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The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) Data Depository and Distribution Element (SD3E) System Architecture

The National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government's future low-Earth orbiting satellite system, will monitor global weather and environmental conditions. Serving as a risk reduction for NPOESS, the NPOESS Preparatory Project (NPP) will provide remotely sensed atmospheric, land, ocean, ozone, and sounder data that will serve the meteorological and global climate change scientific communities. The National Aeronautics and Space Administration (NASA) NPP Science Data Segment's (SDS) primary role is to independently assess the quality of the NPP science and environmental data records for their ability to support climate research. The SDS is composed of nine elements; an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. Each element requires a set of sensor specific science data products for their evaluation. There are four NPP sensors that will be flown on the NPP observatory. They are the Visible Infrared Imagining Radiometer Suite (VIIRS), the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Ozone Mapper/Profiler Suite (OMPS). It is estimated that these four sensors combined will make daily data requests for approximately six terabytes of NPP science products from the operational data providers. As a result, issues associated with duplicate data requests, data transfers of large volumes of diverse products, and data transfer failures raised concerns with respect to the network traffic and bandwidth consumption. Therefore, a central data broker system for receiving and buffering data requests and data products for the SDS was developed. The data element for this system is called the SDS Data Depository and Distribution Element (SD3E). It supports science mission data assessment by assuring the timely and validated acquisition and subsequent transfer of the NPP Science Mission data to the SDS Elements and NPP Science Team. The six science elements that interface with the SD3E span across the NASA Goddard Space Flight Center (GSFC), the NASA Jet Propulsion Laboratory (JPL), and the University of Wisconsin. As the primary communication vehicle for the science elements and science team, the SD3E has an interface to the operational data providers: National Environment Satellite, Data, and Information Service (NESDIS) Interface Data Processing System (IDPS) and the National Oceanic Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship system (CLASS) Archive Data System (ADS), that are responsible for product generation and archive and distribution respectively. The SD3E is designed to be a semi-customizable and semi-automated system. This system is designed to provide flexibility and ease of use for the science users in accessing the latest data products by creating a rolling data cache that temporarily stores the products locally before transferring the data to the SDS Measurement based elements for the land, ocean, atmosphere, sounder, and ozone. This paper describes the design and architecture of one of the nine SDS elements, the SD3E, and how this system has provided a mechanism for efficient data exchange, how it has helped in alleviating some of the network traffic and usage, and how it has contributed to reducing operational costs.

Ho, Evelyn L.↗

Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Validation and Verification on National Oceanographic and Atmospheric Administration (NOAA) Lockheed WP-3D Aircraft

As part of the National Aeronautics and Space Administration's Aviation Safety and Security Program, the Tropospheric Airborne Meteorological Data Reporting project (TAMDAR) developed a low-cost sensor for aircraft flying in the lower troposphere. This activity was a joint effort with support from Federal Aviation Administration, National Oceanic and Atmospheric Administration, and industry. This paper reports the TAMDAR sensor performance validation and verification, as flown on board NOAA Lockheed WP-3D aircraft. These flight tests were conducted to assess the performance of the TAMDAR sensor for measurements of temperature, relative humidity, and wind parameters. The ultimate goal was to develop a small low-cost sensor, collect useful meteorological data, downlink the data in near real time, and use the data to improve weather forecasts. The envisioned system will initially be used on regional and package carrier aircraft. The ultimate users of the data are National Centers for Environmental Prediction forecast modelers. Other users include air traffic controllers, flight service stations, and airline weather centers. NASA worked with an industry partner to develop the sensor. Prototype sensors were subjected to numerous tests in ground and flight facilities. As a result of these earlier tests, many design improvements were made to the sensor. The results of tests on a final version of the sensor are the subject of this report. The sensor is capable of measuring temperature, relative humidity, pressure, and icing. It can compute pressure altitude, indicated air speed, true air speed, ice presence, wind speed and direction, and eddy dissipation rate. Summary results from the flight test are presented along with corroborative data from aircraft instruments.

Tsoucalas, George↗

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths with GOES Data Over ARM/SGP Site

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum et al used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. used a combination infrared (IR), visible (VIS), and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne proposed a 1.6 and 11 micron bispectral threshold method. While all of these methods have made progress in solving this stubborn problem none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the Atmospheric Radiation Measurement (ARM) domains and hence should be identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) used over the ARM Program's Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites to study the capability of detecting overlapping clouds.

Kawamoto, K.↗

Low Resolution Picture Transmission (LRPT) Demonstration System

Low-Resolution Picture Transmission (LRPT) is a proposed standard for direct broadcast transmission of satellite weather images. This standard is a joint effort by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and the National Oceanic Atmospheric Administration (NOAA). As a digital transmission scheme, its purpose is to replace the current analog Automatic Picture Transmission (APT) system for use in the Meteorological Operational (METOP) satellites. Goddard Space Flight Center has been tasked to build an LRPT Demonstration System (LDS). It's main objective is to develop or demonstrate the feasibility of a low-cost receiver utilizing a Personal Computer (PC) as the primary processing component and determine the performance of the protocol in the simulated Radio Frequency (RF) environment. The approach would consist of two phases. In the phase 1, a Commercial-off-the-Shelf (COTS) Modulator-Demodulator (MODEM) board that would perform RF demodulation would be purchased allowing the Central Processing Unit (CPU) to perform the Consultative Committee for Space Data Systems (CCSDS) protocol processing. Also since the weather images are compressed the PC would perform the decompression. Phase 1 was successfully demonstrated on December 1997. Phase 2 consists of developing a high-fidelity receiver, transmitter and environment simulator. Its goal is to find out how the METOP Specification performs in a simulated noise environment in a cost-effective receiver. The approach would be to produce a receiver using as much software as possible to perform front-end processing to take advantage of the latest high-speed PCs. Thus the COTS MODEM used in Phase 1 is performing RF demodulation along with data acquisition providing data to the receiving software. Also, environment simulator is produced using the noise patterns generated by Institute for Telecommunications Sciences (ITS) from their noise environment study.

Fong, Wai↗

Verification and Validation of NASA-Supported Enhancements to the Near Real Time Harmful Algal Blooms Observing System (HABSOS)

This report discusses verification and validation (V&V) assessment of Moderate Resolution Imaging Spectroradiometer (MODIS) ocean data products contributed by the Naval Research Laboratory (NRL) and Applied Coherent Technologies (ACT) Corporation to National Oceanic Atmospheric Administration s (NOAA) Near Real Time (NRT) Harmful Algal Blooms Observing System (HABSOS). HABSOS is a maturing decision support tool (DST) used by NOAA and its partners involved with coastal and public health management.

Spruce, Joseph P.↗

Thermal Band Atmospheric Correction Using Atmospheric Profiles Derived from Global Positioning System Radio Occultation and the Atmospheric Infrared Sounder

This Rapid Prototyping Capability study explores the potential to use atmospheric profiles derived from GPS (Global Positioning System) radio occultation measurements and by AIRS (Atmospheric Infrared Sounder) onboard the Aqua satellite to improve surface temperature retrieval from remotely sensed thermal imagery. This study demonstrates an example of a cross-cutting decision support technology whereby NASA data or models are shown to improve a wide number of observation systems or models. The ability to use one data source to improve others will be critical to the GEOSS (Global Earth Observation System of Systems) where a large number of potentially useful systems will require auxiliary datasets as input for decision support. Atmospheric correction of thermal imagery decouples TOA radiance and separates surface emission from atmospheric emission and absorption. Surface temperature can then be estimated from the surface emission with knowledge of its emissivity. Traditionally, radiosonde sounders or atmospheric models based on radiosonde sounders, such as the NOAA (National Oceanic & Atmospheric Administration) ARL (Air Resources Laboratory) READY (Real-time Environmental Application and Display sYstem), provide the atmospheric profiles required to perform atmospheric correction. Unfortunately, these types of data are too spatially sparse and too infrequently taken. The advent of high accuracy, global coverage, atmospheric data using GPS radio occultation and AIRS may provide a new avenue for filling data input gaps. In this study, AIRS and GPS radio occultation derived atmospheric profiles from the German Aerospace Center CHAMP (CHAllenging Minisatellite Payload), the Argentinean Commission on Space Activities SAC-C (Satellite de Aplicaciones Cientificas-C), and the pair of NASA GRACE (Gravity Recovery and Climate Experiment) satellites are used as input data in atmospheric radiative transport modeling based on the MODTRAN (MODerate resolution atmospheric TRANsmittance) radiative transport software to separate out the atmospheric component of measured top of atmosphere radiance. Simulated water bodies across a variety of MODTRAN model atmospheres including desert, mid-latitude, tropical and sub-artic conditions provide test bed conditions. Atmospherically corrected radiance and surface temperature results were compared to those obtained using traditional radiosonde balloon data and models. In general, differences between the different techniques were less than 2 percent indicating the potential value satellite derived atmospheric profiles have to atmospherically correct thermal imagery.

Pagnutti, Mary↗

Waterway Ice Thickness Measurements

The ship on the opposite page is a U. S. Steel Corporation tanker cruising through the ice-covered waters of the Great Lakes in the dead of winter. The ship's crew is able to navigate safely by plotting courses through open water or thin ice, a technique made possible by a multi-agency technology demonstration program in which NASA is a leading participant. Traditionally, the Great Lakes-St. Lawrence Seaway System is closed to shipping for more than three months of winter season because of ice blockage, particularly fluctuations in the thickness and location of ice cover due to storms, wind, currents and variable temperatures. Shippers have long sought a system of navigation that would allow year-round operation on the Lakes and produce enormous economic and fuel conservation benefits. Interrupted operations require that industrial firms stockpile materials to carry them through the impassable months, which is costly. Alternatively, they must haul cargos by more expensive overland transportation. Studies estimate the economic benefits of year-round Great Lakes shipping in the hundreds of millions of dollars annually and fuel consumption savings in the tens of millions of gallons. Under Project Icewarn, NASA, the U.S. Coast Guard and the National Oceanic Atmospheric Administration collaborated in development and demonstration of a system that permits safe year-round operations. It employs airborne radars, satellite communications relay and facsimile transmission to provide shippers and ships' masters up-to-date ice charts. Lewis Research Center contributed an accurate methods of measuring ice thickness by means of a special "short-pulse" type of radar. In a three-year demonstration program, Coast Guard aircraft equipped with Side-Looking Airborne Radar (SLAR) flew over the Great Lakes three or four times a week. The SLAR, which can penetrate clouds, provided large area readings of the type and distribution of ice cover. The information was supplemented by short-pulse radar measurements of ice thickness. The radar data was relayed by a NOAA satellite to a ground station where NOAA analyzed it and created picture maps, such as the one shown at lower left, showing where icebreakers can cut paths easily or where shipping can move through thin ice without the aid of icebreakers. The ice charts were then relayed directly to the wheelhouses of ships operating on the Lakes. Following up the success of the Great Lakes program, the icewarn team applied its system in another demonstration, this one a similarly successful application designed to aid Arctic coast shipping along the Alaskan North Slope. Further improvement of the ice-monitoring system is planned. Although aircraft-mounted radar is effective, satellites could provide more frequent data. After the launch this year of Seasat, an ocean-monitoring satellite, NASA will conduct tests to determine the ice-mapping capability and accuracy of satellite radar images.

Source record↗

The Effect of a Potentially Low Solar Cycle #24 on Orbital Lifetimes of Fengyun 1-C Debris

The magnitude of Solar Cycle #24 will have a non-trivial impact on the lifetimes of debris pieces that resulted from the intentional hypervelocity impact of the Fengyun 1-C satellite in January 2007. Recent solar flux measurements indicate Solar Cycle #24 has begun in the last few months, and will continue until approximately 2019. While there have been differing opinions on whether the intensity of this solar cycle will be higher or lower than usual, the Space Weather Prediction Center within the National Oceanic Atmospheric Administration (NOAA/SWPC) has recently forecast unusually low solar activity, which would result in longer orbital lifetimes. Using models for both the breakup of Fengyun 1-C and the propagation of the resultant debris cloud, the Orbital Debris Program Office at NASA Johnson Space Center conducted a study to better understand the impact of the solar cycle on lifetimes for pieces as small as 1 mm. Using a modified collision breakup model and PROP3D propagation software, the orbits of nearly 2 million objects 1 mm and larger were propagated for up to 200 years. By comparing a normal solar cycle with that of the NOAA/SWPC forecast low cycle, the effect of the solar flux on the lifetimes of the debris pieces is evaluated. The modeling of the low solar cycle shows an additional debris count of 12% for pieces larger than 10 cm by 2019 when compared to the resultant debris count using a normal cycle. The difference becomes more exaggerated (over 15%) for debris count in the smaller size regimes. However, in 50 years, the models predict the differences in debris count from differing models of Solar Cycle #24 to be less than 10% for all size regimes, with less variance in the smaller sizes. Understanding the longevity of the debris cloud will affect collision probabilities for both operational spacecraft and large derelict objects over the next century and beyond.

Whitlock, David↗

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Department (KMD). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the boundary layer of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-end events over east Africa. KMD currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Nonhydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over eastern Africa. Two organizations at the National Aeronautics and Space Administration Marshall Space Flight Center in Huntsville, AL, SERVIR and the Short-term Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMD for enhancing its regional modeling capabilities. To accomplish this goal, SPoRT and SERVIR will provide experimental land surface initialization datasets and model verification capabilities to KMD. To produce a land-surface initialization more consistent with the resolution of the KMD-WRF runs, the NASA Land Information System (LIS) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

Case. Jonathan↗

Retrieval of Snow Water Equivalent by the Precipitation Imaging Package (PIP) over Northern Great Lakes

Performance of the Precipitation Imaging Package (PIP) for estimating the snow water equivalent (SWE) is evaluated through a comparative study with the collocated National Oceanic and Atmospheric Administration National Weather Service snow stake field measurements. The PIP together with a vertically pointing radar, a weighing bucket gauge, and a laser-optical disdrometer was deployed at the NWS Marquette, Michigan office building for a long-term field study supported by the National Aeronautics and Space Administration’s Global Precipitation Measurement mission Ground Validation program. The site was also equipped with a weather station. During the 2017-18 winter, PIP functioned nearly uninterrupted at frigid temperatures accumulating 2345.8 mm of geometric snow depth over a total of 499 hours. This long record consists of 30 events, and the PIP-retrieved and snow stake field measured SWE differed less than 15% in every event. For the windy events, the wind corrected stake field record agreed better with the PIP-retrieved SWE. Two of the major events with the longest duration and the highest accumulation are examined in detail. The particle mass with a given diameter was much lower during a shallow, colder, uniform lake-effect event than in the deep, less cold, and variable synoptic event. This study demonstrated that PIP is a robust instrument for operational use, and is reliable for deriving the bulk properties of falling snow.

Ali Tokay↗

Surface Radiation Budget (SRB) Release 2.5 QC Longwave Monthly Data in Native Format (SRB_REL2.5_QCLW_MONTHLY)

The surface radiation budget data include downward and net longwave fluxes, as well as three meteorological parameters for the entire globe between 07/01/1983 and 06/30/2005. These parameters were derived within the Quality-Check LW (QCLW) algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=monthly; Temporal_Resolution_Range=monthly].

RADIATIVE FLUX↗

Surface Radiation Budget (SRB) Release 2.5 Longwave 3 hourly Data in Native Format (SRB_REL2.5_LW_3HRLY)

The SRB data include upward and downward fluxes and day/night conditions measured at three hourly intervals for each day for the entire globe between 07/01/1983 and 06/30/2005. These LW surface and Top of the Atmosphere (TOA) radiative parameters were derived with the Longwave algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=3 hourly; Temporal_Resolution_Range=3 hourly].

SURFACE LONGWAVE FLUX↗

Surface Radiation Budget (SRB) Release 2.5 QC Longwave 3 hourly Data in Native Format (SRB_REL2.5_QCLW_3HRLY)

This data set contains average surface downward longwave flux, surface net longwave flux, and surface longwave cloud radiative forcing at three hourly intervals for each day for the entire glob between 07/01/1983 and 06/30/2005. These LW surface radiative parameters were derived with the Quality-Check LW (QCLW) algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=3-hourly; Temporal_Resolution_Range=3-hourly].

SURFACE DOWNWARD LONGWAVE FLUX↗

Surface Radiation Budget (SRB) Release 2 Shortwave Daily Data in Native Format (SRB_REL2_SW_DAILY)

This data set contains upward and downward fluxes, photosynthetically active radiative flux, aerosol and cloud optical depth, cloud fraction, and solar zenith angle measured at three hourly intervals for each day for the entire globe between 07/01/1983 and 10/31/1995. These SW surface radiative parameters were derived with the Shortwave algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1998-07-26] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=daily; Temporal_Resolution_Range=daily].

ALL SKY SW SURFACE UPWARD FLUX↗

Operational Use of the AIRS Total Column Ozone Retrievals Along with the RGB Air Mass Product as Part of the GOES-R Proving Ground

The National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Hydrometeorological Prediction Center (HPC) and Ocean Prediction Center (OPC) provide short-term and medium-range forecast guidance of heavy precipitation, strong winds, and other features often associated with mid-latitude cyclones over both land and ocean. As a result, detection of factors that lead to rapid cyclogenesis and high wind events is key to improving forecast skill. One phenomenon that has been identified with these events is the stratospheric intrusion that occurs near tropopause folds. This allows for deep mixing near the top of the atmosphere where dry air high in ozone concentrations and potential vorticity descends (sometimes rapidly) deep into the mid-troposphere. Observations from satellites can aid in detection of these stratospheric air intrusions (SAI) regions. Specifically, multispectral composite imagery assign a variety of satellite spectral bands to the red, green, and blue (RGB) color components of imagery pixels and result in color combinations that can assist in the detection of dry stratospheric air associated with PV advection, which in turn may alert forecasters to the possibility of a rapidly strengthening storm system. Single channel or RGB satellite imagery lacks quantitative information about atmospheric moisture unless the sampled brightness temperatures or other data are converted to estimates of moisture via a retrieval process. Thus, complementary satellite observations are needed to capture a complete picture of a developing storm system. Here, total column ozone retrievals derived from a hyperspectral sounder are used to confirm the extent and magnitude of SAIs. Total ozone is a good proxy for defining locations and intensity of SAIs and has been used in studies evaluating that phenomenon (e.g. Tian et al. 2007, Knox and Schmidt 2005). Steep gradients in values of total ozone seen by satellites have been linked to stratosphere-troposphere exchange (WMO, 1985).

Folmer, Michael↗

Surface Radiation Budget (SRB) Release 2.5 Longwave 3 hourly Monthly Data in Native Format (SRB_REL2.5_LW_3HRLY_MONTHLY)

The surface radiation budget data include the averageupward and downward fluxes at three hourly intervals for the entire globe between 07/01/1983 and 06/30/2005. These parameters were derived using the Longwave algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=3 hourly values averaged monthly; Temporal_Resolution_Range=monthly].

OUTGOING LONGWAVE RADIATION↗

Improving NOAA's NWLON Through Enhanced Data Inputs from NASA's Ocean Surface Topography

This report assesses the benefit of incorporating NASA's OSTM (Ocean Surface Topography Mission) altimeter data (C- and Ku-band) into NOAA's (National Oceanic and Atmospheric Administration) NWLON (National Water Level Observation Network) DSS (Decision Support System). This data will enhance the NWLON DSS by providing additional inforrnation because not all stations collect all meteorological parameters (sea-surface height, ocean tides, wave height, and wind speed over waves). OSTM will also provide data where NWLON stations are not present. OSTM will provide data on seasurface heights for determining sea-level rise and ocean circulation. Researchers and operational users currently use satellite altimeter data products with the GSFCOO NASA data model to obtain sea-surface height and ocean circulation inforrnation. Accurate and tirnely inforrnation concerning sea-level height, tide, and ocean currents is needed to irnprove coastal tidal predictions, tsunarni and storm surge warnings, and wetland restoration.

Guest, DeNeice C.↗

Solutions Network Formulation Report. Integrating Salinity Measurements from Aquarius into the Harmful Algal Blooms Observing System

This Candidate Solution suggests the use of Aquarius sea surface salinity measurements to improve the NOAA/NCDDC (National Oceanic and Atmospheric Administration s National Coastal Data Development Center) HABSOS (Harmful Algal Blooms Observing System) DST (decision support tool) by enhancing development and movement forecasts of HAB events as well as potential species identification. In the proposed configuration, recurring salinity measurements from the Aquarius mission would augment HABSOS sea surface temperature and in situ ocean current measurements. Thermohaline circulation observations combined with in situ measurements increase the precision of HAB event movement forecasting. These forecasts allow coastal managers and public health officials to make more accurate and timely warnings to the public and to better direct science teams to event sites for collection and further measurements.

Anderson, Daniel↗