NPOESS Preparatory Project Research Articles

A physical algorithm for precipitable water vapour retrieval over land using passive microwave observations

ABSTRACT Precipitable water vapour (PWV) plays an important role in weather prediction, hydrological cycles and climate change. In this study, a physics-based algorithm was proposed to retrieve PWV over land using satellite passive microwave observations near 165.50 GHz and 183.31 GHz, which have higher spatial resolution and lower sensitivity to land surface emissivity than low-frequency channels. The algorithm uses a perturbation formulation of simplified radiative transfer equation to derive PWV and at-surface brightness temperature (BT) in 165.50 GHz simultaneously. It directly derives the at-surface BT instead of land surface temperature, so the algorithm needs no prior information of surface emissivity. Sensitivity analysis and retrieval experiments from simulated data were carried out for Advanced Technology Microwave Sounder (ATMS) onboard the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) satellite. The results showed that the algorithm using ATMS channels 17, 18 and 19 measurements can significantly reduce the PWV retrieval errors caused by surface emissivity uncertainty. The coefficient of determination (R 2), root-mean-square error (RMSE), and bias of the retrieved PWV from ATMS data by the proposed algorithm and SuomiNet Global Positioning System (GPS) PWV were 0.90, 0.43 cm and −0.02 cm, respectively. In addition, the Visible Infrared Imaging Radiometer Suite (VIIRS) cloud products were used to evaluate the effects of cloud on the PWV retrievals. The results showed that the presence of cloud does not decrease the accuracy of the PWV retrievals.

CHLOROPHYLL-A CONCENTRATIONS ESTIMATION FROM AQUA-MODIS AND VIIRS-NPP SATELLITE SENSORS IN SOUTH JAVA SEA WATERS

This study aimed to estimate the concentration of chlorophyll-a from satellite imagery of National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) in the south Java Sea waters and compare it to the concentrations of chlorophyll-a estimation result from the MODIS-Aqua satellite. NPP satellite had Visible/Infrared Imager Radiometer Suite (VIIRS) sensors which performance was same as Moderate Resolution Imaging Spectroradiometer (MODIS) sensor with a better spatial resolution. This study used daily satellite imagery of VIIRS-NPP for the period of September 2012 to August 2013. The algorithm that was used to estimate the concentration of chlorophyll-a was Ocean Color 3-band ratio (OC-3). The results showed that the spatial distribution pattern of chlorophyll-a concentration between VIIRS - NPP sensor and MODIS had the same pattern, but the estimation of chlorophyll-a concentration from the MODIS sensor was higher than VIIRS -NPP sensor. The concentration of chlorophyll-a showed that there were spatial and temporal variation in the south Java Sea waters. Generally, concentrations of chlorophyll-a was higher in East monsoon than West monsoon.

Clouds and Earth Radiant Energy System: From Design to Data

The Clouds and the Earth's Radiant Energy System (CERES) project has instruments aboard the Terra and Aqua spacecraft that have provided a decade of radiation budget data. In October 2011, the CERES flight model 5 was placed in orbit on the NPOESS Preparatory Project spacecraft. Data from these instruments are being used to investigate the radiation balance of the Earth at various time and space scales and the role of clouds in this balance. The design and calibration, both on the ground and in-orbit, and operation of the instrument are discussed.

Cloudy Forecast for Weather Satellite Data

![Figure][1] NPOESS Preparatory Project satellite (artist's rendition). CREDIT: NOAA IN SPACE COLLECTION In the News Focus story “Weather forecasts slowly clearing up” (9 November, p. [734][2]), R. Kerr nicely summarizes how the growing improvement in prediction is coming from a focus on “more computer power, the assimilation of radar observations, and more physically realistic models.” He emphasizes that better assimilation of satellite data is a key element of improved forecasting. Unfortunately, these potential improvements will have little effect on forecasts if the basic data set from the existing polar-orbiting weather satellite system is not available. In a report issued in June 2012 ([ 1 ][3]), the U.S. Government Accountability Office noted that “data from this system is the predominant input to numerical weather prediction models” and warned that “there will likely be a gap in satellite data lasting 17 to 53 months” when the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project satellite ceases operations and NOAA's new satellite system (the Joint Polar Satellite System) launches. The report also notes that there are “potential satellite data gaps in DOD [Department of Defense] and European polar satellite programs which provide supplementary information to NOAA forecasts.” These gaps are a grave problem and would seriously degrade weather forecasts. Therefore, the agencies responsible for weather forecasting—NOAA, DOD, and NASA—should make filling the polar satellite data gaps the first priority in order to ensure that future forecasts are as good as possible. 1. [↵][4] U.S. GAO, “Polar-orbiting environmental satellites: Changing requirements, technical issues, and looming data gaps require focused attention,” GAO-12-604 (2012); [www.gao.gov/products/GAO-12-604][5]. [1]: pending:yes [2]: /lookup/doi/10.1126/science.338.6108.734 [3]: #ref-1 [4]: #xref-ref-1-1 View reference 1 in text [5]: http://www.gao.gov/products/GAO-12-604

Temporal co-registration for TROPOMI cloud clearing

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) is anticipated to provide high-quality and timely global atmospheric composition information through observations of atmospheric constituents such as ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, methane, formaldehyde and aerosol properties. The methane and the aerosol retrievals require very precise cloud clearing, which is difficult to achieve at the TROPOMI spatial resolution (7 by 7 km) and without thermal IR measurements. The TROPOMI carrier – the Sentinel 5 Precursor (S5P), does not include a cloud imager, thus it is planned to fly the S5P mission in a constellation with an instrument yielding an accurate cloud mask. The cloud imagery data will be provided by the US NPOESS Preparatory Project (NPP) mission, which will have the Visible Infrared Imager Radiometer Suite (VIIRS) on board (Scalione, 2004). This paper investigates the temporal co-registration requirements for suitable time differences between the VIIRS measurements of clouds and the TROPOMI methane and aerosol measurements, so that the former could be used for cloud clearing. The temporal co-registration is studied using Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) data with 15 min temporal resolution (Veefkind, 2008b), and with data from the Geostationary Operational Environmental Satellite – 10 (GOES-10) having 1 min temporal resolution. The aim is to understand and assess the relation between the amount of allowed cloud contamination and the required time difference between the two satellites' overflights. Quantitative analysis shows that a time difference of approximately 5 min is sufficient (in most conditions) to use the cloud information from the first instrument for cloud clearing in the retrievals using data from the second instrument. In recent years the A-train constellation demonstrated the benefit of flying satellites in formation. Therefore this study's findings will be useful for designing future Low Earth Orbit (LEO) satellite constellations.

Automated Lightning Flash Detection in Nighttime Visible Satellite Data

Abstract The Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) nighttime visible channel was designed to detect earth–atmosphere features under conditions of low illumination (e.g., near the solar terminator or via moonlight reflection). However, this sensor also detects visible light emissions from various terrestrial sources (both natural and anthropogenic), including lightning-illuminated thunderstorm tops. This research presents an automated technique for objectively identifying and enhancing the bright steaks associated with lightning flashes, even in the presence of lunar illumination, derived from OLS imagery. A line-directional filter is applied to the data in order to identify lightning strike features and an associated false color imagery product enhances this information while minimizing false alarms. Comparisons of this satellite product to U.S. National Lightning Detection Network (NLDN) data in one case as well as to a lightning mapping array (LMA) in another case demonstrate general consistency to within the expected limits of detection. This algorithm is potentially useful in either finding or confirming electrically active storms anywhere on the globe, particularly those occurring in remote areas where surface-based observations are not available. Additionally, the OLS nighttime visible sensor provides heritage data for examining the potential usefulness of the Visible-Infrared Imager-Radiometer Suite (VIIRS) Day/Night Band (DNB) on future satellites including the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP). The VIIRS DNB will offer several improvements to the legacy OLS nighttime visible channel, including full calibration and collocation with 21 narrowband spectral channels.

Comparing MODIS and AIRS Infrared-Based Cloud Retrievals

AbstractComparisons are described for infrared-derived cloud products retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) using measured spatial response functions obtained from prelaunch AIRS calibration. One full day (1 January 2005) of global collection-5 MODIS and version-5 AIRS retrievals of cloud-top temperature Tc, effective cloud fraction f, and derived effective brightness temperature Tb,e is investigated. Comparisons of Tb,e demonstrate that MODIS and AIRS are essentially radiatively consistent and that MODIS Tb,e is 0.62 K higher than AIRS Tb,e for all scenes, increasing to 1.43 K for cloud described by AIRS as single layer and decreasing to 0.50 K for two-layer clouds. Somewhat larger differences in Tc and f are observed between the two instruments. The magnitudes of differences depend partly on whether MODIS uses a CO2-slicing or 11-μm brightness temperature window retrieval method. Some cloud- and regime-type differences and similarities between AIRS and MODIS cloud products are traceable to the assumptions made about the number of cloud layers in AIRS and also to the MODIS retrieval method. This (partially) holistic comparison approach should be useful for ongoing algorithm refinements, rigorous assessments of climate applicability, and establishment of the capability of synergistic MODIS and AIRS retrievals for improved cloud quantities and also should be useful for future observations to be made by the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP).

NPOESS

The United States is merging its two polar-orbiting operational environmental satellite programs operated by the Department of Commerce and the Department of Defense into a single system, which is called the National Polar-orbiting Operational Environmental Satellite System (NPOESS). During the next decade, NPOESS will provide global operational data to meet many of the needs of weather forecasters, climate researchers, and global decision makers for remotely sensed Earth science data and global environmental monitoring. The NPOESS Preparatory Project (NPP) will be launched in 2011 as a precursor to NPOESS to reduce final development risks for NPOESS and to provide continuity of global imaging and atmospheric sounding data from the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) missions. Beginning in 2014, NPOESS spacecraft will be launched into an afternoon orbit and in 2016 into an early-morning orbit to provide significantly improved operational capabilities and benefits to satisfy critical civil and national security requirements for space-based, remotely sensed environmental data. The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteorological Operation (MetOp) spacecraft will complement NPOESS in a midmorning orbit. The joint constellation will provide global coverage with a data refresh rate of approximately four hours. NPOESS will observe more phenomena simultaneously from space and deliver a data volume significantly greater than its operational predecessors with substantially improved data delivery to users. Higher-resolution (spatial and spectral) and more accurate imaging and atmospheric sounding data will enable improvements in short- to medium-range weather forecasts. Multispectral and hyperspectral instruments on NPOESS will provide global imagery and sounding products useful to the forecaster that are complementary to those available from geostationary satellites. NPOESS will support the operational needs of meteorological, oceanographic, environmental, climatic, and space environmental remote sensing programs and provide continuity of data for climate researchers. This article that describes NPOESS was completed and accepted for publication prior to the White House decision in February 2010 ordering a major restructuring of the NPOESS program. The Department of Commerce will now assume primary responsibility for the afternoon polar-orbiting operational environmental satellite orbit and the Department of Defense will take primary responsibility for the early morning orbit. However, NPP, as described in this article, is still scheduled to be launched in 2011. Several of the instruments and program elements described in this article are also likely to be carried forward into future U.S. polar-orbiting operational environmental satellite missions.

Creating Proxy VIIRS Data From MODIS: Spectral Transformations for Mid- and Thermal-Infrared Bands

Prior to the launch of a new satellite, simulated sensor data are often desired to develop and test the new sensors and algorithms. Ideally, these data closely approximate the data that will be collected on-orbit. Although radiative-transfer models can be employed for this purpose, all models have biases, and none can completely mimic the complex heterogeneity of Earth's environmental system. An alternative approach is to derive ldquoproxyrdquo data sets by transforming real observations collected from past or current sensors. Proxy data inherently contain both natural Earth radiation characteristics and sensor noise as the data from the new sensor will. In preparation for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and NPOESS Preparatory Project missions, we developed a methodology to create proxy data for the mid- and thermal-infrared bands of the Visible-Infrared Imager-Radiometer Suite (VIIRS). Specifically, by combining radiative-transfer modeling and data from NASA's Atmospheric Infrared Sounder (AIRS), we developed spectral transformation equations to convert real Moderate Resolution Imaging Spectroradiometer (MODIS) data into proxy VIIRS data. The functional forms of the equations were determined through regression analysis. Typically, the best spectral transformation equation for a given VIIRS band was a function of multiple MODIS bands, sensor/solar geometry, and surface type. All transformation equations are for clear-sky conditions. Our daytime midinfrared transformation equations have an accuracy that is below the predicted sensor noise for all surface types. Our thermal-infrared equations over land are most accurate for vegetated covers; our ocean equations are accurate for most bands. Validation of this approach with the Advanced Very High Resolution Radiometer suggests that this method may provide higher accuracy proxy data than other methods. Although the advantage in using AIRS is its hyperspectral design, allowing simulation of MODIS and VIIRS bands, its coarse spatial resolution presented a disadvantage in identifying pure land-cover and cloud-free pixels for generating the equation coefficients. Our primary intent with this paper is to offer a methodology for consideration by other sensor teams. Our provisional MODIS-to-VIIRS spectral transformation equations are included for some example surface types.

Physically Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

Abstract A physical inversion scheme has been developed dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1D) variational multivariable inversion solution is used to improve an iterative background state defined by an eigenvector-regression retrieval. The solution is iterated in order to account for nonlinearity in the 1D variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud-top level are obtained. For both optically thin and thick cloud situations, the cloud-top height can be retrieved with relatively high accuracy (i.e., error <1 km). National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the The Observing-System Research and Predictability Experiment (THORPEX) Atlantic Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing cloud physics lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project, and the follow-on NPOESS series of satellites.

Cloud base heights retrieved during night‐time conditions with MODIS data

The capability to retrieve cloud base heights was developed under the US National Polar‐orbiting Operational Environmental Satellite System (NPOESS) programme as one of 27 data products to be created from data collected by the Visible Infrared Imager Radiometer Suite (VIIRS). First launch of the VIIRS sensor, which is the high‐resolution Earth imager of the NPOESS programme, comes on National Aeronautics & Space Administration's (NASA) NPOESS Preparatory Project (NPP). In preparation for this launch, extensive testing of the VIIRS cloud algorithms was completed to verify that product performance will satisfy system requirements before the cloud algorithms were hosted in the NPOESS ground processing centre. The approach taken to retrieve cloud base height converts cloud optical properties into a geometric thickness which is then subtracted from the cloud top height. Performance of the cloud base height algorithms has been verified recently using MODIS data, together with temporarily and spatial coincident observations of cloud thickness values made with the millimetre cloud radar operated at the US Department of Energy Atmospheric Radiation Measurement (ARM) Program Southern Great Plains site in Oklahoma. Of particular significance is the clear demonstration that both cloud optical properties and cloud base heights are retrieved accurately during night‐time conditions with the VIIRS algorithms, since neither of these products is currently produced by the NASA EOS programme. Based upon these analyses, the VIIRS cloud algorithms are expected to satisfy NPOESS requirements, making VIIRS the first operational satellite sensor capable of retrieving three‐dimensional cloud fields.

Automated cloud detection and classification of data collected by the Visible Infrared Imager Radiometer Suite (VIIRS)

The Visible Infrared Imager Radiometer Suite (VIIRS) is a high‐resolution Earth imager of the United States National Polar‐orbiting Operational Environmental Satellite System (NPOESS). VIIRS has its heritage in three sensors currently collecting imagery of the Earth—the Advanced Very High Resolution Radiometer, the Moderate Resolution Imaging Spectroradiometer, and the Operational Linescan Sensor. The first launch of the VIIRS sensor is on NASA's NPOESS Preparatory Project (NPP). Data collected by VIIRS will provide products to a variety of users, supporting applications from real‐time to long‐term climate change timescales. VIIRS has been uniquely designed to satisfy this full range of requirements. Cloud masks derived from the automated analyses of VIIRS data are critical data products for the NPOESS program. In this paper, the VIIRS cloud mask (VCM) performance requirements are highlighted, along with the algorithm developed to satisfy these requirements. The expected performance of the VCM algorithm is established using global synthetic cloud simulations and manual cloud analyses of VIIRS proxy imagery. These results show the VCM analyses will satisfy the performance expectations of products created from it, including land and ocean surface products, cloud microphysical products, and automated cloud forecast products. Finally, minor deficiencies that remain in the VCM algorithm logic are identified along with a mitigation plan to resolve each prior to NPP launch or shortly thereafter.

Environmental Satellite Program over budget, behind schedule

The U.S. National Polar‐orbiting Operational Environmental Satellite System (NPOESS) will exceed its $6.9 billion cost estimate by at least 15 percent, and its planners are now considering cutting instruments and satellites in addition to long delays.“[NPOESS] is so badly broken … we could lose a lot of the climate [components], we could lose instruments,” NPOESS Preparatory Project (NPP) project scientist Jim Gleason told a committee of the National Research Council of the U.S. National Academies at a 25 October meeting.