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NASA NTRSDate not supplied

Monthly Mean DNI and GTI Derived from Monthly Mean GHI and DHI Using Two Methods: Comparisons with the BSRN Data and the Results Derived from the CERES Hourly Data

Monthly mean Global Horizontal Irradiances (GHI) and Diffuse Horizontal Irradiances (DHI) are more widely available than monthly mean Direct Normal Irradiances (DNI) and Global Tilted Irradiances (GTI). Empirical methods have been developed to derive monthly mean DNI and GTI from monthly mean GHI or from GHI and DHI. In this paper, we evaluate two such methods. The first one was the Whitlock Method developed by Charles H. Whitlock (2005) for the NASA POWER project by means of regression of the BSRN data. The method expresses the monthly mean DHI-to-GHI ratio as polynomial functions of monthly mean clearness index, sunset hour angle and noon solar elevation angle on the monthly-average-day. The monthly mean DNI is calculated by dividing the monthly mean GHI-DHI difference, or DirHI, by the cosine of the solar zenith angle at the mid-time between sunrise and solar noon on the monthly-average-day. The second method is the LJCR Method developed by Liu and Jorden (1960) and Collares-Pereira and Rabl (1979), and this method empirically splits monthly mean GHI and DHI into hourly means on the monthly-average-day, and the resulting hourly mean GHI and DHI and their difference, DirHI, can then be used to compute the monthly mean DNI, GTI and the global solar tracker irradiance (GTrI). This method is also used by RETScreen. We recently produced a set of hourly DNI and DHI by bias-correcting the CERES hourly DNI and DHI, and computed hourly GTI and GTrI as well. The data span twenty plus years from March 2000 to near present on a 1 by 1 grid system. The monthly mean CERES GHI and the corrected DHI are used as inputs to the above two methods to compute monthly mean DNI, GTI and GTrI. Through comparisons with the BSRN data, it is found that the Whitlock Method, with slight modification, and the LJCR Method can produce results that are nearly as good as the results derived from the CERES hourly data.

Taiping Zhang↗
NASA NTRSDate not supplied

The Use of the BSRN Data as A Benchmark for the POWER Hourly DHI and DNI and In Validating Derived Hourly GTI

The satellite-based CERES SYN1deg hourly data is the source data of the POWER GIS solar data that covers 2001 to near present. The SYN1deg(Ed4.1) hourly GHI agrees well with the BSRN data, but the hourly DHI and DirHI (Direct Horizontal Irradiance) are positively and negatively, respectively, biased with appreciable magnitudes. The hourly DNI, derived by dividing the DirHI by cos(SZA), or the cosine of the solar zenith angle, is therefore negatively biased. Based on the statistics of comparisons with the BSRN data, we performed bias corrections on the hourly DHI and DNI. The corrections were executed in the 3-D phase space of latitude, cos(SZA), and cloud fraction (CLFR). The isotropic model is then used to derive the hourly global tilted irradiance (GTI). For validation purpose, we applied the isotropic model to the BSRN data at the original 1-, 2-, 3- or 5-minute interval. The satellite-based hourly GTI shows good agreement with their BSRN counterpart. We also examined two monthly-mean-based methods that empirically derive monthly mean GTI and DNI from monthly mean GHI and from both monthly mean GHI and DHI. The monthly-mean-based results compare favorably with the hourly-mean-based results. The GEWEX SRB (V4-IP) provides POWER with daily mean GHI for the years before the CERES era, and the data were corrected using quantile mapping by referencing the CERES SYN1deg data. We used the Kolmogorov -Smirnov test (K-S test) and Cramer-von Mises test to examine how well the results agree with the BSRN data. We found that if we set the lower limit for the daily mean GHI to 30 W m-2, the data can pass the K-S test at 0.01 significance level and the Cramer-von Mises test at 0.001 significance level. If no lower limit is set on the daily means, the data fail both tests. The satellite-based CERES SYN1deg hourly data is the source data of the POWER GIS solar data that covers 2001 to near present. The SYN1deg(Ed4.1) hourly GHI agrees well with the BSRN data, but the hourly DHI and DirHI (Direct Horizontal Irradiance) are positively and negatively, respectively, biased with appreciable magnitudes. The hourly DNI, derived by dividing the DirHI by cos(SZA), or the cosine of the solar zenith angle, is therefore negatively biased. Based on the statistics of comparisons with the BSRN data, we performed bias corrections on the hourly DHI and DNI. The corrections were executed in the 3-D phase space of latitude, cos(SZA), and cloud fraction (CLFR). The isotropic model is then used to derive the hourly global tilted irradiance (GTI). For validation purpose, we applied the isotropic model to the BSRN data at the original 1-, 2-, 3- or 5-minute interval. The satellite-based hourly GTI shows good agreement with their BSRN counterpart. We also examined two monthly-mean-based methods that empirically derive monthly mean GTI and DNI from monthly mean GHI and from both monthly mean GHI and DHI. The monthly-mean-based results compare favorably with the hourly-mean-based results. The GEWEX SRB (V4-IP) provides POWER with daily mean GHI for the years before the CERES era, and the data were corrected using quantile mapping by referencing the CERES SYN1deg data. We used the Kolmogorov -Smirnov test (K-S test) and Cramer-von Mises test to examine how well the results agree with the BSRN data. We found that if we set the lower limit for the daily mean GHI to 30 W m-2, the data can pass the K-S test at 0.01 significance level and the Cramer-von Mises test at 0.001 significance level. If no lower limit is set on the daily means, the data fail both tests.

Taiping Zhang↗
NASA NTRSDate not supplied

The Hourly GHI, DHI and DNI: Intercomparison of the CERES-Based Data and the NSRDB Data through Comparison with the Ground-Based BSRN Data

The NASA Clouds and the Earth’s Radiant Energy System (CERES) SYN1deg(Ed4.1) provides hourly global horizontal irradiance (GHI), diffuse horizontal irradiance (DHI) and direct horizontal irradiance (DirHI) at 1-degree latitude by 1-degree longitude resolution, and the time span is from March 2000 to near present. While the GHI agrees well with the ground-based Baseline Surface Radiation Network (BSRN) data, the DHI and DirHI are, respectively, positively and negatively biased against the BSRN data, and so is the direct normal irradiance (DNI) derived simply by dividing the DirHI by the cosine of the hourly solar zenith angle (SZA). We found that the biases tend to be well-defined functions of cos(SZA) and the cloud fraction (CLFR). We thus performed a bias-correction on the hourly DHI and DNI in the latitude-cos(SZA)-CLFR phase space, and therefrom, we derived the hourly global tilted irradiance (GTI) at a number of tilt angles using the isotropic diffuse irradiance model, and the results agree well with the GTI derived from the original BSRN near-instantaneous records. Meanwhile, the National Renewable Energy Laboratory (NREL) has produced the National Solar Radiation Database (NSRDB) with finer spatiotemporal resolution using its Physical Solar Model (PSM) and surface-based measured data, model results and satellite-based data as inputs. Now the NSRDB data covers not only the United States and its neighboring regions, but Europe, Africa, Asia and Oceania. The available temporal resolutions are 5, 10, 15, 30 and 60 minutes and the spatial resolutions are 2, 4 and 10 km, depending on the selected region. In this presentation, we compare both the CERES-based and NSRDB GHI, DHI and DNI with their BSRN counterparts and show how finer spatial resolution may give us an advantage in data accuracy and usability.

Taiping Zhang↗
NASA NTRS2011

Effect of Sulfur on Siderophile Element Partitioning Between Olivine and Martian Primary Melt

Since olivine is a common early crystallizing phase in basaltic magmas that have produced planetary and asteroidal crusts, a number of experimental studies have investigated elemental partitioning between olivine and silicate melt [e.g., 1, 2, 3]. In particular, olivine/melt partition coefficients of Ni and Co (DNi and DCo) have been intensively studied because these elements are preferentially partitioned into olivine and thus provide a uniquely useful insight into the basalt petrogenesis [e.g., 4, 5]. However, none of these experimental studies are consistent with incompatible signatures of Co [e.g., 6, 7, 8] and Ni [7] in olivines from Martian meteorites. Chemical analyses of undegassed MORB samples suggest that S dissolved in silicate melts can reduce DNi up to 50 % compared to S-free experimental systems [9]. High S solubility (up to 4000 ppm) for primitive shergottite melts [10] implies that S might have significantly influenced the Ni and Co partitioning into shergottite olivines. This study conducts melting experiments on Martian magmatic conditions to investigate the effect of S on the partitioning of siderophile elements between olivine and Martian primary melt.

Usui, T.↗
NASA NTRS1998

Prototype Local Data Integration System and Central Florida Data Deficiency

This report describes the Applied Meteorology Unit's (AMU) task on the Local Data Integration System (LDIS) and central Florida data deficiency. The objectives of the task are to identify all existing meteorological data sources within 250 km of the Kennedy Space Center (KSC) and the Eastern Range at Cape Canaveral Air Station (CCAS), identify and configure an appropriate LDIS to integrate these data, and implement a working prototype to be used for limited case studies and data non-incorporation (DNI) experiments. The ultimate goal for running LDIS is to generate products that may enhance weather nowcasts and short-range (less than 6 h) forecasts issued in support of the 45th Weather Squadron (45 WS), Spaceflight Meteorology Group (SMG), and the Melbourne National Weather Service (NWS MLB) operational requirements. The LDIS has the potential to provide added value for nowcasts and short term forecasts for two reasons. First, it incorporates all data operationally available in east central Florida. Second, it is run at finer spatial and temporal resolutions than current national-scale operational models. In combination with a suitable visualization tool, LDIS may provide users with a more complete and comprehensive understanding of evolving fine-scale weather features than could be developed by individually examining the disparate data sets over the same area and time. The utility of LDIS depends largely on the reliability and availability of observational data. Therefore, it is important to document all existing meteorological data sources around central Florida that can be incorporated by it. Several factors contribute to the data density and coverage over east central Florida including the level in the atmosphere, distance from KSC/CCAS, time, and prevailing weather. The central Florida mesonet consists of existing surface meteorological and hydrological data available from the Tampa NWS and data servers at Miami and Jacksonville. However the utility of these data for operational use is limited, mainly because there are relatively few additional meteorological observations within 50 km of KSC/CCAS to supplement existing METAR and KSC/CCAS tower reports.

Manobianco, John↗