Operational calibration of Geostationary Operational Environmental Satellite-8 and-9 imagers and sounders

A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific

Geostationary satellites can retrieve the cloud droplet effective radius (re) but suffer biases from cloud inhomogeneities, internal retrieval nonlinearities, and 3-D scattering/shadowing from neighboring clouds, among others. A 1-D retrieval method was applied to Geostationary Operational Environmental Satellite 13 (GOES-13) imagery, over large areas in South America (5∘ N–30∘ S; 20∘–70∘ W), the Southeast Pacific (5∘ N–30∘ S; 70∘–120∘ W), and the Amazon (2∘ N–7∘ S; 54∘–73∘ W), for four months in each year from 2014–2017. Results were compared against in situ aircraft measurements and the Moderate Resolution Imaging Spectroradiometer cloud product for Terra and Aqua satellites. Monthly regression parameters approximately followed a seasonal pattern. With up to 108,009 of matchups, slope, intercept, and correlation for Terra (Aqua) ranged from about 0.71 to 1.17, −2.8 to 2.5 μm, and 0.61 to 0.91 (0.54 to 0.78, −1.5 to 1.8 μm, 0.63 to 0.89), respectively. We identified evidence for re overestimation (underestimation) correlated with shadowing (enhanced reflectance) in the forward (backscattering) hemisphere, and limitations to illumination and viewing configurations accessible by GOES-13, depending on the time of day and season. A proposition is hypothesized to ameliorate 3-D biases by studying relative illumination and cloud spatial inhomogeneity.

High-accuracy source-independent radiometric calibration with low complexity for infrared photonic sensors

Radiometric calibration (RC) is an essential solution to guarantee measurements from infrared photonic sensors with certain accuracy, the main task of which is to determine the radiometric responsivity of sensor and usually be solved by comparing with some radiation source (i.e., blackbody), called source-based RC (SBRC). In addition to the complexity in manufacture, the nonideal characteristics of an available source will inevitably introduce unexpected uncertainties to reduce the final calibration accuracy by around 0.2-0.5 K in SBRC. Therefore, we propose an original source-independent RC (SIRC) principle based on modeling instead of comparing for SBRC, where the incident background radiation to detector, as a dominated factor influencing the responsivity characteristics of a photonic sensor, is modeled to implement RC for both two fundamental types (photoconductive and photovoltaic) of HgCdTe photonic detectors. The SIRC merely requires the temperature information of main components of a sensor other than some complex source and its assembly, and provides a traceable way at lower uncertainty costs relative to the traditional SBRC. The SIRC is being implemented in Fengyun-2 satellites since 2019, which ensures a long-term stable service of Chinese geostationary meteorological satellites for the global observation system under the framework of World Meteorological Organization. Moreover, a 20-year-period traceable Fengyun-2 dataset to be recalibrated with SIRC will benefit the further climate applications.

Towards a Unified and Coherent Land Surface Temperature Earth System Data Record from Geostationary Satellites

Our objective is to develop a framework for deriving long term, consistent Land Surface Temperatures (LSTs) from Geostationary (GEO) satellites that is able to account for satellite sensor updates. Specifically, we use the Radiative Transfer for TOVS (RTTOV) model driven with Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) information and Combined ASTER and MODIS Emissivity over Land (CAMEL) products. We discuss the results from our comparison of the Geostationary Operational Environmental Satellite East (GOES-E) with the MODIS Land Surface Temperature and Emissivity (MOD11) products, as well as several independent sources of ground observations, for daytime and nighttime independently. Based on a six-year record at instantaneous time scale (2004–2009), most LST estimates are within one std from the mean observed value and the bias is under 1% of the mean. It was also shown that at several ground sites, the diurnal cycle of LST, as averaged over six years, is consistent with a similar record generated from satellite observations. Since the evaluation of the GOES-E LST estimates occurred at every hour, day and night, the data are well suited to address outstanding issues related to the temporal variability of LST, specifically, the diurnal cycle and the amplitude of the diurnal cycle, which are not well represented in LST retrievals form Low Earth Orbit (LEO) satellites.

On the Methods for Recalibrating Geostationary Longwave Channels Using Polar Orbiting Infrared Sounders

This study presents a common recalibration method that has been applied to geostationary imagers’ infrared (IR) and water vapour (WV) channel measurements, referred to as the multi-sensor infrared channel calibration (MSICC) method. The method relies on data of the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS), and High-Resolution Infrared Radiation Sounder (HIRS/2) on polar orbiting satellites. The geostationary imagers considered here are VISSR/JAMI/IMAGER on JMA’s GMS/MTSAT series and MVIRI/SEVIRI on EUMETSAT’s METEOSAT series. IASI hyperspectral measurements are used to determine spectral band adjustment factors (SBAF) that account for spectral differences between the geostationary and polar orbiting satellite measurements. A new approach to handle the spectral gaps of AIRS measurements using IASI spectra is developed and demonstrated. Our method of recalibration can be directly applied to the lowest level of geostationary measurements available, i.e., digital counts, to obtain recalibrated radiances. These radiances are compared against GSICS-corrected radiances and are validated against SEVIRI radiances, both during overlapping periods. Significant reduction in biases have been observed for both IR and WV channels, 4% and 10%, respectively compared to the operational radiances.

CALIPSO IIR Version 2 Level 1b calibrated radiances: analysis and reduction of residual biases in the Northern Hemisphere

Version 2 of the Level 1b calibrated radiances of the Imaging Infrared Radiometer (IIR) on board the Cloud-Aerosol Lidar and Infrared Satellite Observation (CALIPSO) satellite has been released recently. This new version incorporates corrections of small but systematic seasonal calibration biases previously revealed in Version 1 data products mostly north of 30° N. These biases of different amplitudes in the three IIR channels 8.65 µm (IIR1), 10.6 µm (IIR2), and 12.05 µm (IIR3) were made apparent by a striping effect in images of IIR inter-channel brightness temperature differences (BTDs) and through seasonal warm biases of nighttime IIR brightness temperatures in the 30-60° N latitude range. The latter were highlighted through observed and simulated comparisons with similar channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua spacecraft. To characterize the calibration biases affecting Version 1 data, a semi-empirical approach is developed, which is based on the in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels. Two types of calibration biases are revealed: an equalization bias affecting part of the individual IIR images and a global bias affecting the radiometric level of each image. These biases are observed only when the temperature of the instrument increases, and they are found to be functions of elapsed time since night-to-day transition, regardless of the season. Correction coefficients of Version 1 radiances could thus be defined and implemented in the Version 2 code. As a result, the striping effect seen in Version 1 is significantly attenuated in Version 2. Systematic discrepancies between nighttime and daytime IIR-MODIS BTDs in the 30-60° N latitude range in summer are reduced from 0.2 K in Version 1 to 0.1 K in Version 2 for IIR1-MODIS29. For IIR2-MODIS31 and IIR3-MODIS32, they are reduced from 0.4 K to close to zero, except for IIR3-MODIS32 in June, where the night-minus-day difference is around -0.1 K.

A solar radiation database for Chile

Chile hosts some of the sunniest places on earth, which has led to a growing solar energy industry in recent years. However, the lack of high resolution measurements of solar irradiance becomes a critical obstacle for both financing and design of solar installations. Besides the Atacama Desert, Chile displays a large array of “solar climates” due to large latitude and altitude variations, and so provides a useful testbed for the development of solar irradiance maps. Here a new public database for surface solar irradiance over Chile is presented. This database includes hourly irradiance from 2004 to 2016 at 90 m horizontal resolution over continental Chile. Our results are based on global reanalysis data to force a radiative transfer model for clear sky solar irradiance and an empirical model based on geostationary satellite data for cloudy conditions. The results have been validated using 140 surface solar irradiance stations throughout the country. Model mean percentage error in hourly time series of global horizontal irradiance is only 0.73%, considering both clear and cloudy days. The simplicity and accuracy of the model over a wide range of solar conditions provides confidence that the model can be easily generalized to other regions of the world.

Effects of surface reflectance on skylight polarization measurements at the Mauna Loa Observatory

An all-sky imaging polarimeter was deployed in summer 2008 to the Mauna Loa Observatory in Hawaii to study clear-sky atmospheric skylight polarization. The imager operates in five wavebands in the visible and near infrared spectrum and has a fisheye lens for all-sky viewing. This paper describes the deployment and presents comparisons of the degree of skylight polarization observed to similar data observed by Coulson with a principal-plane scanning polarimeter in the late 1970s. In general, the results compared favorably to those of Coulson. In addition, we present quantitative results correlating a variation of the maximum degree of polarization over a range of 70-85% to fluctuation in underlying surface reflectance and upwelling radiance data from the GOES satellite.

Impact of deforestation in the Amazon basin on cloud climatology

Shallow clouds are prone to appear over deforested surfaces whereas deep clouds, much less frequent than shallow clouds, favor forested surfaces. Simultaneous atmospheric soundings at forest and pasture sites during the Rondonian Boundary Layer Experiment (RBLE-3) elucidate the physical mechanisms responsible for the observed correlation between clouds and land cover. We demonstrate that the atmospheric boundary layer over the forested areas is more unstable and characterized by larger values of the convective available potential energy (CAPE) due to greater humidity than that which is found over the deforested area. The shallow convection over the deforested areas is relatively more active than the deep convection over the forested areas. This greater activity results from a stronger lifting mechanism caused by mesoscale circulations driven by deforestation-induced heterogeneities in land cover.