The Cross‐Track Infrared Sounder (CrIS) is a Fourier Transform Michelson interferometer instrument launched on board the Suomi National Polar‐Orbiting Partnership (Suomi NPP) satellite on 28 October 2011. CrIS provides measurements of Earth view interferograms in three infrared spectral bands at 30 cross‐track positions, each with a 3 × 3 array of field of views. The CrIS ground processing software transforms the measured interferograms into calibrated and geolocated spectra in the form of Sensor Data Records (SDRs) that cover spectral bands from 650 to 1095 cm−1, 1210 to 1750 cm−1, and 2155 to 2550 cm−1 with spectral resolutions of 0.625 cm−1, 1.25 cm−1, and 2.5 cm−1, respectively. During the time since launch a team of subject matter experts from government, academia, and industry has been engaged in postlaunch CrIS calibration and validation activities. The CrIS SDR product is defined by three validation stages: Beta, Provisional, and Validated. The product reached Beta and Provisional validation stages on 19 April 2012 and 31 January 2013, respectively. For Beta and Provisional SDR data, the estimated absolute spectral calibration uncertainty is less than 3 ppm in the long‐wave and midwave bands, and the estimated 3 sigma radiometric uncertainty for all Earth scenes is less than 0.3 K in the long‐wave band and less than 0.2 K in the midwave and short‐wave bands. The geolocation uncertainty for near nadir pixels is less than 0.4 km in the cross‐track and in‐track directions.

As our civilization becomes more dependent on space based technolo gies, we become more vulnerable to conditions in space weather. Accurate space weather specification and forecasting require proper modeling which account for the coupling between the sun, the magnetosphere, the thermo sphere, the ionosphere and the mesosphere. In spite of the tremendous advances that have been made in understanding the physics behind differ ent space weather phenomena, the ability to specify or predict space weather is limited due to the lack of continuous and extensive observations in these regions. Placing a constellation of GPS receivers in low-Earth orbit, such as the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), provides an extremely powerful system for continu ously and extensively measuring one of these regions, the ionosphere. COS MIC, by use of GPS occultations, will make it possible to obtain continuous and global 3-dimensional images of electron density, irregularities and TIDs in the ionosphere and plasmasphere. COSMIC would provide nearly 5600 globally distributed occultations per day suitable for ionospheric sensing. Occultations can be processed individually to obtain vertical profiles of elec tron density, with vertical resolution of-lkm, or collectively by means of tomography or data assimilation to obtain 3-D images of electron density or irregularity structure. In this paper we describe the GPS observables for ionospheric sensing and the occultation geometry. Our presentation evolves from discussing simple to more complicated inversion techniques starting with the Abel inversion, gradient-constrained Abel inversion, to mography, and finally data assimilation. In each of these techniques, the accuracy is assessed either via examination of real data from GPS/MET or

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[1] A global assimilative ionospheric model (GAIM) has been developed to improve the modeling of ionospheric weather. GAIM adopts a fixed three-dimensional Eulerian grid following a geomagnetic dipole configuration. A four-dimensional variational approach (4DVAR) with the adjoint technique is presented, which attempts to minimize the difference between modeled and measured line-of-sight total electron content (TEC) using nonlinear least squares minimization. The minimization is achieved by solving for corrections to the initial (climatological) model drivers so that the density state becomes consistent with the observations. The 4DVAR approach is exercised with GAIM in an observation system simulation experiment (OSSE) conducted for estimating the weather behavior of E Â B drift at low latitudes. The OSSE takes the constellation of global positioning system (GPS) satellites and an existing global GPS receiver network as the observation system. The effectiveness of the 4DVAR technique with such an observation system is assessed in the experiment, which indicates that one can solve for the lowlatitude E Â B drift and improve the density modeling using ground-based, integrated line-of-sight (TEC) measurements from a relatively small number of stations.