AIRS impact on precipitation analysis and forecast of tropical cyclones in a global data assimilation and forecast system

<p>Recent efforts have focused on evaluation of the reprocessed Aeolus Level 2B (L2B) wind data with ESA M1 bias correction and its impact on NOAA global forecast. Aeolus wind quality especially the remaining biases vs NOAA global model background is examined. As a result, a revised bias correction taking account of noises in both Aeolus and GFS winds is implemented in the NOAA global data assimilation system to improve Aeolus wind assimilation. &#160;In this study we will present impact from Aeolus wind on NOAA global forecast, focusing on synoptic and mesoscale scale events, e.g., tropical cyclones track and intensity in Eastern Pacific, and heavy rainfalls over the Western Coast of US.</p>

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A Two-Season Impact Study of NOAA Polar-Orbiting Satellites in the NCEP Global Data Assimilation System

Weather and Forecasting ◽

10.1175/2008waf2007065.1 ◽

2008 ◽

Vol 23 (5) ◽

pp. 854-877 ◽

Cited By ~ 9

Author(s):

James A. Jung ◽

Tom H. Zapotocny ◽

John F. Le Marshall ◽

Russ E. Treadon

Keyword(s):

Data Assimilation ◽

Forecast System ◽

Anomaly Correlation ◽

Global Data Assimilation System ◽

Polar Orbiting Satellite ◽

The Impact ◽

Data Assimilation System ◽

Global Data ◽

Assimilation System ◽

Forecast Quality

Abstract Observing system experiments (OSEs) during two seasons are used to quantify the important contributions made to forecast quality from the use of the National Oceanic and Atmospheric Administration’s (NOAA) polar-orbiting satellites. The impact is measured by comparing the analysis and forecast results from an assimilation–forecast system using one NOAA polar-orbiting satellite with results from using two and three polar-orbiting satellites in complementary orbits. The assimilation–forecast system used for these experiments is the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System–Global Forecast System (GDAS–GFS). The case studies chosen consist of periods during January–February and August–September 2003. Differences between the forecasts are accumulated over the two seasons and are analyzed to demonstrate the impact of these satellites. Anomaly correlations (ACs) and geographical forecasts (FIs) are evaluated for all experimental runs during both seasons. The anomaly correlations are generated using the standard NCEP verification software suite and cover the polar regions (60°–90°) and midlatitudes (20°–80°) of each hemisphere. The rms error for 850- and 200-hPa wind vector differences are shown for the tropical region (20°N–20°S). The geographical distribution of forecast impact on geopotential heights, relative humidity, precipitable water, and the u component of wind are also examined. The results demonstrate that the successive addition of each NOAA polar-orbiting satellite increases forecast quality. The use of three NOAA polar-orbiting satellites generally provides the largest improvement to the anomaly correlation scores in the polar and midlatitude regions. Improvements to the anomaly correlation scores are also realized from the use of two NOAA polar-orbiting satellites over only one. The forecast improvements from two satellites are generally smaller than if using three satellites, consistent with the increase in areal coverage obtained with the third satellite.

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Atlantic Tropical Cyclogenetic Processes during SOP-3 NAMMA in the GEOS-5 Global Data Assimilation and Forecast System

Journal of the Atmospheric Sciences ◽

10.1175/2009jas3123.1 ◽

2009 ◽

Vol 66 (12) ◽

pp. 3563-3578 ◽

Cited By ~ 28

Author(s):

Oreste Reale ◽

William K. Lau ◽

Kyu-Myong Kim ◽

Eugenia Brin

Keyword(s):

Data Assimilation ◽

Large Scale ◽

Thermal Structure ◽

Tropical Cyclogenesis ◽

Critical Threshold ◽

Forecast System ◽

Earth Observing System ◽

Moderate Resolution Imaging Spectroradiometer ◽

The One ◽

Global Data

Abstract This article investigates the role of the Saharan air layer (SAL) in tropical cyclogenetic processes associated with a nondeveloping and a developing African easterly wave observed during the Special Observation Period (SOP-3) phase of the 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA). The two waves are chosen because they both interact heavily with Saharan air. A global data assimilation and forecast system, the NASA Goddard Earth Observing System, version 5 (GEOS-5), is being run to produce a set of high-quality global analyses, inclusive of all observations used operationally but with additional satellite information. In particular, following previous works by the same authors, the quality-controlled data from the Atmospheric Infrared Sounder (AIRS) used to produce these analyses have a better coverage than the one adopted by operational centers. From these improved analyses, two sets of 31 five-day high-resolution forecasts, at horizontal resolutions of both half and quarter degrees, are produced. Results indicate that very steep moisture gradients are associated with the SAL in forecasts and analyses, even at great distances from their source over the Sahara. In addition, a thermal dipole in the vertical (warm above, cool below) is present in the nondeveloping case. The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Terra and Aqua satellites shows that aerosol optical thickness, indicative of more dust as opposed to other factors, is higher in the nondeveloping case. Altogether, results suggest that the radiative effect of dust may play some role in producing a thermal structure less favorable to cyclogenesis. Results also indicate that only global horizontal resolutions on the order of 20–30 km can capture the large-scale transport and the fine thermal structure of the SAL, inclusive of the sharp moisture gradients, reproducing the effect of tropical cyclone suppression that has been hypothesized by previous authors from observational and regional modeling perspectives. These effects cannot be fully represented at lower resolutions, therefore global resolution of a quarter of a degree is a minimum critical threshold necessary to investigate Atlantic tropical cyclogenesis from a global modeling perspective.

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