung-hee Sohn

Abstract The Atmospheric Infrared Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI), together with the future Cross-track Infrared Sounder, will provide long-term hyperspectral measurements of the earth and its atmosphere at ∼10 km spatial resolution. Quantifying the radiometric difference between AIRS and IASI is crucial for creating fundamental climate data records and establishing the space-based infrared calibration standard. Since AIRS and IASI have different local equator crossing times, a direct comparison of these two instruments over the tropical regions is not feasible. Using the Geostationary Operational Environmental Satellite (GOES) imagers as transfer radiometers, this study compares AIRS and IASI over warm scenes in the tropical regions for a time period of 16 months. The double differences between AIRS and IASI radiance biases relative to the GOES-11 and -12 imagers are used to quantify the radiance differences between AIRS and IASI within the GOES imager spectral ...


Journal of Geophysical Research | 2014

The CrIMSS EDR Algorithm: Characterization, Optimization, and Validation

Murty Divakarla; Christopher D. Barnet; Xu Liu; Degui Gu; Michael Wilson; Susan Kizer; Xiaozhen Xiong; Eric Maddy; Ralph Ferraro; Robert O. Knuteson; Denise E. Hagan; Xia‐lin Ma; Changyi Tan; Nicholas R. Nalli; Anthony Reale; Andrew K. Mollner; Wenze Yang; Antonia Gambacorta; Michelle Feltz; Flavio Iturbide-Sanchez; Bomin Sun; Mitch Goldberg

The Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) instruments aboard the Suomi National Polar-orbiting Partnership satellite provide high-quality hyperspectral infrared and microwave observations to retrieve atmospheric vertical temperature and moisture profiles (AVTP and AVMP) and many other environmental data records (EDRs). The official CrIS and ATMS EDR algorithm, together called the Cross-track Infrared and Microwave Sounding Suite (CrIMSS), produces EDR products on an operational basis through the interface data processing segment. The CrIMSS algorithm group is to assess and ensure that operational EDRs meet beta and provisional maturity requirements and are ready for stages 1–3 validations. This paper presents a summary of algorithm optimization efforts, as well as characterization and validation of the AVTP and AVMP products using the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis, the Atmospheric Infrared Sounder (AIRS) retrievals, and conventional and dedicated radiosonde observations. The global root-mean-square (RMS) differences between the CrIMSS products and the ECMWF show that the AVTP is meeting the requirements for layers 30–300 hPa (1.53 K versus 1.5 K) and 300–700 hPa (1.28 K versus 1.5 K). Slightly higher RMS difference for the 700 hPa-surface layer (1.78 K versus 1.6 K) is attributable to land and polar profiles. The AVMP product is within the requirements for 300–600 hPa (26.8% versus 35%) and is close in meeting the requirements for 600 hPa-surface (25.3% versus 20%). After just one year of maturity, the CrIMSS EDR products are quite comparable to the AIRS heritage algorithm products and show readiness for stages 1–3 validations.


Journal of Atmospheric and Oceanic Technology | 2009

Spectral Bias Estimation of Historical HIRS Using IASI Observations for Improved Fundamental Climate Data Records

Changyong Cao; Mitch Goldberg; Likun Wang

Abstract A prerequisite for climate change detection from satellites is that the measurements from a series of historical satellites must be consistent and ideally made traceable to the International System of Units (SI). Unfortunately, this requirement is not met for the 14 High Resolution Infrared Radiation Sounders (HIRS) on the historical NOAA satellites, because the instrument was developed for weather forecasts and lacks accuracy and consistency across satellites. It is well known that for HIRS, differences in the spectral response functions (SRF) between instruments and their prelaunch measurement uncertainties often lead to observations of the atmosphere at different altitudes. As a result of the atmospheric lapse rate, they both can introduce significant intersatellite biases. The SRF-dependent biases are further mixed with other effects such as the diurnal cycle because of observation time differences and orbital drifts, on board calibration, and algorithm issues. In this study, the Infrared Atm...


Eos, Transactions American Geophysical Union | 2005

Impact of atmospheric infrared sounder observations on weather forecasts

J. Le Marshall; J. Jung; John Derber; R. Treadon; Stephen J. Lord; Mitch Goldberg; Walter Wolf; H. C. Liu; J. Joiner; J. Woollen; R. Todling; R. Gelaro

Experimental weather forecasts at the Joint Center for Satellite Data Assimilation (JCSDA) using Atmospheric Infrared Sounder (AIRS) radiance observations indicate significant improvements in global forecast skill compared with the operational system without AIRS data. The improvement in forecast skill at six days is equivalent to gaining an extension of forecast capability of several hours. This magnitude of improvement is quite significant when compared with the rate of general forecast improvement over the last decade. A several hour increase in forecast range at five or six days normally takes several years to achieve at operational weather centers.


Sensors | 2009

Use of vegetation health data for estimation of aus rice yield in bangladesh.

Atiqur Rahman; Leonid Roytman; Nir Y. Krakauer; Mohammad Nizamuddin; Mitch Goldberg

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991–2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March–April (weeks 8–13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

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Walter Wolf

National Oceanic and Atmospheric Administration

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Leonid Roytman

City College of New York

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Felix Kogan

National Oceanic and Atmospheric Administration

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John Derber

National Oceanic and Atmospheric Administration

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Stephen J. Lord

National Oceanic and Atmospheric Administration

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Eric Maddy

National Oceanic and Atmospheric Administration

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Lihang Zhou

National Oceanic and Atmospheric Administration

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Changyong Cao

National Oceanic and Atmospheric Administration

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John S. Woollen

National Oceanic and Atmospheric Administration

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