The atmospheric temperature and water vapour profile products, derived from the hyperspectral cross-track infrared sounder/advanced technology microwave sounder (CrIS/ATMS) on board the Suomi national polar orbiting partnership (S-NPP) satellite and the Infrared Atmospheric Sounding Interferometer (IASI) on board MetOP-B satellite, were assessed using radiosonde data as the target. This is achieved by leveraging the strengths of satellite synchronized dedicated, Global Reference Upper Air Network (GRUAN), and conventional radiosonde observations (RAOBs) in the analysis of satellite-radiosonde collocation data, compiled through the NOAA sounding Products Validation System (NPROVS). One of the results found in the study is water vapour profiles of both the NOAA Unique Combined Atmospheric Processing System (NUCAPS) and EUMETSAT IASI L2 products are comparable to or even better than numerical model prediction (NWP) outputs, when dedicated ship RAOBs were used as the benchmark.
Accurate thermal infrared (TIR) fast-forward models are critical for weather forecasting via numerical weather prediction (NWP) satellite radiance assimilation and operational environmental data record (EDR) retrieval algorithms. The thermodynamic and compositional data about the surface and lower troposphere are derived from semi-transparent TIR window bands (i.e., surface-sensitive channels) that can span into the far-infrared (FIR) region under dry polar conditions. To model the satellite observed radiance within these bands, an accurate a priori emissivity is necessary for the surface in question, usually provided in the form of a physical or empirical model. To address the needs of hyperspectral TIR satellite radiance assimilation, this paper discusses the research, development, and preliminary validation of a physically based snow/ice emissivity model designed for practical implementation within operational fast-forward models such as the U.S. National Oceanic and Atmospheric Administration (NOAA) Community Radiative Transfer Model (CRTM). To accommodate the range of snow grain sizes, a hybrid modeling approach is adopted, combining a layer scattering model based on the Mie theory (viz., the Wiscombe–Warren 1980 snow albedo model, its complete derivation provided in the Appendices) with a specular facet model. The Mie-scattering model is valid for the smallest snow grain sizes typical of fresh snow and frost, whereas the specular facet model is better suited for the larger sizes and welded snow surfaces typical of aged snow. Comparisons of the model against the previously published spectral emissivity measurements show reasonable agreement across zenith observing angles and snow grain sizes, and preliminary observing system experiments (OSEs) have revealed notable improvements in snow/ice surface window channel calculations versus hyperspectral TIR satellite observations within the NOAA NWP radiance assimilation system.
Abstract The Cross‐track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) instruments aboard the Suomi National Polar‐orbiting Partnership satellite provide high‐quality hyperspectral infrared and microwave observations to retrieve atmospheric vertical temperature and moisture profiles (AVTP and AVMP) and many other environmental data records (EDRs). The official CrIS and ATMS EDR algorithm, together called the Cross‐track Infrared and Microwave Sounding Suite (CrIMSS), produces EDR products on an operational basis through the interface data processing segment. The CrIMSS algorithm group is to assess and ensure that operational EDRs meet beta and provisional maturity requirements and are ready for stages 1–3 validations. This paper presents a summary of algorithm optimization efforts, as well as characterization and validation of the AVTP and AVMP products using the European Centre for Medium‐Range Weather Forecasts (ECMWF) analysis, the Atmospheric Infrared Sounder (AIRS) retrievals, and conventional and dedicated radiosonde observations. The global root‐mean‐square (RMS) differences between the CrIMSS products and the ECMWF show that the AVTP is meeting the requirements for layers 30–300 hPa (1.53 K versus 1.5 K) and 300–700 hPa (1.28 K versus 1.5 K). Slightly higher RMS difference for the 700 hPa‐surface layer (1.78 K versus 1.6 K) is attributable to land and polar profiles. The AVMP product is within the requirements for 300–600 hPa (26.8% versus 35%) and is close in meeting the requirements for 600 hPa‐surface (25.3% versus 20%). After just one year of maturity, the CrIMSS EDR products are quite comparable to the AIRS heritage algorithm products and show readiness for stages 1–3 validations.
Accurate environmental satellite observations and calculations of top‐of‐atmosphere infrared (IR) spectral radiances are required for the accurate retrieval of environmental data records (EDRs), including atmospheric vertical temperature and moisture profiles. For this reason it is important that systematic differences between observations and calculations under well‐characterized conditions be minimal, and because most sensors must scan the earth surface to facilitate global coverage, this should include unbiased agreement over the range of zenith angles encountered. This paper investigates the “clear‐sky observations” commonly used in such analyses, which include “cloud‐masked” data (as is typical from imagers), as well as “cloud‐cleared radiances” (as is typical from hyper/ultraspectral sounders). Here we derive simple physical conceptual models to examine quantitatively the longwave IR brightness temperature sensitivity arising from the increasing probability of cloudy fields‐of‐view with zenith angle, or alternatively from increased slant‐path through an aerosol layer. To model the angular effect of clouds, we apply previously derived probability of clear line‐of‐sight (PCLoS) models for single‐layer broken opaque clouds. We then generalize this approach to account for the impact of high, semitransparent (non‐opaque) cold clouds, by deriving analytical expressions for the mean slant‐paths through each of the idealized shapes under consideration. Our sensitivity analyses suggest that contamination by residual clouds and/or aerosols within clear‐sky observations can have a measurable concave‐up impact (i.e., an increasing positive bias symmetric over the scanning range) on the angular agreement of hypothetical “observations” with “calculations.” The magnitudes are typically on the order of couple tenths of a Kelvin or more depending on the residual absolute cloud fraction and optical depth (i.e., the degree of cloud contamination), the residual aerosol optical depth (i.e., the degree of aerosol contamination), the temperature difference between the surface and the residual cloud/aerosol layers, and the shape and vertical aspect ratio of the clouds.
Atmospheric Vertical Temperature Profile (AVTP) and Atmospheric Vertical Moisture Profile (AVMP) retrievals produced by the Cross-track Infrared Sounder and the Advanced Technology Microwave Sounder suite (CrIMSS) official algorithm were evaluated with global European Center for Medium Range Weather Forecast (ECMWF) analysis fields, radiosonde (RAOB) measurements, and Aqua-Atmospheric Infrared Sounder (AIRS) heritage algorithm retrievals. The operational CrIMSS AVTP and AVMP product statistics with truth data sets are quite comparable to the AIRS heritage algorithm statistics. Planned updates and improvements to the CrIMSS algorithm will alleviate many issues observed with `day-one' focus-day results and show promise in meeting the Key Performance Parameter (KPP) specifications.
This paper advances hyperspectral infrared (IR) radiative transfer techniques for retrieving water (ocean and lake) surface skin temperature from clear-sky radiance observations obtained within the longwave atmospheric window region (800–1000 cm−1). High spectral resolution has optimal potential for multispectral algorithms because of the capability to resolve, and thus avoid, gas absorption lines that otherwise obscure the surface signal in conventional narrowband radiometers. A hyperspectral radiative transfer model (RTM) is developed for varying satellite zenith angles, atmospheric profiles (cloud and aerosol free), surface wind speeds and skin temperatures, with atmospheric column transmittance spectra computed from fast models. Wind speed variations in surface emissivity and quasi-specular reflection are both rigorously accounted for. The RTM is then used for deriving retrieval algorithms based upon statistical and physical methodologies. The statistical method is based upon linear regression analyses of brightness temperatures, whereas the physical method is based upon solution of a linear perturbation form of the IR radiative transfer equation valid for window channels. The physical method is unique in its simplicity: It does not solve for atmospheric profiles, but rather relies upon local linearities about guess transmittances for extrapolating the skin temperature. Both algorithms are tested against independent forward calculations and then used to retrieve water surface skin temperatures from the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed-Interferometer (NAST-I) flown on board the NASA ER-2. The results demonstrate the capability of hyperspectral radiative transfer for providing an optimal correction for atmospheric gas absorption (viz., water vapor) from the new suite of environmental satellite IR spectrometers.
This paper continues an overview of the validation of operational profile retrievals from the Suomi National Polar-Orbiting Partnership (SNPP), with focus here given to the infrared (IR) ozone profile environmental data record (EDR) product. The SNPP IR ozone profile EDR is retrieved using the cross-track IR sounder (CrIS), a Fourier transform spectrometer that measures high-resolution IR earth radiance spectra containing atmospheric state information, namely, vertical profiles of temperature, moisture, and trace gas constituents. The SNPP CrIS serves as the U.S. low earth orbit (LEO) satellite IR sounding system and will be featured on future Joint Polar Satellite System (JPSS) LEO satellites. The operational sounding algorithm is the National Oceanic and Atmospheric Administration-Unique Combined Atmospheric Processing System (NUCAPS), a legacy sounder science team algorithm that retrieves atmospheric profile EDR products, including ozone and carbon trace gases, with optimal vertical resolution under nonprecipitating (clear to partly cloudy) conditions. The NUCAPS ozone profile product is assessed in this paper using extensive global in situ truth data sets, namely, ozonesonde observations launched from ground-based networks and from ocean-based intensive field campaigns, along with numerical weather prediction model output. Based upon rigorous statistical analyses using these data sets, the NUCAPS ozone profile EDRs are determined to meet the JPSS Level 1 global performance requirements.
A numerical model is developed for computation of the reflection of atmospheric-emitted IR radiance from a wind-roughened water body. The model assumes the Kirchhoff approximation for rough surface scattering. This allows application of the postulates of geometrical optics to determine the reflection of rays from an ensemble of wave facets. We performed the hemispherical integration with Gaussian quadrature by using an uplooking fast transmittance model. This calculation is simplified further through the concept of a reflection–diffusivity angle. The model compares favorably with observed radiance spectra obtained from the Marine-Atmospheric Emitted Radiance Interferometer during the Combined Sensor Program research cruise.
