Community Radiative Transfer Model for Stratospheric Sounding Unit

Abstract

To better use the Stratospheric Sounding Unit (SSU) data for reanalysis and climate studies, issues associated with the fast radiative transfer (RT) model for SSU have recently been revisited and the results have been implemented into the Community Radiative Transfer Model version 2. This study revealed that the spectral resolution for the sensor's spectral response functions (SRFs) calculations is very important, especially for channel 3. A low spectral resolution SRF results, on average, in 0.6-K brightness temperature (BT) errors for that channel. The variations of the SRFs due to the CO 2 cell pressure variations have been taken into account. The atmospheric transmittance coefficients of the fast RT model for the Television and Infrared Observation Satellite (TIROS)-N, NOAA-6, NOAA-7, NOAA-8, NOAA-9, NOAA-11, and NOAA-14 have been generated with CO 2 and O 3 as variable gases. It is shown that the BT difference between the fast RT model and line-by-line model is less than 0.1 K, but the fast RT model is at least two orders of magnitude faster. The SSU measurements agree well with the simulations that are based on the atmospheric profiles from the Earth Observing System Aura Microwave Limb Sounding product and the Sounding of the Atmosphere using Broadband Emission Radiometry on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. The impact of the CO 2 cell pressures shift for SSU has been evaluated by using the Committee on Space Research (COSPAR) International Reference Atmosphere (CIRA) model profiles. It is shown that the impacts can be on an order of 1 K, especially for SSU NOAA-7 channel 2. There are large brightness temperature gaps between observation and model simulation using the available cell pressures for NOAA-7 channel 2 after June 1983. Linear fittings of this channel's cell pressures based on previous cell leaking behaviors have been studied, and results show that the new cell pressures are reasonable. The improved SSU fast model can be applied for reanalysis of the observations. It can also be used to address two important corrections in deriving trends from SSU measurements: CO 2 cell leaking correction and atmospheric CO 2 concentration correction.

Construction of Stratospheric Temperature Data Records from Stratospheric Sounding Units

“…(1) is that these correction terms are all uncorrelated, though the situation is much complicated in the real world. We use the Community Radiative Transfer Model (CRTM; Han et al 2006;Chen et al 2011) simulations to estimate these correction terms. Developed recently at the Joint Center for Satellite Data Assimilation (JCSDA), the CRTM SSU model can well handle the varying cell pressures and atmospheric CO 2 concentration (Chen et al 2011).…”

“…During the satellite operational period, unfortunately, CO 2 gas leakage occurred for all satellites. This caused the instrument cell pressure to decrease and channel weighting functions to peak at different layers with satellite operational time, resulting in a time-varying change in brightness temperature (BT) measurements (Brindley et al 1999;Kobayashi et al 2009;Chen et al 2011). In addition, the cell pressures were not identical among different SSU instruments, which introduced intersatellite biases when linking the observations on different satellites.…”

“…Second, the SSU instruments sense radiation in the 15-mm atmospheric CO 2 absorption band and, hence, their weighting functions are sensitive to changes in atmospheric CO 2 concentration (Shine et al 2008;Chen et al 2011). As atmospheric CO 2 slowly increased, the weighting functions of the three SSU channels would gradually move to higher altitude.…”

“…Our aim is to create a new SSU dataset with nadirlike, gridded BTs that correspond to identical weighting functions with a fixed local observational time from three SSU channels by exploiting the observations from all view angles. We take advantage of the recent advances in the SSU radiative transfer modeling development in our data construction (Kobayashi et al 2009;Chen et al 2011) to handle the varying instrument cell pressures and increasing atmospheric CO 2 concentration. Three SSU channels are referred as channels 1, 2, and 3 in this study, which correspond to channels 25, 26, and 27 in Nash dataset.…”

Reduced major axis approach for correcting GPM/GMI radiometric biases to coincide with radiative transfer simulation

“…The CRTM is developed by the Joint Center for Satellite Data Assimilation (JCSDA) at the NOAA. A thorough description of the CRTM model is depicted in Chen et al [5], Chen et al [4], Ding et al [6], among others. It is a fast radiative transfer model for simulation of satellite radiances.…”