RESUMO
Satellite data assimilation requires a computationally fast and accurate radiative transfer model. Currently, three fast models are commonly used in the Numerical Weather Prediction models (NWP) for satellite data assimilation, including Radiative Transfer for TIROS Operational Vertical Sounder (RTTOV), Community Radiative Transfer Model (CRTM), and Advanced Radiative transfer Modeling System (ARMS). ARMS was initiated in 2018 and is now becoming the third pillar supporting many users in NWP and remote sensing fields. Its radiative transfer solvers (e.g. Doubling Adding method) is inherited from CRTM. In this study, we propose a Discrete Ordinate Adding Method (DOAM) to solve the radiative transfer equation including both solar and thermal source terms. In order to accelerate the DOAM computation, the single scattering approximation is used in the layer with an optical depth less than 10-8 or a single scattering albedo less than 10-10. From principles of invariance, the adding method is then applied to link the radiances between the layers. The accuracy of DOAM is evaluated through four benchmark cases. It is shown that the difference between DOAM and DIScrete Ordinate Radiative Transfer (DISORT) decreases with an increase of stream number. The relative bias of the 4-stream DOAM ranges from -5.03 % to 5.92 % in the triple layers of a visible wavelength case, while the maximum bias of the 8-stream DOAM is only about 1 %. The biases can be significantly reduced by the single scattering correction. Comparing to the visible case, the accuracy of the 4-stream DOAM is much higher in the thermal case with a maximum bias -1.69 %. Similar results are also shown in two multiple-layer cases. In the MacBook Pro (15-inch, 2018) laptop, the 2-stream DOAM only takes 1.68 seconds for calculating azimuthally independent radiance of 3000 profiles in the hyper-spectral oxygen A-band (wavelength ranges from 0.757 µm to 0.775 µm), while the 4-stream DOAM takes 4.06 seconds and the 16-stream DOAM takes 45.93 seconds. The time of the 2-, 4- and 16- stream DOAM are 0.86 seconds, 1.09 seconds and 4.34 seconds for calculating azimuthally averaged radiance. DISORT with 16 streams takes 1521.56 seconds and 127.64 seconds under the same condition. As a new solver, DOAM has been integrated into ARMS and is used to simulate the brightness temperatures at MicroWave Humidity Sounder (MWHS) as well as MicroWave Radiation Imager (MWRI) frequencies. The simulations by DOAM are compared to those by Doubling Adding method and accuracy of both solvers shows a general agreement. All the results show that the DOAM is accurate and computational efficient for applications in NWP data assimilation and satellite remote sensing.
RESUMO
Hematite is the absorbing mineral component of dust aerosols in the shortwave spectral region. However, dust shortwave absorption related to hematite suffers from significant uncertainties. In this study, we evaluated available hematite complex refractive index data in the literature on determining the dust effective refractive index at wavelengths ranging from 0.2 to 1.0 µm using rigorous T-matrix methods. Both spherical and super-spheroidal dust with hematite inclusions were examined to compute the dust optical properties and associated effective refractive indices. We found that the imaginary part of the effective refractive index retrieved from all available hematite complex refractive index data is larger than the measured effective values from Di Biagio et al. [Atmos. Chem. Phys.19, 15503, (2019)10.5194/acp-19-15503-2019]. The result obtained using the hematite refractive index from Hsu and Matijevic [Appl. Opt.241623 (1985)10.1364/AO.24.001623] is closest to but approximately two times larger than Di Biagio et al. [Atmos. Chem. Phys.19, 15503, (2019)10.5194/acp-19-15503-2019]. Our results emphasize the importance of accurate measurements of mineral refractive indices to clarify the dust absorption enigma.
RESUMO
The atmosphere-ocean coupled Hurricane Weather Research and Forecast model (HWRF) developed at the National Centers for Environmental Prediction (NCEP) is used as an example to illustrate the impact of model vertical resolution on track forecasts of tropical cyclones. A number of HWRF forecasting experiments were carried out at different vertical resolutions for Hurricane Joaquin, which occurred from September 27 to October 8, 2015, in the Atlantic Basin. The results show that the track prediction for Hurricane Joaquin is much more accurate with higher vertical resolution. The positive impacts of higher vertical resolution on hurricane track forecasts suggest that National Oceanic and Atmospheric Administration/NCEP should upgrade both HWRF and the Global Forecast System to have more vertical levels.
RESUMO
The Cross-track Infrared Sounder (CrIS) on the Suomi National Polar-orbiting Partnership Satellite (S-NPP) is a Fourier transform spectrometer and provides the sensor data record (SDR) that can be used to retrieve atmospheric temperature and water vapor profiles and can also be directly assimilated in numerical weather prediction models. The noise equivalent differential radiance (NEdN) is part of CrIS SDR products and represents the amount of random noise in the interferometer data. It is a crucial parameter that affects the accuracy of retrieval and satellite radiance assimilation. In this study, we used the international system of units (SI) traceable method Allan deviation to estimate the CrIS NEdN because the internal calibration target (ICT) radiance was slowly varying with time. Compared to the current standard deviation method, this study shows that the NEdN calculated from Allan deviation is converged to a stable value when a number of samples or the average window size is set to 510. Thus, Allan deviation can result in CrIS NEdN SI traceable noise. An optimal averaging window size is 30 if the NEdN is calculated from the standard deviation.
RESUMO
The advanced technology microwave sounder (ATMS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite is a total power radiometer and scans across the track within a range of ±52.77° from nadir. It has 22 channels and measures the microwave radiation at either quasi-vertical or quasi-horizontal polarization from the Earth's atmosphere. The ATMS sensor data record algorithm employed a commonly used two-point calibration equation that derives the earth-view brightness temperature directly from the counts and temperatures of warm target and cold space, and the earth-scene count. This equation is only valid under Rayleigh-Jeans (RJ) approximation. Impacts of RJ approximation on ATMS calibration biases are evaluated in this study. It is shown that the RJ approximation used in ATMS radiometric calibration results in errors on the order of 1-2 K. The error is also scene count dependent and increases with frequency.
RESUMO
The Cross-Track Infrared Sounder (CrIS) on the Suomi National Polar-Orbiting Partnership Satellite is a Fourier transform spectrometer and provides a total of 1305 channels for sounding the atmosphere. Quantifying the CrIS spectral accuracy, which is directly related to radiometric accuracy, is crucial for improving its data assimilation in numerical weather prediction. In this study, a cross-correlation method is used for detecting the effect of Earth-rotation Doppler shift (ERDS) on CrIS observations. Based on a theoretical calculation, the ERDS can be as large as about 1.3 parts in 10(6) (ppm) near Earth's equator and at the satellite scan edge for a field of regard (FOR) of 1 or 30. The CrIS observations exhibit a relative Doppler shift as large as 2.6 ppm for a FOR pair of 1 and 30 near the equator. The variation of the ERDS with latitude and scan position detected from CrIS observations is similar to that derived theoretically, which indicates that the spectral stability of the CrIS instrument is very high. To accurately calibrate CrIS spectral accuracy, the ERDS effect should be removed. Since the ERDS is easily predictable, the Doppler shift is correctable in the CrIS spectra.
RESUMO
The phase function is an important parameter that affects the distribution of scattered radiation. In Rayleigh scattering, a scatterer is approximated by a dipole, and its phase function is analytically related to the scattering angle. For the Henyey-Greenstein (HG) approximation, the phase function preserves only the correct asymmetry factor (i.e., the first moment), which is essentially important for anisotropic scattering. When the HG function is applied to small particles, it produces a significant error in radiance. In addition, the HG function is applied only for an intensity radiative transfer. We develop a combined HG and Rayleigh (HG-Rayleigh) phase function. The HG phase function plays the role of modulator extending the application of the Rayleigh phase function for small asymmetry scattering. The HG-Rayleigh phase function guarantees the correct asymmetry factor and is valid for a polarization radiative transfer. It approaches the Rayleigh phase function for small particles. Thus the HG-Rayleigh phase function has wider applications for both intensity and polarimetric radiative transfers. For microwave radiative transfer modeling in this study, the largest errors in the brightness temperature calculations for weak asymmetry scattering are generally below 0.02 K by using the HG-Rayleigh phase function. The errors can be much larger, in the 1-3 K range, if the Rayleigh and HG functions are applied separately.
RESUMO
Microwave observations made at the third and fourth Stokes parameters can be used to determine the surface wind direction over oceans. However, due to their smaller amplitudes (less than 3 K at the third Stokes parameter and 1 K at the fourth Stokes parameter), the absolute calibration to these measurements becomes crucial. A new methodology is developed in this study to calibrate the Windsat third and fourth Stokes parameters through tropical rain forest measurements over the Amazon and central Africa. It is found that the Windsat fourth Stokes parameter at 18 GHz has biases of the order of 0.5 K, which could severely affect the wind vector retrievals.