Timothy J. Schmit

INTRODUCING THE NEXT-GENERATION ADVANCED BASELINE IMAGER ON GOES-R

Abstract The Advanced Baseline Imager (ABI), designated to be one of the instruments on a future Geo-stationary Operational Environmental Satellite (GOES) series, will introduce a new era for U.S. geostationary environmental remote sensing. ABI is slated to be launched on GOES-R in 2012 and will be used for a wide range of weather, oceanographic, climate, and environmental applications. ABI will have more spectral bands (16), faster imaging (enabling more geographical areas to be scanned), and higher spatial resolution (2 km in the infrared and 1–0.5 km in the visible) than the current GOES Imager. The purposes of the selected spectral bands are summarized in this paper. There will also be improved performance with regard to radiometrics and image navigation/registration. ABI will improve all current GOES Imager products and introduce a host of new products. New capabilities will include detecting upper-level SO2 plumes, monitoring plant health on a diurnal time scale, inferring cloud-top phase and partic...

A Nonlinear Physical Retrieval Algorithm—Its Application to the GOES-8/9 Sounder

Abstract A nonlinear physical retrieval algorithm is developed and applied to the GOES-8/9 sounder radiance observations. The algorithm utilizes Newtonian iteration in which the maximum probability solution for temperature and water vapor profiles is achieved through the inverse solution of the nonlinear radiative transfer equation. The nonlinear physical retrieval algorithm has been tested for one year. It has also been implemented operationally by the National Oceanic and Atmospheric Administration National Environmental Satellite, Data and Information Service during February 1997. Results show that the GOES retrievals of temperature and moisture obtained with the nonlinear algorithm more closely agree with collocated radiosondes than the National Centers for Environmental Prediction (NCEP) forecast temperature and moisture profile used as the initial profile for the solution. The root-mean-square error of the total water vapor from the solution first guess, which is the NCEP 12-h forecast (referred to ...

Retrieval of Cloud Microphysical Properties from MODIS and AIRS

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the NASA Earth Observing System Aqua satellite enable global monitoring of the distribution of clouds during day and night. The MODIS is able to provide a high-spatial-resolution (1–5 km) cloud mask, cloud classification mask, cloud-phase mask, cloud-top pressure (CTP), and effective cloud amount during both the daytime and the nighttime, as well as cloud particle size (CPS) and cloud optical thickness (COT) at 0.55 m during the daytime. The AIRS high-spectral-resolution measurements reveal cloud properties with coarser spatial resolution (13.5 km at nadir). Combined, MODIS and AIRS provide cloud microphysical properties during both the daytime and nighttime. A fast cloudy radiative transfer model for AIRS that accounts for cloud scattering and absorption is described in this paper. Onedimensional variational (1DVAR) and minimum-residual (MR) methods are used to retrieve the CPS and COT from AIRS longwave window region (790–970 cm 1 or 10.31–12.66 m, and 1050–1130 cm 1 or 8.85–9.52 m) cloudy radiance measurements. In both 1DVAR and MR procedures, the CTP is derived from the AIRS radiances of carbon dioxide channels while the cloud-phase information is derived from the collocated MODIS 1-km phase mask for AIRS CPS and COT retrievals. In addition, the collocated 1-km MODIS cloud mask refines the AIRS cloud detection in both 1DVAR and MR procedures. The atmospheric temperature profile, moisture profile, and surface skin temperature used in the AIRS cloud retrieval processing are from the European Centre for Medium-Range Weather Forecasts forecast analysis. The results from 1DVAR are compared with the operational MODIS products and MR cloud microphysical property retrieval. A Hurricane Isabel case study shows that 1DVAR retrievals have a high correlation with either the operational MODIS cloud products or MR cloud property retrievals. 1DVAR provides an efficient way for cloud microphysical property retrieval during the daytime, and MR provides the cloud microphysical property retrievals during both the daytime and nighttime.

AIRS Subpixel Cloud Characterization Using MODIS Cloud Products

Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing Systems (EOSs) Aqua satellite enable improved global monitoring of the distribution of clouds. MODIS is able to provide, at high spatial resolution (∼1–5 km), a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud optical thickness (COT). AIRS is able to provide CTP, ECA, CPS, and COT at coarser spatial resolution (∼13.5 km at nadir) but with much better accuracy using its high-spectral-resolution measurements. The combined MODIS–AIRS system offers the opportunity for improved cloud products over those possible from either system alone. The key steps for synergistic use of imager and sounder radiance measurements are 1) collocation in space and time and 2) imager cloud amount, type, and phase determination within the sounder pixel. The MODIS and AIRS measurements from ...

Optimal cloud-clearing for AIRS radiances using MODIS

The Atmospheric Infrared Sounder (AIRS) onboard the National Aeronautics and Space Administrations Earth Observing Systems (EOS) Aqua spacecraft, with its high spectral resolution and radiometric accuracy, provides atmospheric vertical temperature and moisture sounding information with high vertical resolution and accuracy for numerical weather prediction (NWP). Due to its relatively coarse spatial resolution (13.5 km at nadir), the chance for an AIRS footprint to be completely cloud free is small. However, the Moderate Resolution Imaging Spectroradiometer (MODIS), also on the Aqua satellite, provides colocated clear radiances at several spectrally broad infrared (IR) bands with 1-km spatial resolution; many AIRS cloudy footprints contain clear MODIS pixels. An optimal cloud-correction or cloud-clearing (CC) algorithm, an extension of the traditional single-band N/sup */ technique, is developed. The technique retrieves the hyperspectral infrared sounder clear column radiances from the combined multiband imager IR clear radiance observations with high spatial resolution and the hyperspectral IR sounder cloudy radiances on a single-footprint basis. The concurrent AIRS and MODIS data are used to verify the algorithm. The AIRS cloud-removed or cloud-cleared radiance spectrum is convolved to all the possible MODIS IR spectral bands with spectral response functions (SRFs). The convoluted cloud-cleared brightness temperatures (BTs) are compared with MODIS clear BT observations within AIRS cloud-cleared footprints passing our quality tests. The bias and the standard deviation between the convoluted BTs and MODIS clear BT observations is less than 0.25 and 0.5 K, respectively, over both water and land for most MODIS IR spectral bands. The AIRS cloud-cleared BT spectrum is also compared with its nearby clear BT spectrum, the difference, accounting the effects due to scene nonuniformity, is reasonable according to the analysis. The multiband optimal cloud-clearing is also compared with the traditional single-band N/sup */ cloud-clearing; the performance enhancement of the optimal cloud-clearing over the single-band traditional N/sup */ cloud-clearing is demonstrated and discussed. It is found that more than 30% of the AIRS cloudy (partly and overcast) footprints in this study have been successfully cloud-cleared using the optimal cloud-clearing method, revealing the potential application of this method to the operational processing of hyperspectral IR sounder cloudy radiance measurements when the collocated imager IR data are available. The use of a high spatial resolution imager, along with information from a high spectral resolution sounder for cloud-clearing, is analogous to instruments planned for the next-generation Geostationary Operational Environmental Satellite (GOES-R) instruments-the Advanced Baseline Imager and the Hyperspectral Environmental Suite. Since no microwave instruments are being planned for GOES-R, the cloud-clearing methodology demonstrated in this paper will become the most practical approach for obtaining the reliable clear-column radiances.

Technical note: Quantitative monitoring of a Saharan dust event with SEVIRI on Meteosat-8

An algorithm has been developed to quantitatively retrieve dust properties (identification, optical thickness, particle radius, and dust density) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard Meteosat‐8, the first of the Meteosat Second Generation (MSG). Two SEVIRI thermal infrared (IR) window channels (10.8 µm and 12 µm) were used to monitor the dust event of 3 March 2004 over the Sahara in northern Africa. The identification and evolution of dust are well depicted by SEVIRI data with high spatial resolution (approximately 3 km) and high temporal resolution (15 minutes). This demonstrates the capability of a geostationary advanced imager to monitor dust events over land, their migration and the corresponding air quality.

Derived Product Imagery from GOES-8

Abstract Derived product imagery (DPI) is a method of presenting quantitative meteorological information, derived from satellite measurements, as a color-coded image at single-pixel resolution. Its intended use is as animated sequences to observe trends in the displayed quantities, which for the GOES-8 are total precipitable water, lifted index, and surface skin temperature. Those products are produced once per hour, over the continental United States and the Gulf of Mexico. This paper reviews the development of the DPI and details the algorithm used for GOES-8. The quality of the products is discussed, and an example is given. The greatest value of the DPI probably lies in comparing a sequence of the satellite product with a sequence derived from a numerical forecast. In this way, deviation of the forecast from reality is readily exposed.

Intercalibration of the Infrared Window and Water Vapor Channels on Operational Geostationary Environmental Satellites Using a Single Polar-Orbiting Satellite

Abstract The Cooperative Institute for Meteorological Satellite Studies (CIMSS) has been intercalibrating radiometers on five geostationary satellites (GOES-8, -10, Meteosat-5, -7, and GMS-5) using a single polar-orbiting or low-earth orbiting satellite [NOAA-14 High-Resolution Infrared Radiation Sounder (HIRS) and Advanced Very High Resolution Radiometer (AVHRR)] as a reference on a routine basis using temporally and spatially collocated measurements. This is being done for the 11-μm infrared window (IRW) channels as well as the 6.7-μm water vapor (WV) channels. IRW results between AVHRR or HIRS and all five geostationary instruments show relatively small differences, with all geostationary instruments vicariously comparing to within 0.6 K. The WV results between HIRS and all five geostationary instruments show larger differences, with geostationary instruments separating into two groups: GOES-8, -10, and GMS-5 comparing within 1 K; Meteosat-5 and -7 comparing within 0.1 K; and the two groups comparing w...

Observations and trends of clouds based on GOES sounder data

A 26 month (November 1997 through December 1999) data set of Geostationary Operational Environmental Satellite (GOES) sounder-derived cloud parameters has been analyzed to discern annual and monthly trends. An important outcome of this study is the identification of diurnal trends made possible by the geostationary satellite frequent observations over specific locations. The area of coverage is 20°N to 50°N and 60°W to 160°W, which corresponds to the continental United States and the surrounding waters. The satellite cloud observations were compared to manually observed Pilot Reports (PIREPs) and were found to be, on average, 35 hPa lower. Comparing the frequency of GOES sounder observations of high cloudiness with observations from the National Oceanic and Atmospheric Administration (NOAA) series of polar orbiting weather satellites reveals a correlation coefficient of 0.79 and a bias of 3.4% for the frequency of occurrence (GOES with a mean higher height). The frequency of occurrence and distribution of clouds, cloud top pressure (CTOP), and effective cloud amount are based on a spatial resolution of ∼40 km (3×3 field of view box) and are shown for eight regions. High clouds (CTOP ≤300 hPa) are found to be more prevalent during the Northern Hemisphere summer than winter for all regions. High clouds for 1998 comprise 8.5% of all observations. Also, in 1998 clear conditions are observed ∼34% of the time. Focusing on the strength of the hourly GOES sounder data, it is found that thin high clouds are most prevalent during the summer and fall seasons, occurring most frequently in the late morning and early afternoon.

High-Spectral- and High-Temporal-Resolution Infrared Measurements from Geostationary Orbit

Abstract The first of the next-generation series of the Geostationary Operational Environmental Satellite (GOES-R) is scheduled for launch in 2015. The new series of GOES will not have an infrared (IR) sounder dedicated to acquiring high-vertical-resolution atmospheric temperature and humidity profiles. High-spectral-resolution sensors have a much greater vertical-resolving power of temperature, moisture, and trace gases than low-spectral-resolution sensors. Because of coarse vertical resolution and limited accuracy in the legacy sounding products from the current GOES sounders, placing a high-spectral-resolution IR sounder with high temporal resolution in the geostationary orbit can provide nearly time-continuous three-dimensional moisture and wind profiles. This would allow substantial improvements in monitoring the mesoscale environment for severe weather forecasting and other applications. Application areas include nowcasting (and short-term forecasts) and numerical weather prediction, which require p...