This paper summarizes design, performance estimates and applications of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Visible Infrared Imager Radiometer Suite (VIIRS). VIIRS is approaching Engineering Development Unit (EDU) integration and flight model assembly for delivery in late 2005 for launch on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) satellite in 2006. Applications of VIIRS are anticipated to represent dramatic improvements over heritage capability from the Defense Meteorological Satellite Program (DMSP) Operational Line-scanning System (OLS) and the National Oceanic and Atmospheric Administration (NOAA) Polar-orbiting Operational Environmental Satellite (POES) Advanced Very High Resolution Radiometer (AVHRR). VIIRS draws heavily on the NASA Earth Observing System (EOS) Terra and Aqua satellites MODerate resolution Imaging Spectroradiometers (MODIS), offering similar spectroradiometry at better spatial resolution. The Naval Research Laboratory (NRL) has developed VIIRS on-orbit performance simulations based on MODIS data to illustrate the dramatic improvements VIIRS will offer compared to current operational satellites for meteorology.

The local Equator Crossing Times (EXT) of all NOAA platforms have been summarized as a function of time and approximated analytically. The fit equations (superposition of two harmonic terms, with platform-specific amplitudes, frequencies, and phases) accurately reconstruct all past EXTs to within ±2 min and also allow extrapolation in time. Fit equations are summarized and used to predict the future EXT evolution. This information is important for generation of meaningful environmental and stable climate data records from data of all radiometric sensors onboard NOAA platforms.

The NGST/Raytheon Contractor Team selected to build and operate the system has responsibility for both hardware and algorithms . This paper describes the process being used by the NGST/Raytheon team to convert science-grade algorithm code to operational code. Also discussed are the challenges, rewards, and pitfalls associated with the process of converting an evolving science-grade algorithm code to pre-launch operational code. A major challenge is dealing with two simultaneous feedback loops; one between the NGST and the sensor vendor; another between NGST and its Raytheon partner to convert an evolving and immature science product to an operational product.

The AVHRR (Advanced Very High Resolution Radiometer) data record comprises the longest existing daily satellite dataset. The CSIRO AVHRR time series includes data over Australasia from all of the NOAA polar orbiters since NOAA-6 in 1981 through the currently operational NOAA-17. Both inter- and intrasatellite factors affect the usability of these data for the generation of consistent time series of meteorological and geo/bio-physical parameters. Not only do the particular AVHRR instruments on the individual satellites differ in terms of spectral response and sensitivity, but the sensitivity varies with time, and the evolution of each satellite's orbit results in changes in target illumination and viewing geometry that must be taken into account. To improve our knowledge of the measurement variation of the different AVHRR instruments we have attempted to develop a fully operational method, based on multivariate alternate detection in comparison with pseudo-invariant features. A comparison of the operability and effectiveness of these methods is discussed and their relative impact on the overall consistency and long term calibration of the time series is described.

The Visible/Infrared Imager/Radiometer Suite (VIIRS) will be the operational imaging instrument on three NPOESS satellites, in Sun-synchronous orbits at altitudes of 833 km. The VIIRS is presently planned to have a total of 14 solar reflective spectral bands, with central wavelengths ranging from 412nm to 2250nm. The Advanced Baseline Imager (ABI) will be the operational imaging instrument on two GOES-R satellites in geostationary orbits. The ABI is presently planned to have a total of 6 solar reflective spectral bands, with central wavelengths ranging from 470nm to 2260nm. Some of the ABI’s spectral bands are similar, but not identical to, those of the VIIRS. Each VIIRS instrument and each ABI instrument will be equipped with a solar diffuser for on-board, end-to-end calibration of its reflective channels. Due to the high scan rates of both instruments and the flexible scheduling of the ABI, there will be several opportunities each day for the two instruments to simultaneously view the same area on Earth's surface along nearly identical lines of sight. It should be possible to cross-calibrate the ABI and the VIIRS instruments to far greater precision than has been achieved before, and to merge data from multiple platforms into fused data products. The utility of the combined VIIRS/ABI weather imagery can be improved still more if the ABI's reflective spectral bands are changed to match corresponding bands of the VIIRS.

A method has recently been shown by Aoki to compress the number of channels of vertical atmospheric sounder preserving almost all the information content that the original data has. In this method the weighting function of the original channels is decomposed with empirical orthogonal functions (EOFs) and a system of hypothetical radiances, whose weighting functions are the EOFs, are constructed and used for the analysis. It has been shown that the radiance data of 1200 of original channels, which is obtained from the region 640-760 cm^-1, can be compressed to 23 or less channels of hypothetical radiances with loosing negligible information content. In the present paper, the studies were performed on the a) the relation between the number of the EOFs that is required to reconstruct the weighting functions in sufficient accuracy and the spectral resolution, b) the dependence of the correlation between "measurement error" of hypothetical channels on the range of zenith angle of sample data of weighting function, from which the EOFs are generated, and c) the dependence of the information content on the spectral resolutions 0.1, 0.35 and 0.6 cm^-1.

High spectral resolution infrared radiances from the Hyperspectral Environmental Suite (HES) on Geostationary Operational Environmental Satellite (GOES-R and beyond) will allow for monitoring the evolution of atmospheric temperature and moisture vertical distributions. HES, together with the Advanced Baseline Imager (ABI), will operationally provide enhanced spatial, temporal and vertical information for radiances and atmospheric soundings that are desired by numerical weather forecast models. An algorithm has been developed to analyze the retrieval error and the vertical resolution of soundings from HES radiances. Trade-off studies have been done to balance the spectral coverage, spectral resolution, and signal-to-noise ratio in order to achieve the GOES users' requirement of 1 K accuracy with 1km vertical resolution for temperature and 10% accuracy with 2km vertical resolution for relative humidity. The vertical resolution capability of HES is also compared with that of the current GOES Sounder which has 18 infrared spectral channels and the Advanced Microwave Sounding Unit (AMSU) on the NOAA polar orbiting satellites that has good temperature sensitivity in the lower stratosphere and upper troposphere. The advantage of combination of GOES sounder and AMSU is also investigated.

This paper discusses activities related to mesoscale product development in preparation for the GOES-R satellite to be launched in 2012. These new image products will feature improved spatial, temporal, spectral, and radiometric resolution compared to current GOES imagery. Emphasis in this paper is on simulations of GOES-R data using observations from existing operational and experimental satellites.

The Japanese Advanced Meteorological Imager (JAMI) was developed by Raytheon and delivered to Space Systems/Loral as the Imager Subsystem for Japan's MTSAT-1R satellite. Due to Japan's urgent need to replace MTSAT-1, which was destroyed in a launch failure in 1999, JAMI was developed on an expeditious 39-month schedule. Raytheon's success in responding to the needs of MTSAT-1R and delivering an excellent operational geosynchronous Earth orbit (GEO) imager was enabled by an elegant instrument architecture and use of newer but proven technology that simplified design, assembly and test of the Imager while simultaneously supplying superior performance. JAMI breaks through limitations of earlier three-axis stabilized GEO instruments with significant improvements in many areas, including spatial sampling, radiometric sensitivity, calibration and performance around local midnight.

Raytheon's Santa Barbara Remote Sensing facility in Goleta, California designed and built an advanced meteorological imager for the Japanese Ministry of Transport between March, 2000 and July, 2002 for MTSAT-1R. One of the most stressing requirements is visible band image quality near local midnight. The 30 month program schedule forced the design team to make key decisions about the telescope design based on very preliminary analyses. Subsequent detailed analyses revealed that thermal distortions in the beryllium three-mirror anastigmat telescope would cause unacceptable performance degradation during much of the orbit. Through careful thermal, structural, and optical (STOP) analysis, the design team was able to optimize the designs of the telescope and thermal control system while meeting the challenging procurement schedule for the telescope.

Raytheon's Santa Barbara Remote Sensing (SBRS) division designed and built the MTSAT-1R Japanese Advanced Meteorological Imager for the Japanese Ministry of Transport between March, 1999 and July, 2002. In order to meet the stressing requirements of a geosynchronous orbit, a combination of structural, thermal, and optical (STOP) analyses were used to design and optimize the beryllium three-mirror anastigmat (TMA) telescope. This modeling approach was used to characterize and minimize the thermal distortion around local midnight. On-orbit temperatures and structural deformations were predicted using thermal Desktop/SINDA and PATRAN/NASTRAN software, respectively. The resulting optical performance was evaluated using Raytheon developed HEXAGON software. The telescope design was successfully optimized to attain specified visible channel performance for most of the 24 hour orbit.

For over two decades, meteorologists at the Satellite Analysis Branch (SAB) of the National Environmental Satellite, Data, and Information Service (NESDIS) have provided manual satellite precipitation estimates as guidance for National Weather Service (NWS) field forecasters during heavy rain and flash flood situations. Scientists at the NESDIS Office of Research and Applications (ORA) have developed a number of tools to automate and streamline the processes of both estimating current precipitation and nowcasting near-term precipitation from satellite data. These tools are discussed and illustrated in this paper.

At the Italian Air Force Meteorological Service a neural network model (NN) was defined in order to forecast the convective systems evolution in the Mediterranean area. This model, composed by a system of NNs, uses combination of water vapour absorption (WV) and infrared window (IR) data of Meteosat Second Generation (MSG). We realized that cloud top temperature, from IR window channel, does not give enough information to forecast the evolution of convective systems. As a consequence we introduced information about middle troposphere humidity content, from water vapor absorption band. We had preliminary results using the Meteosat rapid scan (RS) data. The use of WV and IR data from Meteosat-6 RS service, with a time sampling of 10 minutes, allowed us to track satisfactorily the evolution of convective cells and improved the detection of the beginning of the cell life. We can say that information of IR channel temperature only is not enough, for example, to evaluate the dissolving phase of the convective cell. A small decrease of the cloud top temperature (detected in the IR channel) it is not a unique indication for the beginning of that phase. It is known that, during mature phase, a convective cell may have a pulsating behaviour, so its top increases and decreases for an unknown time interval. After having defined two main evolution phases on the base of the features deduced from IR and WV channels, a specific NN algorithm was set up for nowcasting convective cells, using first RS data and then MSG data. A statistical analysis of cross-correlation between time series of different channels was performed for different areas of the Mediterranean region. From these statistics we may conclude that the performance of the NN system is more than satisfactory. This allows us to improve the operational automatic nowcasting application with the insertion of a NN module which gives information on the evolution of convective systems. In this way the forecasters are able to evaluate the probability of an increase or decrease of the severe convective activity.

Satellite observations are a critical component of the global atmospheric observing system, and contribute substantially to the current accuracy of numerical weather forecasts. In this paper, two types of experiments related to the effectiveness of these and other observations are described. These are: Observing System Experiments (OSEs), which are conducted to evaluate the impact of an existing observing system; and Observing System Simulation Experiments (OSSEs) which are conducted to evaluate the potential for future observing systems to improve NWP, as well as to evaluate trade-offs in observing system design, and to develop and test improved methods for data assimilation. This paper summarizes the methodology for such experiments and presents selected results from OSEs to evaluate satellite data sets that have recently become available to the global observing system, such as AIRS and SeaWinds, and results from recent OSSEs to determine the potential impact of space-based lidar winds.

The Joint Center for Satellite Data Assimilation (JCSDA) was established by NASA and NOAA in 2001, with the DoD becoming a partner in 2002. The goal of the JCSDA is to accelerate the use of observations from earth-orbiting satellites in operational numerical analysis and prediction models for the purpose of improving weather forecasts, improving seasonal to interannual climate forecasts, and increasing the accuracy of climate data sets. Advanced instruments of the current and planned satellite missions, do and will increasingly provide large volumes of data related to atmospheric, oceanic, and land surface state. These data will exhibit accuracies and spatial, spectral and temporal resolutions never before achieved. The JCSDA will ensure that the maximum benefit from investment in space is realised from the advanced global observing system. It will also help accelerate the use of satellite data from both operational and experimental spacecraft for weather and climate related activities. To this end the advancement of data assimilation science by JCSDA has included the establishment of the JCSDA Community Radiative Transfer Model (CRTM) and continual upgrades including, the incorporation of AIRS and snow and ice emissivity models for improving the use of microwave sounding data over high latitudes, preparation for use of METOP IASI/AMSU/HSB, DMSP SSMIS and CHAMP GPS data, real-time delivery of EOS-Aqua AMSR-E to NWP centers, and improved physically based SST analyses. Eighteen other research projects are also being supported by the JCSDA (e.g. use of cloudy radiances from advanced satellite instruments) to develop a state of-the-art satellite data assimilation system. The work undertaken by the JCSDA represents a key component of GEOSS. In particular data assimilation, data impact studies, OSSEs, THORPEX and network design studies are key activities of GEOSS.

The U.S. Navy's new three-dimensional variational analysis system NAVDAS became operational at Fleet Numerical Meteorology and Oceanography Center (FNMOC) on October 1, 2003, paving the way for the direct assimilation of NOAA AMSU-A radiances with the Navy Operational Global Atmospheric Prediction System (NOGAPS). AMSU-A radiance assimilation, which became operational at FNMOC on June 9, 2004, leads to significant improvement in forecast skill, as compared with assimilation of NESDIS ATOVS retrievals. The two- to five-day forecast skill at 500 hPa is increased by 3-10 hours in the Northern Hemisphere, and by 12-20 hrs in the Southern Hemisphere, with similar improvements at 1000 hPa. Forecasts with AMSU-A are consistently better, with fewer forecast "busts", fewer synoptic errors and a general strengthening of the circulations in both hemispheres. Overall, NAVDAS analyses and forecasts with AMSU-A exhibit better fit with radiosondes and other observations. Observations from AMSU-B, which are sensitive to the vertical distribution of water vapor in the troposphere, are used to compute 1DVAR humidity retrievals. NAVDAS assimilation of AMSU-B retrievals into NOGAPS dries out the middle and upper troposphere, and strengthens moisture gradients such as the Intertropical Convergence Zone, correcting known model tendencies. Tropical cyclone track and intensity predictions are slightly improved. Transition of AMSU-B retrieval assimilation to operations at FNMOC is targeted for early 2005.

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and 1 km tropospheric layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved effective fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis with regard to daily, monthly mean, and interannual differences of monthly mean fields.

Numerical simulations of hurricanes often require an initial vortex field because the hurricane forecast models normally run at higher resolutions and the wind fields from the global forecast models tend to be too weak, especially for hurricanes at their incipient stages. A scheme was developed to produce more realistic hurricane vortices using the Advanced Microwave Sounding Unit (AMSU) data (Zhu et al. 2002). Recently, several improvements were made to the scheme, including one-dimension variational analysis of atmospheric temperature profiles and two-dimensional optimal interpolation of the retrieved temperatures into the NCEP GFS data assimilation (GDAS) analysis fields for the three-dimension atmospheric temperature field within the storm and its environment. The analysis scheme is also generalized by using AMSU temperature anomaly fields, rather than the temperature itself and is therefore applicable for any NWP model outputs. It is shown that predictions of Hurricane Isabel (2003) from the Weather Research and Forecasting (WRF) model can be significantly improved with the AMSU derived hurricane initial vortex, in terms of improvements in storm tracks and intensity.

The NOAA/NESDIS Office of Research and Applications (ORA) has embarked on a pilot data stewardship project aimed at improving the data record from the Advanced Very High Resolution Radiometer (AVHRR). One part of this larger project includes the generation of a new cloud climatology from the Extended AVHRR Pathfinder Atmospheres (PATMOS-x) data set. Included within the PATMOS-x data-stream is a full suite of cloud products including various cloud amounts. This paper compares the PATMOS-x cloud amount time series for all July data (1982-2004) to the cloud amount time series from the International Satellite Cloud Climatology Project (ISCCP) and University of Wisconsin High Resolution Infrared Sounder (UW/HIRS) data sets. The results indicate that the large intersatellite discontinuities in the total amount seen in the original PATMOS are reduced in PATMOS-x. The total cloud for July time series from PATMOS-x, UW/HIRS and PATMOS show little trend over the period studied but that ISCCP time series does indicate a continuous downward trend When comparing the time series of high cloud amount, it was that PATMOS-x shows no significant trend in high cloud from 20S to 20N.

Under cloud-free conditions during the daytime, global synergistic retrievals of sea surface temperature (SST) and aerosol optical depths (AOD, or ) are made from the AVHRR instruments flown onboard polar-orbiting sun-synchronous NOAA-16 (equator crossing time, EXT~1400) and -17 (EXT~1000) satellites. Validation against buoys and sun-photometers is customarily considered the ultimate check of the quality and accuracy of SST and AOD retrievals. However, ground-truth data are not available globally and their quality is non-uniform. Moreover, the remotely-sensed parameters may not be fully comparable with their counterparts measured from the surface (e.g. skin vs. bulk SST), and the current procedures to merge data in space and time are not fully objective and may themselves introduce additional errors. In this paper, we propose to supplement the traditional validation with another global diagnostic system. The proposed Quality Control/Assurance (QC/QA) system is based on a comprehensive set of statistical self- and cross-consistency checks. Here, it is illustrated with 8 days of global NOAA-16 and -17 data in December 2003. The AODs and SST anomalies have been first aggregated into 1-day, 1-degree boxes, and their global statistics examined. Analyses are best done in anomalies from the expected state (climatology), which is currently available for the SST but not for the AOD. Histograms of NOAA-16 and -17 SST anomalies are highly correlated (R~0.77), both showing an approximately Gaussian shape, with a mean of ~+0.3K and RMS~1K. AODs also show much similarity but reveal significant cross-platform biases. The magnitudes and even the signs of these biases are band-specific, suggesting that they are due to calibration differences between the two AVHRRs flown on the two platforms. Recall that the AVHRR solar reflectance bands used for aerosol retrievals lack on-board calibration, and therefore may be subject to large calibration errors.

The operational Moderate-Resolution Imaging Spectroradiometer (MODIS) products for cloud properties such as cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), cloud optical thickness (COT), and cloud phase (CP) have been available for users globally. An approach to retrieve COT is investigated using MODIS infrared (IR) window spectral bands (8.5 mm, 11mm, and 12 mm). The COT retrieval from MODIS IR bands has the potential to provide microphysical properties with high spatial resolution during night. The results are compared with those from operational MODIS products derived from the visible (VIS) and near-infrared (NIR) bands during day. Sensitivity of COT to MODIS spectral brightness temperature (BT) and BT difference (BTD) values is studied. A look-up table is created from the cloudy radiative transfer model accounting for the cloud absorption and scattering for the cloud microphysical property retrieval. The potential applications and limitations are also discussed. This algorithm can be applied to the future imager systems such as Visible/Infrared Imager/Radiometer Suite (VIIRS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite (GOES)-R.

Radiances and brightness temperatures from three near-infrared/infrared channels that are available on most current and past satellite imagers were used to develop automated algorithms for identifying multilayered cloud systems (cloud overlap) and cirrus clouds at night. The cloud overlap algorithm uses information from the 3.75 micron, 11 micron, and 12 micron regions of the spectrum and the cirrus algorithm uses 3.75 micron and 11 micron channel data. The cloud overlap algorithm was developed assuming that a scene with cloud overlap consists of a semitransparent ice cloud that overlaps a lower cloud composed of liquid water droplets. Cirrus clouds are taken to be high ice clouds with a visible optical depth of 5.0 or less. The algorithms are applied to single satellite pixels that are already assumed to be cloudy based on cloud mask information. The utility of each algorithm was demonstrated on two different Moderate Resolution Imaging Spectroradiometer (MODIS) scenes and the cloud overlap algorithm was validated against millimeter radar-derived cloud boundaries. Overall the results show that both algorithms have the potential to be very useful for nighttime cloud studies.

Near-global total cloud frequencies and multilayered cloud frequencies derived from AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), and GLAS (Geoscience Laser Altimeter System) were analyzed and compared. The GLAS retrievals can be used to quantify the amount of cloud that may go undetected from satellite imagers such AVHRR and MODIS and to help validate satellite cloud overlap detection algorithms. Model sensitivity studies indicate that clouds with a total column optical depth of 0.5 or less may often go undetected by AVHRR and MODIS. The GLAS data show that such cloudy observations comprised 18.3% (14.5%) of all cloudy GLAS footprints during the most convectively active (least convectively active) portion of the day. Where the most (least) convectively active time period is defined as local solar noon plus (minus) 12 hours. It was also shown that the zonal mean total cloud frequency from GLAS and AVHRR and GLAS and MODIS are well correlated but often differ in magnitude because of thin clouds or small-scale cloud systems that are missed by the AVHRR and MODIS cloud detection algorithms. With the exception of the polar regions, the AVHRR and GLAS and the MODIS (via the Visible/Infrared Imager/Radiometer Suite algorithm) and GLAS multilayered cloud frequencies are in good agreement.

The solar reflectance bands (SRB) of the Advanced Very High Resolution Radiometers (AVHRR) flown onboard NOAA satellites are often referred to as non-calibrated in-flight. In contrast, the Earth emission bands (EEB) are calibrated using two reference points, deep space and the internal calibration target. In the SRBs, measurements of space count (SC) are also available, however, historically they are not used to specify the calibration offset ("zero count", ZC), which does not even appear in the calibration equation. A regression calibration formulation is used instead, equivalent to setting the ZC to a constant, whose value is specified from pre-launch measurements. Our analyses supported by a review of the instrument design and a wealth of historical SC information show that the SC varies in-flight and it differs from its pre-launch value. We therefore suggest that (1) the AVHRR calibration equation in the SRBs be re-formulated to explicitly use the ZC, consistently with the EEBs, and (2) the value of ZC be specified from the onboard measurements of SC. This study emphasizes the importance of clear discrimination between the SC (which is a measured quantity and therefore takes on a range of values, characterized by the empirical probability density function, PDF), from the ZC (which is a parameter in the calibration equation, i.e. a number whose value needs to be estimated from the measured SC as a mean, median or other statistic of the measured PDF). The ZC-formulation of the calibration equation is physically solid, and it minimizes human-induced calibration errors resulting from the use of a regression formulation with an un-constrained intercept. Specifying the calibration offset improves radiances, most notably at the low end of radiometric scale, and subsequently provides for more accurate vicarious determinations of the calibration slope (inverse gain). These calibration improvements are important for the products derived from the AVHRR low-radiances, such as aerosol over ocean, and particularly critical when generating their long-term climate data records.

The newly available Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP) data has been extended to create a comprehensive data set, called APP-x, containing cloud microphysical properties, surface temperature and broadband albedo, radiative fluxes and cloud forcing for the Arctic and Antarctic over the 19-year period 1982-2000. The APP-x data show that the annual mean cloud coverage in the Arctic is about 70%, with a maximum in September and a minimum in April. Arctic cloud optical depth averages about 5 ~ 6. The largest downwelling shortwave radiative flux at the surface occurs in June; the largest upwelling shortwave flux occurs in May. The largest downwelling and upwelling longwave and net radiative fluxes occur in July, with the largest loss of longwave radiation from the surface in April. Over the past 19 years, the Arctic has warmed and become cloudier in spring and summer, but has cooled and become less cloudy in winter. The decadal rate of annual surface temperature change is 0.57C for the Arctic region north of 60N. The surface broadband albedo has decreased at a decadal rate of -1.5% (absolute). Cloud fraction has decreased at a decadal rate of 6% (absolute) in winter, and increased at decadal rates of 3.2% and 1.6% in spring and summer, respectively. On an annual time scale, net cloud forcing at the surface has decreased at a decadal rate of -3.35 W/m², indicating an increased cooling by clouds. There are large correlations between surface temperature anomalies and climate indices such as the Arctic Oscillation (AO) index for some areas, implying linkages between global climate change and Arctic climate change.

Temperature retrievals from polar-orbiting satellites are clearly beneficial in the Southern Hemisphere and the stratosphere, due to lack of conventional data, but have neutral impact on Northern Hemisphere forecasts. An alternative to retrievals is the direct assimilation of radiance data. The NRL Variational Data Assimilation System (NAVDAS), coupled with the Navy Operational Global Atmospheric Prediction System (NOGAPS) NWP model, constitute a system capable of three-dimensional variational assimilation (3DVar) of radiance data. In particular, the assimilation of microwave radiance data from the Advanced Microwave Sounding Unit (AMSU-A) has shown clear positive impact on 5-day forecasts in both hemispheres. One requirement for successful radiance assimilation is bias correction. Biases are due both to the satellite instrument, and the underlying airmass, resulting from inaccuracies in the fast radiative transfer model that converts NWP fields into simulated radiances. Our approach to airmass bias correction uses multilinear regression of fifteen days of observed minus computed radiances, with selected NWP fields as predictors. Research into hybrid methods, which add the radiances themselves as predictors, is being pursued. Moisture retrievals from AMSU-B can also benefit from bias correction. Preliminary results comparing uncorrected and bias-corrected AMSU-B moisture retrievals are presented. The need for bias correction is universal. Our methodology is robust and general, and should be applicable to current and future satellites.

Tropospheric wind is a top priority NPOESS EDR that can be retrieved by tracking high spatial resolution altitude-resolved water vapor sounding features in imagery provided by a humidity imaging sounder. A Wedge-filter Imaging Sounder (WIS) can provide the required humidity imagery and has already been studied for application in geostationary orbit by Puschell, Huang and Woolf. The Wedge-filter Imaging Sounder for Humidity (WISH) incorporates the same technology and is suitable for flight on the NPOESS C2 or C3 spacecraft. WISH would take advantage of payload capacity available for P3I demonstrations in NPOESS and would serve as a risk reduction and technology demonstration for future NOAA environmental satellite missions. In this paper, we present our analysis of a preliminary WISH sensor concept design, specification and expected radiometric sensitivity. The practicality of WISH for current NPOESS spacecraft configurations will also be discussed. The performance of WISH toward achieving NPOESS P3I's tropospheric wind objective will be discussed in a companion paper by Huang et al. in SPIE conference 5655.

Cloud cover information and the frequency of upper tropospheric clouds have been extracted from NOAA/HIRS polar orbiting satellite data from 1979 to 2001. The HIRS/2 sensor was flown on nine satellites from TIROS-N through NOAA 14 during this time forming a consistent 22-year record. CO2 slicing was used to infer cloud amount and height. Trends in cloud cover and high cloud frequency are small in these data. High clouds show small but statistically significant increasing trends in the tropics and northern hemisphere. The HIRS analysis contrasts with that from the ISCCP which shows decreasing trends in both total cloud cover and high clouds during most of this period. The HIRS detection of upper tropospheric thin cirrus creates most of the difference with respect to ISCCP; GLAS observations of high thin clouds are largely in agreement with the HIRS.

The main purpose of Very Short-Range Forecasting System (VSRFS) is to develop algorithms for real-time monitoring and forecasting severe weather systems, which may result in flood, flash flood or landslide in Taiwan area. The operational VSRFS has being under progressive development in CWB since 2002. One component of the VSRFS is the QPESUMS system which is under a joint development program between US NOAA/NSSL and CWB. In QPESUMS, the Doppler radar, satellite infrared, raingauge and other data sources are ingested to make QPE for severe weather systems in Taiwan. Products from QPESUMS are presented in web page format. Currently, it shows that the QPE from QPESUMS has a good agreement with the surface observation when precipitation rate is greater than 10mm/hr. Efforts are put to the improvement of QPESUMS for making reasonable 0-2hr QPF by the end of 2005. Another component of the VSRFS is a diabatically initialized LAPS-MM5 system which is under a joint development program between NOAA/FSL and CWB for 2-12hr QPF. LAPS-MM5 is designed to effectively shorten the spin-up problem of simulating convective storms. Various data sources are assimilated into LAPS for MM5 to make time integration. It turns out that LAPS-MM5 is capable to predict the strength and location of heavy precipitation system with 6-hourly rain rate greater than 35mm (higher Equitable Threat Score), yet prone to over-predict the rainfall rate when precipitating system was weaker. In order to suit the need for near real-time (2-12hr) severe weather forecast, many challenging tasks related to the cloud/moisture analysis, dynamic/thermodynamic balance schemes are to be overtaken in the forthcoming years.

Validation of the CLAVR-x cloud detection algorithm over ocean is presented in this paper. CLAVR-x is the latest AVHRR processor developed at the NOAA/NESDIS Office of Research and Applications, with much improved cloud detection algorithm than its CLAVR predecessors. As our first validation study, we have selected sea surface temperature obtained from the NOAA-16 AVHRR GAC data for July 2001. The SST data was matched-up with global buoy data, which was assumed to be ground truth. Both fixed and drifting buoys were considered. This analysis indicates that the CLAVR-x cloud masking allows for generation of sea surface temperature values that are in good agreement with in situ buoys.