Sense size‐dependent dust loading and emission from space using reflected solar and infrared spectral measurements: An observation system simulation experiment

Abstract

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) satellite mission observes hyperspectral Earth reflected solar (RS) and emitted infrared radiance (IR). Such measurements span an additional dimension on spectrally dependent scattering and absorption of dust, the critical signals for particle size. Through a suite of observation system simulation experiments (OSSEs), this study assesses the capability of CLARREO's measurements for recovering size‐dependent dust emissions in GEOS‐Chem chemistry transport model (CTM). To this end, another CTM (Flow‐following finite‐volume Icosahedral Model‐Chem, or FIM‐Chem) is used for the nature run to simulate CLARREO spectral radiances. The spectral signals are then used for analyzing the sensitivities and error characteristics of dust optical depth (DOD) under three observations scenarios (IR only, RS only, and combined IR and RS) using an optimal estimation technique. Next, these synthetic data are assimilated into GEOS‐Chem adjoint model to constrain dust emissions of four particle sizes with radii from 0.1 μm to 6.0 μm. The OSSEs results indicate (1) the IR spectra are most sensitive to dust of the third size bin (1.8–3.0 μm) and least sensitive to the smallest bin (0.1–1.0 μm); (2) the RS spectra are most sensitive to dust of the smallest size bin and the sensitivity decreases as dust size increases; (3) combining IR and RS spectra can fully characterize DOD across all sizes, providing the best constraints for size‐resolved dust emissions; and (4) CLARREO data fail to constrain the spatial distribution of dust sources due to its narrow swath and joint observations from CLARREO‐calibrated sensors with wide swath are desirable.

Identification and Characterization of Dust Source Regions Across North Africa and the Middle East Using MISR Satellite Observations

“…Furthermore, combining MISR DAOD at different wavelengths and multispectral measurements from other satellite instruments provides complementary constraints for model simulation of size-dependent dust emission (Ginoux et al, 2010;Wang et al, 2012;Xu et al, 2017). By quantifying the probability of dust activation at each grid cell from the MISR CMVP, MISR DAOD, MODIS AOD, and SEVIRI DSF, using inverse modeling techniques with statistical or dynamical models, a gridded, daily dust source activity data set will facilitate a more accurate dust source map for the study region.…”

“…By quantifying the probability of dust activation at each grid cell from the MISR CMVP, MISR DAOD, MODIS AOD, and SEVIRI DSF, using inverse modeling techniques with statistical or dynamical models, a gridded, daily dust source activity data set will facilitate a more accurate dust source map for the study region. Furthermore, combining MISR DAOD at different wavelengths and multispectral measurements from other satellite instruments provides complementary constraints for model simulation of size-dependent dust emission (Ginoux et al, 2010;Wang et al, 2012;Xu et al, 2017). By applying the aforementioned accurate dust source map and size-dependent dust loading and emission constraints, the representation of dust aerosols and their feedbacks to the climate in coupled Earth System Models will potentially be improved Heinold et al, 2016), leading to more credible simulations of the current climate state, dust-climate feedbacks, and future projections of aerosol concentration and the impacts of dust aerosols on climate.…”

The influence of simulated surface dust lofting and atmospheric loading on radiative forcing

“…1. WRF was run with the GOCART dust aerosol module (Ginoux et al, 2001), Morrison two-moment microphysics (Morrison et al, 2005(Morrison et al, , 2009), specified aerosol optical properties (Barnard et al, 2010), RRTMG longwave radiation (Iacono et al, 2008), Goddard shortwave radiation (Chou and Suarez, 1999), NOAH Land Surface Model Yang et al, 2011), BMJ cumulus parameterization on the coarse-grid domain (Janjic, 1994), and MYNN level 3 boundary-layer parameterization Niino, 2006, 2009). A summary of the WRF model configuration and a general description of the physics packages used for simulations in this study are given in Table 2.…”

“…Initialization GDAS-FNL reanalysis 1 • data Boundary conditions Lateral boundary nudging from gridded reanalysis (Davies, 1983) Land-surface model NOAH Yang et al, 2011) Cumulus parameterization BMJ parameterization (Janjic, 1994) on Grid 1 Arab Emirates (UAE; Fig. 3).…”

Improving Remote Sensing of Aerosol Microphysical Properties by Near‐Infrared Polarimetric Measurements Over Vegetated Land: Information Content Analysis

“…The outputs of UNL‐VRTM include not only full elements of the Stokes vector but also their sensitivities (i.e., Jacobians) with respect to various parameters that are relevant to the aerosol microphysics and optical properties, gas absorption, and surface properties. UNL‐VRTM has also been widely used to study information contents and develop inversion algorithm for the retrieval of aerosols and surface properties from various measurements (Chen, Wang, et al, ; Ding et al, ; Hou et al, , ; Wang et al, ; Xu et al, ; Xu, Wang, Wang, Henze, et al, ; Xu, Wang, Wang, Zeng, et al, ; Xu & Wang, ).…”