The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key environmental remote-sensing instruments onboard the Suomi National Polar-Orbiting Partnership spacecraft, which was successfully launched on October 28, 2011 from the Vandenberg Air Force Base, California. Following a series of spacecraft and sensor activation operations, the VIIRS nadir door was opened on November 21, 2011. The first VIIRS image acquired signifies a new generation of operational moderate resolution-imaging capabilities following the legacy of the advanced very high-resolution radiometer series on NOAA satellites and Terra and Aqua Moderate-Resolution Imaging Spectroradiometer for NASA's Earth Observing system. VIIRS provides significant enhancements to the operational environmental monitoring and numerical weather forecasting, with 22 imaging and radiometric bands covering wavelengths from 0.41 to 12.5 microns, providing the sensor data records for 23 environmental data records including aerosol, cloud properties, fire, albedo, snow and ice, vegetation, sea surface temperature, ocean color, and nigh-time visible-light-related applications. Preliminary results from the on-orbit verification in the postlaunch check-out and intensive calibration and validation have shown that VIIRS is performing well and producing high-quality images. This paper provides an overview of the onorbit performance of VIIRS, the calibration/validation (cal/val) activities and methodologies used. It presents an assessment of the sensor initial on-orbit calibration and performance based on the efforts from the VIIRS-SDR team. Known anomalies, issues, and future calibration efforts, including the long-term monitoring, and intercalibration are also discussed.

[1] Although the advanced microwave sounding unit (AMSU) on board the NOAA 15 and NOAA 16 satellites is primarily designed for profiling atmospheric temperature and moisture, the products associated with clouds and precipitation are also derived using its window channel measurements with a quality similar to those derived from microwave imagers such as the Special Sensor Microwave Imager. However, the AMSU asymmetry in radiance along the scan was found to be obvious at its window channels and could severely degrade the quality of cloud and precipitation products if not properly corrected. Thus a postlaunch calibration scheme is developed for these channels, and the causes of the asymmetry are analyzed from the AMSU instrument model. A preliminary study shows that the asymmetry may be caused by either the AMSU polarization misalignment or the antenna pointing angle error. A generic radiative transfer model is developed for a single-layered cloud using a two-stream approximation and can be utilized for the retrievals of cloud liquid water (L) and total precipitable water (V), cloud ice water path (IWP), and particle effective diameter (D e ). At the AMSU lower frequencies the scattering from cloud liquid is neglected, and therefore the retrieval of L and V is linearly derived using 23.8 and 31.4 GHz. However, for ice clouds the radiative transfer model is simplified by neglecting the thermal emission, and therefore the retrieval of IWP and D e is analytically derived using the AMSU millimeter wavelength channels at 89 and 150 GHz. These cloud algorithms are tested for the AMSU on board the NOAA 15 and NOAA 16 satellites, and the results are rather promising. It is also found that the AMSUderived cloud ice water path is highly correlated with the surface rain rates and is now directly used to monitor surface precipitation throughout the world.

The successful launch of the Suomi National Polar‐orbiting Partnership Satellite on 28 October 2011 with the key instrument Visible Infrared Imaging Radiometer Suite signifies a new era of moderate‐resolution imaging capabilities following the legacy of AVHRR and Moderate‐Resolution Imaging Spectroradiometer (MODIS). After a year and half of calibration and validation, the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is performing very well. By early 2013, the sensor data records have achieved provisional maturity status and have been used in the routine production of more than 20 environmental data records by users worldwide. Based on comparisons with MODIS, the VIIRS reflective solar band radiometric uncertainties are now comparable in reflectance to that of MODIS Collection 6 equivalent bands (within 2%) although radiance differences could be larger for several bands, while an agreement on the order of 0.1 K has also been achieved for the thermal emissive bands, except for bands with significant spectral differences or certain bands at extreme temperatures (below 200 K or above 343 K). The degradation in the VIIRS rotating telescope assembly mirrors is gradually leveling off after reaching ~30% and thus far has limited impact on instrument performance and products. Environmental data record users are generally satisfied with the VIIRS data quality which meets the product requirements. While the specific technical details are documented in other papers in this special issue and in Cao et al. (2013a), this paper focuses on the major findings of VIIRS calibration and validation since launch, radiometric performance validation, and uncertainties, as well as lessons learned.

A combined active/passive modeling system that converts CloudSat observations to simulated microwave brightness temperatures (T B ) is used to assess different ice particle models under precipitating conditions. Simulation results indicate that certain ice models (e.g., low-density spheres) produce excessive scattering and implausibly low simulated T B s for stratiform precipitation events owing to excessive derived ice water paths (IWPs), while other ice models produce unphysical T B depressions due to the combined effects of elevated derived IWP and excessive particle size distribution-averaged extinction. An ensemble of nonspherical ice particle models, however, consistently produces realistic results under most circumstances and adequately captures the radiative properties of frozen hydrometeors associated with precipitation-with the possible exception of very high IWP events. Large derived IWP uncertainties exceeding 60% are also noted and may indicate IWP retrieval accuracy deficiencies using high-frequency passive microwave observations. Simulated T B uncertainties due to the ice particle model ensemble members approach 9 (5) K at 89 (157) GHz for high ice water path conditions associated with snowfall and ;2-3 (;1-2) K under typical stratiform rain conditions. These uncertainties, however, display considerable variability owing to ice water path, precipitation type, satellite zenith angle, and frequency. Comparisons between 157-GHz simulations and observations under precipitating conditions produce low biases (,1.5 K) and high correlations, but lower-frequency channels display consistent negative biases of 3-4 K in precipitating regions. Sample error correlations and covariance matrices for select microwave frequencies also show strong functional relationships with ice water path and variability depending on precipitation type.

The special sensor microwave imager (SSM/I) is a microwave radiometer having dual‐polarized channels at 19.35, 37, and 85.5 GHz and a vertically polarized channel at 22.235 GHz. The measurements at these frequencies are used to retrieve the liquid water path in precipitating and nonprecipitating clouds over oceans. Three separate algorithms, each accurate for different ranges of liquid water, are combined to measure a large dynamic range of cloud liquid water path up to 3.0 mm. The major improvements of our present algorithm over many other previous studies are (1) the algorithm detects the liquid water in optically thin stratus and low‐level clouds very well; (2) the algorithm measures the liquid water in highly convective clouds; (3) the algorithm can be applied to any climate regime because some of the coefficients (a1 and a2) are derived using a comprehensive training SSM/I data set obtained from various clear sky conditions; and (4) the liquid water derived using the present algorithm agree with that derived using the ground‐based microwave radiometer measurements very well. Global distributions of the cloud liquid water over oceans for August 1993 and January 1994 are derived using the SSM/I data from DMSP F10 and F11 satellites. Our analyses show that the cloud liquid water exhibits a strong diurnal variation over many regions. In particular, the variation over the tropical western Pacific and northwestern Pacific is largest and is attributed to the diurnal variation of raining clouds. The variation over the west coasts of major continents is also very large and is associated with nonraining stratus clouds.

Abstract. Satellite observations using microwave radiometers operating near the window regions are strongly affected by surface emissivity. Presently, the measurements obtained over land are not directly utilized in numerical weather prediction models because of uncertainties in estimating the emissivity. This study develops a new model to quantify the land emissivity over various surface conditions. For surfaces such as snow, deserts, and vegetation, volumetric scattering was calculated using a two-stream radiative transfer approximation. The reflection and transmission at the surface-air interface and lower boundary were derived by modifying the Fresnel equations to account for crosspolarization and surface roughness effects. Several techniques were utilized to compute the optical parameters for the medium, which is used in the radiative transfer solution. In the case of vegetation, geometrical optics is used because the leaf size is typically larger than the wavelength. For snow and deserts, a dense medium theory was adopted to take into account the coherent scattering of closely spaced particles. The emissivity spectra at frequencies between4.9 and94 GHz was simulated and compared with the ground-based radiometer measurements for bare soil, grass land, and snow conditions. It is shown that the features including the spectra, variability, and polarization agree well with the measurements. The simulated global distribution of land surface emissivity is also compared with the satellite retrievals from the Advanced Microwave Sounding Unit (AMSU). It is found that the largest discrepancies primarily occur over high latitudes where the snow properties are complex and least understood.

The Special Sensor Microwave/Imager (SSM/I), first placed into operation in July 1987, has been making measurements of earth-emitted radiation for over eight years. These data are used to estimate both atmospheric and surface hydrological parameters and to generate a time series of global monthly mean products averaged to a 1° lat x 1° long grid. Specifically, this includes monthly estimates of rainfall and its frequency, cloud liquid water and cloud frequency, water vapor, snow cover frequency, and sea ice frequency. This study uses seasonal mean values to demonstrate the spatial and temporal distributions of these hydrological variables. Examples of interannual variability such as the 1993 flooding in the Mississippi Valley and the 1992-93 snow cover changes over the United States are used to demonstrate the utility of these data for regional applications.

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