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Wen Chen, Rachel T. Pinker, Yingtao Ma, Glynn Hulley, Eva Borbas, Tanvir Islam, Kerry-A. Cawse-Nicholson, Simon Hook, Chris Hain, and Jeff Basara


Land surface temperature (LST) is an important climate parameter that controls the surface energy budget. For climate applications, information is needed at the global scale with representation of the diurnal cycle. To achieve global coverage there is a need to merge about five independent geostationary (GEO) satellites that have different observing capabilities. An issue of practical importance is the merging of independent satellite observations in areas of overlap. An optimal approach in such areas could eliminate the need for redundant computations by differently viewing satellites. We use a previously developed approach to derive information on LST from GOES-East (GOES-E), modify it for application to GOES-West (GOES-W) and implement it simultaneously across areas of overlap at 5-km spatial resolution. We evaluate the GOES-based LST against in situ observations and an independent MODIS product for the period of 2004–09. The methodology proposed minimizes differences between satellites in areas of overlap. The mean and median values of the differences in monthly mean LST retrieved from GOES-E and GOES-W at 0600 UTC for July are 0.01 and 0.11 K, respectively. Similarly, at 1800 UTC the respective mean and median value of the differences were 0.15 and 1.33 K. These findings can provide guidelines for potential users to decide whether the reported accuracy based on one satellite alone, meets their needs in area of overlap. Since the 6 yr record of LST was produced at hourly time scale, the data are well suited to address scientific issues that require the representation of LST diurnal cycle or the diurnal temperature range (DTR).

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Robert A. Houze Jr., Shuyi S. Chen, Wen-Chau Lee, Robert F. Rogers, James A. Moore, Gregory J. Stossmeister, Michael M. Bell, Jasmine Cetrone, Wei Zhao, and S. Rita Brodzik

The Hurricane Rainband and Intensity Change Experiment (RAINEX) used three P3 aircraft aided by high-resolution numerical modeling and satellite communications to investigate the 2005 Hurricanes Katrina, Ophelia, and Rita. The aim was to increase the understanding of tropical cyclone intensity change by interactions between a tropical cyclone's inner core and rainbands. All three aircraft had dual-Doppler radars, with the Electra Doppler Radar (ELDORA) on board the Naval Research Laboratory's P3 aircraft, providing particularly detailed Doppler radar data. Numerical model forecasts helped plan the aircraft missions, and innovative communications and data transfer in real time allowed the flights to be coordinated from a ground-based operations center. The P3 aircraft released approximately 600 dropsondes in locations targeted for optimal coordination with the Doppler radar data, as guided by the operations center. The storms were observed in all stages of development, from tropical depression to category 5 hurricane. The data from RAINEX are readily available through an online Field Catalog and RAINEX Data Archive. The RAINEX dataset is illustrated in this article by a preliminary analysis of Hurricane Rita, which was documented by multiaircraft flights on five days 1) while a tropical storm, 2) while rapidly intensifying to a category 5 hurricane, 3) during an eye-wall replacement, 4) when the hurricane became asymmetric upon encountering environmental shear, and 5) just prior to landfall.

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Guo-Yuan Lien, Chung-Han Lin, Zih-Mao Huang, Wen-Hsin Teng, Jen-Her Chen, Ching-Chieh Lin, Hsu-Hui Ho, Jyun-Ying Huang, Jing-Shan Hong, Chia-Ping Cheng, and Ching-Yuang Huang


The FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) Radio Occultation (RO) satellite constellation was launched on June 2019 as a successor of the FORMOSAT-3/COSMIC mission. The Central Weather Bureau (CWB) of Taiwan has received FORMOSAT-7/COSMIC-2 GNSS RO data in real time from Taiwan Analysis Center for COSMIC. With the global numerical prediction system at CWB, a parallel semi-operational experiment assimilating the FORMOSAT-7/COSMIC-2 bending angle data with all other operational observation data has been conducted to evaluate the impact of the FORMOSAT-7/COSMIC-2 data. The first seven-month results show that the quality of the early FORMOSAT-7/COSMIC-2 data has been satisfactory for assimilation. Consistent and significant positive impacts on global forecast skills have been observed since the start of the parallel experiment, with the most significant impact found in the tropical region, reflecting the low-inclination orbital design of the satellites. The impact of the FORMOSAT-7/COSMIC-2 RO data is also estimated using the Ensemble Forecast Sensitivity to Observation Impact (EFSOI) method, showing an average positive impact per observation similar to other existing GNSS RO datasets, while the total impact is impressive by virtue of its large amount. Sensitivity experiments suggest that the quality control processes built in the Gridpoint Statistical Interpolation (GSI) system for RO data work well to achieve a positive impact by the low-level FORMOSAT-7/COSMIC-2 RO data, while more effort on observation error tuning should be focused to obtain an optimal assimilation performance. This study demonstrates the usefulness of the FORMOSAT-7/COSMIC-2 RO data in global numerical weather prediction during the calibration/validation period and leads to the operational use of the data at CWB.

Open access
Travis A. O’Brien, Ashley E. Payne, Christine A. Shields, Jonathan Rutz, Swen Brands, Christopher Castellano, Jiayi Chen, William Cleveland, Michael J. DeFlorio, Naomi Goldenson, Irina V. Gorodetskaya, Héctor Inda Díaz, Karthik Kashinath, Brian Kawzenuk, Sol Kim, Mikhail Krinitskiy, Juan M. Lora, Beth McClenny, Allison Michaelis, John P. O’Brien, Christina M. Patricola, Alexandre M. Ramos, Eric J. Shearer, Wen-Wen Tung, Paul A. Ullrich, Michael F. Wehner, Kevin Yang, Rudong Zhang, Zhenhai Zhang, and Yang Zhou
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