Planetary Data System

The first Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is planned for launch by NASA in 1998. This instrument will provide a new and improved capability for terrestrial satellite remote sensing aimed at meeting the needs of global change research. The MODIS standard products will provide new and improved tools for moderate resolution land surface monitoring. These higher order data products have been designed to remove the burden of certain common types of data processing from the user community and meet the more general needs of global-to-regional monitoring, modeling, and assessment. The near-daily coverage of moderate resolution data from MODIS, coupled with the planned increase in high-resolution sampling from Landsat 7, will provide a powerful combination of observations. The full potential of MODIS will be realized once a stable and well-calibrated time-series of multispectral data has been established. In this paper the proposed MODIS standard products for land applications are described along with the current plans for data quality assessment and product validation.

When analyzing pairs of time series, one often needs to know whether a correlation is statistically significant. If the data are Gaussian distributed and not serially correlated, one can use the results of classical statistics to estimate the significance. While some techniques can handle non-Gaussian distributions, few methods are available for data with nonzero autocorrelation (i.e., serially correlated). In this paper, a nonparametric method is suggested to estimate the statistical significance of a computed correlation coefficient when serial correlation is a concern. This method compares favorably with conventional methods.

Abstract A prominent year-round ensemble response to a global sea surface temperature (SST) anomaly field fixed to that for January 1992 (near the peak of a major warm El Nino–Southern Oscillation episode) was observed in a 20-yr integration of the general circulation model used for operational seasonal prediction by the U.S. National Weather Service. This motivated a detailed observational reassessment of the teleconnections between strong SST anomalies in the central equatorial Pacific Ocean and Pacific–North America region 700-hPa heights and U.S. surface temperatures and precipitation. The approach used consisted of formation of monthly mean composites formed separately from cases in which the SST anomaly in a key area of the central equatorial Pacific Ocean was either large and positive or large and negative. Extensive permutation tests were conducted to test null hypotheses of no signal in these composites. The results provided a substantial case for the presence of teleconnections to either the pos...

In the one hundred years since Wolf died, little effort has gone into research to see if improved reconstructions of sunspot numbers can be made. We have gathered more than 349,000 observations of daily sunspot group counts from more than 350 observers active from 1610 to 1993. Based upon group counts alone, it is possible to make an objective and homogeneous reconstruction of sunspot numbers. From our study, it appears that the Sun has steadily increased in activity since 1700 with the exception of a brief decrease in the Dalton Minimum (1795–1823). The significant results here are the greater depth of the Dalton Minimum, the generally lower activity throughout the 1700's, and the gradual rise in activity from the Maunder Minimum to the present day. This solar activity reconstruction is quite similar to those Wolf published before 1868 rather than the revised Wolf reconstructions after 1873 which used geomagnetic fluctuations.

We have compared total solar irradiance from Nimbus-7 with ground-based photometry from the San Fernando Observatory (SFO) for 109 days between June 1 and December 31, 1988. We have also included in some analyses NOAA-9 SBUV2 data orF10.7 radio flux. The Nimbus-7 data are from orbital samples, averaged to the mean time of observation at SFO. Using the same parameters as in Chapmanet al. (1992), the multiple regression gives anR2 = 0.9131 and a ‘solar minimum’ irradiance,S0, = 1371.76 ± 0.18 W m−2 for the best fit.

From satellite observations the solar total irradiance is known to vary. Sunspot blocking, facular emission, and network emission are three identified causes for the variations. In this paper we examine several different solar indices measured over the past century that are potential proxy measures for the Sun's irradiance. These indices are (1) the equatorial solar rotation rate, (2) the sunspot structure, the decay rate of individual sunspots, and the number of sunspots without umbrae, and (3) the length and decay rate of the sunspot cycle. Each index can be used to develop a model for the Sun's total irradiance as seen at the Earth. Three solar indices allow the irradiance to be modeled back to the mid‐1700s. The indices are (1) the length of the solar cycle, (2) the normalized decay rate of the solar cycle, and (3) the mean level of solar activity. All the indices are well correlated, and one possible explanation for their nearly simultaneous variations is changes in the Sun's convective energy transport. Although changes in the Sun's convective energy transport are outside the realm of normal stellar structure theory (e.g., mixing length theory), one can imagine variations arising from even the simplest view of sunspots as vertical tubes of magnetic flux, which would serve as rigid pillars affecting the energy flow patterns by ensuring larger‐scale eddies. A composite solar irradiance model, based upon these proxies, is compared to the northern hemisphere temperature departures for 1700‐1992. Approximately 71% of the decadal variance in the last century can be modeled with these solar indices, although this analysis does not include anthropogenic or other variations which would affect the results. Over the entire three centuries, ∼50% of the variance is modeled. Both this analysis and previous similar analyses have correlations of model solar irradiances and measured Earth surface temperatures that are significant at better than the 95% confidence level. To understand our present climate variations, we must place the anthropogenic variations in the context of natural variability from solar, volcanic, oceanic, and other sources.