The SPRINTARS version 3.80/4D-Var data assimilation system: development and inversion experiments based on the observing system simulation experiment framework

Yumimoto, Keiya

doi:10.5194/gmd-6-2005-2013

Cited by 25 publications

(19 citation statements)

References 58 publications

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“…Hakami et al (2005) and Yumimoto et al (2007Yumimoto et al ( , 2008 attempted to apply a four-dimensional variational method (a so-called advanced data assimilation method) to inverse modeling of black carbon (BC) and dust aerosols with ground-based observations and regional models. To date, measurements obtained by various observation platforms, including MODIS (Dai et al, 2014;Huneeus et al, 2012;Wang et al, 2012;Zhang et al, 2008), CALIPSO (Sekiyama et al, 2010;Zhang et al, 2011Zhang et al, , 2014, Himawari 8 (Yumimoto et al, 2016), AERONET (Schutgens et al, 2010a), and surface PM 10 (particulate matter with diameters less than 10 µm) monitoring systems (Tombette et al, 2009;Lee et al, 2013;Jiang et al, 2013), have been used in assimilation studies adopting both variational (Benedetti et al, 2009;Dubovik et al, 2008;Hakami et al, 2007;Henze et al, 2007;Yumimoto and Takemura, 2013) and ensemble-based Schutgens et al, 2010b;Di Tomaso et al, 2017;Yumimoto and Takemura, 2011) methods.…”

Section: Introductionmentioning

confidence: 99%

JRAero: the Japanese Reanalysis for Aerosol v1.0

et al. 2017

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Abstract. A global aerosol reanalysis product named the Japanese Reanalysis for Aerosol (JRAero) was constructed by the Meteorological Research Institute (MRI) of the Japan Meteorological Agency. The reanalysis employs a global aerosol transport model developed by MRI and a twodimensional variational data assimilation method. It assimilates maps of aerosol optical depth (AOD) from MODIS onboard the Terra and Aqua satellites every 6 h and has a TL159 horizontal resolution (approximately 1.1 • × 1.1 • ). This paper describes the aerosol transport model, the data assimilation system, the observation data, and the setup of the reanalysis and examines its quality with AOD observations.Comparisons with MODIS AODs that were used for the assimilation showed that the reanalysis showed much better agreement than the free run (without assimilation) of the aerosol model and improved under-and overestimation in the free run, thus confirming the accuracy of the data assimilation system. The reanalysis had a root mean square error (RMSE) of 0.05, a correlation coefficient (R) of 0.96, a mean fractional error (MFE) of 23.7 %, a mean fractional bias (MFB) of 2.8 %, and an index of agreement (IOA) of 0.98. The better agreement of the first guess, compared to the free run, indicates that aerosol fields obtained by the reanalysis can improve short-term forecasts.AOD fields from the reanalysis also agreed well with monthly averaged global AODs obtained by the Aerosol Robotic Network (AERONET) (RMSE = 0.08, R = 0.90, MFE = 28.1 %, MFB = 0.6 %, and IOA = 0.93). Site-by-site comparison showed that the reanalysis was considerably better than the free run; RMSE was less than 0.10 at 86.4 % of the 181 AERONET sites, R was greater than 0.90 at 40.7 % of the sites, and IOA was greater than 0.90 at 43.4 % of the sites. However, the reanalysis tended to have a negative bias at urban sites (in particular, megacities in industrializing countries) and a positive bias at mountain sites, possibly because of insufficient anthropogenic emissions data, the coarse model resolution, and the difference in representativeness between satellite and ground-based observations.

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Section: Introductionmentioning

confidence: 99%

JRAero: the Japanese Reanalysis for Aerosol v1.0

et al. 2017

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“…However, larger source regions show substantial fine structure and throughout the world there are also many individual sources such as in Patagonia, the Arctic plains, and countless dry or drying lake beds. Estimating dust emissions sources can also be performed with satellite data (for examples see Huneeus et al, 2012;Schutgens et al, 2012;Yumimoto and Takemura, 2013;Escribano et al, 2016Escribano et al, , 2017Di Tomaso et al, 2017). Dust models typically employ maps of dust source functions (e.g., Zender et al, 2003;Ginoux et al, 2012) because soil properties in arid and hyper-arid regions from global inventories are insufficient to provide consistent soil texture information.…”

Section: User Requirements For Desert Mineral Dust Emissionsmentioning

confidence: 99%

Status and future of numerical atmospheric aerosol prediction with a focus on data requirements

et al. 2018

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Abstract. Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas-aerosol partitioning, chemical transformation and growth, hygroscopicity). Finally, there are fundamental uncertainties and significant processing overhead in the diverse observations used for verification and assimilation within these systems. Indeed, a significant component of aerosol forecast development consists in streamlining aerosol-related observations and reducing the most important errors through model development and data assimilation. Aerosol particle observations from satellite-and groundbased platforms have been crucial to guide model development of the recent years and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near surface, and aircraft) and freely shared. This paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centers. While some of the requirements are equally applicable to aerosol-climate, the focus here is on global operational prediction of aerosol properties such as mass concentrations and optical parameters. It is also recognized that the term "requirements" is loosely used here given the diversity in global aerosol observing systems and that utilized data are typically not from operational sources. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of "bin" and bulk schemes with limited capability of simulating the size information. However the next generation of aerosol operational models will output both mass and number density concentration to provide a more complete description of the aerosol population. A brief overview of the state of the art is provided with an introduction on the importance of ...

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“…However, Fushimi et al (2011) and Chatani et al (2014) suggested that the difference in the EC concentrations between WRF-CMAQ and the measurements is largely attributed to an underestimation of the EC emission inventory, especially open biomass burning from domestic 252 D. Goto et al: Application of a global nonhydrostatic model to regional aerosol simulations around Japan sources. The local EC emission can be estimated by a combination of the data assimilation and intensive measurements (Schutgens et al, 2012;Wang et al, 2012;Yumimoto and Takemura, 2013).…”

Section: Uncertainty In the Simulationmentioning

confidence: 99%

Application of a global nonhydrostatic model with a stretched-grid system to regional aerosol simulations around Japan

et al. 2015

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Abstract. An aerosol-coupled global nonhydrostatic model with a stretched-grid system has been developed. Circulations over the global and target domains are simulated with a single model, which includes fine meshes covering the target region to calculate meso-scale circulations. The stretched global model involves lower computational costs to simulate atmospheric aerosols with fine horizontal resolutions compared with a global uniform nonhydrostatic model, whereas it may require higher computational costs compared with the general regional models, because the stretched-grid system calculates inside and outside the target domain. As opposed to general regional models, the stretched-grid system requires neither a nesting technique nor lateral boundary conditions. In this study, we developed a new-type regional model for the simulation of aerosols over Japan, especially in the Kanto areas surrounding Tokyo, with a maximum horizontal resolution of approximately 10 km. This model usually reproduces temporal variations and their averages of the observed weather around Japan. This model generally reproduces monthly mean distributions of the observed sulfate and SO 2 over East Asia, with high correlations (R > 0.6), but the underestimation of the simulated concentrations by 40 % (sulfate) and 50 % (SO 2 ). Their underestimation of the simulated sulfate and SO 2 concentrations over East Asia are strongly affected by their underestimation in China and possibly by the uncertainty of the simulated precipitation around Japan. In the Kanto area, this model succeeds in simulating the wind patterns and the diurnal transitions around the center of the Kanto area, although it is inadequate to simulate the wind patterns and the diurnal transitions at some sites located at the edge of the Kanto area and surrounded on three sides by mountains, e.g., Maebashi, mainly due to the insufficient horizontal resolution. This model also generally reproduces both diurnal and synoptic variations of the observed and/or a regional aerosol-transport model, WRF-CMAQ, simulated EC, sulfate, and SO 2 concentrations in the Kanto area, especially with their high correlation (R > 0.5) at Komae/Tokyo. Although the aerosol module used in this study is relatively simplified compared to the general regional aerosol models, this study reveals that our proposed model with the stretchedgrid system can be applicable for the regional aerosol simulation.Published by Copernicus Publications on behalf of the European Geosciences Union. D. Goto et al.: Application of a global nonhydrostatic model to regional aerosol simulations around Japan

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The SPRINTARS version 3.80/4D-Var data assimilation system: development and inversion experiments based on the observing system simulation experiment framework

Cited by 25 publications

References 58 publications

JRAero: the Japanese Reanalysis for Aerosol v1.0

JRAero: the Japanese Reanalysis for Aerosol v1.0

Status and future of numerical atmospheric aerosol prediction with a focus on data requirements

Application of a global nonhydrostatic model with a stretched-grid system to regional aerosol simulations around Japan

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