This study addresses two key uncertainties in the fire radiative power (FRP) retrieval, which is essential for improving global top-down fire emission inventories. First, it proposes a novel FRP retrieval method by combining the ~4 and$\sim 8.6~\mu $m channels based on Monte Carlo simulation, which is verified using the Visible Infrared Imaging Radiometer Suite (VIIRS). The inclusion of the$\sim 8.6~\mu $m channel significantly improves the accuracy of FRP retrieval, especially for highly smoldering fires. Second, atmospheric correction is conducted using outputs from the state-of-the-art unified linearized vector radiative transfer model (UNL-VRTM). The importance of atmospheric correction is demonstrated through the single-channel ($\sim 4~\mu $m) FRP retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire (AF), VIIRS AF, and VIIRS second-generation fire light detection algorithm (FILDA-2) products. Post-correction results show effective mitigation of nighttime FRP angular dependency, achieved by considering the enhanced atmospheric attenuation due to longer path length off-nadir. However, a residual daytime FRP angular dependency remains, likely due to the angular dependency of the thresholds used for daytime fire detection. Additionally, an enhanced agreement is observed between the VIIRS FILDA-2 FRP retrievals from the Suomi National Polar-orbiting Partnership (NPP) and National Oceanic and Atmospheric Administration (NOAA)-20 satellites after correction. Lastly, a global FRP increase is noted across all three products, with VIIRS AF and VIIRS FILDA-2 showing more significant increases (65.8% and 62.5%, respectively) than MODIS AF (20.8%). These advancements in FRP retrievals may enhance the downstream fire emission products, which will benefit the air pollution modeling community.

We present the second-generation Fire Light Detection Algorithm (FILDA-2), which includes advances in fire detection and retrievals of radiative power (FRP), fire visible energy fraction (VEF), and fire modified combustion efficiency (MCE) at nighttime from the holistic use of multiple-spectral radiances measured by the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP (VNP) and NOAA-20/JPSS-1 (VJ1) satellites. Key enhancements include: (1) a new fast algorithm that maps VIIRS Day/Night Band (DNB) radiances to the pixel footprints of VIIRS Moderate (M) and Imagery (I) bands; (2) identification of potential fire pixels through the use of the DNB anomalies and I-Band thermal anomalies; (3) dynamic thresholds for contextual testing of fire pixels; and (4) pixel-specific estimates of FRP, VEF, and MCE. The global benchmark test demonstrates that FILDA-2 can detect approximately 25-30% more smaller and cooler fires than the operational VIIRS Active Fire 375 m I-band algorithm with the added benefit of providing daily global pixel-level characterizations of MCE for nighttime surface fires. The MCE derived by FILDA-2 is in good agreement with limited ground-based observations near the fires. Additionally, FILDA-2 reduces angular dependence in FRP estimates and significantly reduces the ”bow-tie” (double-counting) effect in fire detection compared to the AF-I product. The cross-validation of FILDA-2 products from VNP and VJ1 retrievals confirms good consistency in FRP and MCE retrievals globally. FILDA-2 is being implemented by NASA to generate a new VIIRS data product for fire monitoring, chemical-speciated fire emission estimates, and fire line characterization.

Asian summer monsoon and atmospheric aerosol simultaneously influence the climate in the East Asian region. However, substantial uncertainties exist in the current understanding of the interactions between monsoon and aerosol and their combined effects. Previous studies have shown that aerosols influence the strength of monsoon and monsoon-related water cycles; however, monsoon strongly regulates the aerosol spatial distribution. This letter investigates the radiative flux response at the top of the atmosphere to the Asian summer monsoon by using observations made by the Clouds and Earth's Radiant Energy System and the Moderate Resolution Imaging Spectroradiometer. In comparison with the ten-year (2002-2011) mean climatology, the aerosol radiative effect is estimated over two eastern Asia regions for the months of July in 2002 and 2003, corresponding to a weak and a strong summer monsoon event, respectively. The dramatically different influences show the aerosol radiative forcing over land to be strongly responsive to Asian summer monsoon. Furthermore, the reanalysis-based estimate of the aerosol radiative effect is consistent with its observation-only counterpart.

Abstract Typical weather and climate models need a software tool to couple sub‐scale model components. The high‐performance computing requirements and a variety of model interfaces make the development of such a coupling tool very challenging. In this paper, we describe the approach of the Earth System Modeling Framework, in particular its component and coupling mechanism, and present the results of three cross‐organization model interoperability experiments. Copyright © 2006 John Wiley & Sons, Ltd.

This presentation discusses the NASA data assimilation project at the Data Assimilation Office at the NASA/Goddard Space Flight Center. The goal is to produce accurate gridded datasets of atmospheric fields by assimilating a range of observations along with physically consistent model forecasts. This work produces datasets that are used by the climate research community. The data come from conventional sources that are used for weather forecasts (e.g., radiosondes, earth-surface measurements, and satellite temperature retrievals), as well as new sources such as satellites that will be launched under the Mission To Planet Earth Enterprise. An end-to-end Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) currently supports stratospheric flight missions and reanalysis projects for NASA. The current Core of this system (Model, and Analysis) is a multitasking algorithm that runs on Cray J90 and C90 computers at Goddard and NASA Ames Research Center. Future Core computing will be carried out at Ames, with a new production system scheduled to be ready for the EOS AM-1 satellite launch in June of 1998. The DAO has acquired SGI Origin 2000 computers, with an aggregate of 160 processors in place at Ames, and more planned for the future. The DAO is currently updating the control scripts and programs, and implementing a modular Fortran 90 Core system. During 1998 the Core system will be migrated to distributed-memory software using the Message Passing Interface. Part of this work is being carried out under the NASA High Performance Computing and Communications Earth and Space Sciences program. The algorithmic and performance issues involved in Core system are the main subject of this presentation.